essay about technology for teaching and learning

Essay on Importance of Educational Technology for Teaching and Learning

Technology has rapidly changed the human lifestyle as it has changed the education sector. It is gradually and steadily taking over our education systems which are a few years behind. The website is about how technology is transforming learning by modifying how, where, and when learners learn, as well as empowering them at every step of the journey by offering them a choice over how they study, improving education meaningful to their digital lives, and equipping them for their futures (Kobayashi, 2008, p. 13). When students have access to technology and resources beyond the classroom, they are motivated to become logical thinkers, collaborators, and creators. When technology is correctly incorporated into the classroom, learners acquire a passion for learning (Bishop et al., 2020, p. 26).

Equitable use of technology refers to learners gaining access to information technology despite social status, economic status, ethnicity, physical ability, age, or other qualities. Despite technology having essential opportunities to learn, it is also a basic component in aiding students with gaining the skills and knowledge they require to be digital citizens. Insufficient access to information and technology denies students learning experiences and may limit their future opportunities. Equitable use includes ensuring that each student has the chance to learn from technologically advanced teachers.

Ethical use of technology is the use of technology in an appropriate way to gain from its use rather than using technology selfishly or enviously. Technology and internet use differ for each student. Students may not be victims of cyberbullying and copyright issues, but teachers should ensure that the students obtain the right skills to use technology and the internet.

Educational technology should help instill social responsibility among learners. Social responsibility is the use of technology in an ethical framework to benefit the student, the school, and the community at large. Both teachers and students have the responsibility to use technology responsibly. Students should adopt from activities that make them irresponsible such as software pirating, hacking, and illegal online activities. This helps the students have digital etiquette. Teachers should model ethical technology usage for their learners, acting responsibly.

Research has been done on educational technology to facilitate learning. Different resources were used in this research. Such resources include statistical software, reference management, and online storage. Statistical software helps to improve research expertise, increase speed and robustness of research work, reduce human errors in data analysis, and ease and increase the efficiency of research work.

Reference management refers to archiving of research and findings. The introduction of referencing management has reduced the strictness of referencing rules. Students need to understand the referencing systems to effectively make use of them in class work or the future. Referencing management offers students with research resources such as books, journal articles, conference papers, and thesis.

Online storage is an essential resource for research. It involves moving data to the cloud. It ensures secure data management and storage. Online storage comes with several advantages such as accessing data while anywhere, easy sharing of data, quick data recovery, and many others. On the other hand, in case of improper handling, it can be hazardous. It is also a more convenient and efficient means of obtaining information from students, instructors, and guardians. First of all, web surveys ensure a short time for collecting responses and are both cost and time-effective (“Educational resources and technology,” n.d., p. 2).

Technology integration engages students and allows the teachers to differentiate their learning in multiple ways. This might be frustrating at times, but there are many innovative ways to incorporate technology into regular teaching. One such method is Game-Based Learning and Assessment. Some of the concepts that we know are important in the theory include the ideas of relevant context, having a reason for carrying out various tasks, the cognitive integrity of what is happening in one’s brain while engrossed with the game is similar to the situation in real life utilizing language, the emotional aspect – having an interaction with the game is advantageous to learning. Another method of integration is videos, podcasts. and slideshows created by students One of the key principles of digital or internet literacy is that learners should become makers and critics of media rather than merely consumers.

Technology is integrated into the curriculum instructional design for different reasons. For example, to motivate students, provide new approaches, and increase productivity. Technology must be easily accessible and be used at a point of instruction. Each level must plan well so that technology may be integrated efficiently and easily into the education curriculum. In a curriculum, technology can be integrated with specific disciplines for effectiveness, efficiency, and ease of implementation. You can benefit from considering the usage of technology is an integral part of the curriculum design process through developing new solutions to cope with educational issues and communicate ways to facilitate discussion.

Formative assessment is the process of obtaining feedback to improve the continuing teaching and learning environment. Summative assessment strategy is a method of determining a student’s measure of success by the end of each education session. Integrating technology with formative and summative assessment strategies helps students engage and promote critical thinking. Other advantages include the useful clarification of grading standards as well as the increase of the integrity and consistency of academic results.

Educational technological tools that an educator uses to instill self-directedness and independent learning nay include online education. It introduces students to a broad variety of online materials addressing their points of interest, something that they can learn at their speed. Online learning improves student learning performance. Open educational resources are also another tool offering a solution by lowering the cost of materials for students while increasing their dependence on digital resources.

Assistive technology, particularly in the classroom, is reshaping what is possible for persons with a wide range of learning, cognitive, and physical skills and impairments. Some examples include e-books and apps. There are apps for accessing digital books on handheld devices. Accessibility preferences and some other built-in accessibility options in our handheld devices support many features which are used for different purposes for example text-to-speech output.

Bishop, M. J., Boling, E., Elen, J., & Svihla, V. (2020).  Handbook of research in educational communications and technology: Learning design . Springer Nature.

Educational resources and technology. (n.d.).  https://doi.org/10.21777/2500-2112

Integrating technology into the curriculum . (n.d.). Share and Discover Knowledge on SlideShare.  https://www.slideshare.net/HinaKaynat/integrating-technology-into-the-curriculum-69929434

Keengwe, J. (2013).  Research perspectives and best practices in educational technology integration . IGI Global.

Kobayashi, R. (2008).  New educational technology . Nova Publishers.

Rolfe, V. (2012). Open educational resources: Staff attitudes and awareness.  Research in Learning Technology ,  20 (0).  https://doi.org/10.3402/rlt.v20i0.14395

Using technology to facilitate formative and summative assessments . (n.d.). Sherrilyn’s Classroom.  https://sherrilynhicks.weebly.com/sherrilyns-blog/using-technology-to-facilitate-formative-and-summative-assessments

What is successful technology integration?  (2007, November 6). Edutopia.  https://www.edutopia.org/technology-integration-guide-description

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The Impact of Technology in Education Essay

Introduction, summary of the article, impact of the technologies.

Technology has become essential in education as teachers are finding it more effective to adopt and apply certain technological principles in the learning process. This essay addresses the issue of technology in education by summarizing a scholarly article on the subject and synthesizing the impact of technology in education.

In their 2009 survey, Klopfer et al. (2009) discussed how games and simulations are applied in various fields including medicine, business, government and science in promoting and improving service delivery. Although the technologies have been mainly applied in training of employees at various levels, the authors affirmed that these tools are equally useful in classroom teaching and other educational procedures.

Besides their description on how technology had transformed humanity, they argued that some people have remained reluctant to adopting certain technological ideas (Klopfer et al., 2009). Some of these technologies are social media networks which most education stakeholders believe may cause security challenges to schools and other learning institutions.

The scholars mainly focused on how digital gaming, social media networks and computer simulations had impacted the education system. Through background information, they emphasized that the three technologies had undergone a series of transformations. In addition, they explored major cognitive effects of the above mentioned technologies in the education system as many schools continue to adopt them.

In ensuring fair research details, they explored some of the challenges which had been experienced in applying technology in education. Lastly, the scholars described the future of these technologies in education (Klopfer et al., 2009).

According to Klopfer et al. (2009), digital gaming had become quite common in the United States with over forty five million homes playing these games. The games have particular characteristics like rules, objectives, feedback and competition which impact learners with skills.

With their familiarity among students and parents, learners find digital games easier and compatible when they are applied in the classroom for learning purposes (Klopfer et al., 2009). Most games create an environment which allows learners to grasp certain skills that are quite fundamental in and outside the classroom.

Some of these skills are: conflict resolution, appreciation of group work and embracing apprenticeship programs among others. They therefore reckon that adoption of these games is imperative in understanding their designs and benefits in education.

On the other hand, simulations demonstrate a modified version of the real world with teachers considering this technology as a major teaching tool. Simulations like “MOLECULAR WORKBENCH” are essential for teachers, tutors and lecturers especially in data collection and evaluation of learning using various models (Klopfer et al., 2009).

Moreover, “STARLOGO TNG” simplifies programming languages which are essential in teaching of mathematics. Lastly, customized social networks like “NING”, “THINK.COM”, “DIIGO” and “PANWARA” enhance sharing of filtered information among peers and teachers (Klopfer et al., 2009).

Since teachers have administrative powers, they are able to control web content and functions. Through these, learners share information and consult teachers outside the class.

It is evident that digital games, simulations and social networks present interesting future progress as they get adopted in more learning institutions around the world. More exploration is expected to fix existing barriers and address upcoming challenges (Quillen, 2011). By using these technologies in the current world, teachers and learners create answers for future generations.

From the analysis of the article above, it is clear that there are several technologies which continue to transform education today. Nevertheless, they present countless opportunities for exploration.

Klopfer et al. (2009). Using the technology of today, in the class room today. The Education Arcade, Massachusetts Institute of Technology . Web.

Quillen, I. (2011). Perceptive Computers and the Future of Ed Tech . Digital Education. Web.

• Educational Validity of Business Gaming
• Gambling and Gaming Industry
• Computer Gaming Influence on the Academic Performance
• Computer Technology in Education
• Impact of Technology on Teaching
• The Computer-Mediated Learning Module
• Social Networking: Benefits & Pitfalls to Education From a Cultural Perspective
• Preparing Teachers to Use the Technologies in the Educational Institutions
• Chicago (A-D)
• Chicago (N-B)

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How Important Is Technology in Education? Benefits, Challenges, and Impact on Students

Many of today’s high-demand jobs were created in the last decade, according to the International Society for Technology in Education (ISTE). As advances in technology drive globalization and digital transformation, teachers can help students acquire the necessary skills to succeed in the careers of the future.

How important is technology in education? The COVID-19 pandemic is quickly demonstrating why online education should be a vital part of teaching and learning. By integrating technology into existing curricula, as opposed to using it solely as a crisis-management tool, teachers can harness online learning as a powerful educational tool.

The effective use of digital learning tools in classrooms can increase student engagement, help teachers improve their lesson plans, and facilitate personalized learning. It also helps students build essential 21st-century skills.

Virtual classrooms, video, augmented reality (AR), robots, and other technology tools can not only make class more lively, they can also create more inclusive learning environments that foster collaboration and inquisitiveness and enable teachers to collect data on student performance.

Still, it’s important to note that technology is a tool used in education and not an end in itself. The promise of educational technology lies in what educators do with it and how it is used to best support their students’ needs.

Educational Technology Challenges

BuiltIn reports that 92 percent of teachers understand the impact of technology in education. According to Project Tomorrow, 59 percent of middle school students say digital educational tools have helped them with their grades and test scores. These tools have become so popular that the educational technology market is projected to expand to $342 billion by 2025, according to the World Economic Forum.

However, educational technology has its challenges, particularly when it comes to implementation and use. For example, despite growing interest in the use of AR, artificial intelligence, and other emerging technology, less than 10 percent of schools report having these tools in their classrooms, according to Project Tomorrow. Additional concerns include excessive screen time, the effectiveness of teachers using the technology, and worries about technology equity.

Prominently rising from the COVID-19 crisis is the issue of content. Educators need to be able to develop and weigh in on online educational content, especially to encourage students to consider a topic from different perspectives. The urgent actions taken during this crisis did not provide sufficient time for this. Access is an added concern — for example, not every school district has resources to provide students with a laptop, and internet connectivity can be unreliable in homes.

Additionally, while some students thrive in online education settings, others lag for various factors, including support resources. For example, a student who already struggled in face-to-face environments may struggle even more in the current situation. These students may have relied on resources that they no longer have in their homes.

Still, most students typically demonstrate confidence in using online education when they have the resources, as studies have suggested. However, online education may pose challenges for teachers, especially in places where it has not been the norm.

Despite the challenges and concerns, it’s important to note the benefits of technology in education, including increased collaboration and communication, improved quality of education, and engaging lessons that help spark imagination and a search for knowledge in students.

The Benefits of Technology in Education

Teachers want to improve student performance, and technology can help them accomplish this aim. To mitigate the challenges, administrators should help teachers gain the competencies needed to enhance learning for students through technology. Additionally, technology in the classroom should make teachers’ jobs easier without adding extra time to their day.

Technology provides students with easy-to-access information, accelerated learning, and fun opportunities to practice what they learn. It enables students to explore new subjects and deepen their understanding of difficult concepts, particularly in STEM. Through the use of technology inside and outside the classroom, students can gain 21st-century technical skills necessary for future occupations.

Still, children learn more effectively with direction. The World Economic Forum reports that while technology can help young students learn and acquire knowledge through play, for example, evidence suggests that learning is more effective through guidance from an adult, such as a teacher.

Leaders and administrators should take stock of where their faculty are in terms of their understanding of online spaces. From lessons learned during this disruptive time, they can implement solutions now for the future. For example, administrators could give teachers a week or two to think carefully about how to teach courses not previously online. In addition to an exploration of solutions, flexibility during these trying times is of paramount importance.

Below are examples of how important technology is in education and the benefits it offers to students and teachers.

Increased Collaboration and Communication

Educational technology can foster collaboration. Not only can teachers engage with students during lessons, but students can also communicate with each other. Through online lessons and learning games, students get to work together to solve problems. In collaborative activities, students can share their thoughts and ideas and support each other. At the same time, technology enables one-on-one interaction with teachers. Students can ask classroom-related questions and seek additional help on difficult-to-understand subject matter. At home, students can upload their homework, and teachers can access and view completed assignments using their laptops.

Personalized Learning Opportunities

Technology allows 24/7 access to educational resources. Classes can take place entirely online via the use of a laptop or mobile device. Hybrid versions of learning combine the use of technology from anywhere with regular in-person classroom sessions. In both scenarios, the use of technology to tailor learning plans for each student is possible. Teachers can create lessons based on student interests and strengths. An added benefit is that students can learn at their own pace. When they need to review class material to get a better understanding of essential concepts, students can review videos in the lesson plan. The data generated through these online activities enable teachers to see which students struggled with certain subjects and offer additional assistance and support.

Curiosity Driven by Engaging Content

Through engaging and educational content, teachers can spark inquisitiveness in children and boost their curiosity, which research says has ties to academic success. Curiosity helps students get a better understanding of math and reading concepts. Creating engaging content can involve the use of AR, videos, or podcasts. For example, when submitting assignments, students can include videos or interact with students from across the globe.

Improved Teacher Productivity and Efficiency

Teachers can leverage technology to achieve new levels of productivity, implement useful digital tools to expand learning opportunities for students, and increase student support and engagement. It also enables teachers to improve their instruction methods and personalize learning. Schools can benefit from technology by reducing the costs of physical instructional materials, enhancing educational program efficiency, and making the best use of teacher time.

Become a Leader in Enriching Classrooms through Technology

Educators unfamiliar with some of the technology used in education may not have been exposed to the tools as they prepared for their careers or as part of their professional development. Teachers looking to make the transition and acquire the skills to incorporate technology in education can take advantage of learning opportunities to advance their competencies. For individuals looking to help transform the education system through technology, American University’s School of Education online offers a Master of Arts in Teaching and a Master of Arts in Education Policy and Leadership to prepare educators with essential tools to become leaders. Courses such as Education Program and Policy Implementation and Teaching Science in Elementary School equip graduate students with critical competencies to incorporate technology into educational settings effectively.

Learn more about American University’s School of Education online and its master’s degree programs.

Virtual Reality in Education: Benefits, Tools, and Resources

Data-Driven Decision Making in Education: 11 Tips for Teachers & Administration

Helping Girls Succeed in STEM

BuiltIn, “Edtech 101”

EdTech, “Teaching Teachers to Put Tech Tools to Work”

International Society for Technology in Education, “Preparing Students for Jobs That Don’t Exist”

The Journal, “How Teachers Use Technology to Enrich Learning Experiences”

Pediatric Research, “Early Childhood Curiosity and Kindergarten Reading and Math Academic Achievement”

Project Tomorrow, “Digital Learning: Peril or Promise for Our K-12 Students”

World Economic Forum, “The Future of Jobs Report 2018”

World Economic Forum, “Learning through Play: How Schools Can Educate Students through Technology”

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How education technology can improve learning for all students

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Alejandro j. ganimian , alejandro j. ganimian nonresident fellow - global economy and development , center for universal education @aganimian emiliana vegas , and emiliana vegas former co-director - center for universal education , former senior fellow - global economy and development @emivegasv fred dews fred dews managing editor, podcasts and digital products - office of communications @publichistory.

September 11, 2020

New research from the Center for Universal Education (CUE) at Brookings finds that technology’s impact on learning and teaching has been limited, especially in low- and middle-income countries, largely because tech has been used to replace analog tools. On this episode, two of the authors of a new report, titled, “ Realizing the Promise: How can education technology improve learning for all? ,” discuss their findings. Alejandro Ganimian is an assistant professor of applied technology and economics at New York University, and a CUE nonresident fellow. Emiliana Vegas is co-director of the center and a senior fellow in the Global Economy and Development program at Brookings.

Also on this episode, Governance Studies Senior Fellow Molly Reynolds on what’s happening in Congress, including  whether another government shutdown due to funding disagreements is possible, and  a look at a new COVID-19 relief package proposed by Senate Majority Leader Mitch McConnell, why it failed, and the politics behind it.  

Subscribe to Brookings podcasts  here  or on  iTunes , send feedback email to  [email protected] , and follow us and tweet us at  @policypodcasts  on Twitter.

The Brookings Cafeteria is part of the  Brookings Podcast Network .

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Education reform and change driven by digital technology: a bibliometric study from a global perspective

• Chengliang Wang 1 ,
• Xiaojiao Chen 1 ,
• Teng Yu   ORCID: orcid.org/0000-0001-5198-7261 2 , 3 ,
• Yidan Liu 1 , 4 &
• Yuhui Jing 1  

Humanities and Social Sciences Communications volume  11 , Article number:  256 ( 2024 ) Cite this article

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• Development studies
• Science, technology and society

Amidst the global digital transformation of educational institutions, digital technology has emerged as a significant area of interest among scholars. Such technologies have played an instrumental role in enhancing learner performance and improving the effectiveness of teaching and learning. These digital technologies also ensure the sustainability and stability of education during the epidemic. Despite this, a dearth of systematic reviews exists regarding the current state of digital technology application in education. To address this gap, this study utilized the Web of Science Core Collection as a data source (specifically selecting the high-quality SSCI and SCIE) and implemented a topic search by setting keywords, yielding 1849 initial publications. Furthermore, following the PRISMA guidelines, we refined the selection to 588 high-quality articles. Using software tools such as CiteSpace, VOSviewer, and Charticulator, we reviewed these 588 publications to identify core authors (such as Selwyn, Henderson, Edwards), highly productive countries/regions (England, Australia, USA), key institutions (Monash University, Australian Catholic University), and crucial journals in the field ( Education and Information Technologies , Computers & Education , British Journal of Educational Technology ). Evolutionary analysis reveals four developmental periods in the research field of digital technology education application: the embryonic period, the preliminary development period, the key exploration, and the acceleration period of change. The study highlights the dual influence of technological factors and historical context on the research topic. Technology is a key factor in enabling education to transform and upgrade, and the context of the times is an important driving force in promoting the adoption of new technologies in the education system and the transformation and upgrading of education. Additionally, the study identifies three frontier hotspots in the field: physical education, digital transformation, and professional development under the promotion of digital technology. This study presents a clear framework for digital technology application in education, which can serve as a valuable reference for researchers and educational practitioners concerned with digital technology education application in theory and practice.

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Introduction.

Digital technology has become an essential component of modern education, facilitating the extension of temporal and spatial boundaries and enriching the pedagogical contexts (Selwyn and Facer, 2014 ). The advent of mobile communication technology has enabled learning through social media platforms (Szeto et al. 2015 ; Pires et al. 2022 ), while the advancement of augmented reality technology has disrupted traditional conceptions of learning environments and spaces (Perez-Sanagustin et al., 2014 ; Kyza and Georgiou, 2018 ). A wide range of digital technologies has enabled learning to become a norm in various settings, including the workplace (Sjöberg and Holmgren, 2021 ), home (Nazare et al. 2022 ), and online communities (Tang and Lam, 2014 ). Education is no longer limited to fixed locations and schedules, but has permeated all aspects of life, allowing learning to continue at any time and any place (Camilleri and Camilleri, 2016 ; Selwyn and Facer, 2014 ).

The advent of digital technology has led to the creation of several informal learning environments (Greenhow and Lewin, 2015 ) that exhibit divergent form, function, features, and patterns in comparison to conventional learning environments (Nygren et al. 2019 ). Consequently, the associated teaching and learning processes, as well as the strategies for the creation, dissemination, and acquisition of learning resources, have undergone a complete overhaul. The ensuing transformations have posed a myriad of novel issues, such as the optimal structuring of teaching methods by instructors and the adoption of appropriate learning strategies by students in the new digital technology environment. Consequently, an examination of the principles that underpin effective teaching and learning in this environment is a topic of significant interest to numerous scholars engaged in digital technology education research.

Over the course of the last two decades, digital technology has made significant strides in the field of education, notably in extending education time and space and creating novel educational contexts with sustainability. Despite research attempts to consolidate the application of digital technology in education, previous studies have only focused on specific aspects of digital technology, such as Pinto and Leite’s ( 2020 ) investigation into digital technology in higher education and Mustapha et al.’s ( 2021 ) examination of the role and value of digital technology in education during the pandemic. While these studies have provided valuable insights into the practical applications of digital technology in particular educational domains, they have not comprehensively explored the macro-mechanisms and internal logic of digital technology implementation in education. Additionally, these studies were conducted over a relatively brief period, making it challenging to gain a comprehensive understanding of the macro-dynamics and evolutionary process of digital technology in education. Some studies have provided an overview of digital education from an educational perspective but lack a precise understanding of technological advancement and change (Yang et al. 2022 ). Therefore, this study seeks to employ a systematic scientific approach to collate relevant research from 2000 to 2022, comprehend the internal logic and development trends of digital technology in education, and grasp the outstanding contribution of digital technology in promoting the sustainability of education in time and space. In summary, this study aims to address the following questions:

RQ1: Since the turn of the century, what is the productivity distribution of the field of digital technology education application research in terms of authorship, country/region, institutional and journal level?

RQ2: What is the development trend of research on the application of digital technology in education in the past two decades?

RQ3: What are the current frontiers of research on the application of digital technology in education?

Literature review

Although the term “digital technology” has become ubiquitous, a unified definition has yet to be agreed upon by scholars. Because the meaning of the word digital technology is closely related to the specific context. Within the educational research domain, Selwyn’s ( 2016 ) definition is widely favored by scholars (Pinto and Leite, 2020 ). Selwyn ( 2016 ) provides a comprehensive view of various concrete digital technologies and their applications in education through ten specific cases, such as immediate feedback in classes, orchestrating teaching, and community learning. Through these specific application scenarios, Selwyn ( 2016 ) argues that digital technology encompasses technologies associated with digital devices, including but not limited to tablets, smartphones, computers, and social media platforms (such as Facebook and YouTube). Furthermore, Further, the behavior of accessing the internet at any location through portable devices can be taken as an extension of the behavior of applying digital technology.

The evolving nature of digital technology has significant implications in the field of education. In the 1890s, the focus of digital technology in education was on comprehending the nuances of digital space, digital culture, and educational methodologies, with its connotations aligned more towards the idea of e-learning. The advent and subsequent widespread usage of mobile devices since the dawn of the new millennium have been instrumental in the rapid expansion of the concept of digital technology. Notably, mobile learning devices such as smartphones and tablets, along with social media platforms, have become integral components of digital technology (Conole and Alevizou, 2010 ; Batista et al. 2016 ). In recent times, the burgeoning application of AI technology in the education sector has played a vital role in enriching the digital technology lexicon (Banerjee et al. 2021 ). ChatGPT, for instance, is identified as a novel educational technology that has immense potential to revolutionize future education (Rospigliosi, 2023 ; Arif, Munaf and Ul-Haque, 2023 ).

Pinto and Leite ( 2020 ) conducted a comprehensive macroscopic survey of the use of digital technologies in the education sector and identified three distinct categories, namely technologies for assessment and feedback, mobile technologies, and Information Communication Technologies (ICT). This classification criterion is both macroscopic and highly condensed. In light of the established concept definitions of digital technology in the educational research literature, this study has adopted the characterizations of digital technology proposed by Selwyn ( 2016 ) and Pinto and Leite ( 2020 ) as crucial criteria for analysis and research inclusion. Specifically, this criterion encompasses several distinct types of digital technologies, including Information and Communication Technologies (ICT), Mobile tools, eXtended Reality (XR) Technologies, Assessment and Feedback systems, Learning Management Systems (LMS), Publish and Share tools, Collaborative systems, Social media, Interpersonal Communication tools, and Content Aggregation tools.

Methodology and materials

Research method: bibliometric.

The research on econometric properties has been present in various aspects of human production and life, yet systematic scientific theoretical guidance has been lacking, resulting in disorganization. In 1969, British scholar Pritchard ( 1969 ) proposed “bibliometrics,” which subsequently emerged as an independent discipline in scientific quantification research. Initially, Pritchard defined bibliometrics as “the application of mathematical and statistical methods to books and other media of communication,” however, the definition was not entirely rigorous. To remedy this, Hawkins ( 2001 ) expanded Pritchard’s definition to “the quantitative analysis of the bibliographic features of a body of literature.” De Bellis further clarified the objectives of bibliometrics, stating that it aims to analyze and identify patterns in literature, such as the most productive authors, institutions, countries, and journals in scientific disciplines, trends in literary production over time, and collaboration networks (De Bellis, 2009 ). According to Garfield ( 2006 ), bibliometric research enables the examination of the history and structure of a field, the flow of information within the field, the impact of journals, and the citation status of publications over a longer time scale. All of these definitions illustrate the unique role of bibliometrics as a research method for evaluating specific research fields.

This study uses CiteSpace, VOSviewer, and Charticulator to analyze data and create visualizations. Each of these three tools has its own strengths and can complement each other. CiteSpace and VOSviewer use set theory and probability theory to provide various visualization views in fields such as keywords, co-occurrence, and co-authors. They are easy to use and produce visually appealing graphics (Chen, 2006 ; van Eck and Waltman, 2009 ) and are currently the two most widely used bibliometric tools in the field of visualization (Pan et al. 2018 ). In this study, VOSviewer provided the data necessary for the Performance Analysis; Charticulator was then used to redraw using the tabular data exported from VOSviewer (for creating the chord diagram of country collaboration); this was to complement the mapping process, while CiteSpace was primarily utilized to generate keyword maps and conduct burst word analysis.

Data retrieval

This study selected documents from the Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI) in the Web of Science Core Collection as the data source, for the following reasons:

(1) The Web of Science Core Collection, as a high-quality digital literature resource database, has been widely accepted by many researchers and is currently considered the most suitable database for bibliometric analysis (Jing et al. 2023a ). Compared to other databases, Web of Science provides more comprehensive data information (Chen et al. 2022a ), and also provides data formats suitable for analysis using VOSviewer and CiteSpace (Gaviria-Marin et al. 2019 ).

(2) The application of digital technology in the field of education is an interdisciplinary research topic, involving technical knowledge literature belonging to the natural sciences and education-related literature belonging to the social sciences. Therefore, it is necessary to select Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI) as the sources of research data, ensuring the comprehensiveness of data while ensuring the reliability and persuasiveness of bibliometric research (Hwang and Tsai, 2011 ; Wang et al. 2022 ).

After establishing the source of research data, it is necessary to determine a retrieval strategy (Jing et al. 2023b ). The choice of a retrieval strategy should consider a balance between the breadth and precision of the search formula. That is to say, it should encompass all the literature pertaining to the research topic while excluding irrelevant documents as much as possible. In light of this, this study has set a retrieval strategy informed by multiple related papers (Mustapha et al. 2021 ; Luo et al. 2021 ). The research by Mustapha et al. ( 2021 ) guided us in selecting keywords (“digital” AND “technolog*”) to target digital technology, while Luo et al. ( 2021 ) informed the selection of terms (such as “instruct*,” “teach*,” and “education”) to establish links with the field of education. Then, based on the current application of digital technology in the educational domain and the scope of selection criteria, we constructed the final retrieval strategy. Following the general patterns of past research (Jing et al. 2023a , 2023b ), we conducted a specific screening using the topic search (Topics, TS) function in Web of Science. For the specific criteria used in the screening for this study, please refer to Table 1 .

Literature screening

Literature acquired through keyword searches may contain ostensibly related yet actually unrelated works. Therefore, to ensure the close relevance of literature included in the analysis to the research topic, it is often necessary to perform a manual screening process to identify the final literature to be analyzed, subsequent to completing the initial literature search.

The manual screening process consists of two steps. Initially, irrelevant literature is weeded out based on the title and abstract, with two members of the research team involved in this phase. This stage lasted about one week, resulting in 1106 articles being retained. Subsequently, a comprehensive review of the full text is conducted to accurately identify the literature required for the study. To carry out the second phase of manual screening effectively and scientifically, and to minimize the potential for researcher bias, the research team established the inclusion criteria presented in Table 2 . Three members were engaged in this phase, which took approximately 2 weeks, culminating in the retention of 588 articles after meticulous screening. The entire screening process is depicted in Fig. 1 , adhering to the PRISMA guidelines (Page et al. 2021 ).

The process of obtaining and filtering the necessary literature data for research.

Data standardization

Nguyen and Hallinger ( 2020 ) pointed out that raw data extracted from scientific databases often contains multiple expressions of the same term, and not addressing these synonymous expressions could affect research results in bibliometric analysis. For instance, in the original data, the author list may include “Tsai, C. C.” and “Tsai, C.-C.”, while the keyword list may include “professional-development” and “professional development,” which often require merging. Therefore, before analyzing the selected literature, a data disambiguation process is necessary to standardize the data (Strotmann and Zhao, 2012 ; Van Eck and Waltman, 2019 ). This study adopted the data standardization process proposed by Taskin and Al ( 2019 ), mainly including the following standardization operations:

Firstly, the author and source fields in the data are corrected and standardized to differentiate authors with similar names.

Secondly, the study checks whether the journals to which the literature belongs have been renamed in the past over 20 years, so as to avoid the influence of periodical name change on the analysis results.

Finally, the keyword field is standardized by unifying parts of speech and singular/plural forms of keywords, which can help eliminate redundant entries in the knowledge graph.

Performance analysis (RQ1)

This section offers a thorough and detailed analysis of the state of research in the field of digital technology education. By utilizing descriptive statistics and visual maps, it provides a comprehensive overview of the development trends, authors, countries, institutions, and journal distribution within the field. The insights presented in this section are of great significance in advancing our understanding of the current state of research in this field and identifying areas for further investigation. The use of visual aids to display inter-country cooperation and the evolution of the field adds to the clarity and coherence of the analysis.

Time trend of the publications

To understand a research field, it is first necessary to understand the most basic quantitative information, among which the change in the number of publications per year best reflects the development trend of a research field. Figure 2 shows the distribution of publication dates.

Time trend of the publications on application of digital technology in education.

From the Fig. 2 , it can be seen that the development of this field over the past over 20 years can be roughly divided into three stages. The first stage was from 2000 to 2007, during which the number of publications was relatively low. Due to various factors such as technological maturity, the academic community did not pay widespread attention to the role of digital technology in expanding the scope of teaching and learning. The second stage was from 2008 to 2019, during which the overall number of publications showed an upward trend, and the development of the field entered an accelerated period, attracting more and more scholars’ attention. The third stage was from 2020 to 2022, during which the number of publications stabilized at around 100. During this period, the impact of the pandemic led to a large number of scholars focusing on the role of digital technology in education during the pandemic, and research on the application of digital technology in education became a core topic in social science research.

Analysis of authors

An analysis of the author’s publication volume provides information about the representative scholars and core research strengths of a research area. Table 3 presents information on the core authors in adaptive learning research, including name, publication number, and average number of citations per article (based on the analysis and statistics from VOSviewer).

Variations in research foci among scholars abound. Within the field of digital technology education application research over the past two decades, Neil Selwyn stands as the most productive author, having published 15 papers garnering a total of 1027 citations, resulting in an average of 68.47 citations per paper. As a Professor at the Faculty of Education at Monash University, Selwyn concentrates on exploring the application of digital technology in higher education contexts (Selwyn et al. 2021 ), as well as related products in higher education such as Coursera, edX, and Udacity MOOC platforms (Bulfin et al. 2014 ). Selwyn’s contributions to the educational sociology perspective include extensive research on the impact of digital technology on education, highlighting the spatiotemporal extension of educational processes and practices through technological means as the greatest value of educational technology (Selwyn, 2012 ; Selwyn and Facer, 2014 ). In addition, he provides a blueprint for the development of future schools in 2030 based on the present impact of digital technology on education (Selwyn et al. 2019 ). The second most productive author in this field, Henderson, also offers significant contributions to the understanding of the important value of digital technology in education, specifically in the higher education setting, with a focus on the impact of the pandemic (Henderson et al. 2015 ; Cohen et al. 2022 ). In contrast, Edwards’ research interests focus on early childhood education, particularly the application of digital technology in this context (Edwards, 2013 ; Bird and Edwards, 2015 ). Additionally, on the technical level, Edwards also mainly prefers digital game technology, because it is a digital technology that children are relatively easy to accept (Edwards, 2015 ).

Analysis of countries/regions and organization

The present study aimed to ascertain the leading countries in digital technology education application research by analyzing 75 countries related to 558 works of literature. Table 4 depicts the top ten countries that have contributed significantly to this field in terms of publication count (based on the analysis and statistics from VOSviewer). Our analysis of Table 4 data shows that England emerged as the most influential country/region, with 92 published papers and 2401 citations. Australia and the United States secured the second and third ranks, respectively, with 90 papers (2187 citations) and 70 papers (1331 citations) published. Geographically, most of the countries featured in the top ten publication volumes are situated in Australia, North America, and Europe, with China being the only exception. Notably, all these countries, except China, belong to the group of developed nations, suggesting that economic strength is a prerequisite for fostering research in the digital technology education application field.

This study presents a visual representation of the publication output and cooperation relationships among different countries in the field of digital technology education application research. Specifically, a chord diagram is employed to display the top 30 countries in terms of publication output, as depicted in Fig. 3 . The chord diagram is composed of nodes and chords, where the nodes are positioned as scattered points along the circumference, and the length of each node corresponds to the publication output, with longer lengths indicating higher publication output. The chords, on the other hand, represent the cooperation relationships between any two countries, and are weighted based on the degree of closeness of the cooperation, with wider chords indicating closer cooperation. Through the analysis of the cooperation relationships, the findings suggest that the main publishing countries in this field are engaged in cooperative relationships with each other, indicating a relatively high level of international academic exchange and research internationalization.

In the diagram, nodes are scattered along the circumference of a circle, with the length of each node representing the volume of publications. The weighted arcs connecting any two points on the circle are known as chords, representing the collaborative relationship between the two, with the width of the arc indicating the closeness of the collaboration.

Further analyzing Fig. 3 , we can extract more valuable information, enabling a deeper understanding of the connections between countries in the research field of digital technology in educational applications. It is evident that certain countries, such as the United States, China, and England, display thicker connections, indicating robust collaborative relationships in terms of productivity. These thicker lines signify substantial mutual contributions and shared objectives in certain sectors or fields, highlighting the interconnectedness and global integration in these areas. By delving deeper, we can also explore potential future collaboration opportunities through the chord diagram, identifying possible partners to propel research and development in this field. In essence, the chord diagram successfully encapsulates and conveys the multi-dimensionality of global productivity and cooperation, allowing for a comprehensive understanding of the intricate inter-country relationships and networks in a global context, providing valuable guidance and insights for future research and collaborations.

An in-depth examination of the publishing institutions is provided in Table 5 , showcasing the foremost 10 institutions ranked by their publication volume. Notably, Monash University and Australian Catholic University, situated in Australia, have recorded the most prolific publications within the digital technology education application realm, with 22 and 10 publications respectively. Moreover, the University of Oslo from Norway is featured among the top 10 publishing institutions, with an impressive average citation count of 64 per publication. It is worth highlighting that six institutions based in the United Kingdom were also ranked within the top 10 publishing institutions, signifying their leading position in this area of research.

Analysis of journals

Journals are the main carriers for publishing high-quality papers. Some scholars point out that the two key factors to measure the influence of journals in the specified field are the number of articles published and the number of citations. The more papers published in a magazine and the more citations, the greater its influence (Dzikowski, 2018 ). Therefore, this study utilized VOSviewer to statistically analyze the top 10 journals with the most publications in the field of digital technology in education and calculated the average citations per article (see Table 6 ).

Based on Table 6 , it is apparent that the highest number of articles in the domain of digital technology in education research were published in Education and Information Technologies (47 articles), Computers & Education (34 articles), and British Journal of Educational Technology (32 articles), indicating a higher article output compared to other journals. This underscores the fact that these three journals concentrate more on the application of digital technology in education. Furthermore, several other journals, such as Technology Pedagogy and Education and Sustainability, have published more than 15 articles in this domain. Sustainability represents the open access movement, which has notably facilitated research progress in this field, indicating that the development of open access journals in recent years has had a significant impact. Although there is still considerable disagreement among scholars on the optimal approach to achieve open access, the notion that research outcomes should be accessible to all is widely recognized (Huang et al. 2020 ). On further analysis of the research fields to which these journals belong, except for Sustainability, it is evident that they all pertain to educational technology, thus providing a qualitative definition of the research area of digital technology education from the perspective of journals.

Temporal keyword analysis: thematic evolution (RQ2)

The evolution of research themes is a dynamic process, and previous studies have attempted to present the developmental trajectory of fields by drawing keyword networks in phases (Kumar et al. 2021 ; Chen et al. 2022b ). To understand the shifts in research topics across different periods, this study follows past research and, based on the significant changes in the research field and corresponding technological advancements during the outlined periods, divides the timeline into four stages (the first stage from January 2000 to December 2005, the second stage from January 2006 to December 2011, the third stage from January 2012 to December 2017; and the fourth stage from January 2018 to December 2022). The division into these four stages was determined through a combination of bibliometric analysis and literature review, which presented a clear trajectory of the field’s development. The research analyzes the keyword networks for each time period (as there are only three articles in the first stage, it was not possible to generate an appropriate keyword co-occurrence map, hence only the keyword co-occurrence maps from the second to the fourth stages are provided), to understand the evolutionary track of the digital technology education application research field over time.

2000.1–2005.12: germination period

From January 2000 to December 2005, digital technology education application research was in its infancy. Only three studies focused on digital technology, all of which were related to computers. Due to the popularity of computers, the home became a new learning environment, highlighting the important role of digital technology in expanding the scope of learning spaces (Sutherland et al. 2000 ). In specific disciplines and contexts, digital technology was first favored in medical clinical practice, becoming an important tool for supporting the learning of clinical knowledge and practice (Tegtmeyer et al. 2001 ; Durfee et al. 2003 ).

2006.1–2011.12: initial development period

Between January 2006 and December 2011, it was the initial development period of digital technology education research. Significant growth was observed in research related to digital technology, and discussions and theoretical analyses about “digital natives” emerged. During this phase, scholars focused on the debate about “how to use digital technology reasonably” and “whether current educational models and school curriculum design need to be adjusted on a large scale” (Bennett and Maton, 2010 ; Selwyn, 2009 ; Margaryan et al. 2011 ). These theoretical and speculative arguments provided a unique perspective on the impact of cognitive digital technology on education and teaching. As can be seen from the vocabulary such as “rethinking”, “disruptive pedagogy”, and “attitude” in Fig. 4 , many scholars joined the calm reflection and analysis under the trend of digital technology (Laurillard, 2008 ; Vratulis et al. 2011 ). During this phase, technology was still undergoing dramatic changes. The development of mobile technology had already caught the attention of many scholars (Wong et al. 2011 ), but digital technology represented by computers was still very active (Selwyn et al. 2011 ). The change in technological form would inevitably lead to educational transformation. Collins and Halverson ( 2010 ) summarized the prospects and challenges of using digital technology for learning and educational practices, believing that digital technology would bring a disruptive revolution to the education field and bring about a new educational system. In addition, the term “teacher education” in Fig. 4 reflects the impact of digital technology development on teachers. The rapid development of technology has widened the generation gap between teachers and students. To ensure smooth communication between teachers and students, teachers must keep up with the trend of technological development and establish a lifelong learning concept (Donnison, 2009 ).

In the diagram, each node represents a keyword, with the size of the node indicating the frequency of occurrence of the keyword. The connections represent the co-occurrence relationships between keywords, with a higher frequency of co-occurrence resulting in tighter connections.

2012.1–2017.12: critical exploration period

During the period spanning January 2012 to December 2017, the application of digital technology in education research underwent a significant exploration phase. As can be seen from Fig. 5 , different from the previous stage, the specific elements of specific digital technology have started to increase significantly, including the enrichment of technological contexts, the greater variety of research methods, and the diversification of learning modes. Moreover, the temporal and spatial dimensions of the learning environment were further de-emphasized, as noted in previous literature (Za et al. 2014 ). Given the rapidly accelerating pace of technological development, the education system in the digital era is in urgent need of collaborative evolution and reconstruction, as argued by Davis, Eickelmann, and Zaka ( 2013 ).

In the domain of digital technology, social media has garnered substantial scholarly attention as a promising avenue for learning, as noted by Pasquini and Evangelopoulos ( 2016 ). The implementation of social media in education presents several benefits, including the liberation of education from the restrictions of physical distance and time, as well as the erasure of conventional educational boundaries. The user-generated content (UGC) model in social media has emerged as a crucial source for knowledge creation and distribution, with the widespread adoption of mobile devices. Moreover, social networks have become an integral component of ubiquitous learning environments (Hwang et al. 2013 ). The utilization of social media allows individuals to function as both knowledge producers and recipients, which leads to a blurring of the conventional roles of learners and teachers. On mobile platforms, the roles of learners and teachers are not fixed, but instead interchangeable.

In terms of research methodology, the prevalence of empirical studies with survey designs in the field of educational technology during this period is evident from the vocabulary used, such as “achievement,” “acceptance,” “attitude,” and “ict.” in Fig. 5 . These studies aim to understand learners’ willingness to adopt and attitudes towards new technologies, and some seek to investigate the impact of digital technologies on learning outcomes through quasi-experimental designs (Domínguez et al. 2013 ). Among these empirical studies, mobile learning emerged as a hot topic, and this is not surprising. First, the advantages of mobile learning environments over traditional ones have been empirically demonstrated (Hwang et al. 2013 ). Second, learners born around the turn of the century have been heavily influenced by digital technologies and have developed their own learning styles that are more open to mobile devices as a means of learning. Consequently, analyzing mobile learning as a relatively novel mode of learning has become an important issue for scholars in the field of educational technology.

The intervention of technology has led to the emergence of several novel learning modes, with the blended learning model being the most representative one in the current phase. Blended learning, a novel concept introduced in the information age, emphasizes the integration of the benefits of traditional learning methods and online learning. This learning mode not only highlights the prominent role of teachers in guiding, inspiring, and monitoring the learning process but also underlines the importance of learners’ initiative, enthusiasm, and creativity in the learning process. Despite being an early conceptualization, blended learning’s meaning has been expanded by the widespread use of mobile technology and social media in education. The implementation of new technologies, particularly mobile devices, has resulted in the transformation of curriculum design and increased flexibility and autonomy in students’ learning processes (Trujillo Maza et al. 2016 ), rekindling scholarly attention to this learning mode. However, some scholars have raised concerns about the potential drawbacks of the blended learning model, such as its significant impact on the traditional teaching system, the lack of systematic coping strategies and relevant policies in several schools and regions (Moskal et al. 2013 ).

2018.1–2022.12: accelerated transformation period

The period spanning from January 2018 to December 2022 witnessed a rapid transformation in the application of digital technology in education research. The field of digital technology education research reached a peak period of publication, largely influenced by factors such as the COVID-19 pandemic (Yu et al. 2023 ). Research during this period was built upon the achievements, attitudes, and social media of the previous phase, and included more elements that reflect the characteristics of this research field, such as digital literacy, digital competence, and professional development, as depicted in Fig. 6 . Alongside this, scholars’ expectations for the value of digital technology have expanded, and the pursuit of improving learning efficiency and performance is no longer the sole focus. Some research now aims to cultivate learners’ motivation and enhance their self-efficacy by applying digital technology in a reasonable manner, as demonstrated by recent studies (Beardsley et al. 2021 ; Creely et al. 2021 ).

The COVID-19 pandemic has emerged as a crucial backdrop for the digital technology’s role in sustaining global education, as highlighted by recent scholarly research (Zhou et al. 2022 ; Pan and Zhang, 2020 ; Mo et al. 2022 ). The online learning environment, which is supported by digital technology, has become the primary battleground for global education (Yu, 2022 ). This social context has led to various studies being conducted, with some scholars positing that the pandemic has impacted the traditional teaching order while also expanding learning possibilities in terms of patterns and forms (Alabdulaziz, 2021 ). Furthermore, the pandemic has acted as a catalyst for teacher teaching and technological innovation, and this viewpoint has been empirically substantiated (Moorhouse and Wong, 2021 ). Additionally, some scholars believe that the pandemic’s push is a crucial driving force for the digital transformation of the education system, serving as an essential mechanism for overcoming the system’s inertia (Romero et al. 2021 ).

The rapid outbreak of the pandemic posed a challenge to the large-scale implementation of digital technologies, which was influenced by a complex interplay of subjective and objective factors. Objective constraints included the lack of infrastructure in some regions to support digital technologies, while subjective obstacles included psychological resistance among certain students and teachers (Moorhouse, 2021 ). These factors greatly impacted the progress of online learning during the pandemic. Additionally, Timotheou et al. ( 2023 ) conducted a comprehensive systematic review of existing research on digital technology use during the pandemic, highlighting the critical role played by various factors such as learners’ and teachers’ digital skills, teachers’ personal attributes and professional development, school leadership and management, and administration in facilitating the digitalization and transformation of schools.

The current stage of research is characterized by the pivotal term “digital literacy,” denoting a growing interest in learners’ attitudes and adoption of emerging technologies. Initially, the term “literacy” was restricted to fundamental abilities and knowledge associated with books and print materials (McMillan, 1996 ). However, with the swift advancement of computers and digital technology, there have been various attempts to broaden the scope of literacy beyond its traditional meaning, including game literacy (Buckingham and Burn, 2007 ), information literacy (Eisenberg, 2008 ), and media literacy (Turin and Friesem, 2020 ). Similarly, digital literacy has emerged as a crucial concept, and Gilster and Glister ( 1997 ) were the first to introduce this concept, referring to the proficiency in utilizing technology and processing digital information in academic, professional, and daily life settings. In practical educational settings, learners who possess higher digital literacy often exhibit an aptitude for quickly mastering digital devices and applying them intelligently to education and teaching (Yu, 2022 ).

The utilization of digital technology in education has undergone significant changes over the past two decades, and has been a crucial driver of educational reform with each new technological revolution. The impact of these changes on the underlying logic of digital technology education applications has been noticeable. From computer technology to more recent developments such as virtual reality (VR), augmented reality (AR), and artificial intelligence (AI), the acceleration in digital technology development has been ongoing. Educational reforms spurred by digital technology development continue to be dynamic, as each new digital innovation presents new possibilities and models for teaching practice. This is especially relevant in the post-pandemic era, where the importance of technological progress in supporting teaching cannot be overstated (Mughal et al. 2022 ). Existing digital technologies have already greatly expanded the dimensions of education in both time and space, while future digital technologies aim to expand learners’ perceptions. Researchers have highlighted the potential of integrated technology and immersive technology in the development of the educational metaverse, which is highly anticipated to create a new dimension for the teaching and learning environment, foster a new value system for the discipline of educational technology, and more effectively and efficiently achieve the grand educational blueprint of the United Nations’ Sustainable Development Goals (Zhang et al. 2022 ; Li and Yu, 2023 ).

Hotspot evolution analysis (RQ3)

The examination of keyword evolution reveals a consistent trend in the advancement of digital technology education application research. The emergence and transformation of keywords serve as indicators of the varying research interests in this field. Thus, the utilization of the burst detection function available in CiteSpace allowed for the identification of the top 10 burst words that exhibited a high level of burst strength. This outcome is illustrated in Table 7 .

According to the results presented in Table 7 , the explosive terminology within the realm of digital technology education research has exhibited a concentration mainly between the years 2018 and 2022. Prior to this time frame, the emerging keywords were limited to “information technology” and “computer”. Notably, among them, computer, as an emergent keyword, has always had a high explosive intensity from 2008 to 2018, which reflects the important position of computer in digital technology and is the main carrier of many digital technologies such as Learning Management Systems (LMS) and Assessment and Feedback systems (Barlovits et al. 2022 ).

Since 2018, an increasing number of research studies have focused on evaluating the capabilities of learners to accept, apply, and comprehend digital technologies. As indicated by the use of terms such as “digital literacy” and “digital skill,” the assessment of learners’ digital literacy has become a critical task. Scholarly efforts have been directed towards the development of literacy assessment tools and the implementation of empirical assessments. Furthermore, enhancing the digital literacy of both learners and educators has garnered significant attention. (Nagle, 2018 ; Yu, 2022 ). Simultaneously, given the widespread use of various digital technologies in different formal and informal learning settings, promoting learners’ digital skills has become a crucial objective for contemporary schools (Nygren et al. 2019 ; Forde and OBrien, 2022 ).

Since 2020, the field of applied research on digital technology education has witnessed the emergence of three new hotspots, all of which have been affected to some extent by the pandemic. Firstly, digital technology has been widely applied in physical education, which is one of the subjects that has been severely affected by the pandemic (Parris et al. 2022 ; Jiang and Ning, 2022 ). Secondly, digital transformation has become an important measure for most schools, especially higher education institutions, to cope with the impact of the pandemic globally (García-Morales et al. 2021 ). Although the concept of digital transformation was proposed earlier, the COVID-19 pandemic has greatly accelerated this transformation process. Educational institutions must carefully redesign their educational products to face this new situation, providing timely digital learning methods, environments, tools, and support systems that have far-reaching impacts on modern society (Krishnamurthy, 2020 ; Salas-Pilco et al. 2022 ). Moreover, the professional development of teachers has become a key mission of educational institutions in the post-pandemic era. Teachers need to have a certain level of digital literacy and be familiar with the tools and online teaching resources used in online teaching, which has become a research hotspot today. Organizing digital skills training for teachers to cope with the application of emerging technologies in education is an important issue for teacher professional development and lifelong learning (Garzón-Artacho et al. 2021 ). As the main organizers and practitioners of emergency remote teaching (ERT) during the pandemic, teachers must put cognitive effort into their professional development to ensure effective implementation of ERT (Romero-Hall and Jaramillo Cherrez, 2022 ).

The burst word “digital transformation” reveals that we are in the midst of an ongoing digital technology revolution. With the emergence of innovative digital technologies such as ChatGPT and Microsoft 365 Copilot, technology trends will continue to evolve, albeit unpredictably. While the impact of these advancements on school education remains uncertain, it is anticipated that the widespread integration of technology will significantly affect the current education system. Rejecting emerging technologies without careful consideration is unwise. Like any revolution, the technological revolution in the education field has both positive and negative aspects. Detractors argue that digital technology disrupts learning and memory (Baron, 2021 ) or causes learners to become addicted and distracted from learning (Selwyn and Aagaard, 2020 ). On the other hand, the prudent use of digital technology in education offers a glimpse of a golden age of open learning. Educational leaders and practitioners have the opportunity to leverage cutting-edge digital technologies to address current educational challenges and develop a rational path for the sustainable and healthy growth of education.

Discussion on performance analysis (RQ1)

The field of digital technology education application research has experienced substantial growth since the turn of the century, a phenomenon that is quantifiably apparent through an analysis of authorship, country/region contributions, and institutional engagement. This expansion reflects the increased integration of digital technologies in educational settings and the heightened scholarly interest in understanding and optimizing their use.

Discussion on authorship productivity in digital technology education research

The authorship distribution within digital technology education research is indicative of the field’s intellectual structure and depth. A primary figure in this domain is Neil Selwyn, whose substantial citation rate underscores the profound impact of his work. His focus on the implications of digital technology in higher education and educational sociology has proven to be seminal. Selwyn’s research trajectory, especially the exploration of spatiotemporal extensions of education through technology, provides valuable insights into the multifaceted role of digital tools in learning processes (Selwyn et al. 2019 ).

Other notable contributors, like Henderson and Edwards, present diversified research interests, such as the impact of digital technologies during the pandemic and their application in early childhood education, respectively. Their varied focuses highlight the breadth of digital technology education research, encompassing pedagogical innovation, technological adaptation, and policy development.

Discussion on country/region-level productivity and collaboration

At the country/region level, the United Kingdom, specifically England, emerges as a leading contributor with 92 published papers and a significant citation count. This is closely followed by Australia and the United States, indicating a strong English-speaking research axis. Such geographical concentration of scholarly output often correlates with investment in research and development, technological infrastructure, and the prevalence of higher education institutions engaging in cutting-edge research.

China’s notable inclusion as the only non-Western country among the top contributors to the field suggests a growing research capacity and interest in digital technology in education. However, the lower average citation per paper for China could reflect emerging engagement or different research focuses that may not yet have achieved the same international recognition as Western counterparts.

The chord diagram analysis furthers this understanding, revealing dense interconnections between countries like the United States, China, and England, which indicates robust collaborations. Such collaborations are fundamental in addressing global educational challenges and shaping international research agendas.

Discussion on institutional-level contributions to digital technology education

Institutional productivity in digital technology education research reveals a constellation of universities driving the field forward. Monash University and the Australian Catholic University have the highest publication output, signaling Australia’s significant role in advancing digital education research. The University of Oslo’s remarkable average citation count per publication indicates influential research contributions, potentially reflecting high-quality studies that resonate with the broader academic community.

The strong showing of UK institutions, including the University of London, The Open University, and the University of Cambridge, reinforces the UK’s prominence in this research field. Such institutions are often at the forefront of pedagogical innovation, benefiting from established research cultures and funding mechanisms that support sustained inquiry into digital education.

Discussion on journal publication analysis

An examination of journal outputs offers a lens into the communicative channels of the field’s knowledge base. Journals such as Education and Information Technologies , Computers & Education , and the British Journal of Educational Technology not only serve as the primary disseminators of research findings but also as indicators of research quality and relevance. The impact factor (IF) serves as a proxy for the quality and influence of these journals within the academic community.

The high citation counts for articles published in Computers & Education suggest that research disseminated through this medium has a wide-reaching impact and is of particular interest to the field. This is further evidenced by its significant IF of 11.182, indicating that the journal is a pivotal platform for seminal work in the application of digital technology in education.

The authorship, regional, and institutional productivity in the field of digital technology education application research collectively narrate the evolution of this domain since the turn of the century. The prominence of certain authors and countries underscores the importance of socioeconomic factors and existing academic infrastructure in fostering research productivity. Meanwhile, the centrality of specific journals as outlets for high-impact research emphasizes the role of academic publishing in shaping the research landscape.

As the field continues to grow, future research may benefit from leveraging the collaborative networks that have been elucidated through this analysis, perhaps focusing on underrepresented regions to broaden the scope and diversity of research. Furthermore, the stabilization of publication numbers in recent years invites a deeper exploration into potential plateaus in research trends or saturation in certain sub-fields, signaling an opportunity for novel inquiries and methodological innovations.

Discussion on the evolutionary trends (RQ2)

The evolution of the research field concerning the application of digital technology in education over the past two decades is a story of convergence, diversification, and transformation, shaped by rapid technological advancements and shifting educational paradigms.

At the turn of the century, the inception of digital technology in education was largely exploratory, with a focus on how emerging computer technologies could be harnessed to enhance traditional learning environments. Research from this early period was primarily descriptive, reflecting on the potential and challenges of incorporating digital tools into the educational setting. This phase was critical in establishing the fundamental discourse that would guide subsequent research, as it set the stage for understanding the scope and impact of digital technology in learning spaces (Wang et al. 2023 ).

As the first decade progressed, the narrative expanded to encompass the pedagogical implications of digital technologies. This was a period of conceptual debates, where terms like “digital natives” and “disruptive pedagogy” entered the academic lexicon, underscoring the growing acknowledgment of digital technology as a transformative force within education (Bennett and Maton, 2010 ). During this time, the research began to reflect a more nuanced understanding of the integration of technology, considering not only its potential to change where and how learning occurred but also its implications for educational equity and access.

In the second decade, with the maturation of internet connectivity and mobile technology, the focus of research shifted from theoretical speculations to empirical investigations. The proliferation of digital devices and the ubiquity of social media influenced how learners interacted with information and each other, prompting a surge in studies that sought to measure the impact of these tools on learning outcomes. The digital divide and issues related to digital literacy became central concerns, as scholars explored the varying capacities of students and educators to engage with technology effectively.

Throughout this period, there was an increasing emphasis on the individualization of learning experiences, facilitated by adaptive technologies that could cater to the unique needs and pacing of learners (Jing et al. 2023a ). This individualization was coupled with a growing recognition of the importance of collaborative learning, both online and offline, and the role of digital tools in supporting these processes. Blended learning models, which combined face-to-face instruction with online resources, emerged as a significant trend, advocating for a balance between traditional pedagogies and innovative digital strategies.

The later years, particularly marked by the COVID-19 pandemic, accelerated the necessity for digital technology in education, transforming it from a supplementary tool to an essential platform for delivering education globally (Mo et al. 2022 ; Mustapha et al. 2021 ). This era brought about an unprecedented focus on online learning environments, distance education, and virtual classrooms. Research became more granular, examining not just the pedagogical effectiveness of digital tools, but also their role in maintaining continuity of education during crises, their impact on teacher and student well-being, and their implications for the future of educational policy and infrastructure.

Across these two decades, the research field has seen a shift from examining digital technology as an external addition to the educational process, to viewing it as an integral component of curriculum design, instructional strategies, and even assessment methods. The emergent themes have broadened from a narrow focus on specific tools or platforms to include wider considerations such as data privacy, ethical use of technology, and the environmental impact of digital tools.

Moreover, the field has moved from considering the application of digital technology in education as a primarily cognitive endeavor to recognizing its role in facilitating socio-emotional learning, digital citizenship, and global competencies. Researchers have increasingly turned their attention to the ways in which technology can support collaborative skills, cultural understanding, and ethical reasoning within diverse student populations.

In summary, the past over twenty years in the research field of digital technology applications in education have been characterized by a progression from foundational inquiries to complex analyses of digital integration. This evolution has mirrored the trajectory of technology itself, from a facilitative tool to a pervasive ecosystem defining contemporary educational experiences. As we look to the future, the field is poised to delve into the implications of emerging technologies like AI, AR, and VR, and their potential to redefine the educational landscape even further. This ongoing metamorphosis suggests that the application of digital technology in education will continue to be a rich area of inquiry, demanding continual adaptation and forward-thinking from educators and researchers alike.

Discussion on the study of research hotspots (RQ3)

The analysis of keyword evolution in digital technology education application research elucidates the current frontiers in the field, reflecting a trajectory that is in tandem with the rapidly advancing digital age. This landscape is sculpted by emergent technological innovations and shaped by the demands of an increasingly digital society.

Interdisciplinary integration and pedagogical transformation

One of the frontiers identified from recent keyword bursts includes the integration of digital technology into diverse educational contexts, particularly noted with the keyword “physical education.” The digitalization of disciplines traditionally characterized by physical presence illustrates the pervasive reach of technology and signifies a push towards interdisciplinary integration where technology is not only a facilitator but also a transformative agent. This integration challenges educators to reconceptualize curriculum delivery to accommodate digital tools that can enhance or simulate the physical aspects of learning.

Digital literacy and skills acquisition

Another pivotal frontier is the focus on “digital literacy” and “digital skill”, which has intensified in recent years. This suggests a shift from mere access to technology towards a comprehensive understanding and utilization of digital tools. In this realm, the emphasis is not only on the ability to use technology but also on critical thinking, problem-solving, and the ethical use of digital resources (Yu, 2022 ). The acquisition of digital literacy is no longer an additive skill but a fundamental aspect of modern education, essential for navigating and contributing to the digital world.

Educational digital transformation

The keyword “digital transformation” marks a significant research frontier, emphasizing the systemic changes that education institutions must undergo to align with the digital era (Romero et al. 2021 ). This transformation includes the redesigning of learning environments, pedagogical strategies, and assessment methods to harness digital technology’s full potential. Research in this area explores the complexity of institutional change, addressing the infrastructural, cultural, and policy adjustments needed for a seamless digital transition.

Engagement and participation

Further exploration into “engagement” and “participation” underscores the importance of student-centered learning environments that are mediated by technology. The current frontiers examine how digital platforms can foster collaboration, inclusivity, and active learning, potentially leading to more meaningful and personalized educational experiences. Here, the use of technology seeks to support the emotional and cognitive aspects of learning, moving beyond the transactional view of education to one that is relational and interactive.

Professional development and teacher readiness

As the field evolves, “professional development” emerges as a crucial area, particularly in light of the pandemic which necessitated emergency remote teaching. The need for teacher readiness in a digital age is a pressing frontier, with research focusing on the competencies required for educators to effectively integrate technology into their teaching practices. This includes familiarity with digital tools, pedagogical innovation, and an ongoing commitment to personal and professional growth in the digital domain.

Pandemic as a catalyst

The recent pandemic has acted as a catalyst for accelerated research and application in this field, particularly in the domains of “digital transformation,” “professional development,” and “physical education.” This period has been a litmus test for the resilience and adaptability of educational systems to continue their operations in an emergency. Research has thus been directed at understanding how digital technologies can support not only continuity but also enhance the quality and reach of education in such contexts.

Ethical and societal considerations

The frontier of digital technology in education is also expanding to consider broader ethical and societal implications. This includes issues of digital equity, data privacy, and the sociocultural impact of technology on learning communities. The research explores how educational technology can be leveraged to address inequities and create more equitable learning opportunities for all students, regardless of their socioeconomic background.

Innovation and emerging technologies

Looking forward, the frontiers are set to be influenced by ongoing and future technological innovations, such as artificial intelligence (AI) (Wu and Yu, 2023 ; Chen et al. 2022a ). The exploration into how these technologies can be integrated into educational practices to create immersive and adaptive learning experiences represents a bold new chapter for the field.

In conclusion, the current frontiers of research on the application of digital technology in education are multifaceted and dynamic. They reflect an overarching movement towards deeper integration of technology in educational systems and pedagogical practices, where the goals are not only to facilitate learning but to redefine it. As these frontiers continue to expand and evolve, they will shape the educational landscape, requiring a concerted effort from researchers, educators, policymakers, and technologists to navigate the challenges and harness the opportunities presented by the digital revolution in education.

Conclusions and future research

Conclusions.

The utilization of digital technology in education is a research area that cuts across multiple technical and educational domains and continues to experience dynamic growth due to the continuous progress of technology. In this study, a systematic review of this field was conducted through bibliometric techniques to examine its development trajectory. The primary focus of the review was to investigate the leading contributors, productive national institutions, significant publications, and evolving development patterns. The study’s quantitative analysis resulted in several key conclusions that shed light on this research field’s current state and future prospects.

(1) The research field of digital technology education applications has entered a stage of rapid development, particularly in recent years due to the impact of the pandemic, resulting in a peak of publications. Within this field, several key authors (Selwyn, Henderson, Edwards, etc.) and countries/regions (England, Australia, USA, etc.) have emerged, who have made significant contributions. International exchanges in this field have become frequent, with a high degree of internationalization in academic research. Higher education institutions in the UK and Australia are the core productive forces in this field at the institutional level.

(2) Education and Information Technologies , Computers & Education , and the British Journal of Educational Technology are notable journals that publish research related to digital technology education applications. These journals are affiliated with the research field of educational technology and provide effective communication platforms for sharing digital technology education applications.

(3) Over the past two decades, research on digital technology education applications has progressed from its early stages of budding, initial development, and critical exploration to accelerated transformation, and it is currently approaching maturity. Technological progress and changes in the times have been key driving forces for educational transformation and innovation, and both have played important roles in promoting the continuous development of education.

(4) Influenced by the pandemic, three emerging frontiers have emerged in current research on digital technology education applications, which are physical education, digital transformation, and professional development under the promotion of digital technology. These frontier research hotspots reflect the core issues that the education system faces when encountering new technologies. The evolution of research hotspots shows that technology breakthroughs in education’s original boundaries of time and space create new challenges. The continuous self-renewal of education is achieved by solving one hotspot problem after another.

The present study offers significant practical implications for scholars and practitioners in the field of digital technology education applications. Firstly, it presents a well-defined framework of the existing research in this area, serving as a comprehensive guide for new entrants to the field and shedding light on the developmental trajectory of this research domain. Secondly, the study identifies several contemporary research hotspots, thus offering a valuable decision-making resource for scholars aiming to explore potential research directions. Thirdly, the study undertakes an exhaustive analysis of published literature to identify core journals in the field of digital technology education applications, with Sustainability being identified as a promising open access journal that publishes extensively on this topic. This finding can potentially facilitate scholars in selecting appropriate journals for their research outputs.

Limitation and future research

Influenced by some objective factors, this study also has some limitations. First of all, the bibliometrics analysis software has high standards for data. In order to ensure the quality and integrity of the collected data, the research only selects the periodical papers in SCIE and SSCI indexes, which are the core collection of Web of Science database, and excludes other databases, conference papers, editorials and other publications, which may ignore some scientific research and original opinions in the field of digital technology education and application research. In addition, although this study used professional software to carry out bibliometric analysis and obtained more objective quantitative data, the analysis and interpretation of data will inevitably have a certain subjective color, and the influence of subjectivity on data analysis cannot be completely avoided. As such, future research endeavors will broaden the scope of literature screening and proactively engage scholars in the field to gain objective and state-of-the-art insights, while minimizing the adverse impact of personal subjectivity on research analysis.

Data availability

The datasets analyzed during the current study are available in the Dataverse repository: https://doi.org/10.7910/DVN/F9QMHY

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Acknowledgements

This research was supported by the Zhejiang Provincial Social Science Planning Project, “Mechanisms and Pathways for Empowering Classroom Teaching through Learning Spaces under the Strategy of High-Quality Education Development”, the 2022 National Social Science Foundation Education Youth Project “Research on the Strategy of Creating Learning Space Value and Empowering Classroom Teaching under the background of ‘Double Reduction’” (Grant No. CCA220319) and the National College Student Innovation and Entrepreneurship Training Program of China (Grant No. 202310337023).

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College of Humanities and Social Sciences, Beihang University, Beijing, China

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Wang, C., Chen, X., Yu, T. et al. Education reform and change driven by digital technology: a bibliometric study from a global perspective. Humanit Soc Sci Commun 11 , 256 (2024). https://doi.org/10.1057/s41599-024-02717-y

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A meta-analysis of learners’ continuance intention toward online education platforms.

• Chengliang Wang

Education and Information Technologies (2024)

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New advances in technology are upending education, from the recent debut of new artificial intelligence (AI) chatbots like ChatGPT to the growing accessibility of virtual-reality tools that expand the boundaries of the classroom. For educators, at the heart of it all is the hope that every learner gets an equal chance to develop the skills they need to succeed. But that promise is not without its pitfalls.

“Technology is a game-changer for education – it offers the prospect of universal access to high-quality learning experiences, and it creates fundamentally new ways of teaching,” said Dan Schwartz, dean of Stanford Graduate School of Education (GSE), who is also a professor of educational technology at the GSE and faculty director of the Stanford Accelerator for Learning . “But there are a lot of ways we teach that aren’t great, and a big fear with AI in particular is that we just get more efficient at teaching badly. This is a moment to pay attention, to do things differently.”

For K-12 schools, this year also marks the end of the Elementary and Secondary School Emergency Relief (ESSER) funding program, which has provided pandemic recovery funds that many districts used to invest in educational software and systems. With these funds running out in September 2024, schools are trying to determine their best use of technology as they face the prospect of diminishing resources.

Here, Schwartz and other Stanford education scholars weigh in on some of the technology trends taking center stage in the classroom this year.

AI in the classroom

In 2023, the big story in technology and education was generative AI, following the introduction of ChatGPT and other chatbots that produce text seemingly written by a human in response to a question or prompt. Educators immediately worried that students would use the chatbot to cheat by trying to pass its writing off as their own. As schools move to adopt policies around students’ use of the tool, many are also beginning to explore potential opportunities – for example, to generate reading assignments or coach students during the writing process.

AI can also help automate tasks like grading and lesson planning, freeing teachers to do the human work that drew them into the profession in the first place, said Victor Lee, an associate professor at the GSE and faculty lead for the AI + Education initiative at the Stanford Accelerator for Learning. “I’m heartened to see some movement toward creating AI tools that make teachers’ lives better – not to replace them, but to give them the time to do the work that only teachers are able to do,” he said. “I hope to see more on that front.”

He also emphasized the need to teach students now to begin questioning and critiquing the development and use of AI. “AI is not going away,” said Lee, who is also director of CRAFT (Classroom-Ready Resources about AI for Teaching), which provides free resources to help teach AI literacy to high school students across subject areas. “We need to teach students how to understand and think critically about this technology.”

Immersive environments

The use of immersive technologies like augmented reality, virtual reality, and mixed reality is also expected to surge in the classroom, especially as new high-profile devices integrating these realities hit the marketplace in 2024.

The educational possibilities now go beyond putting on a headset and experiencing life in a distant location. With new technologies, students can create their own local interactive 360-degree scenarios, using just a cell phone or inexpensive camera and simple online tools.

“This is an area that’s really going to explode over the next couple of years,” said Kristen Pilner Blair, director of research for the Digital Learning initiative at the Stanford Accelerator for Learning, which runs a program exploring the use of virtual field trips to promote learning. “Students can learn about the effects of climate change, say, by virtually experiencing the impact on a particular environment. But they can also become creators, documenting and sharing immersive media that shows the effects where they live.”

Integrating AI into virtual simulations could also soon take the experience to another level, Schwartz said. “If your VR experience brings me to a redwood tree, you could have a window pop up that allows me to ask questions about the tree, and AI can deliver the answers.”

Gamification

Another trend expected to intensify this year is the gamification of learning activities, often featuring dynamic videos with interactive elements to engage and hold students’ attention.

“Gamification is a good motivator, because one key aspect is reward, which is very powerful,” said Schwartz. The downside? Rewards are specific to the activity at hand, which may not extend to learning more generally. “If I get rewarded for doing math in a space-age video game, it doesn’t mean I’m going to be motivated to do math anywhere else.”

Gamification sometimes tries to make “chocolate-covered broccoli,” Schwartz said, by adding art and rewards to make speeded response tasks involving single-answer, factual questions more fun. He hopes to see more creative play patterns that give students points for rethinking an approach or adapting their strategy, rather than only rewarding them for quickly producing a correct response.

Data-gathering and analysis

The growing use of technology in schools is producing massive amounts of data on students’ activities in the classroom and online. “We’re now able to capture moment-to-moment data, every keystroke a kid makes,” said Schwartz – data that can reveal areas of struggle and different learning opportunities, from solving a math problem to approaching a writing assignment.

But outside of research settings, he said, that type of granular data – now owned by tech companies – is more likely used to refine the design of the software than to provide teachers with actionable information.

The promise of personalized learning is being able to generate content aligned with students’ interests and skill levels, and making lessons more accessible for multilingual learners and students with disabilities. Realizing that promise requires that educators can make sense of the data that’s being collected, said Schwartz – and while advances in AI are making it easier to identify patterns and findings, the data also needs to be in a system and form educators can access and analyze for decision-making. Developing a usable infrastructure for that data, Schwartz said, is an important next step.

With the accumulation of student data comes privacy concerns: How is the data being collected? Are there regulations or guidelines around its use in decision-making? What steps are being taken to prevent unauthorized access? In 2023 K-12 schools experienced a rise in cyberattacks, underscoring the need to implement strong systems to safeguard student data.

Technology is “requiring people to check their assumptions about education,” said Schwartz, noting that AI in particular is very efficient at replicating biases and automating the way things have been done in the past, including poor models of instruction. “But it’s also opening up new possibilities for students producing material, and for being able to identify children who are not average so we can customize toward them. It’s an opportunity to think of entirely new ways of teaching – this is the path I hope to see.”

5 Ways to Use Technology to Improve Teaching and Learning

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Technology has played a critical role in sustaining schools during the pandemic: Record numbers of students now have their own school-issued digital devices, educators have become more-critical evaluators of technology tools, and a hard push is underway at the federal, state, and local levels to get all homes connected to high-speed internet.

But making all these developments translate into better use of technology in schools will not be easy.

Using in-depth reporting combined with exclusive EdWeek Research Center survey data from teachers, principals, and district leaders, Education Week’s annual Technology Counts report examines these challenges.

Below is an outline of the tech priorities schools must address now and next school year, with links to helpful resources for how to tackle those challenges.

1. Getting virtual instruction right

Teachers, principals, and district leaders should be thinking hard about how to make remote learning better, especially if they are continuing to offer it even as most students have returned to school buildings. Read the story, here.

2. Connecting SEL and technology

Social media, virtual learning, online gaming, and ubiquitous devices present new social challenges for kids. So, what social-emotional skills do they need to flourish in an increasingly tech-centric world, and are schools teaching them? Learn more, here .

3. Cutting down on excessive screen time

Without even counting digital instruction, the amount of time teenagers and tweens spend staring at computer screens rivals how much time they would spend working at a full- or a part-time job. Educators and children’s health experts alike argue students need more support to prevent the overuse of technology from leading to unhealthy behaviors in the classroom. Read more, here .

4. Protecting student data

Student data privacy encompasses a broad range of considerations, from students’ own smartphones, to classroom applications discovered and embraced by teachers, to district-level data systems, to state testing programs. Here’s why schools are struggling to protect that data .

5. Using artificial intelligence in smart ways

Schools are embracing education technologies that use artificial intelligence for everything from teaching math to optimizing bus routes. But how can educators know if the data and design processes those products rely on have been skewed by racial bias? And what happens if they’re afraid to ask? Learn more here .

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Digital learning and transformation of education

Digital technologies have evolved from stand-alone projects to networks of tools and programmes that connect people and things across the world, and help address personal and global challenges. Digital innovation has demonstrated powers to complement, enrich and transform education, and has the potential to speed up progress towards Sustainable Development Goal 4 (SDG 4) for education and transform modes of provision of universal access to learning. It can enhance the quality and relevance of learning, strengthen inclusion, and improve education administration and governance. In times of crises, distance learning can mitigate the effects of education disruption and school closures.

What you need to know about digital learning and transformation of education

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or 63%of the world’s population, were using the Internet in 2021

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How to use technology to help teachers be better and to make life better for teachers

David evans.

Teachers matter enormously to student learning. Teachers deliver academic knowledge. Teachers impart model socioemotional skills. Good teachers boost students’ long-term life outcomes. Teachers can inspire (and in another demonstration of their importance, in some cases, sadly, teachers can disappoint or even abuse ). 

Yet teachers, often lionized and occasionally villainized , are people. They enter the profession for a wide range of reasons, they have their own families to feed, and – like most professionals – they respond to incentives, support, accountability, and the quality of the management around them. In short, they are part of a system . 

Getting teacher policies right isn’t always easy, and sometimes education technology solutions can seem like a shortcut. It’s tempting to search for the perfect app that will “disrupt” the learning process and allow countries to “leapfrog” to high-quality, equitable education without having to engage with these complicated people near the center of the learning process. (Let’s keep learners at the actual center.) Education technology interventions have had both successes and failures . Even as the COVID crisis has heightened attention to education technology, many parts of the world lack the infrastructure for it have an extended, effective reach, with big implications for educational inequality .

In a recent note—“ Education Technology for Effective Teachers ”—I look for examples of how education technology—rather than seeking to circumvent teachers—can help teachers to be as effective as possible and make their jobs and lives easier in the process. Looking at a wide range of experiences, mostly in low- and middle-income countries, I identify and discuss four principles to guide investments in technology to boost teacher effectiveness.

Beyond these principles, which may seem obvious but which anyone who has worked in the implementation or evaluation of education technology can tell you are often not applied, I provide practical examples of six ways that education systems are using technology to support teachers. I summarize these in the table below, but you can find more country experiences in the note.

Technology is not the solution, but just like books and classrooms and blackboards, technological tools can help teachers to improve their skills, to use their skills most effectively, and to be accountable. These investments should never be made on the basis of evidence-free optimism but rather evidence-based realism in terms of systems’ capacity to maintain the technology, teacher willingness to engage the technology, and whether the technology will perform better than the cheaper, analog alternative.

(In Kenya, a tablet-based literacy program boosted learning, but no more so than the analog alternative and at higher cost.) 

But in cases where technology passes those tests, it can be a valuable complement to teachers. It can also make teachers’ jobs a little bit easier so they can focus their energy on teaching.

Further reading:

• For more on how this brief fits within the World Bank’s program for teachers, check out Saavedra’s blog post from earlier this month, “ Realizing the promise of effective teachers for every child – a global platform for successful teachers ”
• For more on how to foster effective teachers, check out Béteille’s and my approach paper “ Successful Teachers, Successful Students: Recruiting and Supporting Society’s Most Crucial Profession ” or the World Development Report 2018 chapter on teachers . 
• For a broader framework on how to apply education technology in systems (beyond its interactions with teachers), check out Ganimian, Vegas, and Hess’s 2020 report “ Realizing the Promise: How Can Education Technology Improve Learning for All? ”

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ORIGINAL RESEARCH article

Teaching and learning in times of covid-19: uses of digital technologies during school lockdowns.

• Department of Basic Psychology, Faculty of Psychology, Autonomous University of Madrid, Madrid, Spain

The closure of schools as a result of COVID-19 has been a critical global incident from which to rethink how education works in all our countries. Among the many changes generated by this crisis, all teaching became mediated by digital technologies. This paper intends to analyze the activities carried out during this time through digital technologies and the conceptions of teaching and learning that they reflect. We designed a Likert-type online questionnaire to measure the frequency of teaching activities. It was answered by 1,403 teachers from Spain (734 primary and 669 secondary education teachers). The proposed activities varied depending on the learning promoted (reproductive or constructive), the learning outcomes (verbal, procedural, or attitudinal), the type of assessment to which the activities were directed, and the presence of cooperative activities. The major result of this study was that teachers used reproductive activities more frequently than constructive ones. We also found that most activities were those favoring verbal and attitudinal learning. The cooperative activities were the least frequent. Finally, through a cluster analysis, we identified four teaching profiles depending on the frequency and type of digital technologies use: Passive, Active, Reproductive, and Interpretative. The variable that produced the most consistent differences was previous digital technologies use These results show that Information and Communication Technologies (ICT) uses are reproductive rather than constructive, which impedes effective digital technologies integration into the curriculum so that students gain 21st-century competencies.

Introduction

When schools were closed in most countries in March 2020 because of the COVID-19 pandemic, teachers had no other option but to change their classrooms into online learning spaces. It was a critical global incident. In research on identity and teacher training ( Tripp, 1993 ; Butterfield et al., 2005 ; Monereo, 2010 ), a critical incident is an unexpected situation that hinders the development of the planned activity and that, by exceeding a certain emotional threshold, puts the identity in crisis and obliges that teachers review their concepts, strategies, and feelings. Thus, these incidents can become meaningful resources for training and changing teaching and learning practices because they allow us to review our deep beliefs ( Monereo et al., 2015 ).

The critical global incident generated by the pandemic forced most teachers to assume virtual teaching where they had to use digital technologies, sometimes for the first time, to facilitate their students’ learning. The closure of schools as a consequence of COVID-19 led to substantial changes in education with profound consequences. Today we know that educational inequalities have widened ( Dorn et al., 2020 ), while students have suffered greater social and emotional imbalances ( Colao et al., 2020 ). In this context, families have also been more involved in the school education of their children ( Bubb and Jones, 2020 ). Moreover, concerning the objectives of this study, it has been necessary to rethink the teaching strategies in the new virtual classrooms. In fact, this research focuses precisely on analyzing the uses that teachers made of the digital technologies or Information and Communication Technologies (ICT) (from now on, we will use this acronym) during the confinement to become familiar with their practices and use them to review their conceptions of teaching and learning.

For several decades, many authors have argued that ICT as educational devices facilitate the adaptation of teaching to each student. Some argue this is because they can promote collaboration, interactivity, the use of multimedia codes, and greater control of learning by the learner (e.g., Jaffee, 1997 ; Collins and Halverson, 2009 ). In this way, their integration in the curriculum would contribute to the acquisition of 21st-century competencies (autonomy, collaboration, critical thinking, and problem-solving) that the OECD ( Ananiadou and Claro, 2009 ) links to the so-called “global competence” that should define the current education ( Ertmer et al., 2015 ).

However, after decades of use of ICT in classrooms, they have not fully achieved their promise to transform teaching and learning processes. The results of a lot of international studies are, in fact, quite discouraging, like those claimed by the PISA studies ( OECD, 2015 ). In its report, the OECD(2015 , p. 3) concludes that “the results also show no appreciable improvements in student achievement in reading, mathematics or science in the countries that had invested heavily in ICT for education.” Thus, Biagi and Loi (2013) found that the more education ICT uses reported, the less learning in reading, mathematics, and science achieved. These data caused even Andreas Schleicher, head and coordinator of PISA studies, to claim that “the reality is that technology is doing more harm than good in our schools today” ( Bagshaw, 2016 ).

These conclusions contrast with the results obtained in most of the experimental research on the effects of ICT on learning. A decade ago, after conducting a second-order meta-analysis of 25 meta-analyses, Tamim et al.(2011 , p. 14) found “a significant positive small to moderate effect size favoring the utilization of technology in the experimental condition over more traditional instruction (i.e., technology-free) in the control group,” a conclusion that is still valid today. Various studies and meta-analyses reflect moderate but positive effects on learning, whether for example from the use of touch screens in preschools ( Xie et al., 2018 ), from cell phones ( Alrasheedi et al., 2015 ; Sung et al., 2015 ) or video games ( Clark et al., 2016 ; Mayer, 2019 ). It has also been found that they favor collaboration in secondary education ( Corcelles Seuba and Castelló, 2015 ) or learning mathematics ( Li and Ma, 2010 ; Genlott and Grönlund, 2016 ), science ( Hennessy et al., 2007 ) or second languages ( Farías et al., 2010 ).

What is the reason for this disagreement between research conducted in experimental laboratories and large-scale studies? Many factors could explain this distance ( de Aldama, 2020 ). But one difference is that the experimental studies have been carefully designed and controlled to promote these forms of learning mentioned above, while the usual work in the classroom is mediated by the activity of teachers who, in most cases, have little training using ICT ( Sigalés et al., 2008 ). Several authors ( Gorder, 2008 ; Comi et al., 2017 ; Tondeur et al., 2017 ) conclude that it is not the ICT themselves that can transform the classroom and learning, but rather the use that teachers make of them. While the experimental studies mostly promote activities that encourage autonomous learning ( Collins and Halverson, 2009 ), the most widespread uses of ICT, as reflected in these international studies with more diverse samples, report other kinds of use whose benefits are more doubtful.

Different classifications of teachers’ use of ICT in the classroom have been proposed in recent years (e.g., Gorder, 2008 ; Mama and Hennessy, 2013 ; Comi et al., 2017 ). Tondeur et al. (2008a) differentiate three types of educational computer use: (a) basic computer skills; (b) use of computers as an information tool, and (c) use of them as a learning tool. Laying aside the acquisition of basic skills related to digital devices, learning is promoted by the last two uses that lead to second-order digital skills related to information management and its conversion into knowledge ( Fulton, 1997 ; Gorder, 2008 ). Thus, the distinction is usually made between two types of use. The first use is aimed at traditional teaching, focused on the transmission and access to information, and usually called teacher-centered use (although perhaps it should be called content-centered use). The second one, called student-centered use, promotes diverse competencies (autonomy, collaboration, critical thinking, argumentation, and problem-solving) and is part of the Global Competence characteristic of 21st-century education ( Ananiadou and Claro, 2009 ; OECD, 2019 , 2020 ). According to Tondeur et al. (2017) , integration of ICT in education requires assuming a constructivist conception of learning and adopting a student-centered approach in which the students manage the information through the ICT instead of, as in the more traditional approach (content-centered), it being the teacher who uses the ICT.

The experimental studies mentioned above show that student-centered approaches improve verbal earning, producing a better understanding of the subjects studied, promoting self-regulation of the learning processes themselves, and generating critical and collaborative attitudes toward knowledge. Thus, Comi et al.(2017 , pp 36–37), after analyzing data from different standardized assessments, conclude: “computer-based teaching practices increase student performance if they are aimed at increasing students’ awareness of ICT use and at improving their navigation critical skills, developing students’ ability to distinguish between relevant and irrelevant material and to access, locate, extract, evaluate, and organize digital information.” Besides, they also found a slight negative correlation between using ICT to convey information and academic performance.

In spite of these better results of adopting student-centered uses, the studies support that the most frequent uses in classrooms are still centered on the teachers, who indeed use ICT as a substitute for other more traditional resources to transmit information ( Loveless and Dore, 2002 ; Sigalés et al., 2008 ; de Aldama and Pozo, 2016 ). Even if what Ertmer (1999) called type I barriers are overcome, related to the availability of these technological resources and the working conditions in the centers, several studies show that there are other types II barriers that limit the use of ICT ( Ertmer et al., 2015 ); in particular, the conceptions about learning and teaching to the extent that they mediate the use of ICT ( Hermans et al., 2008 ).

Different studies have shown that these teachers’ beliefs about learning and teaching are the best predictor of the use made of ICT in the classroom ( Ertmer, 2005 ; Ertmer et al., 2015 ). Most of the work on these beliefs ( Hofer and Pintrich, 1997 , 2002 ; Pozo et al., 2006 ; Fives and Gill, 2015 ) identifies two types of conceptions: some closer to a reproductive vision of learning, which would be related to the teacher or content-centered teaching uses, and others nearer to constructivist perspectives, which promote student-centered teaching uses. Studies show teachers who have constructivist beliefs tend to use more ICT than those with more traditional beliefs ( Judson, 2006 ; Law and Chow, 2008 ; Ertmer et al., 2015 ). They also employ them in a more student-centered way, and their uses are oriented toward the development of problem-solving skills ( Tondeur et al., 2017 ). On the other hand, teachers with more traditional beliefs use them primarily to present information ( Ertmer et al., 2012 ).

However, the relationship between conceptions and educational practices is not so clear and linear ( Liu, 2011 ; Fives and Buehl, 2012 ; Tsai and Chai, 2012 ; Mama and Hennessy, 2013 ; Ertmer et al., 2015 ; de Aldama and Pozo, 2016 ; de Aldama, 2020 ). Many studies show a mismatch between beliefs and practices, above all, when we refer to beliefs closer to constructivism that do not always correspond to constructive or student-centered practices. We can distinguish three types of arguments that explain the mismatches. First, the beliefs seem to be more complex and less dichotomous than what is assumed ( Ertmer et al., 2015 ). The studies comparing beliefs and practices tend to focus on the more extreme positions of the spectrum -reproductive vs. constructive beliefs-, despite research showing they are part of a continuum of intermediate beliefs between both aspects ( Hofer and Pintrich, 1997 , 2002 ; Pérez Echeverría et al., 2006 ). Thus, for example, the so-called interpretive beliefs maintain traditional reproductive epistemological positions. People who have these conceptions think that learning is an exact reflection of reality or the content which should be learned, whereas they also think teaching is mediated by cognitive processes of the learner which are based on his or her activity ( Pozo et al., 2006 ; López-Íñiguez and Pozo, 2014 ; Martín et al., 2014 ; Pérez Echeverría, in press ). Other examples of this belief can be found in the technological-reproductive conception described by Strauss and Shilony (1994) , which is close to a naïve information processing theory.

Second, we must acknowledge that neither teachers’ beliefs nor their educational practices remain stable but vary according to the teaching contexts. As Ertmer et al. (2015) claim, beliefs are not unidimensional, but teachers assume them in varying degrees and with different types of relationships. The teacher’s beliefs seem to be organized in profiles that gather aspects of the different theories about teaching and whose activation depends on the contextual demands ( Tondeur et al., 2008a ; Bautista et al., 2010 ; López-Íñiguez et al., 2014 ; Ertmer et al., 2015 ).

Third, we consider that this multidimensionality of beliefs makes them very difficult to measure or evaluate ( Pajares, 1992 ( Schraw and Olafson, 2015 ; see also Ertmer et al., 2015 ; Pérez Echeverría and Pozo, in press ), so perhaps different studies are measuring different components. For example, many studies focus on explicit beliefs, or “what teachers believe to be true” for learning, and therefore evaluate more the general ideas about what ICT-based education should be. Usually, these statements tend to be relatively more favorable to the advantages mentioned above. In this paper, we have chosen to analyze teachers’ stated practices as a means of addressing specific beliefs about teaching.

In addition to beliefs, other variables have been identified that influence the use of ICTs such as gender, age, educational level, or subject curriculum, with results that are usually inconclusive. Thus, while Mathews and Guarino (2000) found that men were more inclined toward the use of ICTs than women, in other studies no differences were found ( Gorder, 2008 ; Law and Chow, 2008 ). Similarly, other studies ( van Braak et al., 2004 ; Suárez et al., 2012 ) concluded that there was an inverse relationship between the age of the teachers and their interest in ICT, but other studies did not confirm this conclusion ( Gorder, 2008 ; Law and Chow, 2008 ; Inan and Lowther, 2010 ). Finally, the teaching experience gives equally ambiguous results; some papers report a negative relationship ( Mathews and Guarino, 2000 ; Baek et al., 2008 ; Inan and Lowther, 2010 ) while others find no relationship ( Gorder, 2008 ).

The influence of factors like educational level or curriculum subjects has also been analyzed. The data seem to be more conclusive regarding educational level: teachers in secondary education have more favorable attitudes toward ICT than teachers of earlier levels ( Gorder, 2008 ; Vanderlinde et al., 2010 ). However, the data are not so conclusive regarding the influence of curriculum subjects ( Williams et al., 2000 ; Gorder, 2008 ; Vanderlinde et al., 2010 ).

Although it will take time to understand what has happened in teaching during these months, many studies and proposals have analyzed the use of ICT in distance education. We can classify them into three types of research. The first type of analyses has measured the impact of classroom closures on the education of students, many of them focusing on their effects on inequality or the way different countries have dealt with this crisis ( Crawford et al., 2020 ; Reimers and Schleicher, 2020 ; Zhang et al., 2020 ). Second, studies have aimed at proposing principles that should guide the use of ICT in the classroom ( Ferdig et al., 2020 ; Rapanta et al., 2020 ; Sangrà et al., 2020 ). The last ones, which are close to the aims of this study, are focused on how teachers have used ICT for the COVID-19 crisis. Some of these studies have carried out qualitative case analyses in different contexts, institutions ( Koçoğlu and Tekdal, 2020 ; Rasmitadila et al., 2020 ), and even countries ( Hall et al., 2020 ; Iivari et al., 2020 ). However, others have resorted to the use of questionnaires applied to larger samples to inquire about the teaching experience for confined education ( Devitt et al., 2020 ; Luengo and Manso, 2020 ; Tartavulea et al., 2020 ; Trujillo-Sáez et al., 2020 ). These studies have concluded the most common use by teachers was to upload materials to a platform ( Tartavulea et al., 2020 ); the most activities were teacher-centered ( Koçoğlu and Tekdal, 2020 ); or the more constructivist the teachers are, the more ICT use is reported for confined education ( Luengo and Manso, 2020 ).

However, despite these indications, there has been no study that analyzes the activities and uses of ICT in school during confinement. What learning have teachers prioritized in this period? Has it been more oriented toward verbal, procedural, or attitudinal learning? ( Pozo, in press ). Through what activities, either more constructive or reproductive, have these learnings been promoted? Have the ICT been used to assess the accumulation of information or the global competencies in its management? What variables prompt carrying out one type of activity or another? These are some questions that have guided our research and are reflected in the following specific objectives.

1. Identifying the frequency with which Spanish teachers of primary, and compulsory and non-compulsory secondary education carried out activities using ICT during the pandemic, and how some variables influence this frequency (gender, teaching experience, previous ICT use, educational level, and curriculum subjects).

2. Analyzing the type of learning (reproductive or teacher-centered vs. constructive or student-centered) promoted most frequently by these teachers, as well as the influence of the variables mentioned.

3. Analyzing the types of outcomes (verbal learning, procedural learning, or attitudinal learning), assessment, and social organization promoted by the ICT and the possible influence of the mentioned variables.

4. Investigating if different teaching profiles can be identified in the use of ICT, as well as their relationship with the variables studied.

Regarding objective 1, as the contradictory results reviewed in the Introduction showed, it is difficult to sustain a concrete hypothesis. However, in the case of objective 2, as argued in the Introduction, we expect to find a higher frequency of reproductive activities (or teacher-centered) than constructive (student-centered). Along the same lines, concerning the third objective, we hope to find more activities oriented to verbal learning, reproductive assessment, and individual organization of tasks, with few activities based on cooperation between students. Finally, about objective 4, we hope to identify teacher profiles that differ in the frequency and type of activities proposed to their students and that these profiles are related to some of the demographic variables analyzed in the study.

Materials and Methods

Task and procedure.

To achieve these objectives, we designed a questionnaire on ICT through the Qualtrics software and sent telematically to various networks of teachers and primary and secondary education centers in Spain. For the construction of the questionnaire, we consulted different blogs where teachers shared the activities they were applying during the pandemic. The questionnaire was composed of two parts. In the first one, after participants gave informed consent, they were requested to provide personal and professional information (see Table 2 ). The second part comprised 36 items that described different types of teaching activities. Participants were asked to rate how often they carried them out on a Likert scale (1, Never; 2 Some days per month; 3, Some days per week; and 4, Every day). After the analysis of the methodologies carried out in the Introduction, we considered asking teachers what they were doing in their classrooms was the most accurate procedure to know the true practices they were carrying out. On the one hand, we wanted to avoid the bias of classic questionaries on conceptions that require teachers to express their agreement with some beliefs. On the other hand, the analysis of teachers’ actual practices in their classrooms would require a different, more qualitative work, with a smaller sample size.

As we show in Table 1 , these activities were directed toward reproductive and constructive learning and different types of learning outcomes (verbal, procedural, and attitudinal), assessment (usually called summative and formative assessment), and cooperative activities.

Table 1. Structure and examples of questionnaire items.

Table 2. Characteristics of the sample and variables.

Participants

The participants were primary and secondary education teachers who were working in Spain when they completed the questionnaire. In Spain, compulsory education is from 6 to 16 years. In primary education (6–12 years), a single generalist teacher imparts most of the subjects, while specialist teachers (music, physical education, foreign language, etc.) only attend class during the hours of their subjects. After compulsory secondary education, there is a non-compulsory secondary education (16–18 years old) that is taught in the same centers as compulsory secondary education and by the same teachers.

We used directories of emails from public, private schools, and high schools of Spain to get in contact with the participants. Besides, to encourage participation, we raffled 75 euros for the purchase of teaching materials among all participants. We collected 1,541 answers. We eliminated 52 of them because they belonged to people who were not teachers of primary or secondary education in Spain. Then, we removed 45 participants who completed the questionnaire in less than 5 min, insufficient time to read and complete it, and we excluded 41 participants who indicated the 3rd (“Some days per week”) or 4th option (“Every day”) in over 80% of the items. We argue this exclusion as it is unlikely that a teacher could carry out such a quantity of activities in the span of a week. The questionnaire has 36 activities, so doing over 80% of items with a frequency of a minimum some days per week implies carrying out almost 29 activities per week. We consider this is not possible in the pertaining virtual class context and noted several contradictions in the answers. Therefore, the final sample had 1,403 teachers (see Table 2 ). Note that the sum of all variables does not reach this total because some values were so unusual that they were not considered in the statistical analyses.

Data Analysis

To ensure the consistency of the questionnaire and the dimensions, a reliability analysis was carried out using Cronbach’s Alpha coefficient. The reliability of the scale was 0.90, the reproductive and constructive scales obtained alphas above 0.75, and the verbal, procedural, attitudinal, assessment, and cooperation dimensions got alphas above 0.65.

The 1, 2, and 3 objectives were analyzed with one and two-factor ANOVA. These factors can be both repeated measures and completely randomized, according to the characteristics of the variable. Besides, we carried out post hoc analysis in which the Tukey or Bonferroni correction was applied depending on whether the ANOVA was 1 or 2 factors, to see the differences between categories in the ANOVA analyses. However, post hoc analyses were only performed on the ANOVA of the two factors when the interaction effects were significant.

Finally, a cluster analysis was implemented to identify different teaching profiles (objective 4). Once identified, we created contingency tables and their corresponding Corrected Typified Residuals (CTR) to know which variables were related to each profile. Finally, we carried out ANOVA to analyze the differences between profiles according to each of the designed dimensions. All the statistical analyses were carried out using SPPS version 26.

The results are written referring to what the teachers were doing to facilitate reading. However, in all cases, we refer to declared activities.

Frequency of Activities Carried Out

Regarding the first objective, teachers performed the activities between Some days per week and Some days per month on average ( M = 2.44, SD = 0.50). However, this frequency varied according to teaching experience, educational level, curriculum subject, and previous ICT use. Gender did not produce differences (see Table 3 ). In the case of teaching experience, according to the post hoc tests, teachers with intermediate experience (from 16 to 25 years) carried out a lower number of activities than novice teachers (5 years or fewer) ( p < 0.05). In turn, teachers who taught children between 6 and 9 years old were also less active than the rest ( p < 0.01). Within primary education, the generalists, who spend more time with the same students, proposed more activities than the specialists ( p < 0.01). In secondary education, the teachers of Spanish language were more active than those of mathematics and physical education ( p < 0.01). Finally, there seems to be a positive linear relationship between previous ICT use and the amount of activity for confined education ( F = 61.66, p < 0.001).

Table 3. Influence of personal and professional variables on the frequency of activities.

Teaching Activities: Reproductive or Constructive?

Nevertheless, we were not so much interested in the total amount of activities carried out as in the type of learning they promoted (reproductive or constructive). For this, we proposed objective 2. The data was overwhelming. They showed much greater use of reproductive ( M = 2.79, SD = 0.50) than constructive ( M = 2.16, SD = 0.60) learning activities ( F = 2,217.91, p < 0.001, η p 2 = 0.61). This is the largest and most robust effect size in this study; it occurs in all groups and for all variables ( p < 0.001), although to a different degree, as shown in Table 4 .

Table 4. Influence of the different variables on the type of activity.

Post hoc results reveal that novice teachers (5 years or fewer), the most active group according to the previous analysis, performed more reproductive activities than teachers with experience from 16 to 25 years ( p < 0.01), the least active one. However, the most experienced teachers (more than 25 years) executed more constructive activities than those with intermediate experience (from 16 to 25 years) ( p < 0.05). The teachers of children between 6 and 9 years old did less reproductive and constructive activities ( p < 0.05) than the rest of the groups, with significant differences in all cases except in the case of the teachers of non-compulsory secondary education, who stated less reproductive activities than they did.

In secondary education, the mathematics teachers did less constructive activities than those of Spanish language and social sciences ( p < 0.05). In turn, physical education teachers performed less reproductive activities than the rest of their classmates ( p < 0.01).

Finally, the higher the previous ICT the teachers used, the higher the frequencies indicated by them in both reproductive ( F = 33.57, p < 0.001) and constructive activities ( F = 61.61, p < 0.001). Notwithstanding, the size of the observed effect shows greater differences in the case of constructive activities (reproductive, F = 13.94, p < 0.001, η p 2 = 0.29, vs. constructive, F = 25.60, p < 0.001, η p 2 = 0.95).

Learning Outcomes, Assessment, and Cooperation Dimensions

The third objective was to determine what kind of learning outcomes resulted from the activities. As we show in Figure 1 , the teachers focused more on verbal and attitudinal learning than on procedural ( F = 100.11, p < 0.001, η p 2 = 0.07). On the other hand, the mean responses of the assessment tasks were similar to those of verbal learning and attitudinal learning, but the cooperative activities were less frequent than the remainder ( p < 0.001), performed between never and some days per month ( M = 1.78; SD = 0.74). However, as we see in Table 5 , these results are mediated by the effect of some variables.

Figure 1. Average of the frequencies of each type of activity.

Table 5. Influence of different variables on the frequency of activities for each dimension.

Post hoc analyses show that men carried out more activities focused on procedural learning than women ( p < 0.05), who in turn promoted more activities related to attitudinal learning ( p < 0.001). Men also carried out more cooperation activities than women ( p < 0.01), but there were no differences among them in the Assessment activities. However, the only effect related to teaching experience shows that less experienced teachers (5 years or fewer) carried out more assessment activities than teachers with intermediate experience (from 16 to 25 years) ( p < 0.05).

The teachers of the youngest children (6–9 years old) carried out more activities aimed at attitudinal learning ( p < 0.05) and fewer at procedural learning ( p < 0.01) than the rest of the teachers. Interestingly, the activities aimed at attitudinal learning decreased progressively when the educational level increased, with differences between the upper level of primary education (9–12 years) and secondary education ( p < 0.001). At the same time, the older the students were, the more verbal learning activities they performed, with differences between the first years of primary education (6–9 years) and secondary education (12–18) ( p < 0.05). Besides, the assessment and cooperation activities became more frequent as the educational levels advanced, with differences in both cases between the teachers of the first years of primary education ( p < 0.01) and the last years of primary education and non-compulsory secondary education ( p < 0.05).

In secondary education, verbal learning predominates in almost every subject. However, the Spanish language and foreign language teachers also carried out many activities aimed at attitudinal learning. Only in technology were more activities aimed at procedural learning executed compared to the others ( p < 0.05). At the same time, the mathematics teachers stand out for their little use of cooperation activities. To sum up, the activities aimed at verbal learning increase their frequency when the educational level increases, while attitudinal learning decreases. Nevertheless, the characteristics of each subject have some influence on the increases among educational levels. The cooperation activities also increase, although their frequency is still small. Finally, again, the higher the previous ICT use, the higher the frequency of all activities during the pandemic ( p < 0.001).

But all these differences become more meaningful when we look at the type of learning (reproductive or constructive) that is promoted by these activities. Again, as we see in Figure 2 , there is a considerable difference between the reproductive and constructive activities regardless of the dimension involved (see Table 6 ), a trend also confirmed by the low frequency of cooperation activities that, by their nature, promote constructive learning. It is remarkable that the highest differences between both scales happen in attitudinal learning. In fact, the most frequent activities in the questionnaire involved attitudinal reproductive learning.

Figure 2. Average of the reproductive and constructive activities in each dimension.

Table 6. Differences between reproductive and constructive activities in the dimensions.

Profiles of Teachers in the Use of ICT

Our final objective was to identify possible profiles in the use of ICT during confined education. For this purpose, we proceeded with a cluster analysis that allowed us to identify different teaching profiles as we showed in Figure 3 . After testing clusters of three centers in which the groups only differed in the number of activities, we executed a four centers cluster, which showed differences in the amount of activity ( F = 2,220.33, p < 0.001, η p 2 = 0.83) and the mean differences between reproductive and constructive activities ( F = 310.39, p < 0.001, η p 2 = 0.40).

Figure 3. Frequency of use of reproductive and constructive activities for each teachers’ profile.

• The first profile (“Passive”) was composed of 327 teachers who were characterized by a very low activity (MD = 0.63, SD = 0.02, p < 0.001), essentially reproductive ( M = 2.15, SD = 0.35) and scarcely constructive ( M = 1.52, SD = 0.29).

• The second profile (“Active”) was composed of 424 teachers, was the most numerous. It had a very similar pattern to the previous one, focused mainly on reproductive activities ( M = 2.82, SD = 0.33) rather than constructive ( M = 2.41, SD = 0.21) but with a higher level of activity ( MD = 0.41, SD = 0.02, p < 0.001).

• The third profile (“Reproductive”) was composed of 263 teachers with a similar level of activity to the previous one. However, they have a relatively higher frequency of reproductive activities ( M = 2.93, SD = 0.29) with hardly any constructive activities ( M = 1.82, SD = 0.24).

• The fourth profile (“Interpretative”) which was composed of 389 teachers, was corresponded to the most active teachers. This profile had the smallest differences between reproductive ( M = 3.32, SD = 0.29) and constructive activities ( M = 3.04, SD = 0.31), ( MD = 0.29, SD = 0.02, p < 0.001). According to the terminology used in the introduction, we have called it Interpretative because it integrated both types of activities.

Among the different profiles, we found systematic differences in the dimensions and types of learning. In fact, all differences among profiles were significant ( p < 0.01) except between the Active and Reproductive profiles in verbal, procedural, and attitudinal reproductive learning. There were also no differences between the Passive and Reproductive profiles in cooperative activities because of their low frequency in both groups. On the other hand, teachers in the Interpretive profile carried out more activities in all dimensions than the rest of the groups; the teachers of the Passive profile did fewer tasks than the others (except in the cases already indicated) and finally, the other two profiles maintained an intermediate level of activity, with the difference that the teachers of the Reproductive profile focused almost exclusively on reproductive activities as we see in Figure 4 .

Figure 4. Use of each dimension for each teachers’ profile.

The distribution of teachers in each of the four profiles varied depending on educational level (χ 2 = 29.57, p < 0.001), primary curriculum subjects (χ 2 = 60.97, p < 0.001), secondary curriculum subjects (χ 2 = 60.97, p < 0.001), and previous ICT use (χ 2 = 77.46, p < 0.001). We did not find any relationship with gender or teaching experience, the variables with the least influence in the study.

As we see in Table 7 , the first profile or Passive was over-represented by teachers of children aged 6–9, and teachers of non-compulsory secondary education were under-represented. Between the primary education teachers, specialists predominated, and there were practically no generalist teachers. The only secondary education teachers that appeared in this profile were physical education ones. Finally, there is a significant number of teachers who had not used ICT with their students before the confinement, and there was hardly any representation of those who had most used them.

Table 7. Variables related to each of the profiles.

The second or Active profile is distributed homogeneously way among the different educational levels. It is predominantly formed by secondary education teachers of Spanish language and social sciences. In the third or Reproductive profile, secondary education teachers who taught mathematics, and those who had never used ITC in the classroom were over-represented.

The fourth or Interpretative profile, characterized by integrating reproductive and constructive activities, had hardly any teachers of children from 6 to 9 years old nor specialist teachers of primary education, unlike the first profile. However, this profile included a high number of generalist teachers of primary education and Spanish language teachers of secondary education. On the other hand, it had a few mathematics teachers from secondary education who were over-represented in the Reproductive profile. Finally, the teachers who used ICT more before confinement were also over-represented, and there were hardly any teachers who had not used them.

Discussion and Conclusion

In this study, taking advantage of the critical incident caused by the COVID-19 pandemic, we analyzed the type of activities with ICT that primary and secondary education teachers proposed to their students. Our purpose was to check if, in this context, ICT contributed to promoting more constructive ways of teaching. The most dominant effect of the results, related to the second aim of the study, showed that teachers carried out significantly more activities oriented to reproductive learning than constructive ones. In other words, they preferred teacher-centered activities to student-centered ones. This effect was very robust ( F = 2,217.91, p < 0.001, η p 2 = 0.61), and it was manifested in all dimensions of the questionnaire, was maintained when we introduced any of the variables studied and was presented in all profiles.

On the other hand, our work has revealed other variables that influence the frequency of ICT use. Thus, we have found that teachers who attend to young children use them less than teachers of older students. These data coincide with those found in other works ( Gorder, 2008 ; Vanderlinde et al., 2010 ) and are probably related to the characteristics of the teaching activity itself. It is undoubtedly more arduous to use ICT in class with young children than with adolescents or adults. We have also found a greater frequency of use by generalists than specialists because the former teach more hours in the same class and consequently have more responsibilities with their students. Both the specialists and the teachers of the youngest children were overrepresented in the Passive profile. Nevertheless, the influence of the subjects taught in compulsory and non-compulsory secondary education is not so clear. We found there was hardly any influence of gender on different results. Data from other studies show that the influence of this variable is quite unstable and varies among studies ( Mathews and Guarino, 2000 ; Gorder, 2008 ; Law and Chow, 2008 ). However, teaching experience seems to influence in another way: whereas less experienced teachers are more reproductive, the more experienced teachers present fewer differences between reproductive and constructive activities. It should be noted that in other studies this variable has also shown ambiguous results ( Mathews and Guarino, 2000 ; Baek et al., 2008 ; Gorder, 2008 ; Inan and Lowther, 2010 ).

The third objective analyzed the learning outcomes that the activities provided, the type of assessment used, and the cooperation that activities promoted. In general, we have seen that teachers performed more verbal and attitudinal learning than procedural. However, in these cases (as well as in the assessment), activities were aimed at reproductive instead of constructive learning. The least frequent activities were cooperative (between never and some days per month), which is consistent with the importance given to reproduction. The salience of verbal learning increased as the higher the educational level was and, in the same way, the attitudinal activities decreased, with hardly any change in the procedural ones.

Considering that these data were collected in Spain when there were strict confinement and social isolation, we would emphasize that the activities related to attitudes were directed at maintaining classroom control in all groups and profiles (but outside the classroom) whereas there was much less frequency of activities focused on getting the ability to managing student attitudes, behavior or self-control during that situation of confinement. This difference suggests that teachers were more concerned about controlling their students’ study habits.

Regarding our fourth objective, we find four profiles of teachers (Passive, Active, Reproductive, and Interpretative). The first two differed only in the amount of total activity performed, while the Reproductive one was characterized by almost exclusively executing reproductive learning activities. Although, as in the previous groups, the Interpretative teachers carried out many reproductive activities, they also carried out constructive activities with considerable frequency. Teachers of children from 3 to 6 years, for whom engaging in the virtual activity is more complicated, abounded in the Passive profile. However, in the Reproductive profile, teachers of mathematics of secondary education predominated. In contrast, in the Interpretative profile, in which there were fewer differences between reproductive and constructive activities, generalists of primary education and teachers of social and natural sciences and Spanish language of secondary education were over-represented. But principally, this profile was over-represented by teachers who had previously used ICT.

In conclusion, it seems the teachers in this study use ICT essentially for presenting different kinds of information ( Tondeur et al., 2008b ) and do not use them as learning tools that help students to build, manage, and develop their knowledge. On the other hand, this study seems to show that teachers’ beliefs are much closer to the reproductive pole than to the constructive one. In this study, beliefs have been inferred through the frequency with which the teachers stated they carried out predetermined activities. In our view, the description of the activities was much closer to the actual practices and theories of the teachers than the results that questionnaires on beliefs could provide us with. For this reason, we expect the mismatch between theories and practices ( Liu, 2011 ; Fives and Buehl, 2012 ; Tsai and Chai, 2012 ; Mama and Hennessy, 2013 ; Ertmer et al., 2015 ; de Aldama and Pozo, 2016 ) was smaller and helped us to discover the true beliefs of teachers when they teach.

We could therefore conclude that, despite all the educational possibilities and all the promises of change in teaching that ICT raise ( Jaffee, 1997 ; Collins and Halverson, 2009 ), teachers have only perceived these tools as informative support. It seems the critical incident caused by the pandemic has not been resolved in the short-term with a change in favor of student-centered activities and content-centered ones continue predominating. Therefore, our data are more consistent with the results of some international mass studies ( Biagi and Loi, 2013 ; OECD, 2015 ) than with the experimental works that analyze how teachers who are previously chosen use ICT ( Tamim et al., 2011 ; Alrasheedi et al., 2015 ; Sung et al., 2015 ; Clark et al., 2016 ; Xie et al., 2018 ; Mayer, 2019 ). However, there is no doubt that the pandemic has contributed to familiarizing teachers with ICT. In our results, previous use of ICT was the variable that produced the most systematic differences in both the frequency of proposed reproductive and constructive activities. In this sense, perhaps the pandemic may have contributed to an increase in teachers’ experience in two of the three educational computer uses described by Tondeur et al. (2008a) : basic computer skills and use of computers as an information tool. Maybe, this fact could contribute in the future to using the third one, the use of ICT as learning tools. However, there are undoubtedly other variables related to first-order and second-order barriers (beliefs) or teacher training with ICT that influence this possibility of change.

In summary, our work shows that activities carried out through ICT during confined schooling were more teacher-centered than student-centered and hardly promoted the 21st-century skills, that digital technologies should facilitate ( Ertmer et al., 2015 ). However, the data also show that the greater the stated previous use of ICT, the greater and more constructive its use was reported for the pandemic. Previous use of ICTs is related not only to beliefs about their usefulness but also to specific training to master these tools and to use them in a versatile manner, adapted to different purposes or objectives. It seems clear that teacher training should be promoted not only to encourage more frequent use of ICT but also to change conceptions toward them to promote constructive learning. In this sense, the forced use of ICT because of COVID-19 will only encourage this change if we support teachers with adequate resources and activities which facilitate reflection on their use.

However, we should consider that one limitation of this study is that the practices analyzed were those declared by the teachers. It would be necessary to complete this study with an analysis of the practices that the teachers really applied and to analyze their relationship with their conceptions of learning and teaching. In fact, we are currently analyzing the actual practices of a sub-sample of the teachers who filled out the questionnaire, taking the profiles found in this work as the independent variable. In future research, it would be necessary to analyze the relationship between student learning and these different teaching practices.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

The studies involving human participants were reviewed and approved by the Ethics Committee of the Autonomous University of Madrid. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

J-IP: funding acquisition, project administration, conceptualiza-tion, methodology, supervision, writing – original draft, and writing – review and editing. M-PE: funding acquisition, conceptualization, methodology, validation, writing – original draft, and writing – review and editing. BC: conceptualization, methodology, data curation, formal analysis, investigation, software, writing – original draft, writing – review and editing, and visualization. DLS: conceptualization, methodology, and writing – review and editing. All authors contributed to the article and approved the submitted version.

This work was supported by the Ministry of Innovation and Science of Spain (EDU2017-82243-C2-1-R).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We would like to thank our colleagues from SEIACE for their participation in the item dimension task. We would also like to thank Ricardo Olmos for sharing his statistical knowledge with us. Finally, we would like to appreciate Krystyna Sleziaka her support with the translation of this paper.

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Keywords : digital technologies uses, constructive learning, reproductive learning, learning and teaching conceptions, learning outcomes, COVID-19

Citation: Pozo J-I, Pérez Echeverría M-P, Cabellos B and Sánchez DL (2021) Teaching and Learning in Times of COVID-19: Uses of Digital Technologies During School Lockdowns. Front. Psychol. 12:656776. doi: 10.3389/fpsyg.2021.656776

Received: 21 January 2021; Accepted: 07 April 2021; Published: 29 April 2021.

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Copyright © 2021 Pozo, Pérez Echeverría, Cabellos and Sánchez. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Juan-Ignacio Pozo, [email protected]

† These authors have contributed equally to this work and share first authorship

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

• Review article
• Open access
• Published: 14 December 2022

The use of technology in higher education teaching by academics during the COVID-19 emergency remote teaching period: a systematic review

• McQueen Sum   ORCID: orcid.org/0000-0002-7763-1105 1 &
• Alis Oancea 1  

International Journal of Educational Technology in Higher Education volume  19 , Article number:  59 ( 2022 ) Cite this article

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This paper presents a systematic review of scholarly efforts that uniquely emerged at the onset of the COVID-19 pandemic and focused primarily on higher education teachers’ perspectives on technology use and on associated changes in the relationship between teachers and students amidst the transition to emergency remote teaching worldwide. Our narrative synthesis of 32 studies, the majority of which come from lower-and middle-income countries/regions, suggests that numerous factors interact to shape academics’ technology use in emergency remote teaching across higher education contexts. We report strong findings of teachers’ resilience and resourcefulness in their self-exploration of various technologies and teaching strategies in response to the continued severity of the pandemic. Ultimately, this review suggests directions for further research on engaging educational leaders and faculty in reimagining teaching as not only a core academic function of higher education, but also, and importantly, a humanising experience shaped by an ethics of care.

Review of literature and research questions

Since the continued devastating spread of COVID-19 across continents from early 2020, the coronavirus pandemic has led to massive numbers of hospitalisations and deaths around the world, abruptly upending public health and many other domains of life. As the disaster has unfolded, a multitude of sweeping challenges have continued to reshape the global higher education (‘HE’) landscape. With HE institutions (‘HEIs’) worldwide closing their campuses in Spring 2020, teachers were forced to make a hasty transition from typically in-person teaching configured in physically proximate space to alternative teaching approaches in response to the COVID-19 emergency (Crawford et al., 2020 ).

The term ‘emergency remote teaching’ (‘ERT’) is used by Hodges et al. ( 2020 ) and subsequent literature to denote the rapid and putatively ephemeral shift to remote teaching to continue teaching and learning during emergencies. Although ‘ERT’ and ‘online teaching’ may be two domains with considerable overlaps, ‘online teaching’ is importantly distinguished from ‘ERT’ as it includes teaching and learning arising from a prolonged collective effort in curriculum planning and instructional design from a wide range of stakeholders pre-launching (Hodges et al., 2020 ).

Despite the growing literature on ERT, few efforts had been made to review this body of research systematically at the time of conducting this review (see Table 1 for a few exceptions). Since there have been abundant discussions on the perspectives of students at the HE level during COVID-19 [see, for example, Chakraborty et al. ( 2021 ) on Indian students’ opinions on various aspects of ERT; Mok et al. ( 2021 ) on Hong Kong students’ evaluation of their learning experiences during ERT; Resch et al. ( 2022 ) on social and academic integration of Austrian students; and Salas-Pilco et al. ( 2022 ) for a systematic review focusing on student engagement in Latin American HE], our review focuses systematically on synthesising the body of worldwide literature on teachers’ perspectives on technology use during the period of ERT. Moreover, much attention has been devoted to medical education (Rajab et al., 2020 ; see also Table 1 ) and STEM education since the coronavirus outbreak (Amunga, 2021 ; Bond et al., 2021 ; Gaur et al., 2020 ; Singh-Pillay & Naidoo, 2020 ). Our review focuses on the less explored perspectives of humanities, arts, and social sciences (HASS) teachers—whose perceived difficulties of using digital technologies in teaching were reportedly distinct from those of their counterparts in other disciplines, both before (Mercader & Gairín, 2020 ) and during the COVID-19 outbreak (Wu et al., 2020 ).

Prior to COVID-19, a respectable amount of scholarly work was devoted to the development and adaptation of theoretical models to identify, explain, and even predict factors that influenced technology use in educational contexts (Granić & Marangunić, 2019 ). But Lee and Jung ( 2021 ) argue that ‘in higher education contexts, crisis-driven changes may happen differently from pre-planned, voluntary change, and that factors influencing crisis-driven changes are different from those influencing voluntary changes; as reported in previous studies based on technology acceptance theories and models’ (p. 16). Given the novelty of COVID-19, few studies have been conducted to explicate the factors shaping HE teachers’ decisions about, and experiences of, technology use in the unique context of the global pandemic [see Mittal et al. ( 2021 ) for an exception that studies faculty members in Northern India and Lee and Jung ( 2021 ) for another study on South Korean university educators]. Therefore, the first question that this review aims to answer is: How have different potential factors, as identified by teachers in the included studies, shaped teachers’ technology use across various higher education contexts during the COVID-19 emergency remote teaching period?

Existing scholarly efforts that aim to provide an overview of the literature focus predominantly on a bifurcated discussion of the opportunities and challenges, or advantages and disadvantages pertinent to using technologies in teaching during the COVID-19 crisis (Adedoyin & Soykan, 2020 ; Dhawan, 2020 ; Pokhrel & Chhetri, 2021 ; Stewart, 2021 ). We therefore frame the second research question in a way that circumvents a binary pros-and-cons discussion of the implications of technology use in times of the COVID pandemic, as already well-documented in the literature. Hence, our second question is: What are the implications of technology use in COVID-19 emergency remote teaching from the perspectives of higher education teachers?

The broader term ‘technology’ (in the singular form) used in the review questions includes the socio-cultural contexts of the educational settings in which technology use is situated. The discussion of ‘context’ is of particular importance (Selwyn, 2022 ). Although pre-COVID studies (such as Broadbent & Poon, 2015 ; Liu et al., 2020 ) offered valuable insights into technology use in HE teaching, the pandemic brought about starkly and often perilously different contexts for research as well as for teaching and learning (Stewart, 2021 ; Williamson et al., 2020 ).

We use the term ‘technologies’ in its plural form throughout this review, in a narrower sense, meaning specifically the wide range of digital tools and systems and other technical resources that are used for pedagogical purposes. These can include but are not limited to electronic hardware devices, software systems, online services, and social media. We note, however, that the meanings attached to the term ‘technologies’ may be substantively different across contexts. Some of the studies included in this review, as we will show below, extend it to other-than-digital forms of technologies, leading to results beyond our initial scope of research. As a result, the use of (digital) technologies is understood in this review as an often necessary but not sufficient condition for ERT—a novel concept to many teachers who had been using various ‘technologies’ in other ways in facilitating their teaching for years before the COVID-19 outbreak.

Methodology

Characterised by the principles of replicability and transparency, a systematic review aims to ‘review ... existing research using explicit, accountable rigorous research methods’ (Gough et al., 2017 , p. 4). This methodology is used because it helps elucidate the current understanding and available evidence of the above research questions, clarify any replication of existing research findings, and inform future research and policy directions in HE teaching in a systematic and trustworthy manner. Below is a detailed, transparent report of the processes involved in conducting this systematic review.

Inclusion/exclusion criteria

Our review is restricted to peer-reviewed journal articles that report original empirical studies written in English and/or simplified Chinese. Papers written in these two languages account for a high volume of worldwide literature published at the onset of the COVID-19 outbreak. Also, Chinese studies are particularly valuable for this review, for mainland China was the first region affected by COVID-19 and its HE system was amongst the first to respond to the challenges ensuing from the spread of coronavirus.

Since the review seeks to capture a ‘snapshot’ of perspectives on technology use by teachers during the immediate COVID-19 outbreak, only articles published in 2020 (including those published online ahead of print that year) were eligible for review. Included publications may cover any country/region worldwide but should systematically gather data from teachers other than the authors themselves and focus primarily on the perspectives of HASS teachers on matters pertaining to technology use in ERT in HE settings. Opinion pieces, editorials, reflection articles on one’s own practice, conference papers, and books are not within the purview of this review (see Appendix 1  for detailed inclusion/exclusion criteria).

Search strategy

Prior to conducting the database search, we piloted and modified the search strings several times. Our final search strategy is a combination of Boolean operators and variations of four key terms: ‘higher education’, ‘technology’, ‘teaching’, and ‘COVID-19’ (see Appendix 2  for detailed search terms).

Screening and selection

On 13 January 2021, a targeted search returned 4204 records indexed in fourteen databases including Scopus, Web of Science, and three Chinese databases (see Appendix 3  for PRISMA flow diagram and the complete list of databases). From these, we extracted 20 different papers at random to screen by title and abstract independently by applying the inclusion/exclusion criteria, and with the intention to repeat the process until unanimous agreement was reached. Having achieved full inter-reviewer agreement in our first attempt and after a further calibration session, we then proceeded to de-duplication and title-and-abstract screening, after which only 129 papers remained for full-text retrieval and further screening. Meanwhile, 16 relevant publications from various other sources were also identified and passed the initial screening. We then examined the full text of the resulting total of 145 articles and excluded any that did not fulfil the inclusion criteria, leading to a set of 40 studies to be considered for review.

Quality and relevance assessment and content extraction

To assess the 40 papers’ quality and relevance to this review, we adapted the assessment rubric from Oancea et al. ( 2021 ) (see Appendix 4 ). In parallel with the quality assessment, we developed a grid for content extraction by piloting on three papers, after which multiple revisions of the extraction grid were made. Then both authors used the updated extraction grid (see Appendix 5 ) and extracted content from two full papers independently to check for inter-reviewer agreement. In subsequent communications, discrepancies of our extraction were reconciled and the final quality thresholds for inclusion were agreed upon. As of May 2021, after excluding 8 papers of low quality, the final corpus for review comprised 32 articles.

Analysis and synthesis

We developed an initial coding scheme with broad theme boundaries based on the research questions, and resolved any conflicting views. We coded line-by-line the extracted data both deductively and inductively: we first applied the pre-configured coding scheme to the full set of data, and then updated and re-applied the coding scheme to include further themes identified through inductive coding. For example, we realised that the category of ‘ethical use of technology’ spanned the themes of ‘pedagogical implications’ and ‘work-related implications’. As a result we categorised it under a separate theme titled ‘cross-cutting implications’. After multiple rounds of scheme refinement and iterative coding which started in June 2021, the process of synthesis concluded in late December 2021.

The research synthesis is presented narratively; note that we integrated quantitative findings (for example, from surveys) descriptively into the narrative analysis, as in most cases the samples were not representative, the analysis was largely descriptive and findings from qualitative answers to open questions were presented in detail.

Limitations

Our review did not include insights from reflection pieces (such as Czerniewicz et al., 2020 ; Jandrić et al., 2020 ; Joseph & Trinick, 2021 ) and reports not published in peer-reviewed journals (such as Ferdig et al., 2020 ); these exclusions are not a judgment on either the quality or the level of insight of such pieces, nor on the modes of research and scholarship that they embody. This decision, as well as the focus on studies published in English and Chinese, limit the extent to which this review covers the experiences of ERT technology use by teacher populations across the world.

Due to our international remit, another limitation is the integration of findings grounded in different local contexts and HE environments. We overcome this partially by extracting from each paper the context in which teachers’ technology use is situated and taking such information into account when narratively integrating data across studies and presenting our review findings (see Appendix 5 ). However, the inconsistent terminology used to allude to the notions of ‘technology’ and ‘emergency remote teaching’ in the reviewed articles poses a major challenge to our cross-context comparison [see discussion on the jingle-jangle fallacy in Sum and Oancea ( 2021 )]. Another review conducted by Bond et al. ( 2021 ) also found at least ten different terms used for ‘online teaching’ (including ‘emergency remote teaching’) in their selected papers.

Although uniformly agreed-upon definitions of these terms are absent (Singh & Thurman, 2019 ), the nuances of concepts underlying them have not been given due consideration in the majority of the studies reviewed (see “ Description of included articles ” section). Further terminological complexity arises from the imperfect overlap between Chinese and English vocabularies. Whilst we tried to overcome this by extracting information on each study’s conceptualisation of ‘technology’ and ‘ERT’ (see Appendix 5 ) and accompanying translations with original Chinese terms (for example, the phrase ‘线上教学’ in Chinese can be sometimes translated into ‘online teaching and learning’), we acknowledge that terminological and translation gaps remain in our cross-context synthesis of the selected literature.

Description of included articles

Included in our final synthesis are 32 empirical research studies covering 71 countries and reporting perspectives from 4725 HE teachers altogether. Of these, the largest proportion focuses on the HE context in Asia (n = 15), followed by Europe (n = 7) and Africa (n = 6) (see Table 2 ). Given our inclusion of articles indexed in Chinese databases, Mainland China alone is the focal context of n = 5 studies. A wide range of subject areas in HASS disciplines are covered (see Table 3 ). Studies using qualitative data are most common (n = 14) (see Table 4 ), and a sample size of fewer than 50 teachers is often reported (n = 21) (see Table 5 ). Appendix 6 presents a summary of the characteristics of included studies.

Exactly half of the studies (n = 16) have a local remit (see Table 6 ), amongst which many recruited fellow academics from the authors’ institutions (n = 14). As noted by several researchers in their papers, the public health emergency and its concomitant restrictions had in various ways altered the methods for research and data collection, including shifting to a local focus whilst access to other settings was limited.

Authors of three quarters of the reviewed studies (n = 24) obtained data from participants remotely, either by phone or online. Much empirical data were collected in a space that was relatively new and unfamiliar to the researcher and the researched during a time when both individuals were coping with not only the expected expeditious embrace of various technologies for ERT but also, amongst other things, the physical and psychological burden posed by the coronavirus pandemic. Hence, this review integrates, in a systematic and holistic fashion, data from the discrete, often inevitably limited, yet valiant research initiatives undertaken in different countries during the periods of drastic increases in infections and deaths at the incipient phase of the COVID-19 outbreak.

In terms of substantive focus, whilst most of the included studies describe ‘what’ and/or ‘how’ technologies were being used by teachers during ERT (n = 14) and offer a dichotomous pros-or-cons narrative of technology use for ERT (n = 21), often vis-à-vis in-person teaching prior to COVID-19, some (n = 7) also examine the wider implications for teachers and HE at large.

Due partly to the novelty of COVID-19 and the haste with which research was conducted, the conceptualisation of technology and its relation with remote teaching in times of COVID-19 is either weak or largely absent in the majority of the reviewed studies. Technologically deterministic views seem prevalent in the literature reviewed. Many studies place ‘technology’ as the centre of inquiry and underscore the palpable ‘impact’ that various technical objects impose on teaching. For example, the attribution of recent pedagogical innovations and educational developments to technological advancements features prominently in the introductory paragraphs of numerous papers. Some assert that the emergence of social networking sites has begun to direct all walks of life including the ways in which teaching has been carried out since before the pandemic. Additionally, the discussion of ‘technology-enabled’ and ‘technology-enhanced’ teaching used in some articles implies that ‘technology’ plays an almost indispensable role in teaching and that teaching would be seriously disrupted without it. In contrast, there was little awareness in many of these papers of the extent to which technologies may carry political or commercial agendas or may be underpinned by complex ideologies and social structures (Selwyn et al., 2020 ). This echoes the conclusions of pre-COVID research by An and Oliver ( 2021 ) and Costa et al. ( 2019 ) that theoretical understanding of ‘technology’ in educational research is under-developed.

A brief narrative of ERT experiences from teachers’ perspectives

An eclectic range of technological artefacts and their uses during ERT across HE settings is reported in the studies. Cases of initial technology use range widely from straightforward approaches such as uploading teaching materials online to (mis)uses such as creating excessive recorded lectures and assignments. What is common, however, across reports in most studies is the acutely negative sentiments of intimidation, angst, confusion, and even despair of ERT amongst teachers at the outset of the transitioning period. It gave teachers great shock and pain to make a forced, often slapdash migration to ERT—a terrain that many of them were unfamiliar with and uncertain of—whilst juggling with their home and other work responsibilities during the distressing period. In addition to the psychological burden, teachers were worried about the well-being of their students, particularly those from underprivileged backgrounds and in vulnerable environments. Across HE settings worldwide, teachers had on average less than a week’s preparation time, leaving them feeling woefully unprepared. Hence, it is unsurprising that the majority of teachers in the studies reviewed found the immediate phase of migration to ERT burdensome and emotionally exhausting. Yet, some sought a silver lining and considered ERT as a creative challenge and an opportunity for a long-needed meaningful reflection and overhaul of HE teaching practices.

We mapped each included article’s findings about teachers’ overall attitudes towards ERT using the World Bank’s classification of country development (2020) (see Table 7 ). For studies not examining teachers’ attitudes directly, we inferred negative attitudes from teachers’ reports of dissatisfaction and frustrations over the challenges in ERT, and any indication of concern and anxiety; positive attitudes were inferred from teachers’ expressions of satisfaction and awareness of benefits brought by ERT, and any indication of optimism and hope.

Reports by teachers from higher-income countries/regions were more positive whilst those from lower-and middle-income countries/regions tended to be more negative, though with a few exceptions (for example, teachers in mainland China had relatively positive emotional responses and teachers of hearing-impaired students in high-income Saudi Arabia reported overwhelmingly negative emotional responses during the ERT period). In propitious circumstances, teachers’ emotional responses could change substantially over time from apprehension, frustration, and pessimism to relief, affirmation, and an eventual sense of achievement. Sometimes, as teachers gradually became conversant with various technological artefacts and encountered a suitable way of teaching, either serendipitously or after multiple experimentation, they eventually saw ERT as a humbling and rewarding experience. Some teachers evaluated the pedagogical revisions they made during ERT positively and even expressed the intention to keep part of their teaching online or expected to continue to use the technologies employed for ERT in the future.

Factors shaping technology use by teachers in ERT across HE contexts

The 32 papers reviewed include results on qualitative and quantitative factors identified by teacher participants that potentially shape teachers’ technology use in ERT. Note that these are not always empirically validated, nor explicitly identified as ‘factors’ in the included articles (particularly in qualitative accounts they may be described as reasons, drivers, challenges, barriers, and conditions). Thus, we adopted an open and inclusive definition of factors based on the implied or explicit direction of influence on ERT, and we grouped them thematically. Summary accounts of these thematic groupings based on the data presented in the review corpus are discussed below in descending order of the respective strength of evidence in the reviewed studies (see full references in Table 8 ).

Social-technological factors

Whilst Tartavulea et al. ( 2020 ) note that the transition to ERT can be facilitated by having online platforms and facilities, they also found that access to electronic devices and internet connection can be a luxury. Frequently reported technical concerns by teachers include the unreliability of network conditions, lack of devices and equipment, and limitations of digital infrastructure. These issues are not only powerful barriers to technology use in emergency teaching but they also disproportionately affect teachers and students in lower-income countries/regions. Note, however, that even in the context of an affluent country like the United States, teachers and students may report inequitable access to the necessities of ERT from home (Cutri et al., 2020 ; Sales et al., 2020 ).

Beneath the surface of these technical difficulties are the imbalanced allocation of resources and entrenched socio-economic problems which most commonly beset lower-and middle-income countries and regions (Tanga et al., 2020 ). Whilst the issues teachers face are highly contextualised, a considerable number of students come from underprivileged backgrounds. Even before the pandemic hit, these students had been confronting different challenges such as, particularly in lower-income countries, frequent commute of several miles from rural areas to the city for internet connection. Even if internet access were provided at home, these students would still need to overcome problems of intermittent or no power supply in their localities. In addition, during lockdowns they may shoulder more home-care responsibilities, sometimes in overcrowded or even abusive home environments.

Some teachers were also amongst vulnerable groups and had limited access to the internet at home, for example due to the sharing of cellular data with household members, and therefore exposed themselves to greater health risks by visiting commercial establishments such as cafés with free internet provision in order to teach remotely. Compounding this predicament is that HE teachers reported that they often had little information about students’ backgrounds, which hindered their efforts to address students’ educational and psychological needs and any equity issues pertinent to their studies (Cutri et al., 2020 ). These technical complications are situated in specific social contexts and have been a major hindrance to technology use in ERT.

Institutional factors

In most of the studies reviewed, the migration to ERT was described as mandatory, and teachers’ use of certain applications was often resultant from policies imposed by their institutions—whose regulations on teaching could be heavily influenced by government decisions, for example in universities in Mainland China (Tang et al., 2020 ). To ensure continuity and safety of teaching and learning in times of upheaval and uncertainty, some HEIs exercised greater control over the ways in which technologies were used in teaching, such as mandating the use of certain Learning Management Systems (LMS) in teaching (Khoza & Mpungose, 2020 ) or prohibiting asynchronous methods of teaching (Cutri et al., 2020 ). Whilst some teachers felt that their creative freedoms to use different technologies in their teaching were constrained by institutional policies , others sought detailed guidance and perceived the lack of clear institutional protocols as a significant barrier to technology use in this emergency (Sobaih et al., 2020 ).

Aside from policy, different forms of institutional support (such as the provision of digital infrastructure and training for both teachers and students) could also be of value to teachers in ERT, although the level of support felt by teachers could vary by discipline (Watermeyer et al., 2021 ). However, the value of technical assistance might be undermined when technology specialists were just as confused as teachers about teaching remotely in emergency times (Gyampoh et al., 2020 ; Tanga et al., 2020 ). Another gap in institutional support pointed out by some studies is the lack of recognising teachers’ hardship and efforts in teaching in the form of pecuniary (such as support for procurement of equipment) and non-pecuniary rewards (such as teaching awards) (Joshi et al., 2020 ).

Individual factors

Sometimes teachers resisted institutional policies and employed instead other technologies of their own preference. Individual factors therefore play an important role in shaping teachers’ technology use. Despite the challenges posed by the pandemic, some teachers were tolerant of uncertainties, valiantly departing from their previous pedagogical praxis and forging ahead with ‘pedagogical agility’ (Kidd & Murray, 2020 )—the flexibility of adapting to the new teaching conditions in rapid yet meaningful ways. Resilient and adaptive, these teachers ‘rolled up their sleeves’ and worked around the clock to seek teaching solutions and countermeasures through constant, active self-exploration (Sales et al., 2020 ). Some music teachers, for instance, would make immediate remedies for the connection disruptions to synchronous lessons by providing students with recordings of their playing as examples (Akyürek, 2020 ). In an Israeli college, teacher educators incorporated topics like ‘distance learning’ into the teacher training curriculum to reflect the new circumstances of teaching (Hadar et al., 2021 ). One teacher educator even painted a wall at home with special paint to make it into a ‘blackboard’ where his writings were presented and screened to students (Hadar et al., 2021 ). These are just a few of the many manifestations of teachers’ agentic creativity and ongoing inventiveness in innovating their own use of technologies and resources despite the presence of severe constraints in ERT times.

In terms of readiness, despite receiving considerable institutional support in some cases, teachers often felt ill-prepared for ERT and doubtful of their abilities in using various technologies to teach (Scherer et al., 2021 ), and only a minority felt rather ready for ERT (Alqabbani et al., 2020 ). The studies reviewed discussed the variation in teachers’ readiness for ERT in relation to gender, academic discipline, and country context (Scherer et al., 2021 ). For example, in predominantly high-income economies teachers moved from a customary integration of technologies in pre-COVID teaching to fully-online ERT (Mideros, 2020 ; Sales et al., 2020 ). But not all teachers and students had had the opportunities to familiarise themselves with various technologies (including otherwise widely used applications like Word processing) prior to COVID-19 (Gyampoh et al., 2020 ). Whilst experienced online teachers felt more prepared and expected themselves to employ more frequently a wide array of technologies in teaching, across HE contexts many teachers had seriously limited prior experience in ‘online teaching’ and were apprehensive about using technologies for teaching purposes (Bailey & Lee, 2020 ). Besides, being experienced in ‘online teaching’ does not necessarily translate to successful handling of ERT, given the limited time frame and the stressful and even traumatising circumstances at the outset of the crisis.

Pedagogical factors

Across HE settings, teachers considered how to connect and engage dislocated groups of students through technologies, how to empower students to explore beyond the curriculum as students gained more control over what and how they study in the shifting context of teaching and learning (Mideros, 2020 ), and how to reconfigure spaces in ways that provide students with a nourishing, inter-connected intellectual environment despite being physically apart during the ERT period (Kidd & Murray, 2020 ). In Australia, teachers were especially concerned about first-year students, as the southern hemisphere’s Autumn 2020 was their very first term at the university. In addition to providing students with considered feedback, these teachers employed strategies such as the online polls and hand-raising functions on various EdTech platforms (Zeng, 2020 ), or made students the host of Blackboard Collaborate in order for teaching to be more engaging (Marshalsey & Sclater, 2020 ).

As coronavirus infections spread, teachers also attended to students’ emotional and educational well-being. Some teacher educators in the United Kingdom offered one-on-one tutorials online to establish personal connections with student teachers and monitor their progress (Kidd & Murray, 2020 ). A teacher in Pakistan went the extra mile to care for the students living in far-flung areas without internet access by sending them CD recordings of their lectures (Said et al., 2021 ). In Saudi Arabia, teachers of hard-of-hearing students used a special configuration of multiple spaces to enable the inclusion of synchronous sign-language translation in their online lectures (Alsadoon & Turkestani, 2020 ). In cases where the discrepancy between technology use by teachers and students was significant, teachers would often bridge the gap by adapting and adopting technologies (such as social media) that they were not always conversant with, but which were most used and preferred by students. As a teacher participant put it, teachers have ‘to go where [students] are, and not wait for [students] to come to where [they] are’ (Sales et al., 2020 , p. 13).

Often teachers would consider the compatibility of certain technologies with their teaching philosophies and practices within their disciplines. Teacher educators in Israel, for example, might feel additional pressure from the expectation that their pedagogical use of technologies has to set examples for their student teachers (Hadar et al., 2021 ). As another example, teaching translation/interpretation in Mainland China was especially challenging during the ERT period since teachers have to demonstrate to students the operation of simultaneous interpretation equipment and the use of dual-track recording function—which is not commonly found in existing online applications (Ren, 2020 ).

Peer factors

Teachers reported that they saw their colleagues as not only sources of inspiration for technology use, but also remedies for stress and uncertainty during the ERT period (Ren, 2020 ). Unlike in prior ‘online teaching’ where they could still meet in person to discuss technology use, many teachers struggled with technological learning-by-doing in relative isolation during the COVID-19 lockdown period (Cutri et al., 2020 ). In view of the absence of physical spaces for colleagues to informally exchange professional practices and channel their emotionality and empathy for one another (Cutri et al., 2020 ; Scherer et al., 2021 ), some teachers put in deliberate effort into organising new networking spaces to bring the academic community together online. In an attempt to alleviate the uncertainties brought by ERT and their adverse impact on psychological well-being, teachers worked together remotely as a team to explore solutions and share useful insights about technology use in teaching. They felt empowered by the constant encouragement and motivational texts from their peers (Ren, 2020 ). Teachers thrived on establishing connections with technology-proficient colleagues whose technical expertise and guidance were relied upon (Bailey & Lee, 2020 ; Mouchantaf, 2020 ) and whose ingenious engagement with technologies inspired and were even assimilated into their own teaching practices. As a mitigation strategy to ease teachers’ hasty migration into ERT, mutual empowerment through facilitated discussions amongst colleagues meaningfully shaped the ways technologies were used by teachers in ERT.

Interplay of factors

Whilst we have delineated potential factors shaping technology use in ERT in a linear, point-by-point fashion, this list of non-exhaustive items should not be conceived as separate, stand-alone factors since they interact in a complex and nuanced way across various contexts. For instance, having little institutional support and no access to LMS or students’ information, some teachers in public HEIs in Egypt resorted to reaching students through popular social media. Teachers then explored on their own the ways in which they could continue teaching activities via these platforms which were new to them (Sobaih et al., 2020 ). As for teachers in an Israeli college, upon realising some Arabic female students refused to appear online due to their cultural values, they made allowance for students’ decisions to keep their cameras off (Hadar et al., 2021 ). But the inability to read students’ expressions during class added to the teaching challenges during ERT and demanded additional flexibility and pedagogical adjustments from teachers. Therefore, technology use is influenced by the combined factors of students’ socio-cultural backgrounds and teachers’ resources and adaptability to changes. In addition to the complex interplay of these factors, these examples demonstrate that teachers’ technology use in ERT is heavily contextualised across HE settings and should therefore be understood in its wider cultural embedding and socio-economic contexts.

Implications of technology use in ERT for teachers

As for our second research question, the studies reviewed indicate that the implications of technology use in ERT for teachers are manifold. These findings are categorised into pedagogical, work-related, and cross-cutting implications, discussed below (see Table 9 for a summary table).

Pedagogical implications

With the paradoxical amalgam of being ‘together but (physically) apart’ (Marshalsey & Sclater, 2020 ) in the new COVID-19 context of teaching, the notions of space and time, as well as the dynamics of the classroom and teacher-student relationship, have undergone less palpable yet important changes.

Spatiality-wise, teachers realised the loss of important physical spaces and the erosion of values traditionally attached to these spaces during the transition to ERT. Marshalsey and Sclater ( 2020 ), for example, reason how a physical art and design studio embodies a distinctive set of values, resources, and the signature experiential hands-on pedagogical practice of their discipline. But when artworks are presented online, their materiality, colours, and texture may be diminished.

Temporality-wise, some teachers felt a strongly contorted notion of time which rendered futile any discussion on the ordinary longitudinal perception of ‘being ready for teaching’ (Cutri et al., 2020 ). Not only was the migration to ERT perceived as rushed and disorganised but teachers also felt time as short, discrete intervals when many changes could occur. Some even found it difficult to find ‘a point of reference for their sense of self as experienced professionals’ (Cutri et al., 2020 , p. 533). This new sense of temporality is perhaps most concisely summarised by a comment made by a teacher during ERT: ‘I always plan a month ahead. Now I live from one day to the next’ (Hadar et al., 2021 , p. 454).

Within this new spatial–temporal context, teachers often felt that student engagement in remote teaching and learning activities was superficial and unequally distributed (Joshi et al., 2020 ; Kidd & Murray, 2020 ). Deprived of in-person interaction, teachers can neither hear the voices nor see the expressions of all students, and find the classroom discourse to be dominated by students who are generally more confident in sharing their ideas in front of the whole class (Hadar et al., 2021 ; Marshalsey & Sclater, 2020 ). With the loss of informal physical spaces where students used to ask questions and interact further with teachers before and after class (Cutri et al., 2020 ), some teachers commented that both teachers and students were more likely to stay in their ‘echo chambers’ during the pandemic (Eringfeld, 2021 ).

Teachers adopted different strategies to navigate being outside the comfort zone of the physical classroom. Some attempted to retain or increase control over interactions in the remote ‘classroom’ (Mideros, 2020 ) such as by only letting students speak when allowed (Gyampoh et al., 2020 ) and shifting to a predominantly teacher-centric, didactic approach of lecturing because of the perceived difficulty of implementing hands-on training in an exclusively remote teaching environment (Cutri et al., 2020 ). The students, too, adopted their own strategies, often distinct from their teachers’ (Callo & Yazon, 2020 ; Sobaih et al., 2020 ). As some students generally adapted to ERT with relative ease (Mideros, 2020 ; Ren, 2020 ), sometimes they even used technology as a defensive wall to exclude teachers (who were in some cases less tech-savvy than their students) from being involved in their studies during the pandemic (Sales et al., 2020 ). Many teachers in the studies reviewed reported that the mandated use of various technologies in ERT puts a strain on pedagogy, the major implications of which may include an elevated feeling of detachment from the class, a heightened distance from students (Kidd & Murray, 2020 ), and a more pronounced gap in teacher-student interactions (Callo & Yazon, 2020 ; Sales et al., 2020 ).

Moreover, ERT is thought to have precipitated the collapse of ‘yishigan’ (仪式感)—a Chinese expression which, when applied to this context, refers to the sense that teaching is a special, ritualised occasion (Lu, 2020 ; Ren, 2020 ). As ‘yishigan’ abates in the context of ERT, so does the sense of formality and immediacy felt by teachers and students, both of whom may no longer view teaching and learning as a serious, formalised routine of life in the same way as before; some of the studies reviewed note that motivation and classroom engagement are lowered as a result of this change in perception (see examples in Joshi et al., 2020 ; Lu, 2020 ; Marshalsey & Sclater, 2020 ).

In contrast with the sense of limitation, hierarchy, and loss illustrated by the accounts summarised above, other teachers reported a sense of the ‘intimacy of distance’ and a less visible teacher-student hierarchy as a combined result of emergency technology use during the pandemic. Such teachers valued the creation of spaces for more student-oriented and student-empowering pedagogy. In Mainland China, for example, the classroom atmosphere was livened up as students were encouraged by teachers to engage in class via alternative forms of interaction online such as sending emojis, raising ‘hands’, and taking polls (Gao & Zhang, 2020 ; Zeng, 2020 ). In other contexts, teachers felt an idiosyncratic sense of closeness as they shared a screen and read the same text with students on their devices (Eringfeld, 2021 ). They also reported a better understanding of students’ personal circumstances, home environment, and even household responsibilities as students turned on their cameras in class (Hadar et al., 2021 ; Kidd & Murray, 2020 ). In many ways, teachers observed their students being more relaxed in class, which enabled teachers to build personal relationships with their students in ways that they had never envisioned before (Marshalsey & Sclater, 2020 ).

Because of the collapse of ‘yishigan’ and the resultant casual and more relaxed classroom dynamics in the new spatiality, some teachers adapt to the ‘online etiquette’ by using emojis and GIFs when communicating with students (Marshalsey & Sclater, 2020 ). Also, the fact that students may be more technology-competent than teachers meaningfully shifts the dynamic of the teacher-student relationship in the ERT classroom (Kidd & Murray, 2020 ), for teachers often solicited help from students on questions regarding technology use, and during this process teachers increasingly saw students as their partners in teaching rather than subordinates to themselves (Cutri et al., 2020 ). As Cutri et al. ( 2020 ) remark, ‘the negative connotations of risk-taking and making mistakes while learning to teach online seem to have been mitigated by a combination of affective factors such as humility, empathy, and even optimism’ (p. 523). As an experience of vulnerability, ERT has grounded and humbled teachers, allowing them to develop both more appreciation for self-care (Eringfeld, 2021 ), and more empathy for students (Khoza & Mpungose, 2020 ; Kidd & Murray, 2020 ).

Teachers realised the salience of exercising care for students and themselves and considering the emotionality of students, especially those in vulnerable states (Alqabbani et al., 2020 ; Sales et al., 2020 ). Pastoral care took priority during particularly distressing periods when students were most in need of emotional support (Sobaih et al., 2020 ; Tejedor et al., 2020 ). All these examples suggest that under the new spatial–temporal reorientation an intricate web of human relations has evolved and, to varying degrees, been revitalised.

Work-related implications

The task of transitioning teaching to an alternative mode is only one of the many challenges teachers face in the larger contexts of academia during the pandemic period (Cutri et al., 2020 ). Although the extra time seemingly freed up by, say, the lack of commutes is highly valued for student support, self-care or family care (Eringfeld, 2021 ; Kidd & Murray, 2020 ; Tejedor et al., 2020 ), there has also been an excessive intensification of workload in preparation for ERT (Khan et al., 2020 ; Lu, 2020 ; Mouchantaf, 2020 ; Said et al., 2021 ), and this is expected to last for a few years into the post-ERT era (Watermeyer et al., 2021 ). When working from home, teachers received as many as hundreds of students’ inquiries throughout the day via various applications (Alsadoon & Turkestani, 2020 ; Sobaih et al., 2020 ). Coupled with the pressure to prove that work has been conducted remotely (Kidd & Murray, 2020 ; Marshalsey & Sclater, 2020 ), some teachers report feeling compelled to be present online around the clock. The ‘timelessness’ of working remotely in a home setting has been succinctly summarised by a teacher: ‘it is too easy to “just send one more email”’ (Watermeyer et al., 2021 ). The praxis and boundaries of academic work were shifted and reconstructed in ways many perceived as intrusive into the personal life sphere and deteriorative to work-life balance and also teachers’ well-being and occupational welfare (Watermeyer et al., 2021 ).

In addition, with looming financial challenges to the HE sector, casualised and untenured staff reported an elevated feeling of job precarity because their extra commitment to teaching cuts into time for other academic work, such as publishing research—which they perceived as often prioritised over teaching efforts in HE career progression (Cutri et al., 2020 ). Some reported that these teachers’ vulnerability was compounded by the management’s misperception that teaching remotely during emergency lightens teachers’ workload, and by their misinterpretation that low scores given by students on evaluations of ERT are a marker of ‘teacher quality’ rather than a way for students to express disinclination towards ERT in general (Watermeyer et al., 2021 ).

Technology use in ERT was further complicated by the need for swift re-coordination of private routines and domestic spaces to make room for professional work. A teacher, for example, asked all household members to disconnect from the Wi-Fi when teaching (Kidd & Murray, 2020 ). Having a separate, free-of-disturbance workspace at home is a luxury that not many teachers could afford (Gyampoh et al., 2020 ; Joshi et al., 2020 ) especially in contexts like Pakistan where joint families may live together in a crowded household (Said et al., 2021 ). Due to the non-separation of home/workspaces, customary parameters between the private and public domains were being reconstituted, and the boundaries between teachers’ personal and professional identities became blurry (Khoza & Mpungose, 2020 ). Consequently, female academics with caring responsibilities were disproportionately affected, and increasingly teachers found themselves struggling to perform either role well (Watermeyer et al., 2021 ).

In the larger context of HE, teachers were also worried about the ‘placelessness’ of HE during lockdowns and that the role of HE as an embodied, communal space for teaching and learning, self-formation, and socialisation was being undermined (Eringfeld, 2021 ). In two studies based in the UK (Eringfeld, 2021 ; Watermeyer et al., 2021 ), the accounts of their teacher participants add up to a strong ‘dystopian’ rhetoric, reflecting their fears that the ERT migration epitomises the beginning of a prolonged contraction of HE as an on-campus experience and monetisation of part of the HE experience driven largely by massification but not quality, thereby undermining the core academic values and humanising aims of HE.

Not all studies reviewed painted a consistently gloomy picture of the work-related implications of ERT and technology use. Some studies note that the compulsory, emergency move to remote teaching may have offered multiple opportunities. For example, in some propitious circumstances, teachers were able to constitute their networking spaces online to channel mutual support and facilitate exchanges on technology use. There are also reports that more trust was placed on technology specialists, technicians, and younger faculty who were often seen as more technologically adept and relied upon during ERT (Watermeyer et al., 2021 ). Moreover, the infrastructural divisions that used to separate departments on a physical campus are largely dismantled with the migration to ERT, enabling possibilities of various forms of inter-departmental communication and cross-disciplinary collaboration (Tejedor et al., 2020 ) and thereby making HE a flatter-structured and less hierarchically-organised workplace for teachers (Eringfeld, 2021 ).

Cross-cutting implications

Some of the teachers in the studies reviewed commented on the potential of ERT to undermine the ethos of the academic profession and imperil the work of academics. They noted that ERT could be pedagogically regressive, as teachers’ role may be reduced to merely technical functions, such as uploading materials online. This challenged their beliefs about what good teaching entails and compromised their often long-established pedagogical practices (Watermeyer et al., 2021 ). Other teachers struggled with balancing depth in their teaching with what they saw as their students’ preference for over-simplified yet visually appealing inputs such as bite-sized explanations shared on TikTok and other social media (Sales et al., 2020 ). Some anticipate worrying trends of ‘dumbing down’ of HE if teaching continues to be impersonal, disembodied and mediated predominantly by digital technologies in the post-ERT era (Watermeyer et al., 2021 ).

We have discussed so far the changes to HE teaching due to the relocation to newly formed spaces, as reported in the studies reviewed. Yet, some principles and values that teachers apply to guide their teaching practices remained unchanged amidst the ongoing crisis. These include the upholding of integrity, academic transparency, privacy, and other ethical principles in teaching (Mouchantaf, 2020 ). For example, teachers were concerned about the potential collection of students’ data for third-party use without prior informed consent (Diningrat et al., 2020 ; Joshi et al., 2020 ). Others also recognise the importance for students of using technology responsibly (Gyampoh et al., 2020 ) and being equipped with critical and reflective thinking capacity to evaluate the accuracy and relevance of information online (Sales et al., 2020 ; Tejedor et al., 2020 ), including resisting the temptation to reuse others’ ideas as their own work (Dampson et al., 2020 ) and refraining from using improper language on social media (Ghounane, 2020 ; Sobaih et al., 2020 ). This was especially relevant during the absence of teacher’s in-person monitoring, when the responsibility to access and study educational materials was partially shifted to students (Gyampoh et al., 2020 ), many of whom were inclined to explore topics of interest on their own (Marshalsey & Sclater, 2020 ; Mideros, 2020 ; Sales et al., 2020 ).

For teachers themselves, their practical wisdom and professional deliberation to ‘consider when, why, and how to use technology properly’ (Diningrat et al., 2020 , p. 706) were put to the test during the emergency contexts of teaching. A teacher participant in the study by Cutri et al. ( 2020 ) shared his belated reflection on an inadvertent, frivolous ridicule he had made about a student’s slow internet speed in front of the entire class online. This anecdote alludes to two problems looming in the wider context of HE teaching: (1) the largely absent code of conduct that delineates appropriate practices and roles of teachers and students in the new spatiality (and this can be due partly to the short time horizon in ERT); and (2) the difficulty for teachers to create supportive yet private spaces to address equity issues and attend to students’ emotionality in strict confidence when being online (Cutri et al., 2020 ).

Teachers participating in the studies reviewed in this paper indicated a multiplicity of factors that interacted to shape their technology use during the ERT period. In line with Liu et al. ( 2020 )’s pre-pandemic work, we find strong evidence that technology use in teaching is a context-sensitive, socially-embedded topic of study and hence should be understood in the socio-political, cultural and material context in which academics and students are situated (Selwyn et al., 2020 ). For example, the label ‘technical issues’ could encompass a wide range of contextualised problems, from power outages to long commutes for Internet access, from material shortages to widespread hunger, from trenchant poverty to deep-seated structured inequalities, which afflict disproportionately relatively poor, underserved communities and the most disadvantaged segments of populations (Chan et al., 2022 ) but are also palpable within higher-income countries/regions [see, for example, Cullinan et al. ( 2021 ) for a study on broadband access disparities in Ireland].

The narrative account we constructed is indicative of the resourcefulness and resilience of teachers to continue teaching during the crisis, even those in marginalised communities where resources are limited. This view is also shared by Padilla Rodríguez et al. ( 2021 ) who study the changes teachers in rural Mexico have made to their teaching practice in response to the suspension of in-person classes without receiving much external support during the pandemic. Around the world, teachers forayed into ERT during times of uncertainty by seeking to empower themselves and exploring various technological artefacts in teaching on their own, on the one hand; and by endorsing mutual empowerment and drawing inspiration from amongst their peers, on the other. Their collective efforts in supporting one another in the wake of crisis created what Matthewman and Uekusa ( 2021 ) call ‘disaster communitas’, which temporarily served to support teachers when adapting to the hasty conversion to ERT. We concur with Hickling et al. ( 2021 ) that the creation of a supportive space and environment for HE teachers to commiserate, discuss experiences, and share insights and resources with colleagues helps advance teaching practices with technology.

In answering the second research question, we have discussed at length the implications of a more encompassing use of technology in ERT and how evolving notions of space and time combined to reconstitute teacher-student relationships and the nature of academics’ work (Williamson et al., 2020 ). The studies reviewed indicate that the rushed transition to ERT has affected the sense of professional identity of academics as HE teachers (Littlejohn et al., 2021 ) in ways that are as yet only partly explored. Echoing the findings of Ramlo ( 2021 ), we believe that teachers’ negotiation of the blurring home-workspace boundaries (Blumsztajn et al., 2022 ; Littlejohn et al., 2021 ) and attempts to rebalance their professional work and personal life have important implications for future HE teaching and merit further investigation (Gourlay et al., 2021 ).

As COVID-19 continues to take a toll on people’s lives, we draw on the studies reviewed to emphasise the importance of re-prioritising the value of social and emotional connections in HE teaching, as well as the overall well-being of both teachers and students (Baker et al., 2022 ; Yeung & Yau, 2021 ). ‘Networks of care’ between teachers and students as well as amongst teachers themselves may be constructed to ameliorate uncertainties brought by the pandemic (Czerniewicz et al., 2020 ; Joseph & Trinick, 2021 ). Elements of care can be developed by simple acts of kindness (Murray et al., 2020 ) and gestures to communicate approachability (Glantz et al., 2021 ), all of which contribute to constructing more supportive and less hierarchical teacher-student relationships in the digital context. We note, however, that evidence scattered across the studies reviewed indicates that academic recognition and reward systems have not accounted well for the creative efforts that academics (including casualised and untenured staff) have put into teaching and maintaining relationships with their colleagues and students in response to the ongoing challenges ensuing from the coronavirus crisis. This is another priority for HEIs and leadership teams. On a final note, future research may explore further, innovative ways in which HE teaching can be reconstituted in the presence and context of technology without undermining teachers’ professional identity or compromising the revitalisation of teaching as an embodied, communal, and humanising experience as campuses around the world re-open, in full or in part, for in-person activities in post-pandemic times.

Appendix 1. A detailed version of inclusion/exclusion criteria

Appendix 2. search terms in english and chinese (note that the search strategy varied slightly across databases due to the different limits they set on the length of search input), appendix 3. prisma 2020 flow diagram for systematic review (page et al., 2021 ).

Appendix 4. Quality and relevance assessment rubric and the average scores of the 32 included studies (adapted from Oancea et al., 2021 )

• a Score description: 4—criterion fully met; 3—criterion mostly met, though with some weaknesses; 2—criterion only partly met, with several or serious weaknesses; 1—criterion largely not met

Appendix 5. Data extraction grid

Appendix 6. summary of characteristics of 32 reviewed studies.

• a The references of four articles show the publication year of 2021. These four articles were published online ahead of print in 2020 and hence are included in this study

Availability of data and materials

All data generated or analysed during this study are included in this published article.

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Acknowledgements

The corresponding author gave a presentation on the preliminary findings of this systematic review at the 1st International Yidan Prize Doctoral Conference (online) organized by the University of Oxford on 27 May 2021. The insightful questions raised by the audience are gratefully acknowledged. We would like to thank Dr. Victoria Elliott, Ms. Renyu Jiang, Ms. Abbey Palmer, and Ms. Catherine Scutt who have directly and indirectly provided their support for this research project.

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The corresponding author is a doctoral candidate reading Education. This paper is an original work, conducted by the corresponding author in parallel to the preparation for submission of a thesis for a Doctor of Philosophy (DPhil) degree under the supervision of the second author. Preliminary findings of this systematic review have been published in the Proceedings of the Yidan Prize Doctoral Conference under the terms of a Creative Commons Attribution License (CC-BY) (see Sum & Oancea, 2021 ).

This work was generously supported by a scholarship jointly awarded by the Clarendon Fund and New College of the University of Oxford (2020–2023).

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Under the guidance and supervision of AO, MS performed all stages of the systematic review, from conceptualising the review project to writing the manuscript. Both authors worked collaboratively from late 2020 to mid 2022 on this project. MS and AO independently coded and analysed a selection of data excerpts at various stages to check for inter-rater reliability as mentioned in ‘ Methodology ’ section. The rubric for quality assessment was based on past work by AO. Communications between the authors were maintained throughout the research process. MS worked on drafting this paper, which was subsequently revised by the AO. Both authors read and approved the final manuscript.

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Sum, M., Oancea, A. The use of technology in higher education teaching by academics during the COVID-19 emergency remote teaching period: a systematic review. Int J Educ Technol High Educ 19 , 59 (2022). https://doi.org/10.1186/s41239-022-00364-4

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DOI : https://doi.org/10.1186/s41239-022-00364-4

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Center for Teaching

From the students’ view: thoughts on technology and learning.

This article was originally published in the Fall 2000 issue of the CFT’s newsletter, Teaching Forum .

Victor Sung, Senior, A&S, Neuroscience; Benjamin Crist, Freshman, A&S, English; and Dayle Savage, Graduate Student, Peabody, Human Resources Development, reflect on the use of technology in the classroom.

CFT : How do you best learn? And how does technology help you in your learning?

Benjamin : I am a visual-kinesthetic learner. What that phrase (which I learned in middle school) means for me is that I learn the quickest that which I can see before me, and when combined with activities by me or the professor, I achieve the maximum from the class. For example, I have no problem reading a book in order to do well in the class. But as man students know, this is a poor substitute if the class is less than engaging. That is why I then require active participation of the professor and the rest of the class in order to really grasp the material. But I do not sit in the back of a class waiting for this to happen. I do everything I can to start discussions or continue ones which my professor and classmates have already begun. The reason that I am so adamant about the necessity of discussion and active participation is because I know that learning is an exchange-an exchange of ideas, beliefs, and knowledge. But in any exchange you will only receive as much as the other party wishes to give. I think that the only way to truly learn is to facilitate exchange in the classroom as best I can.

Victor : I learn best by seeing things presented in different ways and then going over them again. With this I mean that I don’t think I would learn very well if I had to listen to an audio-tape of someone drone on and one about something Visual stimulations keeps me interested and also helps me remember things better.

Dayle : The focus of my doctoral work is adult education and how adults learn. Therefore, it is interesting to ponder how I learn. As a graduate student in the 40-soething generation, I value my thirst for knowledge. It is abundantly clear to me that I have always been a seeker. I question. I am very curious and my questions today do not embarrass me; they motivate me to continue learning. My greatest teachers have been those who have encouraged me to seek the answers myself with unabashed vigor while providing steady support. I have found the journey to a “higher education” is the ultimate test of independence, determination and authenticity.

CFT : Given the ways in which you learn best, how does technology help-or fail to help-that process?

Benjamin : Technology is a great aid in my learning. Not only does much of it allow the professor or students to communicate knowledge and ideas in new and exciting ways, it also eases the ability to then access that information for later perusal. For example, a group could present a PowerPoint presentation and then allow the teacher to publish or stream it from a web site which the students could access form their dorm rooms. This is a great way to reinforce an exchange that took place in a classroom earlier in the semester without requiring more time and resources by the professor in a latter class period. Also, new technologies inherently attract the attention of the younger generation as we move farther into the information revolution. Look at the number of cellular phones and laptops being carried by students today. This makes the technology transfer easier in the classroom because many times the teacher will only have to gloss over instructions on how to use the technology Because so many already use it) and there will be less new resources consumed overall. Such examples in the classroom allow one to see how the learning process is enhanced by new uses of technology.

As I said earlier, the learning process can best be defined as an exchange. That exchange requires both parties to actively participate in order to get the most out of the exchange for everyone. Technology only increases the ability to accomplish this task and eases the transition into the digital world of the future.

Victor : Technology comes into play because it can serve to enhance the visual presentation. The classic example of this is the increasing use of PowerPoint presentations in lectures. This is helpful to me because the visual gives me a clue on how I should take my notes or how the information is structured and categorized. Things like diagrams, pictures, and even movies can be integrated directly into the text of the lecture, and this helps me to get a vivid reinforcement through visual examples of the material that has just been presented. One of the greatest advantages of having lecture son PowerPoint is that the drawings and diagrams so prevalent in my science courses can be much more effective in full color and not hastily sketched onto a chalkboard or copied onto a transparency.

Some potential disadvantages of having lectures in a PowerPoint type format include the tendency of a professor to move too quickly through the slides since he or she does not have to write out or demonstrate the material much more than what is already displayed on the screen. Some students also get too caught up in copying down every last thing on the screen and do not listen as well to the professor’s deeper explanation of what the slide is showing. This is often remedied by the professor offering the chance to view the lectures online either by putting the files up on Prometheus or by putting them on the class web site. I have found both of these options extremely helpful because I do not feel pressured to copy every word off of each slide if I know that I will have access to it later on. It also helps immensely in review for a test to be able to go through and inspect the color diagrams again to test my understanding, and to review each lecture again in order as a way of grasping the big picture and seeing how the different lectures fit together.

Other instances where dependence of lectures on technology has been a hindrance have been related to the classroom setup. I have a class this semester in which the classroom itself does not have a projector, so each class, we hope that the projector to be connected to the professor’s laptop is already there by the time we arrive. If not, then we have to wait for it to get there, which uses up some class time. Also there are the frequent glitches where certain pictures or movies do not display correctly. These kinds of glitches, though, are often solved by early setup by the professor or by afterwards printing out the pictures that did not show up or otherwise correcting the presentation and then putting it up for view on the web.

All this is not to say that all lecturers must make the move towards the integration of technology into their lectures, but rather that the most effective learning occurs when the material is presented in as clear a way as possible. Sometimes this means presenting the material multiple times in multiple ways. Since all students do not learn in the same way, the availability of new technologies allows for the presentation of material in a variety of ways that can be effective for all. Finally, I think that use of technology in the classroom should not be an excuse of the educator to remain glued behind a podium without interaction with the students; instead the technology can clearly be an opportunity for interaction between the educator and the material, the material and the students, the students and each other, and finally, the educator and the students.

Dayle : Technology has been a blessing and a curse for me. Fortunately, I took a class last year on the technology of learning organizations that demystified the technology enigma. I learned that I really couldn’t break my computer. With that freedom, I became willing to experiment. Today, I can try anything. Using a learning contract was a very good tool for this class. Each student was asked to complete a contract to learn a new technology or improve a technology skill. For example, members of the class created web sites, learned video conferencing, developed digital photography, and created PowerPoint presentations with sound, movement and videos.

In addition, as a class we learned to create on-line curriculum and used the chat room on Prometheus to have discussions about articles and readings assigned. The class was paperless except for the handouts produced during our final class projects and the books we purchased online. It appeared to be a gratifying experience for the luddites and experts alike. Technology allows me abundant opportunities to explore, create and communicate.

I have witnessed the frustration of technology from my instructors, as the tools we possess sometimes do not cooperate, and the training received is inconsistent and often nonexistent. As a teaching assistant, I have found myself in techno-hell in front of a class of students. It is embarrassing but I have also found students who are very forgiving and willing to assist. None of us can be literate in all of the wonderful technology available to us-it is constantly changing and differs depending on the setting in which one finds oneself. Practicing patience, becoming willing to learn new things, and knowing that “I can’t break it” allow me to let technology enrich my world and send me to places I would have never dreamed of going.

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Information and communication technology (ICT) in education

Information and communications technology (ict) can impact student learning when teachers are digitally literate and understand how to integrate it into curriculum..

Schools use a diverse set of ICT tools to communicate, create, disseminate, store, and manage information.(6) In some contexts, ICT has also become integral to the teaching-learning interaction, through such approaches as replacing chalkboards with interactive digital whiteboards, using students’ own smartphones or other devices for learning during class time, and the “flipped classroom” model where students watch lectures at home on the computer and use classroom time for more interactive exercises.

When teachers are digitally literate and trained to use ICT, these approaches can lead to higher order thinking skills, provide creative and individualized options for students to express their understandings, and leave students better prepared to deal with ongoing technological change in society and the workplace.(18)

ICT issues planners must consider include: considering the total cost-benefit equation, supplying and maintaining the requisite infrastructure, and ensuring investments are matched with teacher support and other policies aimed at effective ICT use.(16)

Issues and Discussion

Digital culture and digital literacy: Computer technologies and other aspects of digital culture have changed the ways people live, work, play, and learn, impacting the construction and distribution of knowledge and power around the world.(14) Graduates who are less familiar with digital culture are increasingly at a disadvantage in the national and global economy. Digital literacy—the skills of searching for, discerning, and producing information, as well as the critical use of new media for full participation in society—has thus become an important consideration for curriculum frameworks.(8)

In many countries, digital literacy is being built through the incorporation of information and communication technology (ICT) into schools. Some common educational applications of ICT include:

• One laptop per child: Less expensive laptops have been designed for use in school on a 1:1 basis with features like lower power consumption, a low cost operating system, and special re-programming and mesh network functions.(42) Despite efforts to reduce costs, however, providing one laptop per child may be too costly for some developing countries.(41)
• Tablets: Tablets are small personal computers with a touch screen, allowing input without a keyboard or mouse. Inexpensive learning software (“apps”) can be downloaded onto tablets, making them a versatile tool for learning.(7)(25) The most effective apps develop higher order thinking skills and provide creative and individualized options for students to express their understandings.(18)
• Interactive White Boards or Smart Boards : Interactive white boards allow projected computer images to be displayed, manipulated, dragged, clicked, or copied.(3) Simultaneously, handwritten notes can be taken on the board and saved for later use. Interactive white boards are associated with whole-class instruction rather than student-centred activities.(38) Student engagement is generally higher when ICT is available for student use throughout the classroom.(4)
• E-readers : E-readers are electronic devices that can hold hundreds of books in digital form, and they are increasingly utilized in the delivery of reading material.(19) Students—both skilled readers and reluctant readers—have had positive responses to the use of e-readers for independent reading.(22) Features of e-readers that can contribute to positive use include their portability and long battery life, response to text, and the ability to define unknown words.(22) Additionally, many classic book titles are available for free in e-book form.
• Flipped Classrooms: The flipped classroom model, involving lecture and practice at home via computer-guided instruction and interactive learning activities in class, can allow for an expanded curriculum. There is little investigation on the student learning outcomes of flipped classrooms.(5) Student perceptions about flipped classrooms are mixed, but generally positive, as they prefer the cooperative learning activities in class over lecture.(5)(35)

ICT and Teacher Professional Development: Teachers need specific professional development opportunities in order to increase their ability to use ICT for formative learning assessments, individualized instruction, accessing online resources, and for fostering student interaction and collaboration.(15) Such training in ICT should positively impact teachers’ general attitudes towards ICT in the classroom, but it should also provide specific guidance on ICT teaching and learning within each discipline. Without this support, teachers tend to use ICT for skill-based applications, limiting student academic thinking.(32) To sup­port teachers as they change their teaching, it is also essential for education managers, supervisors, teacher educators, and decision makers to be trained in ICT use.(11)

Ensuring benefits of ICT investments: To ensure the investments made in ICT benefit students, additional conditions must be met. School policies need to provide schools with the minimum acceptable infrastructure for ICT, including stable and affordable internet connectivity and security measures such as filters and site blockers. Teacher policies need to target basic ICT literacy skills, ICT use in pedagogical settings, and discipline-specific uses. (21) Successful imple­mentation of ICT requires integration of ICT in the curriculum. Finally, digital content needs to be developed in local languages and reflect local culture. (40) Ongoing technical, human, and organizational supports on all of these issues are needed to ensure access and effective use of ICT. (21)

Resource Constrained Contexts: The total cost of ICT ownership is considerable: training of teachers and administrators, connectivity, technical support, and software, amongst others. (42) When bringing ICT into classrooms, policies should use an incremental pathway, establishing infrastructure and bringing in sustainable and easily upgradable ICT. (16) Schools in some countries have begun allowing students to bring their own mobile technology (such as laptop, tablet, or smartphone) into class rather than providing such tools to all students—an approach called Bring Your Own Device. (1)(27)(34) However, not all families can afford devices or service plans for their children. (30) Schools must ensure all students have equitable access to ICT devices for learning.

Inclusiveness Considerations

Digital Divide: The digital divide refers to disparities of digital media and internet access both within and across countries, as well as the gap between people with and without the digital literacy and skills to utilize media and internet.(23)(26)(31) The digital divide both creates and reinforces socio-economic inequalities of the world’s poorest people. Policies need to intentionally bridge this divide to bring media, internet, and digital literacy to all students, not just those who are easiest to reach.

Minority language groups: Students whose mother tongue is different from the official language of instruction are less likely to have computers and internet connections at home than students from the majority. There is also less material available to them online in their own language, putting them at a disadvantage in comparison to their majority peers who gather information, prepare talks and papers, and communicate more using ICT. (39) Yet ICT tools can also help improve the skills of minority language students—especially in learning the official language of instruction—through features such as automatic speech recognition, the availability of authentic audio-visual materials, and chat functions. (2)(17)

Students with different styles of learning: ICT can provide diverse options for taking in and processing information, making sense of ideas, and expressing learning. Over 87% of students learn best through visual and tactile modalities, and ICT can help these students ‘experience’ the information instead of just reading and hearing it. (20)(37) Mobile devices can also offer programmes (“apps”) that provide extra support to students with special needs, with features such as simplified screens and instructions, consistent placement of menus and control features, graphics combined with text, audio feedback, ability to set pace and level of difficulty, appropriate and unambiguous feedback, and easy error correction. (24)(29)

Plans and policies

• India [ PDF ]
• Detroit, USA [ PDF ]
• Finland [ PDF ]
• Alberta Education. 2012. Bring your own device: A guide for schools . Retrieved from http://education.alberta.ca/admin/technology/research.aspx
• Alsied, S.M. and Pathan, M.M. 2015. ‘The use of computer technology in EFL classroom: Advantages and implications.’ International Journal of English Language and Translation Studies . 1 (1).
• BBC. N.D. ‘What is an interactive whiteboard?’ Retrieved from http://www.bbcactive.com/BBCActiveIdeasandResources/Whatisaninteractivewhiteboard.aspx
• Beilefeldt, T. 2012. ‘Guidance for technology decisions from classroom observation.’ Journal of Research on Technology in Education . 44 (3).
• Bishop, J.L. and Verleger, M.A. 2013. ‘The flipped classroom: A survey of the research.’ Presented at the 120th ASEE Annual Conference and Exposition. Atlanta, Georgia.
• Blurton, C. 2000. New Directions of ICT-Use in Education . United National Education Science and Culture Organization (UNESCO).
• Bryant, B.R., Ok, M., Kang, E.Y., Kim, M.K., Lang, R., Bryant, D.P. and Pfannestiel, K. 2015. ‘Performance of fourth-grade students with learning disabilities on multiplication facts comparing teacher-mediated and technology-mediated interventions: A preliminary investigation. Journal of Behavioral Education. 24.
• Buckingham, D. 2005. Educación en medios. Alfabetización, aprendizaje y cultura contemporánea, Barcelona, Paidós.
• Buckingham, D., Sefton-Green, J., and Scanlon, M. 2001. 'Selling the Digital Dream: Marketing Education Technologies to Teachers and Parents.'  ICT, Pedagogy, and the Curriculum: Subject to Change . London: Routledge.
• "Burk, R. 2001. 'E-book devices and the marketplace: In search of customers.' Library Hi Tech 19 (4)."
• Chapman, D., and Mählck, L. (Eds). 2004. Adapting technology for school improvement: a global perspective. Paris: International Institute for Educational Planning.
• Cheung, A.C.K and Slavin, R.E. 2012. ‘How features of educational technology applications affect student reading outcomes: A meta-analysis.’ Educational Research Review . 7.
• Cheung, A.C.K and Slavin, R.E. 2013. ‘The effectiveness of educational technology applications for enhancing mathematics achievement in K-12 classrooms: A meta-analysis.’ Educational Research Review . 9.
• Deuze, M. 2006. 'Participation Remediation Bricolage - Considering Principal Components of a Digital Culture.' The Information Society . 22 .
• Dunleavy, M., Dextert, S. and Heinecke, W.F. 2007. ‘What added value does a 1:1 student to laptop ratio bring to technology-supported teaching and learning?’ Journal of Computer Assisted Learning . 23.
• Enyedy, N. 2014. Personalized Instruction: New Interest, Old Rhetoric, Limited Results, and the Need for a New Direction for Computer-Mediated Learning . Boulder, CO: National Education Policy Center.
• Golonka, E.M., Bowles, A.R., Frank, V.M., Richardson, D.L. and Freynik, S. 2014. ‘Technologies for foreign language learning: A review of technology types and their effectiveness.’ Computer Assisted Language Learning . 27 (1).
• Goodwin, K. 2012. Use of Tablet Technology in the Classroom . Strathfield, New South Wales: NSW Curriculum and Learning Innovation Centre.
• Jung, J., Chan-Olmsted, S., Park, B., and Kim, Y. 2011. 'Factors affecting e-book reader awareness, interest, and intention to use.' New Media & Society . 14 (2)
• Kenney, L. 2011. ‘Elementary education, there’s an app for that. Communication technology in the elementary school classroom.’ The Elon Journal of Undergraduate Research in Communications . 2 (1).
• Kopcha, T.J. 2012. ‘Teachers’ perceptions of the barriers to technology integration and practices with technology under situated professional development.’ Computers and Education . 59.
• Miranda, T., Williams-Rossi, D., Johnson, K., and McKenzie, N. 2011. "Reluctant readers in middle school: Successful engagement with text using the e-reader.' International journal of applied science and technology . 1 (6).
• Moyo, L. 2009. 'The digital divide: scarcity, inequality and conflict.' Digital Cultures . New York: Open University Press.
• Newton, D.A. and Dell, A.G. 2011. ‘Mobile devices and students with disabilities: What do best practices tell us?’ Journal of Special Education Technology . 26 (3).
• Nirvi, S. (2011). ‘Special education pupils find learning tool in iPad applications.’ Education Week . 30 .
• Norris, P. 2001. Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide . Cambridge, USA: Cambridge University Press.
• Project Tomorrow. 2012. Learning in the 21st century: Mobile devices + social media = personalized learning . Washington, D.C.: Blackboard K-12.
• Riasati, M.J., Allahyar, N. and Tan, K.E. 2012. ‘Technology in language education: Benefits and barriers.’ Journal of Education and Practice . 3 (5).
• Rodriquez, C.D., Strnadova, I. and Cumming, T. 2013. ‘Using iPads with students with disabilities: Lessons learned from students, teachers, and parents.’ Intervention in School and Clinic . 49 (4).
• Sangani, K. 2013. 'BYOD to the classroom.' Engineering & Technology . 3 (8).
• Servon, L. 2002. Redefining the Digital Divide: Technology, Community and Public Policy . Malden, MA: Blackwell Publishers.
• Smeets, E. 2005. ‘Does ICT contribute to powerful learning environments in primary education?’ Computers and Education. 44 .
• Smith, G.E. and Thorne, S. 2007. Differentiating Instruction with Technology in K-5 Classrooms . Eugene, OR: International Society for Technology in Education.
• Song, Y. 2014. '"Bring your own device (BYOD)" for seamless science inquiry in a primary school.' Computers & Education. 74 .
• Strayer, J.F. 2012. ‘How learning in an inverted classroom influences cooperation, innovation and task orientation.’ Learning Environment Research. 15.
• Tamim, R.M., Bernard, R.M., Borokhovski, E., Abrami, P.C. and Schmid, R.F. 2011. ‘What forty years of research says about the impact of technology on learning: A second-order meta-analysis and validation study. Review of Educational Research. 81 (1).
• Tileston, D.W. 2003. What Every Teacher Should Know about Media and Technology. Thousand Oaks, CA: Corwin Press.
• Turel, Y.K. and Johnson, T.E. 2012. ‘Teachers’ belief and use of interactive whiteboards for teaching and learning.’ Educational Technology and Society . 15(1).
• Volman, M., van Eck, E., Heemskerk, I. and Kuiper, E. 2005. ‘New technologies, new differences. Gender and ethnic differences in pupils’ use of ICT in primary and secondary education.’ Computers and Education. 45 .
• Voogt, J., Knezek, G., Cox, M., Knezek, D. and ten Brummelhuis, A. 2013. ‘Under which conditions does ICT have a positive effect on teaching and learning? A call to action.’ Journal of Computer Assisted Learning. 29 (1).
• Warschauer, M. and Ames, M. 2010. ‘Can one laptop per child save the world’s poor?’ Journal of International Affairs. 64 (1).
• Zuker, A.A. and Light, D. 2009. ‘Laptop programs for students.’ Science. 323 (5910).

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Over the last four decades, studies have investigated the incorporation of Artificial Intelligence (AI) into education. A recent prominent AI-powered technology that has impacted the education sector is ChatGPT. This article provides a systematic review of 14 empirical studies incorporating ChatGPT into various educational settings, published in 2022 and before the 10th of April 2023—the date of conducting the search process. It carefully followed the essential steps outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines, as well as Okoli’s (Okoli in Commun Assoc Inf Syst, 2015) steps for conducting a rigorous and transparent systematic review. In this review, we aimed to explore how students and teachers have utilized ChatGPT in various educational settings, as well as the primary findings of those studies. By employing Creswell’s (Creswell in Educational research: planning, conducting, and evaluating quantitative and qualitative research [Ebook], Pearson Education, London, 2015) coding techniques for data extraction and interpretation, we sought to gain insight into their initial attempts at ChatGPT incorporation into education. This approach also enabled us to extract insights and considerations that can facilitate its effective and responsible use in future educational contexts. The results of this review show that learners have utilized ChatGPT as a virtual intelligent assistant, where it offered instant feedback, on-demand answers, and explanations of complex topics. Additionally, learners have used it to enhance their writing and language skills by generating ideas, composing essays, summarizing, translating, paraphrasing texts, or checking grammar. Moreover, learners turned to it as an aiding tool to facilitate their directed and personalized learning by assisting in understanding concepts and homework, providing structured learning plans, and clarifying assignments and tasks. However, the results of specific studies (n = 3, 21.4%) show that overuse of ChatGPT may negatively impact innovative capacities and collaborative learning competencies among learners. Educators, on the other hand, have utilized ChatGPT to create lesson plans, generate quizzes, and provide additional resources, which helped them enhance their productivity and efficiency and promote different teaching methodologies. Despite these benefits, the majority of the reviewed studies recommend the importance of conducting structured training, support, and clear guidelines for both learners and educators to mitigate the drawbacks. This includes developing critical evaluation skills to assess the accuracy and relevance of information provided by ChatGPT, as well as strategies for integrating human interaction and collaboration into learning activities that involve AI tools. Furthermore, they also recommend ongoing research and proactive dialogue with policymakers, stakeholders, and educational practitioners to refine and enhance the use of AI in learning environments. This review could serve as an insightful resource for practitioners who seek to integrate ChatGPT into education and stimulate further research in the field.

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1 Introduction

Educational technology, a rapidly evolving field, plays a crucial role in reshaping the landscape of teaching and learning [ 82 ]. One of the most transformative technological innovations of our era that has influenced the field of education is Artificial Intelligence (AI) [ 50 ]. Over the last four decades, AI in education (AIEd) has gained remarkable attention for its potential to make significant advancements in learning, instructional methods, and administrative tasks within educational settings [ 11 ]. In particular, a large language model (LLM), a type of AI algorithm that applies artificial neural networks (ANNs) and uses massively large data sets to understand, summarize, generate, and predict new content that is almost difficult to differentiate from human creations [ 79 ], has opened up novel possibilities for enhancing various aspects of education, from content creation to personalized instruction [ 35 ]. Chatbots that leverage the capabilities of LLMs to understand and generate human-like responses have also presented the capacity to enhance student learning and educational outcomes by engaging students, offering timely support, and fostering interactive learning experiences [ 46 ].

The ongoing and remarkable technological advancements in chatbots have made their use more convenient, increasingly natural and effortless, and have expanded their potential for deployment across various domains [ 70 ]. One prominent example of chatbot applications is the Chat Generative Pre-Trained Transformer, known as ChatGPT, which was introduced by OpenAI, a leading AI research lab, on November 30th, 2022. ChatGPT employs a variety of deep learning techniques to generate human-like text, with a particular focus on recurrent neural networks (RNNs). Long short-term memory (LSTM) allows it to grasp the context of the text being processed and retain information from previous inputs. Also, the transformer architecture, a neural network architecture based on the self-attention mechanism, allows it to analyze specific parts of the input, thereby enabling it to produce more natural-sounding and coherent output. Additionally, the unsupervised generative pre-training and the fine-tuning methods allow ChatGPT to generate more relevant and accurate text for specific tasks [ 31 , 62 ]. Furthermore, reinforcement learning from human feedback (RLHF), a machine learning approach that combines reinforcement learning techniques with human-provided feedback, has helped improve ChatGPT’s model by accelerating the learning process and making it significantly more efficient.

This cutting-edge natural language processing (NLP) tool is widely recognized as one of today's most advanced LLMs-based chatbots [ 70 ], allowing users to ask questions and receive detailed, coherent, systematic, personalized, convincing, and informative human-like responses [ 55 ], even within complex and ambiguous contexts [ 63 , 77 ]. ChatGPT is considered the fastest-growing technology in history: in just three months following its public launch, it amassed an estimated 120 million monthly active users [ 16 ] with an estimated 13 million daily queries [ 49 ], surpassing all other applications [ 64 ]. This remarkable growth can be attributed to the unique features and user-friendly interface that ChatGPT offers. Its intuitive design allows users to interact seamlessly with the technology, making it accessible to a diverse range of individuals, regardless of their technical expertise [ 78 ]. Additionally, its exceptional performance results from a combination of advanced algorithms, continuous enhancements, and extensive training on a diverse dataset that includes various text sources such as books, articles, websites, and online forums [ 63 ], have contributed to a more engaging and satisfying user experience [ 62 ]. These factors collectively explain its remarkable global growth and set it apart from predecessors like Bard, Bing Chat, ERNIE, and others.

In this context, several studies have explored the technological advancements of chatbots. One noteworthy recent research effort, conducted by Schöbel et al. [ 70 ], stands out for its comprehensive analysis of more than 5,000 studies on communication agents. This study offered a comprehensive overview of the historical progression and future prospects of communication agents, including ChatGPT. Moreover, other studies have focused on making comparisons, particularly between ChatGPT and alternative chatbots like Bard, Bing Chat, ERNIE, LaMDA, BlenderBot, and various others. For example, O’Leary [ 53 ] compared two chatbots, LaMDA and BlenderBot, with ChatGPT and revealed that ChatGPT outperformed both. This superiority arises from ChatGPT’s capacity to handle a wider range of questions and generate slightly varied perspectives within specific contexts. Similarly, ChatGPT exhibited an impressive ability to formulate interpretable responses that were easily understood when compared with Google's feature snippet [ 34 ]. Additionally, ChatGPT was compared to other LLMs-based chatbots, including Bard and BERT, as well as ERNIE. The findings indicated that ChatGPT exhibited strong performance in the given tasks, often outperforming the other models [ 59 ].

Furthermore, in the education context, a comprehensive study systematically compared a range of the most promising chatbots, including Bard, Bing Chat, ChatGPT, and Ernie across a multidisciplinary test that required higher-order thinking. The study revealed that ChatGPT achieved the highest score, surpassing Bing Chat and Bard [ 64 ]. Similarly, a comparative analysis was conducted to compare ChatGPT with Bard in answering a set of 30 mathematical questions and logic problems, grouped into two question sets. Set (A) is unavailable online, while Set (B) is available online. The results revealed ChatGPT's superiority in Set (A) over Bard. Nevertheless, Bard's advantage emerged in Set (B) due to its capacity to access the internet directly and retrieve answers, a capability that ChatGPT does not possess [ 57 ]. However, through these varied assessments, ChatGPT consistently highlights its exceptional prowess compared to various alternatives in the ever-evolving chatbot technology.

The widespread adoption of chatbots, especially ChatGPT, by millions of students and educators, has sparked extensive discussions regarding its incorporation into the education sector [ 64 ]. Accordingly, many scholars have contributed to the discourse, expressing both optimism and pessimism regarding the incorporation of ChatGPT into education. For example, ChatGPT has been highlighted for its capabilities in enriching the learning and teaching experience through its ability to support different learning approaches, including adaptive learning, personalized learning, and self-directed learning [ 58 , 60 , 91 ]), deliver summative and formative feedback to students and provide real-time responses to questions, increase the accessibility of information [ 22 , 40 , 43 ], foster students’ performance, engagement and motivation [ 14 , 44 , 58 ], and enhance teaching practices [ 17 , 18 , 64 , 74 ].

On the other hand, concerns have been also raised regarding its potential negative effects on learning and teaching. These include the dissemination of false information and references [ 12 , 23 , 61 , 85 ], biased reinforcement [ 47 , 50 ], compromised academic integrity [ 18 , 40 , 66 , 74 ], and the potential decline in students' skills [ 43 , 61 , 64 , 74 ]. As a result, ChatGPT has been banned in multiple countries, including Russia, China, Venezuela, Belarus, and Iran, as well as in various educational institutions in India, Italy, Western Australia, France, and the United States [ 52 , 90 ].

Clearly, the advent of chatbots, especially ChatGPT, has provoked significant controversy due to their potential impact on learning and teaching. This indicates the necessity for further exploration to gain a deeper understanding of this technology and carefully evaluate its potential benefits, limitations, challenges, and threats to education [ 79 ]. Therefore, conducting a systematic literature review will provide valuable insights into the potential prospects and obstacles linked to its incorporation into education. This systematic literature review will primarily focus on ChatGPT, driven by the aforementioned key factors outlined above.

However, the existing literature lacks a systematic literature review of empirical studies. Thus, this systematic literature review aims to address this gap by synthesizing the existing empirical studies conducted on chatbots, particularly ChatGPT, in the field of education, highlighting how ChatGPT has been utilized in educational settings, and identifying any existing gaps. This review may be particularly useful for researchers in the field and educators who are contemplating the integration of ChatGPT or any chatbot into education. The following research questions will guide this study:

What are students' and teachers' initial attempts at utilizing ChatGPT in education?

What are the main findings derived from empirical studies that have incorporated ChatGPT into learning and teaching?

2 Methodology

To conduct this study, the authors followed the essential steps of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) and Okoli’s [ 54 ] steps for conducting a systematic review. These included identifying the study’s purpose, drafting a protocol, applying a practical screening process, searching the literature, extracting relevant data, evaluating the quality of the included studies, synthesizing the studies, and ultimately writing the review. The subsequent section provides an extensive explanation of how these steps were carried out in this study.

2.1 Identify the purpose

Given the widespread adoption of ChatGPT by students and teachers for various educational purposes, often without a thorough understanding of responsible and effective use or a clear recognition of its potential impact on learning and teaching, the authors recognized the need for further exploration of ChatGPT's impact on education in this early stage. Therefore, they have chosen to conduct a systematic literature review of existing empirical studies that incorporate ChatGPT into educational settings. Despite the limited number of empirical studies due to the novelty of the topic, their goal is to gain a deeper understanding of this technology and proactively evaluate its potential benefits, limitations, challenges, and threats to education. This effort could help to understand initial reactions and attempts at incorporating ChatGPT into education and bring out insights and considerations that can inform the future development of education.

2.2 Draft the protocol

The next step is formulating the protocol. This protocol serves to outline the study process in a rigorous and transparent manner, mitigating researcher bias in study selection and data extraction [ 88 ]. The protocol will include the following steps: generating the research question, predefining a literature search strategy, identifying search locations, establishing selection criteria, assessing the studies, developing a data extraction strategy, and creating a timeline.

2.3 Apply practical screen

The screening step aims to accurately filter the articles resulting from the searching step and select the empirical studies that have incorporated ChatGPT into educational contexts, which will guide us in answering the research questions and achieving the objectives of this study. To ensure the rigorous execution of this step, our inclusion and exclusion criteria were determined based on the authors' experience and informed by previous successful systematic reviews [ 21 ]. Table 1 summarizes the inclusion and exclusion criteria for study selection.

2.4 Literature search

We conducted a thorough literature search to identify articles that explored, examined, and addressed the use of ChatGPT in Educational contexts. We utilized two research databases: Dimensions.ai, which provides access to a large number of research publications, and lens.org, which offers access to over 300 million articles, patents, and other research outputs from diverse sources. Additionally, we included three databases, Scopus, Web of Knowledge, and ERIC, which contain relevant research on the topic that addresses our research questions. To browse and identify relevant articles, we used the following search formula: ("ChatGPT" AND "Education"), which included the Boolean operator "AND" to get more specific results. The subject area in the Scopus and ERIC databases were narrowed to "ChatGPT" and "Education" keywords, and in the WoS database was limited to the "Education" category. The search was conducted between the 3rd and 10th of April 2023, which resulted in 276 articles from all selected databases (111 articles from Dimensions.ai, 65 from Scopus, 28 from Web of Science, 14 from ERIC, and 58 from Lens.org). These articles were imported into the Rayyan web-based system for analysis. The duplicates were identified automatically by the system. Subsequently, the first author manually reviewed the duplicated articles ensured that they had the same content, and then removed them, leaving us with 135 unique articles. Afterward, the titles, abstracts, and keywords of the first 40 manuscripts were scanned and reviewed by the first author and were discussed with the second and third authors to resolve any disagreements. Subsequently, the first author proceeded with the filtering process for all articles and carefully applied the inclusion and exclusion criteria as presented in Table  1 . Articles that met any one of the exclusion criteria were eliminated, resulting in 26 articles. Afterward, the authors met to carefully scan and discuss them. The authors agreed to eliminate any empirical studies solely focused on checking ChatGPT capabilities, as these studies do not guide us in addressing the research questions and achieving the study's objectives. This resulted in 14 articles eligible for analysis.

2.5 Quality appraisal

The examination and evaluation of the quality of the extracted articles is a vital step [ 9 ]. Therefore, the extracted articles were carefully evaluated for quality using Fink’s [ 24 ] standards, which emphasize the necessity for detailed descriptions of methodology, results, conclusions, strengths, and limitations. The process began with a thorough assessment of each study's design, data collection, and analysis methods to ensure their appropriateness and comprehensive execution. The clarity, consistency, and logical progression from data to results and conclusions were also critically examined. Potential biases and recognized limitations within the studies were also scrutinized. Ultimately, two articles were excluded for failing to meet Fink’s criteria, particularly in providing sufficient detail on methodology, results, conclusions, strengths, or limitations. The review process is illustrated in Fig.  1 .

The study selection process

2.6 Data extraction

The next step is data extraction, the process of capturing the key information and categories from the included studies. To improve efficiency, reduce variation among authors, and minimize errors in data analysis, the coding categories were constructed using Creswell's [ 15 ] coding techniques for data extraction and interpretation. The coding process involves three sequential steps. The initial stage encompasses open coding , where the researcher examines the data, generates codes to describe and categorize it, and gains a deeper understanding without preconceived ideas. Following open coding is axial coding , where the interrelationships between codes from open coding are analyzed to establish more comprehensive categories or themes. The process concludes with selective coding , refining and integrating categories or themes to identify core concepts emerging from the data. The first coder performed the coding process, then engaged in discussions with the second and third authors to finalize the coding categories for the first five articles. The first coder then proceeded to code all studies and engaged again in discussions with the other authors to ensure the finalization of the coding process. After a comprehensive analysis and capturing of the key information from the included studies, the data extraction and interpretation process yielded several themes. These themes have been categorized and are presented in Table  2 . It is important to note that open coding results were removed from Table  2 for aesthetic reasons, as it included many generic aspects, such as words, short phrases, or sentences mentioned in the studies.

2.7 Synthesize studies

In this stage, we will gather, discuss, and analyze the key findings that emerged from the selected studies. The synthesis stage is considered a transition from an author-centric to a concept-centric focus, enabling us to map all the provided information to achieve the most effective evaluation of the data [ 87 ]. Initially, the authors extracted data that included general information about the selected studies, including the author(s)' names, study titles, years of publication, educational levels, research methodologies, sample sizes, participants, main aims or objectives, raw data sources, and analysis methods. Following that, all key information and significant results from the selected studies were compiled using Creswell’s [ 15 ] coding techniques for data extraction and interpretation to identify core concepts and themes emerging from the data, focusing on those that directly contributed to our research questions and objectives, such as the initial utilization of ChatGPT in learning and teaching, learners' and educators' familiarity with ChatGPT, and the main findings of each study. Finally, the data related to each selected study were extracted into an Excel spreadsheet for data processing. The Excel spreadsheet was reviewed by the authors, including a series of discussions to ensure the finalization of this process and prepare it for further analysis. Afterward, the final result being analyzed and presented in various types of charts and graphs. Table 4 presents the extracted data from the selected studies, with each study labeled with a capital 'S' followed by a number.

This section consists of two main parts. The first part provides a descriptive analysis of the data compiled from the reviewed studies. The second part presents the answers to the research questions and the main findings of these studies.

3.1 Part 1: descriptive analysis

This section will provide a descriptive analysis of the reviewed studies, including educational levels and fields, participants distribution, country contribution, research methodologies, study sample size, study population, publication year, list of journals, familiarity with ChatGPT, source of data, and the main aims and objectives of the studies. Table 4 presents a comprehensive overview of the extracted data from the selected studies.

3.1.1 The number of the reviewed studies and publication years

The total number of the reviewed studies was 14. All studies were empirical studies and published in different journals focusing on Education and Technology. One study was published in 2022 [S1], while the remaining were published in 2023 [S2]-[S14]. Table 3 illustrates the year of publication, the names of the journals, and the number of reviewed studies published in each journal for the studies reviewed.

3.1.2 Educational levels and fields

The majority of the reviewed studies, 11 studies, were conducted in higher education institutions [S1]-[S10] and [S13]. Two studies did not specify the educational level of the population [S12] and [S14], while one study focused on elementary education [S11]. However, the reviewed studies covered various fields of education. Three studies focused on Arts and Humanities Education [S8], [S11], and [S14], specifically English Education. Two studies focused on Engineering Education, with one in Computer Engineering [S2] and the other in Construction Education [S3]. Two studies focused on Mathematics Education [S5] and [S12]. One study focused on Social Science Education [S13]. One study focused on Early Education [S4]. One study focused on Journalism Education [S9]. Finally, three studies did not specify the field of education [S1], [S6], and [S7]. Figure  2 represents the educational levels in the reviewed studies, while Fig.  3 represents the context of the reviewed studies.

Educational levels in the reviewed studies

Context of the reviewed studies

3.1.3 Participants distribution and countries contribution

The reviewed studies have been conducted across different geographic regions, providing a diverse representation of the studies. The majority of the studies, 10 in total, [S1]-[S3], [S5]-[S9], [S11], and [S14], primarily focused on participants from single countries such as Pakistan, the United Arab Emirates, China, Indonesia, Poland, Saudi Arabia, South Korea, Spain, Tajikistan, and the United States. In contrast, four studies, [S4], [S10], [S12], and [S13], involved participants from multiple countries, including China and the United States [S4], China, the United Kingdom, and the United States [S10], the United Arab Emirates, Oman, Saudi Arabia, and Jordan [S12], Turkey, Sweden, Canada, and Australia [ 13 ]. Figures  4 and 5 illustrate the distribution of participants, whether from single or multiple countries, and the contribution of each country in the reviewed studies, respectively.

The reviewed studies conducted in single or multiple countries

The Contribution of each country in the studies

3.1.4 Study population and sample size

Four study populations were included: university students, university teachers, university teachers and students, and elementary school teachers. Six studies involved university students [S2], [S3], [S5] and [S6]-[S8]. Three studies focused on university teachers [S1], [S4], and [S6], while one study specifically targeted elementary school teachers [S11]. Additionally, four studies included both university teachers and students [S10] and [ 12 , 13 , 14 ], and among them, study [S13] specifically included postgraduate students. In terms of the sample size of the reviewed studies, nine studies included a small sample size of less than 50 participants [S1], [S3], [S6], [S8], and [S10]-[S13]. Three studies had 50–100 participants [S2], [S9], and [S14]. Only one study had more than 100 participants [S7]. It is worth mentioning that study [S4] adopted a mixed methods approach, including 10 participants for qualitative analysis and 110 participants for quantitative analysis.

3.1.5 Participants’ familiarity with using ChatGPT

The reviewed studies recruited a diverse range of participants with varying levels of familiarity with ChatGPT. Five studies [S2], [S4], [S6], [S8], and [S12] involved participants already familiar with ChatGPT, while eight studies [S1], [S3], [S5], [S7], [S9], [S10], [S13] and [S14] included individuals with differing levels of familiarity. Notably, one study [S11] had participants who were entirely unfamiliar with ChatGPT. It is important to note that four studies [S3], [S5], [S9], and [S11] provided training or guidance to their participants before conducting their studies, while ten studies [S1], [S2], [S4], [S6]-[S8], [S10], and [S12]-[S14] did not provide training due to the participants' existing familiarity with ChatGPT.

3.1.6 Research methodology approaches and source(S) of data

The reviewed studies adopted various research methodology approaches. Seven studies adopted qualitative research methodology [S1], [S4], [S6], [S8], [S10], [S11], and [S12], while three studies adopted quantitative research methodology [S3], [S7], and [S14], and four studies employed mixed-methods, which involved a combination of both the strengths of qualitative and quantitative methods [S2], [S5], [S9], and [S13].

In terms of the source(s) of data, the reviewed studies obtained their data from various sources, such as interviews, questionnaires, and pre-and post-tests. Six studies relied on interviews as their primary source of data collection [S1], [S4], [S6], [S10], [S11], and [S12], four studies relied on questionnaires [S2], [S7], [S13], and [S14], two studies combined the use of pre-and post-tests and questionnaires for data collection [S3] and [S9], while two studies combined the use of questionnaires and interviews to obtain the data [S5] and [S8]. It is important to note that six of the reviewed studies were quasi-experimental [S3], [S5], [S8], [S9], [S12], and [S14], while the remaining ones were experimental studies [S1], [S2], [S4], [S6], [S7], [S10], [S11], and [S13]. Figures  6 and 7 illustrate the research methodologies and the source (s) of data used in the reviewed studies, respectively.

Research methodologies in the reviewed studies

Source of data in the reviewed studies

3.1.7 The aim and objectives of the studies

The reviewed studies encompassed a diverse set of aims, with several of them incorporating multiple primary objectives. Six studies [S3], [S6], [S7], [S8], [S11], and [S12] examined the integration of ChatGPT in educational contexts, and four studies [S4], [S5], [S13], and [S14] investigated the various implications of its use in education, while three studies [S2], [S9], and [S10] aimed to explore both its integration and implications in education. Additionally, seven studies explicitly explored attitudes and perceptions of students [S2] and [S3], educators [S1] and [S6], or both [S10], [S12], and [S13] regarding the utilization of ChatGPT in educational settings.

3.2 Part 2: research questions and main findings of the reviewed studies

This part will present the answers to the research questions and the main findings of the reviewed studies, classified into two main categories (learning and teaching) according to AI Education classification by [ 36 ]. Figure  8 summarizes the main findings of the reviewed studies in a visually informative diagram. Table 4 provides a detailed list of the key information extracted from the selected studies that led to generating these themes.

The main findings in the reviewed studies

4 Students' initial attempts at utilizing ChatGPT in learning and main findings from students' perspective

4.1 virtual intelligent assistant.

Nine studies demonstrated that ChatGPT has been utilized by students as an intelligent assistant to enhance and support their learning. Students employed it for various purposes, such as answering on-demand questions [S2]-[S5], [S8], [S10], and [S12], providing valuable information and learning resources [S2]-[S5], [S6], and [S8], as well as receiving immediate feedback [S2], [S4], [S9], [S10], and [S12]. In this regard, students generally were confident in the accuracy of ChatGPT's responses, considering them relevant, reliable, and detailed [S3], [S4], [S5], and [S8]. However, some students indicated the need for improvement, as they found that answers are not always accurate [S2], and that misleading information may have been provided or that it may not always align with their expectations [S6] and [S10]. It was also observed by the students that the accuracy of ChatGPT is dependent on several factors, including the quality and specificity of the user's input, the complexity of the question or topic, and the scope and relevance of its training data [S12]. Many students felt that ChatGPT's answers were not always accurate and most of them believed that it requires good background knowledge to work with.

4.2 Writing and language proficiency assistant

Six of the reviewed studies highlighted that ChatGPT has been utilized by students as a valuable assistant tool to improve their academic writing skills and language proficiency. Among these studies, three mainly focused on English education, demonstrating that students showed sufficient mastery in using ChatGPT for generating ideas, summarizing, paraphrasing texts, and completing writing essays [S8], [S11], and [S14]. Furthermore, ChatGPT helped them in writing by making students active investigators rather than passive knowledge recipients and facilitated the development of their writing skills [S11] and [S14]. Similarly, ChatGPT allowed students to generate unique ideas and perspectives, leading to deeper analysis and reflection on their journalism writing [S9]. In terms of language proficiency, ChatGPT allowed participants to translate content into their home languages, making it more accessible and relevant to their context [S4]. It also enabled them to request changes in linguistic tones or flavors [S8]. Moreover, participants used it to check grammar or as a dictionary [S11].

4.3 Valuable resource for learning approaches

Five studies demonstrated that students used ChatGPT as a valuable complementary resource for self-directed learning. It provided learning resources and guidance on diverse educational topics and created a supportive home learning environment [S2] and [S4]. Moreover, it offered step-by-step guidance to grasp concepts at their own pace and enhance their understanding [S5], streamlined task and project completion carried out independently [S7], provided comprehensive and easy-to-understand explanations on various subjects [S10], and assisted in studying geometry operations, thereby empowering them to explore geometry operations at their own pace [S12]. Three studies showed that students used ChatGPT as a valuable learning resource for personalized learning. It delivered age-appropriate conversations and tailored teaching based on a child's interests [S4], acted as a personalized learning assistant, adapted to their needs and pace, which assisted them in understanding mathematical concepts [S12], and enabled personalized learning experiences in social sciences by adapting to students' needs and learning styles [S13]. On the other hand, it is important to note that, according to one study [S5], students suggested that using ChatGPT may negatively affect collaborative learning competencies between students.

4.4 Enhancing students' competencies

Six of the reviewed studies have shown that ChatGPT is a valuable tool for improving a wide range of skills among students. Two studies have provided evidence that ChatGPT led to improvements in students' critical thinking, reasoning skills, and hazard recognition competencies through engaging them in interactive conversations or activities and providing responses related to their disciplines in journalism [S5] and construction education [S9]. Furthermore, two studies focused on mathematical education have shown the positive impact of ChatGPT on students' problem-solving abilities in unraveling problem-solving questions [S12] and enhancing the students' understanding of the problem-solving process [S5]. Lastly, one study indicated that ChatGPT effectively contributed to the enhancement of conversational social skills [S4].

4.5 Supporting students' academic success

Seven of the reviewed studies highlighted that students found ChatGPT to be beneficial for learning as it enhanced learning efficiency and improved the learning experience. It has been observed to improve students' efficiency in computer engineering studies by providing well-structured responses and good explanations [S2]. Additionally, students found it extremely useful for hazard reporting [S3], and it also enhanced their efficiency in solving mathematics problems and capabilities [S5] and [S12]. Furthermore, by finding information, generating ideas, translating texts, and providing alternative questions, ChatGPT aided students in deepening their understanding of various subjects [S6]. It contributed to an increase in students' overall productivity [S7] and improved efficiency in composing written tasks [S8]. Regarding learning experiences, ChatGPT was instrumental in assisting students in identifying hazards that they might have otherwise overlooked [S3]. It also improved students' learning experiences in solving mathematics problems and developing abilities [S5] and [S12]. Moreover, it increased students' successful completion of important tasks in their studies [S7], particularly those involving average difficulty writing tasks [S8]. Additionally, ChatGPT increased the chances of educational success by providing students with baseline knowledge on various topics [S10].

5 Teachers' initial attempts at utilizing ChatGPT in teaching and main findings from teachers' perspective

5.1 valuable resource for teaching.

The reviewed studies showed that teachers have employed ChatGPT to recommend, modify, and generate diverse, creative, organized, and engaging educational contents, teaching materials, and testing resources more rapidly [S4], [S6], [S10] and [S11]. Additionally, teachers experienced increased productivity as ChatGPT facilitated quick and accurate responses to questions, fact-checking, and information searches [S1]. It also proved valuable in constructing new knowledge [S6] and providing timely answers to students' questions in classrooms [S11]. Moreover, ChatGPT enhanced teachers' efficiency by generating new ideas for activities and preplanning activities for their students [S4] and [S6], including interactive language game partners [S11].

5.2 Improving productivity and efficiency

The reviewed studies showed that participants' productivity and work efficiency have been significantly enhanced by using ChatGPT as it enabled them to allocate more time to other tasks and reduce their overall workloads [S6], [S10], [S11], [S13], and [S14]. However, three studies [S1], [S4], and [S11], indicated a negative perception and attitude among teachers toward using ChatGPT. This negativity stemmed from a lack of necessary skills to use it effectively [S1], a limited familiarity with it [S4], and occasional inaccuracies in the content provided by it [S10].

5.3 Catalyzing new teaching methodologies

Five of the reviewed studies highlighted that educators found the necessity of redefining their teaching profession with the assistance of ChatGPT [S11], developing new effective learning strategies [S4], and adapting teaching strategies and methodologies to ensure the development of essential skills for future engineers [S5]. They also emphasized the importance of adopting new educational philosophies and approaches that can evolve with the introduction of ChatGPT into the classroom [S12]. Furthermore, updating curricula to focus on improving human-specific features, such as emotional intelligence, creativity, and philosophical perspectives [S13], was found to be essential.

5.4 Effective utilization of CHATGPT in teaching

According to the reviewed studies, effective utilization of ChatGPT in education requires providing teachers with well-structured training, support, and adequate background on how to use ChatGPT responsibly [S1], [S3], [S11], and [S12]. Establishing clear rules and regulations regarding its usage is essential to ensure it positively impacts the teaching and learning processes, including students' skills [S1], [S4], [S5], [S8], [S9], and [S11]-[S14]. Moreover, conducting further research and engaging in discussions with policymakers and stakeholders is indeed crucial for the successful integration of ChatGPT in education and to maximize the benefits for both educators and students [S1], [S6]-[S10], and [S12]-[S14].

6 Discussion

The purpose of this review is to conduct a systematic review of empirical studies that have explored the utilization of ChatGPT, one of today’s most advanced LLM-based chatbots, in education. The findings of the reviewed studies showed several ways of ChatGPT utilization in different learning and teaching practices as well as it provided insights and considerations that can facilitate its effective and responsible use in future educational contexts. The results of the reviewed studies came from diverse fields of education, which helped us avoid a biased review that is limited to a specific field. Similarly, the reviewed studies have been conducted across different geographic regions. This kind of variety in geographic representation enriched the findings of this review.

In response to RQ1 , "What are students' and teachers' initial attempts at utilizing ChatGPT in education?", the findings from this review provide comprehensive insights. Chatbots, including ChatGPT, play a crucial role in supporting student learning, enhancing their learning experiences, and facilitating diverse learning approaches [ 42 , 43 ]. This review found that this tool, ChatGPT, has been instrumental in enhancing students' learning experiences by serving as a virtual intelligent assistant, providing immediate feedback, on-demand answers, and engaging in educational conversations. Additionally, students have benefited from ChatGPT’s ability to generate ideas, compose essays, and perform tasks like summarizing, translating, paraphrasing texts, or checking grammar, thereby enhancing their writing and language competencies. Furthermore, students have turned to ChatGPT for assistance in understanding concepts and homework, providing structured learning plans, and clarifying assignments and tasks, which fosters a supportive home learning environment, allowing them to take responsibility for their own learning and cultivate the skills and approaches essential for supportive home learning environment [ 26 , 27 , 28 ]. This finding aligns with the study of Saqr et al. [ 68 , 69 ] who highlighted that, when students actively engage in their own learning process, it yields additional advantages, such as heightened motivation, enhanced achievement, and the cultivation of enthusiasm, turning them into advocates for their own learning.

Moreover, students have utilized ChatGPT for tailored teaching and step-by-step guidance on diverse educational topics, streamlining task and project completion, and generating and recommending educational content. This personalization enhances the learning environment, leading to increased academic success. This finding aligns with other recent studies [ 26 , 27 , 28 , 60 , 66 ] which revealed that ChatGPT has the potential to offer personalized learning experiences and support an effective learning process by providing students with customized feedback and explanations tailored to their needs and abilities. Ultimately, fostering students' performance, engagement, and motivation, leading to increase students' academic success [ 14 , 44 , 58 ]. This ultimate outcome is in line with the findings of Saqr et al. [ 68 , 69 ], which emphasized that learning strategies are important catalysts of students' learning, as students who utilize effective learning strategies are more likely to have better academic achievement.

Teachers, too, have capitalized on ChatGPT's capabilities to enhance productivity and efficiency, using it for creating lesson plans, generating quizzes, providing additional resources, generating and preplanning new ideas for activities, and aiding in answering students’ questions. This adoption of technology introduces new opportunities to support teaching and learning practices, enhancing teacher productivity. This finding aligns with those of Day [ 17 ], De Castro [ 18 ], and Su and Yang [ 74 ] as well as with those of Valtonen et al. [ 82 ], who revealed that emerging technological advancements have opened up novel opportunities and means to support teaching and learning practices, and enhance teachers’ productivity.

In response to RQ2 , "What are the main findings derived from empirical studies that have incorporated ChatGPT into learning and teaching?", the findings from this review provide profound insights and raise significant concerns. Starting with the insights, chatbots, including ChatGPT, have demonstrated the potential to reshape and revolutionize education, creating new, novel opportunities for enhancing the learning process and outcomes [ 83 ], facilitating different learning approaches, and offering a range of pedagogical benefits [ 19 , 43 , 72 ]. In this context, this review found that ChatGPT could open avenues for educators to adopt or develop new effective learning and teaching strategies that can evolve with the introduction of ChatGPT into the classroom. Nonetheless, there is an evident lack of research understanding regarding the potential impact of generative machine learning models within diverse educational settings [ 83 ]. This necessitates teachers to attain a high level of proficiency in incorporating chatbots, such as ChatGPT, into their classrooms to create inventive, well-structured, and captivating learning strategies. In the same vein, the review also found that teachers without the requisite skills to utilize ChatGPT realized that it did not contribute positively to their work and could potentially have adverse effects [ 37 ]. This concern could lead to inequity of access to the benefits of chatbots, including ChatGPT, as individuals who lack the necessary expertise may not be able to harness their full potential, resulting in disparities in educational outcomes and opportunities. Therefore, immediate action is needed to address these potential issues. A potential solution is offering training, support, and competency development for teachers to ensure that all of them can leverage chatbots, including ChatGPT, effectively and equitably in their educational practices [ 5 , 28 , 80 ], which could enhance accessibility and inclusivity, and potentially result in innovative outcomes [ 82 , 83 ].

Additionally, chatbots, including ChatGPT, have the potential to significantly impact students' thinking abilities, including retention, reasoning, analysis skills [ 19 , 45 ], and foster innovation and creativity capabilities [ 83 ]. This review found that ChatGPT could contribute to improving a wide range of skills among students. However, it found that frequent use of ChatGPT may result in a decrease in innovative capacities, collaborative skills and cognitive capacities, and students' motivation to attend classes, as well as could lead to reduced higher-order thinking skills among students [ 22 , 29 ]. Therefore, immediate action is needed to carefully examine the long-term impact of chatbots such as ChatGPT, on learning outcomes as well as to explore its incorporation into educational settings as a supportive tool without compromising students' cognitive development and critical thinking abilities. In the same vein, the review also found that it is challenging to draw a consistent conclusion regarding the potential of ChatGPT to aid self-directed learning approach. This finding aligns with the recent study of Baskara [ 8 ]. Therefore, further research is needed to explore the potential of ChatGPT for self-directed learning. One potential solution involves utilizing learning analytics as a novel approach to examine various aspects of students' learning and support them in their individual endeavors [ 32 ]. This approach can bridge this gap by facilitating an in-depth analysis of how learners engage with ChatGPT, identifying trends in self-directed learning behavior, and assessing its influence on their outcomes.

Turning to the significant concerns, on the other hand, a fundamental challenge with LLM-based chatbots, including ChatGPT, is the accuracy and quality of the provided information and responses, as they provide false information as truth—a phenomenon often referred to as "hallucination" [ 3 , 49 ]. In this context, this review found that the provided information was not entirely satisfactory. Consequently, the utilization of chatbots presents potential concerns, such as generating and providing inaccurate or misleading information, especially for students who utilize it to support their learning. This finding aligns with other findings [ 6 , 30 , 35 , 40 ] which revealed that incorporating chatbots such as ChatGPT, into education presents challenges related to its accuracy and reliability due to its training on a large corpus of data, which may contain inaccuracies and the way users formulate or ask ChatGPT. Therefore, immediate action is needed to address these potential issues. One possible solution is to equip students with the necessary skills and competencies, which include a background understanding of how to use it effectively and the ability to assess and evaluate the information it generates, as the accuracy and the quality of the provided information depend on the input, its complexity, the topic, and the relevance of its training data [ 28 , 49 , 86 ]. However, it's also essential to examine how learners can be educated about how these models operate, the data used in their training, and how to recognize their limitations, challenges, and issues [ 79 ].

Furthermore, chatbots present a substantial challenge concerning maintaining academic integrity [ 20 , 56 ] and copyright violations [ 83 ], which are significant concerns in education. The review found that the potential misuse of ChatGPT might foster cheating, facilitate plagiarism, and threaten academic integrity. This issue is also affirmed by the research conducted by Basic et al. [ 7 ], who presented evidence that students who utilized ChatGPT in their writing assignments had more plagiarism cases than those who did not. These findings align with the conclusions drawn by Cotton et al. [ 13 ], Hisan and Amri [ 33 ] and Sullivan et al. [ 75 ], who revealed that the integration of chatbots such as ChatGPT into education poses a significant challenge to the preservation of academic integrity. Moreover, chatbots, including ChatGPT, have increased the difficulty in identifying plagiarism [ 47 , 67 , 76 ]. The findings from previous studies [ 1 , 84 ] indicate that AI-generated text often went undetected by plagiarism software, such as Turnitin. However, Turnitin and other similar plagiarism detection tools, such as ZeroGPT, GPTZero, and Copyleaks, have since evolved, incorporating enhanced techniques to detect AI-generated text, despite the possibility of false positives, as noted in different studies that have found these tools still not yet fully ready to accurately and reliably identify AI-generated text [ 10 , 51 ], and new novel detection methods may need to be created and implemented for AI-generated text detection [ 4 ]. This potential issue could lead to another concern, which is the difficulty of accurately evaluating student performance when they utilize chatbots such as ChatGPT assistance in their assignments. Consequently, the most LLM-driven chatbots present a substantial challenge to traditional assessments [ 64 ]. The findings from previous studies indicate the importance of rethinking, improving, and redesigning innovative assessment methods in the era of chatbots [ 14 , 20 , 64 , 75 ]. These methods should prioritize the process of evaluating students' ability to apply knowledge to complex cases and demonstrate comprehension, rather than solely focusing on the final product for assessment. Therefore, immediate action is needed to address these potential issues. One possible solution would be the development of clear guidelines, regulatory policies, and pedagogical guidance. These measures would help regulate the proper and ethical utilization of chatbots, such as ChatGPT, and must be established before their introduction to students [ 35 , 38 , 39 , 41 , 89 ].

In summary, our review has delved into the utilization of ChatGPT, a prominent example of chatbots, in education, addressing the question of how ChatGPT has been utilized in education. However, there remain significant gaps, which necessitate further research to shed light on this area.

7 Conclusions

This systematic review has shed light on the varied initial attempts at incorporating ChatGPT into education by both learners and educators, while also offering insights and considerations that can facilitate its effective and responsible use in future educational contexts. From the analysis of 14 selected studies, the review revealed the dual-edged impact of ChatGPT in educational settings. On the positive side, ChatGPT significantly aided the learning process in various ways. Learners have used it as a virtual intelligent assistant, benefiting from its ability to provide immediate feedback, on-demand answers, and easy access to educational resources. Additionally, it was clear that learners have used it to enhance their writing and language skills, engaging in practices such as generating ideas, composing essays, and performing tasks like summarizing, translating, paraphrasing texts, or checking grammar. Importantly, other learners have utilized it in supporting and facilitating their directed and personalized learning on a broad range of educational topics, assisting in understanding concepts and homework, providing structured learning plans, and clarifying assignments and tasks. Educators, on the other hand, found ChatGPT beneficial for enhancing productivity and efficiency. They used it for creating lesson plans, generating quizzes, providing additional resources, and answers learners' questions, which saved time and allowed for more dynamic and engaging teaching strategies and methodologies.

However, the review also pointed out negative impacts. The results revealed that overuse of ChatGPT could decrease innovative capacities and collaborative learning among learners. Specifically, relying too much on ChatGPT for quick answers can inhibit learners' critical thinking and problem-solving skills. Learners might not engage deeply with the material or consider multiple solutions to a problem. This tendency was particularly evident in group projects, where learners preferred consulting ChatGPT individually for solutions over brainstorming and collaborating with peers, which negatively affected their teamwork abilities. On a broader level, integrating ChatGPT into education has also raised several concerns, including the potential for providing inaccurate or misleading information, issues of inequity in access, challenges related to academic integrity, and the possibility of misusing the technology.

Accordingly, this review emphasizes the urgency of developing clear rules, policies, and regulations to ensure ChatGPT's effective and responsible use in educational settings, alongside other chatbots, by both learners and educators. This requires providing well-structured training to educate them on responsible usage and understanding its limitations, along with offering sufficient background information. Moreover, it highlights the importance of rethinking, improving, and redesigning innovative teaching and assessment methods in the era of ChatGPT. Furthermore, conducting further research and engaging in discussions with policymakers and stakeholders are essential steps to maximize the benefits for both educators and learners and ensure academic integrity.

It is important to acknowledge that this review has certain limitations. Firstly, the limited inclusion of reviewed studies can be attributed to several reasons, including the novelty of the technology, as new technologies often face initial skepticism and cautious adoption; the lack of clear guidelines or best practices for leveraging this technology for educational purposes; and institutional or governmental policies affecting the utilization of this technology in educational contexts. These factors, in turn, have affected the number of studies available for review. Secondly, the utilization of the original version of ChatGPT, based on GPT-3 or GPT-3.5, implies that new studies utilizing the updated version, GPT-4 may lead to different findings. Therefore, conducting follow-up systematic reviews is essential once more empirical studies on ChatGPT are published. Additionally, long-term studies are necessary to thoroughly examine and assess the impact of ChatGPT on various educational practices.

Despite these limitations, this systematic review has highlighted the transformative potential of ChatGPT in education, revealing its diverse utilization by learners and educators alike and summarized the benefits of incorporating it into education, as well as the forefront critical concerns and challenges that must be addressed to facilitate its effective and responsible use in future educational contexts. This review could serve as an insightful resource for practitioners who seek to integrate ChatGPT into education and stimulate further research in the field.

Data availability

The data supporting our findings are available upon request.

Abbreviations

• Artificial intelligence

AI in education

Large language model

Artificial neural networks

Chat Generative Pre-Trained Transformer

Recurrent neural networks

Long short-term memory

Reinforcement learning from human feedback

Natural language processing

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

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The paper is co-funded by the Academy of Finland (Suomen Akatemia) Research Council for Natural Sciences and Engineering for the project Towards precision education: Idiographic learning analytics (TOPEILA), Decision Number 350560.

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YA contributed to the literature search, data analysis, discussion, and conclusion. Additionally, YA contributed to the manuscript’s writing, editing, and finalization. MS contributed to the study’s design, conceptualization, acquisition of funding, project administration, allocation of resources, supervision, validation, literature search, and analysis of results. Furthermore, MS contributed to the manuscript's writing, revising, and approving it in its finalized state. NP contributed to the results, and discussions, and provided supervision. NP also contributed to the writing process, revisions, and the final approval of the manuscript in its finalized state. MT contributed to the study's conceptualization, resource management, supervision, writing, revising the manuscript, and approving it.

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Correspondence to Yazid Albadarin .

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See Table  4

The process of synthesizing the data presented in Table  4 involved identifying the relevant studies through a search process of databases (ERIC, Scopus, Web of Knowledge, Dimensions.ai, and lens.org) using specific keywords "ChatGPT" and "education". Following this, inclusion/exclusion criteria were applied, and data extraction was performed using Creswell's [ 15 ] coding techniques to capture key information and identify common themes across the included studies.

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Albadarin, Y., Saqr, M., Pope, N. et al. A systematic literature review of empirical research on ChatGPT in education. Discov Educ 3 , 60 (2024). https://doi.org/10.1007/s44217-024-00138-2

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Received : 22 October 2023

Accepted : 10 May 2024

Published : 26 May 2024

DOI : https://doi.org/10.1007/s44217-024-00138-2

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Practical Applications of AI in Education for Accessibility

2024-05-28 | By Orcam Staff

The intersection of artificial intelligence (AI) and education is a rapidly evolving field. It holds immense potential for transforming learning experiences, particularly for students with diverse needs.

AI in education for accessibility is a topic of growing interest. It focuses on leveraging AI tools and solutions to enhance accessibility in learning environments.

This article delves into the practical applications of AI in education. It highlights how AI is breaking down barriers and creating inclusive learning spaces.

We will explore various AI tools that are making education more accessible. From real-time captioning to adaptive learning platforms, AI is revolutionizing the way we approach education.

We will also touch upon the ethical considerations and data privacy issues surrounding the use of AI in education.

Join us as we navigate the exciting landscape of AI in education for accessibility. Discover how AI is shaping the future of inclusive learning.

Understanding AI in Education for Accessibility

AI in education means using smart computer programs to improve teaching and learning. These programs can adjust lessons to fit each student's needs.

Using AI in education helps make learning more inclusive and accessible, especially for students with disabilities.

The following are some of the ways AI is being used to enhance accessibility in education:

Providing real-time captioning and transcription services

Creating adaptive learning platforms that adjust to individual learning styles

Developing assistive technologies for visually and hearing-impaired students

The Significance of AI for Learners with Disabilities

AI has the potential to revolutionize education for learners with disabilities. It can provide customized learning experiences that cater to individual needs and abilities.

For instance, AI tools can convert text to speech for visually impaired students. They can also provide real-time captioning for students with hearing impairments.

These AI tools help make learning easier and more accessible for students with disabilities, allowing them to join in and learn just like their classmates.

Overcoming Educational Barriers with AI

AI is playing a crucial role in overcoming educational barriers. It is helping to create a more inclusive and equitable learning environment.

AI-powered adaptive learning platforms are online tools that change how they teach based on how a student learns best.

They can provide personalized learning pathways that cater to each student's strengths and weaknesses.

Moreover, AI can facilitate language translation and support English as a Second Language (ESL) learners. This can help break down language barriers and make education more accessible to all.

AI Tools Enhancing Learning Support

AI tools are playing a pivotal role in enhancing learning support. They are providing innovative solutions to address the diverse needs of learners.

One of the key areas where AI is making a significant impact is in real-time captioning and transcription services. These tools are particularly beneficial for students with hearing impairments.

AI is also revolutionizing assistive technologies for visually impaired students. It is helping to create more inclusive learning environments.

Moreover, AI is at the forefront of developing adaptive learning platforms. These platforms are transforming education by providing personalized learning experiences.

Real-time Captioning and Transcription Services

AI-powered real-time captioning and transcription services are a game-changer in education. They are making learning more accessible for students with hearing impairments.

AI tools can add captions to live classes and discussions right away. They can also turn spoken words into written text, helping students keep up with the lessons.

By providing real-time captioning and transcription, AI is ensuring that all students can participate fully in the learning process.

Accessibility Technology for Visual and Hearing Impairments

AI is playing a crucial role in developing accessibility technologies for visually and hearing-impaired students. These technologies are enhancing accessibility and inclusivity in education.

For instance, AI-powered tools can convert text to speech for visually impaired students. They can also provide audio descriptions for visual content.

Similarly, AI can enhance the learning experience for students with hearing impairments. It can provide real-time captioning and sign language interpretation.

These AI solutions are not only enhancing accessibility but also empowering students with disabilities to participate fully in the learning process.

Adaptive Learning Platforms and Personalized Education

AI is at the forefront of developing adaptive learning platforms. These platforms use AI algorithms to adjust to individual learning styles.

They can analyze a student's performance and provide personalized learning pathways. This can help cater to each student's strengths and weaknesses.

Moreover, these platforms can provide immediate feedback and assessment. This can help students understand their progress and areas needing improvement.

By providing personalized and accessible education, AI is helping to create a more inclusive and equitable learning environment.

Ethical Considerations and Data Privacy in Educational AI

As AI continues to transform education, ethical considerations and data privacy have become paramount. These issues are critical to ensuring the responsible use of AI in education.

AI systems often require large amounts of data to function effectively. This data can include sensitive information about students' learning habits and performance. Therefore, it's crucial to have robust data privacy measures in place.

We need to make sure AI is used in a fair and open way, with clear rules to protect everyone's privacy. These principles can help ensure that AI tools are used to enhance learning and not to disadvantage or discriminate against certain groups of students.

Case Studies: AI's Impact in Educational Settings

AI's impact on education is not just theoretical. It's already being felt in classrooms around the world. Let's explore some case studies that highlight the transformative power of AI in education.

Supporting ESL Learners and Language Translation

AI has been a game-changer for English as a Second Language (ESL) learners. Tools like Microsoft's Immersive Reader use AI to translate text into different languages, making content more accessible for non-native speakers. This technology is helping to break down language barriers in education.

AI-Driven Analytics for Student Progress

AI is also revolutionizing the way we track student progress. For instance, AI-powered platforms like BrightBytes analyze student data to provide insights into learning patterns. This allows educators to identify areas where students may need additional support, enhancing the learning experience.

The Future of AI in Education and Accessibility

The future of AI in education and accessibility looks promising. As technology continues to evolve, we can expect to see even more innovative AI solutions that enhance learning for all students.

However, it's important to remember that AI is not a magic bullet. It's a tool that can be used to improve education, but it's not a substitute for good teaching and supportive learning environments.

Challenges and Limitations of AI in Education

Despite its potential, AI in education also faces challenges. One of the main issues is the digital divide. Not all students have access to the technology needed to benefit from AI tools.

Moreover, there are concerns about data privacy and the ethical implications of using AI in education. These issues need to be addressed to ensure that AI is used responsibly and effectively.

The Road Ahead: Potential Developments in AI for Education

Looking ahead, we can expect to see AI playing an even bigger role in education. From personalized learning pathways to AI-powered tutoring systems, the possibilities are endless.

However, for these developments to be successful, it's crucial that educators, policymakers, and AI developers work together. By collaborating, we can ensure that AI is used to create inclusive, accessible, and effective learning environments for all students.

Conclusion: Embracing AI for Inclusive Learning

In conclusion, AI holds immense potential to revolutionize education and make it more accessible. It's a powerful tool that can help overcome barriers and create inclusive learning environments.

However, it's crucial that we approach AI with a critical eye, ensuring it's used ethically and effectively to truly enhance education for all.