technology in future will change education essay

How Has Technology Changed Education?

Technology has impacted almost every aspect of life today, and education is no exception. Or is it? In some ways, education seems much the same as it has been for many years. A 14th century illustration by Laurentius de Voltolina depicts a university lecture in medieval Italy. The scene is easily recognizable because of its parallels to the modern day. The teacher lectures from a podium at the front of the room while the students sit in rows and listen. Some of the students have books open in front of them and appear to be following along. A few look bored. Some are talking to their neighbors. One appears to be sleeping. Classrooms today do not look much different, though you might find modern students looking at their laptops, tablets, or smart phones instead of books (though probably open to Facebook). A cynic would say that technology has done nothing to change education.

However, in many ways, technology has profoundly changed education. For one, technology has greatly expanded access to education. In medieval times, books were rare and only an elite few had access to educational opportunities. Individuals had to travel to centers of learning to get an education. Today, massive amounts of information (books, audio, images, videos) are available at one’s fingertips through the Internet, and opportunities for formal learning are available online worldwide through the Khan Academy, MOOCs, podcasts, traditional online degree programs, and more. Access to learning opportunities today is unprecedented in scope thanks to technology.

Opportunities for communication and collaboration have also been expanded by technology. Traditionally, classrooms have been relatively isolated, and collaboration has been limited to other students in the same classroom or building. Today, technology enables forms of communication and collaboration undreamt of in the past. Students in a classroom in the rural U.S., for example, can learn about the Arctic by following the expedition of a team of scientists in the region, read scientists’ blog posting, view photos, e-mail questions to the scientists, and even talk live with the scientists via a videoconference. Students can share what they are learning with students in other classrooms in other states who are tracking the same expedition. Students can collaborate on group projects using technology-based tools such as wikis and Google docs. The walls of the classrooms are no longer a barrier as technology enables new ways of learning, communicating, and working collaboratively.

Technology has also begun to change the roles of teachers and learners. In the traditional classroom, such as what we see depicted in de Voltolina’s illustration, the teacher is the primary source of information, and the learners passively receive it. This model of the teacher as the “sage on the stage” has been in education for a long time, and it is still very much in evidence today. However, because of the access to information and educational opportunity that technology has enabled, in many classrooms today we see the teacher’s role shifting to the “guide on the side” as students take more responsibility for their own learning using technology to gather relevant information. Schools and universities across the country are beginning to redesign learning spaces to enable this new model of education, foster more interaction and small group work, and use technology as an enabler.

Technology is a powerful tool that can support and transform education in many ways, from making it easier for teachers to create instructional materials to enabling new ways for people to learn and work together. With the worldwide reach of the Internet and the ubiquity of smart devices that can connect to it, a new age of anytime anywhere education is dawning. It will be up to instructional designers and educational technologies to make the most of the opportunities provided by technology to change education so that effective and efficient education is available to everyone everywhere.

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The Future of Education: 8 Predictions for the Next Decade

The world of education is changing rapidly, and it can be difficult to keep up with all the latest trends and developments. In this article, we will explore eight key predictions for the future of education. We will examine the rise of online learning, personalized learning, and other trends that are likely to shape the education landscape in the years to come.

With rapid advancements in technology and shifts in societal needs, many are asking, “How do you think the education system will change in the future?” as we anticipate a move towards more personalized, flexible, and technology-driven learning environments.

By staying informed about these future trends in education, educators and policymakers can better anticipate changes and adapt their strategies to ensure that they meet the evolving needs of students and prepare them for success in an increasingly dynamic world.

AI and the Future of Education – Teaching in the Age of Artificial Intelligence

Prediction 1: Online Learning Will Continue to Grow

Online learning has been around for years, but it really took off during the COVID-19 pandemic. Many schools and universities were forced to transition to online learning, and this trend is likely to continue in the future. In fact, a recent report by Research and Markets predicts that the global online education market will grow by over 10% annually between 2021 and 2026.

There are many benefits to online learning, including increased accessibility and flexibility. Students can learn at their own pace, and from anywhere in the world. Online learning is also often more affordable than traditional in-person learning, making education more accessible to a wider range of students.

As we look ahead, the future of learning will likely see a continued expansion of online education, driven by its accessibility, flexibility, and cost-effectiveness, which will reshape how and where students engage with their studies.

Prediction 2: Personalized Learning Will be the Norm

Using AI Chatbots to Enhance Planning and Instruction

Personalized learning is a method that involves tailoring learning experiences to suit the needs and preferences of individual students. This approach is becoming increasingly popular, and it’s predicted that it will become the norm in the future of education.

In traditional classroom settings, teachers often deliver lessons to a large group of students, with little opportunity for individual attention or customization. However, with the rise of technology and data analytics, personalized learning has become much more feasible.

The benefits of personalized learning are significant. Students can learn at their own pace, and in a way that is most comfortable and effective for them. This leads to greater engagement and retention, as well as higher levels of academic achievement.

According to a report by the Gates Foundation, schools that have implemented personalized learning have seen significant improvements in student outcomes. For example, students in a personalized learning program in Chicago’s public schools showed a 50% increase in math proficiency, compared to their peers in traditional classrooms.

As personalized learning becomes more prevalent, the future of schooling will increasingly focus on tailoring educational experiences to meet individual needs, leading to more effective and engaging learning environments that drive academic success and better prepare students for the future.

Prediction 3: Artificial Intelligence Will Revolutionize Education

Artificial Intelligence (AI) is already changing the face of education, and this trend is set to continue. AI can be used to automate administrative tasks, such as grading, which frees up teachers’ time to focus on more meaningful work. It can also be used to create personalized learning experiences, by analyzing data on student performance and providing targeted feedback and recommendations.

AI is also being used to develop intelligent tutoring systems, which provide students with personalized support and guidance. These systems can help identify knowledge gaps, provide additional resources, and even adjust the pace and difficulty of learning to suit individual students’ needs.

Another area where AI is set to revolutionize education is in the development of adaptive assessments. These assessments use machine learning algorithms to adapt to each student’s level of understanding, providing a more accurate and comprehensive evaluation of their knowledge.

As AI continues to evolve, the question of “how will education change in the future?” will increasingly focus on the integration of these technologies to enhance teaching and learning, ultimately shaping the education in future to be more efficient, personalized, and effective.

Are you looking for some of the top AI courses and learning platforms? Read our article Best AI Courses and Learning Platforms for more details.

Prediction 4: Virtual and Augmented Reality Will Transform Education

Virtual and augmented reality (VR/AR) technology has already been used in many industries, including entertainment, sports, and healthcare. However, it is now making its way into the world of education. VR/AR technology allows students to interact with digital objects and environments in a way that was previously impossible. It can create a completely immersive learning experience that engages multiple senses, making it easier for students to remember what they’ve learned.

According to a report by Technavio, the global market for VR in education is expected to grow at a compound annual growth rate of over 58% from 2019 to 2023. This growth is due to the increasing demand for immersive learning experiences and the declining cost of VR/AR hardware. As more schools and universities adopt VR/AR technology, it is likely to become an integral part of the education system.

One of the most exciting applications of VR/AR technology in education is the ability to take students on virtual field trips. This allows students to visit places that would be difficult or impossible to access in real life, such as the surface of Mars or the depths of the ocean. It can also help to bridge cultural and geographical gaps, allowing students to experience different cultures and ways of life.

Another benefit of VR/AR technology is the ability to provide hands-on learning experiences without the need for expensive equipment or resources. For example, medical students can practice surgical procedures in a virtual environment, without the need for cadavers or expensive equipment. This can also be applied to other fields such as engineering, where students can build and test virtual prototypes.

However, the adoption of VR/AR technology in education is not without its challenges. One of the biggest barriers to adoption is the cost of hardware and software. While the cost of VR/AR technology has been declining, it still remains out of reach for many schools and universities. Another challenge is the lack of content available for VR/AR learning experiences. As more educational content is developed, it is likely that the adoption of VR/AR technology in education will accelerate.

Looking for the best virtual reality headsets for education? Read our article 5 Best Virtual Reality Headsets and Their Transformative Use in Classrooms for more details.

Prediction 5: Learning Will Be Lifelong

In the past, education was typically something that was completed in the first two decades of life, with a few exceptions for continuing education programs. However, in the future, learning will be a lifelong pursuit.

This is partly due to the rapid pace of technological change, which means that workers will need to constantly update their skills to remain relevant in the job market. Additionally, as people live longer and retire later, they will have more time and opportunity to continue learning throughout their lives.

According to a report by the Pew Research Center, the majority of Americans believe that lifelong learning will become more important in the future. This means that schools and educational institutions will need to adapt their programs to cater to learners of all ages and backgrounds.

Moreover, as the future of work evolves, the emphasis on lifelong learning will become crucial, prompting educational institutions to develop flexible and accessible learning opportunities that support skill development and career growth throughout an individual’s entire life.

In order to achieve lifelong learning, you can make it an ultimate goal and gradually break it down into smaller goals with several milestones. As you accomplish each milestone, you can reward yourself with customized Me dals thus better motivating yourself to keep learning.

Prediction 6: The Role of Teachers Will Change

As technology becomes more prevalent in the classroom, the role of teachers will inevitably change. While teachers will always be essential to the learning process, their roles will shift from being the primary source of information to being facilitators of learning.

With online resources and personalized learning becoming more common, students will be able to access information and learn at their own pace. Teachers will be there to guide students, answer questions, and provide feedback.

Additionally, as classrooms become more diverse, teachers will need to become more culturally responsive. They will need to understand the unique needs and backgrounds of their students and create inclusive learning environments.

A survey by the Education Week Research Center found that 80% of teachers believe that technology is changing the role of teachers in the classroom. However, 49% also reported feeling unprepared to integrate technology into their teaching.

Hence, the future of teaching and learning will increasingly emphasize mentorship and support, with educators focusing on nurturing critical thinking, creativity, and emotional intelligence to complement the technology-driven aspects of education.

Prediction 7: Competency-Based Education Will Gain Traction

Competency-based education is an approach to learning that focuses on mastering specific skills and knowledge rather than completing a certain amount of time in a class. This approach allows students to move at their own pace and focus on areas where they need more support.

In a competency-based education system, students are assessed on their ability to demonstrate mastery of a particular skill or concept. Once they have demonstrated mastery, they can move on to the next skill or concept.

This approach to education is gaining traction, particularly in higher education. According to the Competency-Based Education Network, there are currently more than 600 colleges and universities in the United States offering competency-based programs.

The benefits of competency-based education are numerous. It allows students to learn at their own pace, focus on areas where they need more support, and demonstrate mastery of specific skills and knowledge. However, there are also challenges to implementing a competency-based education system, including the need for new assessment methods and teacher training.

As we explore the potential of a competency-based education system, it’s clear that adapting to these challenges will be crucial in shaping a future education system that is both flexible and effective in meeting diverse student needs.

Prediction 8: Education Will Become More Global

Thanks to advancements in technology and transportation, the world is becoming increasingly connected. This means that in the education in the future will become more global in nature.

Already, there are many opportunities for students to study abroad, participate in international exchange programs, and engage in online learning with students from around the world. However, in the future, these opportunities will become even more widespread and accessible. Global education will be important for preparing students to work in a globalized economy, as well as for promoting cross-cultural understanding and cooperation.

In conclusion, the future of education is exciting and full of potential. With the advancements in technology and changing needs of the workforce, it is important that the education system adapts to prepare students for the future. The predictions discussed in this article are just a glimpse of what’s to come, and it is up to educators and policymakers to ensure that our education system evolves to meet the needs of future generations.

Embracing the future of technology in education will be key to creating innovative learning environments that not only keep pace with technological advancements but also equip students with the skills and knowledge necessary for success in a rapidly evolving world. Read our article the future of educational technology for more insights on how technology will reshape education.

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How Technology Is Changing Education Essay

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Introduction

Technology in the education sector.

Technology is impacting education simultaneously while evolving itself. With new technologies coming into action, the education sector is witnessing a revolutionary change. No one imagined e-learning, smart learning, or hands-on experience in the last ten years. Thanks to digitalization and the Internet, many new technological-driven approaches have been alternate methods of improving the learning experience. Education is an important part of people’s lives.

In the last centuries, education was limited to a few people with strong financial backgrounds, but things have changed in the modern era as technology is making education accessible for millions of people. For example, online tutorials, online learning, and discussions, among others, have transformed the education sector completely. With the availability of learning content, digitalization, and access to learning tools such as eBooks, technology is changing the education sector for the better, despite a few drawbacks such as students accessing inappropriate content online.

Like never before, technology has brought forth many changes in modern society. For example, it has helped students in gaining more insights and ideas to innovate and work on new technologies. The availability of content and curriculum over the Internet, step-by-step guidance projects, various platforms, and forums to discuss new and exciting changes around the world has given students more exposure and a great learning experience.

Although students study and understand concepts at different paces and degrees, with the help of technology, they are now able to explore more ideas, alternatives, and elements to expand their horizons and capacity. They can view multiple opportunities in which they can work and get help from different people.

With digitalization, information can be attained instantly and transferred to someone who requires help. Unlike in the past when accessing learning materials was difficult, students in the modern learning environment have unlimited access to online content. From photography to software development, the Internet is a platform that can support and provide users with how to tackle problems. Moreover, many online learning centers are empowering students to advance their learning experience.

Further, technology is changing the way of learning and teaching across the globe. In the past, books were considered to be the only source of learning content. However, things have changed nowadays, and information can be accessed on the internet in many forms. Earlier, teacher-to-student interactions were only done in class, unlike in the modern world where educators and learning can interact online anytime. Online education provides flexible timings for course intake, and this makes students balance their time.

However, although technology is changing the education sector for the better, some disadvantages cannot be ignored. For example, it is worth noting that with access to unlimited Internet, some students may end up accessing inappropriate content online. Consequently, this can affect their concentration on their learning process. Nonetheless, technology remains one of the most important innovations that are changing the education system across the globe.

In summary, technology is a platform that enables individuals to create their own space and make a difference in their society. In the education sector, technology has made learning content, digitalization, and access to learning tools easier. However, some drawbacks such as students accessing inappropriate content online cannot be ignored. Nonetheless, there is no doubt that technology creates a dynamic environment for the modern generation to thrive in different fields, including the education sector.

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How Technology Is Changing the Future of Higher Education

Labs test artificial intelligence, virtual reality and other innovations that could improve learning and lower costs for Generation Z and beyond.

By Jon Marcus

This article is part of our latest Learning special report . We’re focusing on Generation Z, which is facing challenges from changing curriculums and new technology to financial aid gaps and homelessness.

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It is one of a small but growing number of places where experts are testing new ideas that will shape the future of a college education, using everything from blockchain networks to computer simulations to artificial intelligence, or A.I.

Theirs is not a future of falling enrollment, financial challenges and closing campuses. It’s a brighter world in which students subscribe to rather than enroll in college, learn languages in virtual reality foreign streetscapes with avatars for conversation partners, have their questions answered day or night by A.I. teaching assistants and control their own digital transcripts that record every life achievement.

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• Published: 12 February 2024

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
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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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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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Chengliang Wang, Xiaojiao Chen, Yidan Liu & Yuhui Jing

Graduate School of Business, Universiti Sains Malaysia, Minden, Malaysia

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Conceptualization: Y.J., C.W.; methodology, C.W.; software, C.W., Y.L.; writing-original draft preparation, C.W., Y.L.; writing-review and editing, T.Y., Y.L., C.W.; supervision, X.C., T.Y.; project administration, Y.J.; funding acquisition, X.C., Y.L. All authors read and approved the final manuscript. All authors have read and approved the re-submission of the manuscript.

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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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Learning Loss, AI and the Future of Education: Our 24 Most-Read Essays of 2023

From rethinking the american high school to the fiscal cliff, tutoring and special ed, what our most incisive opinion contributors had to say.

Some of America’s biggest names in education tackled some of the thorniest issues facing the country’s schools on the op-ed pages of The 74 this year, expressing their concerns about continuing COVID-driven deficits among students and the future of education overall. There were some grim predictions, but also reasons for hope. Here are some of the most read, most incisive and most controversial essays we published in 2023.

David Steiner

America’s education system is a mess, and students are paying the price.

COVID-19, the legacy of race-based redlining, the lack of support for health care, child care and parental leave, and other social and economic policies have taken a terrible toll on student learning. But the fundamental cause of poor outcomes, writes contributor David Steiner of the Johns Hopkins Institute for Education Policy , is that policy leaders have eroded the instructional core and designed our education system for failure. As we have sown, so shall we reap. The challenges and rewards of learning are being washed away, and students are desperately the worse for the mess we have made. Read More

Margaret Raymond

The terrible truth — current solutions to covid learning loss are doomed to fail.

Despite well-intended and rapid responses to COVID learning loss, solutions such as tutoring or summer school are doomed to fail, says contributor Margaret (Macke) Raymond of the Center for Research on Education Outcomes at Stanford University. How do we know? CREDO researchers looked at learning patterns for students at three levels of achievement in 16 states and found that even with five extra years of education, only about 75% will be at grade level by high school graduation. No school can offer that much. It is time to decide whether to make necessary changes or continue to support a system that will almost certainly fail.  Read More

Mark Schneider

The future is stem — but without enough students, the u.s. will be left behind.

America no longer produces the most science and engineering research publications, patents or natural-science Ph.D.s, and these trends are unlikely to change anytime soon. The problem isn’t a lack of universities to train future scientists or an economy incapable of encouraging innovation. Rather, says contributor Mark Schneider of the Institute of Education Sciences, it originates much earlier in the supply chain, in elementary school. Congress has a chance to help turn this around, by passing the New Essential Education Discoveries (NEED) Act.  Read More

John Bailey

The Promise of Personalized Learning Never Delivered. Today’s AI Is Different

Educators often encounter lofty promises of technology revolutionizing learning, only to find reality fails to meet expectations. But based on his experiences with the new generation of artificial intelligence tools, contributor John Bailey believes society may be in the early stages of a transformative moment. This may very well usher in an era of individualized learning, empowering all students to realize their full potential and fostering a more equitable and effective educational experience. Read his four reasons why this generation of AI tools is likely to succeed where other technologies have failed. Read More

Chad Aldeman

Interactive — With More Teachers & Fewer Students, Districts Are Set up for Financial Trouble

To understand the teacher labor market, you have to hold two competing narratives in your head. On one hand, teacher turnover hit new highs, morale is low and schools are facing shortages. At the same time, public schools employ more teachers than before COVID, while serving 1.9 million fewer students. Student-teacher ratios are near all-time lows. Contributor Chad Aldeman and Eamonn Fitzmaurice, The 74’s art and technology director, plotted these changes on an exclusive, interactive map — and explain how they’re putting districts in financial peril. View the Map

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Schools Could Lose 136,000 Teaching Jobs When Federal COVID Funds Run Out

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What will the future of education look like in a world with generative AI?

Mit leaders in education explore the future of technology in and beyond the classroom..

By Sara Feijo and Katherine Ouellette

Generative AI is already changing the education landscape, but can educators ensure a positive impact from this powerful technology?

In a Nov. 29 “Generative AI + Education’’ symposium hosted by MIT Open Learning, leaders in education took more than 250 people on a journey to the future of generative AI in and beyond the classroom. They emphasized how educators must first envision the desired outcomes for children, schools, and society before determining how best to use digital tools to achieve those goals.

Panelists explored how these technologies are transforming the learning experience and teaching practice in K-12, post-secondary education, and workforce upskilling. They also examined the role generative AI should play in supporting effective, engaging, and equitable learning at any age. Key takeaways included:

1. Generative AI has already changed education.

Students are already using generative AI tools like ChatGPT for homework assistance, which alarms educators because they may bypass the assignment’s intended learning objective. For example, essays are often used to teach the mechanics of writing, but learners won’t hone that skill if they’re prompting AI to generate an entire essay for them. Panelists framed this technology as both a potential opportunity and a potential hindrance. If educators reevaluate what they want students to learn, they can revise their curricula to facilitate higher levels of cognitive processing. They can also think about the new opportunities generative AI tools offer to both educators and learners.

However, this isn’t just about technical skills. The Scratch programming language, which is a product of the Lifelong Kindergarten group at the MIT Media Lab, is used by millions of children — and adults — around the world to create and share multimedia projects. But Mitch Resnick, professor and director of the Lifelong Kindergarten group, noted that “we want people to learn about processes and strategies of design that go beyond coding.” Educators should consider how to get students to work creatively, think beyond simple mechanics, and encourage them to ponder deeply about their work.

In a world where information and processes change rapidly and continually, educators and researchers are questioning the value of mere memorization and narrow skills. On the other hand, pedagogies that develop agile learners who are capable of adapting to new and unexpected scenarios are favored by many. Panelists emphasized the importance of fostering opportunities where learners can become creative, collaborative, and curious thinkers. With this in mind, educators could leverage generative AI in their teaching to foster higher-level skills such as critical thinking, analysis, and strategy.

Janet Rankin, director of the MIT Teaching + Learning Lab, said educators should be driven by thinking about what they want their students to do. Once educators know that, they can think about how generative AI fits with those ideas, she said. There have been plenty of disruptive technologies in schools including calculators and the internet. Schools also have a long history of other technologies that had a lot of hype and little impact. Panelists stressed the need to understand which path AI is on.

2. Educators and policymakers must rethink the existing education model.

Many educators and researchers advocate for hands-on constructionist learning, which centers students in the learning process and encourages students to develop their own understanding. However, the instructivist learning model, where teachers deliver instruction to students, is still the dominant education model in many schools. Panelists pointed out that, regardless of the technology at hand, our education system should be moving to more constructionist approaches, where students work on hands-on, project-based learning. With that idea in mind, the question becomes: How can AI support that model?

Modern education balances multiple purposes: instruction, workforce preparation, citizen development, and more. “Historically, technologists have not done a great job of understanding those complex, social, technical systems,” said Justin Reich, director of the MIT Teaching Systems Lab, resulting in new tools developed for the way we wished students learned and schools operated, instead of the ways they actually work. “If you don’t understand these systems you’re building for, then you’re not going to build things that work for those systems,” Reich said.

Pattie Maes, Germeshausen Professor of Media Arts and Sciences at MIT Media Lab, has been thinking about the future and the ways that AI could play a role in learning. When asked about her moonshot, Maes envisioned a context-aware device that is with learners at all times, so its educational assistance would be informed by learners’ experiences. The device could serve as “a mentor, thought-provoker, encouraging you to see things differently and go deeper,” Maes said.

3. Keep equity and access top of mind.

A recurring goal for multiple speakers was to give learners from a broad range of backgrounds control and agency over technology. They expressed concern if these powerful technologies are only developed with limited perspectives, whether it’s a small number of companies in the field or programmers from a narrow demographic. “Who gets included in technology and who does not? What happens when more people participate in tech?” said Randi Williams, research assistant in the MIT Personal Robots group.

Panelists also expressed concern over the increasing disparities that AI technology could bring. If the best AI technologies come with a price tag and take resources to be used effectively, they may privilege well-resourced schools. Panelists stressed the need to think about ways to address these concerns so that AI narrows, rather than widens, existing disparities.

Hal Abelson, professor of computer science and engineering at MIT, argued that generative AI technology should be a tool for everyone, not just highly educated or well-resourced people or those with a technical background. Computational action — a model that seeks to empower children to make a difference in their communities through technology — shows that all children can create tools that improve lives and have meaningful social impacts. For example, high schoolers in Moldova developed a mobile app where people can enter and view clean sources of water on a shared map, a resource that addresses a nationwide problem. Speakers called for the creation of policies to address biases in generative AI and ensure that everyone has access to these powerful technologies.

Generative AI in action

The symposium gave participants a sneak peek into 12 MIT cutting-edge generative AI projects  — from K-12 curricula and professional development for teachers about ChatGPT and hidden biases in these tools, to a personalized educational chat tutor for quantum mechanics, to a mobile app that uses AI-assisted observational learning to improve public speaking skills.

The symposium was part of MIT Generative AI Week . This three-day event series explored the latest cutting-edge research, the implications and possibilities of generative AI, and the opportunities and challenges posed by this technology in education, health, climate science, and management.

Visit the MIT News website for the full coverage of MIT Generative AI Week, including an overview of the entire week, a recap of the “Generative AI: Shaping the Future” symposium and a presentation on generative AI-aided art .

What will the future of education look like in a world with generative AI? was originally published in MIT Open Learning on Medium, where people are continuing the conversation by highlighting and responding to this story.

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Transforming education systems: Why, what, and how

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Rebecca winthrop and rebecca winthrop director - center for universal education , senior fellow - global economy and development the hon. minister david sengeh the hon. minister david sengeh minister of education and chief innovation officer - government of sierra leone, chief innovation officer - directorate of science, technology and innovation in sierra leone.

June 23, 2022

Today, the topic of education system transformation is front of mind for many leaders. Ministers of education around the world are seeking to build back better as they emerge from COVID-19-school closures to a new normal of living with a pandemic. The U.N. secretary general is convening the Transforming Education Summit (TES) at this year’s general assembly meeting (United Nations, n.d.). Students around the world continue to demand transformation on climate and not finding voice to do this through their schools are regularly leaving class to test out their civic action skills.      

It is with this moment in mind that we have developed this shared vision of education system transformation. Collectively we offer insights on transformation from the perspective of a global think tank and a national government: the Center for Universal Education (CUE) at Brookings brings years of global research on education change and transformation, and the Ministry of Education of Sierra Leone brings on-the-ground lessons from designing and implementing system-wide educational rebuilding.   

This brief is for any education leader or stakeholder who is interested in charting a transformation journey in their country or education jurisdiction such as a state or district. It is also for civil society organizations, funders, researchers, and anyone interested in the topic of national development through education. In it, we answer the following three questions and argue for a participatory approach to transformation:  

• Why is education system transformation urgent now? We argue that the world is at an inflection point. Climate change, the changing nature of work, increasing conflict and authoritarianism together with the urgency of COVID recovery has made the transformation agenda more critical than ever. 
• What is education system transformation? We argue that education system transformation must entail a fresh review of the goals of your system – are they meeting the moment that we are in, are they tackling inequality and building resilience for a changing world, are they fully context aware, are they owned broadly across society – and then fundamentally positioning all components of your education system to coherently contribute to this shared purpose.  
• How can education system transformation advance in your country or jurisdiction? We argue that three steps are crucial: Purpose (developing a broadly shared vision and purpose), Pedagogy (redesigning the pedagogical core), and Position (positioning and aligning all components of the system to support the pedagogical core and purpose). Deep engagement of educators, families, communities, students, ministry staff, and partners is essential across each of these “3 P” steps.    

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Our aim is not to provide “the answer” — we are also on a journey and continually learning about what it takes to transform systems — but to help others interested in pursuing system transformation benefit from our collective reflections to date. The goal is to complement and put in perspective — not replace — detailed guidance from other actors on education sector on system strengthening, reform, and redesign. In essence, we want to broaden the conversation and debate.

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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.”

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Rough Drafts: The Transformative Impact of Technology on Education

The evolution of technology has permeated every aspect of our lives, and the field of education is no exception. As we navigate the 21st century, the integration of technology into education is reshaping traditional paradigms. This essay explores the profound impact of technology on education, examining the implementation of personalized learning, the enhancement of teaching efficiency, and the global accessibility of education.

Technology’s Impact on Education: Personalized Learning (Argument 1):

In the realm of education, personalized learning emerges as a groundbreaking paradigm facilitated by technological advancements. The utilization of innovative technologies tailors educational experiences to individual student needs. With the application of adaptive learning platforms and artificial intelligence, students can progress at their own pace, focusing on areas of weakness and accelerating through familiar concepts. This individualized approach not only caters to diverse learning styles but also fosters a deeper understanding of subjects.

Counter Argument 1: Concerns about Unemployment

However, this shift towards personalized learning raises concerns about potential unemployment among educators. The fear is that automation might replace traditional teaching roles. To address this, it is crucial to invest in training programs that empower educators to adapt and integrate technology effectively. By embracing a collaborative model, where technology augments rather than replaces human instructors, we can strike a balance between innovation and job preservation.

Technology’s Impact on Education: Enhanced Teaching Efficiency (Argument 2):

The integration of technology in education extends beyond personalized learning to enhance overall teaching efficiency. Online resources, interactive multimedia, and automated assessment tools contribute to a dynamic and engaging learning environment. Educators can leverage a wealth of digital materials to supplement traditional teaching methods, providing students with a rich and varied educational experience.

Counter Argument 2: Dependency on Technology

Despite these advantages, concerns linger about the overreliance on technology in the learning process. Students may become dependent on digital tools, potentially hindering the development of critical thinking and problem-solving skills. Striking a balance between technology and traditional teaching methods is imperative to ensure a holistic and well-rounded education.

Sokolov, M. (2001). Technology’s impact on society: The issue of mass-customized education.  Technological Forecasting and Social Change ,  68 (2), 195-206.

Peters, M. A. (2019). Technological unemployment: Educating for the fourth industrial revolution. In  The Chinese dream: Educating the future  (pp. 99-107). Routledge.

Schmid, R. F., Bernard, R. M., Borokhovski, E., Tamim, R., Abrami, P. C., Wade, C. A., … & Lowerison, G. (2009). Technology’s effect on achievement in higher education: a Stage I meta-analysis of classroom applications.  Journal of computing in higher education ,  21 , 95-109.

Altbach, P. G. (1977). Servitude of the Mind?: Education, Dependency, and Neocolonialism.  Teachers College Record ,  79 (2), 1-11.

Nordlöf, C., Hallström, J., & Höst, G. E. (2019). Self-efficacy or context dependency?: Exploring teachers’ perceptions of and attitudes towards technology education.  International Journal of Technology and Design Education ,  29 (1), 123-141.

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Life in 2050: A Glimpse at Education in the Future

Thanks to growing internet access and emerging technologies, the way we think of education will dramatically change..

Matthew S. Williams

Welcome back to our “Life in 2050” series, where we examine how changes that are anticipated for the coming decades will alter the way people live their lives. In previous installments, we looked at how warfare , the economy , housing , and space exploration (which took two installments to cover!) will change by mid-century.

Today, we take a look at education and how social, economic, and technological changes will revolutionize the way children, youth, and adults go to school. Whereas modern education has generally followed the same model for over three hundred years, a transition is currently taking place that will continue throughout this century.

This transition is similar to what is also taking place in terms of governance, the economy, and recreation. In much the same way, the field of education will evolve in this century to adapt to four major factors. They include:

• Growing access to the internet
• Improvements in technology
• Distributed living and learning
• A new emphasis on problem-solving and gamification

The resulting seismic shift expected to occur by 2050 and after will be tantamount to a revolution in how we think about education and learning. Rather than a centralized structure where information is transmitted, and retention is tested, the classroom of the future is likely to be distributed in nature and far more hands-on.

To the next generations, education in the future will look a lot more like playtime than schooling!

A Time-Honored Model

Since the 19th century, public education has become far more widespread. In 1820, only 12% of people worldwide could read and write. As of 2016, that figure was reversed, where only 14% of the world’s population remained illiterate. Beyond basic literacy, the overall level of education has also increased steadily over time.

Since the latter half of the 20th century, secondary and post-secondary studies (university and college) have expanded considerably across the world. Between 1970 and 2020 , the percentage of adults with no formal education went from 23% to less than 10%; those with a partial (or complete) secondary education went from 16% to 36%; and those with a post-secondary education from about 3.3% to 10%.

Of course, there remains a disparity between the developing and developed world when it comes to education outcomes. According to data released in 2018 by the Organization for Economic Co-operation and Development (OECD), the percentage of people to graduate secondary school (among their 38 member nations) was 76.86% for men and 84.82% for women.

The same data indicated that among OECD nations, an average of 36.55% of the population (29.41% men and 44.10% women) received a post-secondary degree. This ranges from a Bachelor’s degree (24.07% men, 36.91% women) and a Master’s degree (10.5% men, 16.17% women) to a Ph.D. (less than 1% of men and women).

Despite this expansion in learning, the traditional model of education has remained largely unchanged since the 19th century. This model consists of people divided by age (grades), learning a standardized curriculum that is broken down by subject (maths, sciences, arts, social sciences, and athletics), and being subject to evaluation (quizzes, tests, final exam).

This model has been subject to revision and expansion over time, mainly in response to new technologies, socio-political developments, and economic changes. However, the structure has remained largely intact, with the institutions, curricula, and accreditation standards subject to centralized oversight and control.

Global Internet

According to a 2019 report compiled by the United Nations’ Department of Economic and Social Affairs — titled “ World Population Prospects 2019 ” — the global population is expected to reach 9.74 billion by mid-century. With a population of around 5.29 billion, Asia will still be the most populous continent on the planet.

However, it will be Africa that experiences the most growth between now and mid-century. Currently, Africa has a population of 1.36 billion, which is projected to almost double by 2050 — reaching up to 2.5 billion (an increase of about 83%). This population growth will be mirrored by economic growth, which will then drive another sort of growth.

According to a 2018 report by the UN’s International Telecommunication Union (ITU), 90% of the global population will have access to broadband internet services by 2050, thanks to the growth of mobile devices and satellite internet services . That’s 8.76 billion people, a 220% increase over the 4 billion people (about half of the global population) that have access right now.

The majority of these new users will come from the “developing nations,” meaning countries in Africa, South America, and Oceania. Therefore, the internet of the future will be far more representative of the global population as more stories, events, and trends that drive online behavior come from outside of Europe and North America.

Similarly, the internet will grow immensely as trillions of devices, cameras, sensors, homes, and cities are connected to the internet — creating a massive expansion in the “ Internet of Things .” Given the astronomical amount of data that this will generate on a regular basis, machine learning and AI will be incorporated to keep track of it all, find patterns in the chaos, and even predict future trends.

AI will also advance thanks to research into the human brain and biotechnology, which will lead to neural net computing that is much closer to the real thing. Similarly, this research will lead to more advanced versions of Neuralink , neural implants that will help remedy neurological disorders and brain injuries, and also allow for brain-to-machine interfacing.

This means that later in this century, people will be able to perform all the tasks they rely on their computers for, but in a way that doesn’t require a device. For those who find the idea of neural implants unsettling or repugnant, computing will still be possible using smart glasses, smart contact lenses , and wearable computers .

From Distance Ed to MOOCs

In the past year, the coronavirus and resulting school closures have been a major driving force for the growth of online learning. However, the trend towards decentralization was underway long before that, with virtual classrooms and online education experiencing considerable growth over the past decade.

In fact, a report compiled in February of 2020 by Research and Markets indicated that by 2025, the online education market would be valued at about $320 billion USD . This represents a growth of 170% — and a compound annual growth rate (CAGR) of 9.23% since 2019 when the e-learning industry was valued at $187.87 billion USD .

What’s more, much of this growth will be powered by economic progress and rising populations in the developing nations (particularly in Africa, Asia, and South America). Already, online education is considered a cost-effective means to address the rising demand for education in developing nations.

As Stefan Trines, a research editor with the World Education News & Reviews, explained in an op-ed he penned in August of 2018 :

“While still embryonic, digital forms of education will likely eventually be pursued in the same vein as traditional distance learning models and the privatization of education, both of which have helped increase access to education despite concerns over educational quality and social equality.

“Distance education already plays a crucial role in providing access to education for millions of people in the developing world. Open distance education universities in Bangladesh, India, Iran, Pakistan, South Africa, and Turkey alone currently enroll more than 7 million students combined.”

While barriers remain in the form of technological infrastructure (aka. the “digital divide”), the growth of internet access in the next few decades will be accompanied by an explosion in online learning. Another consequence will be the proliferation of Massive Open Online Courses (MOOCs) and other forms of e-learning, which will replace traditional distance education.

Here too, the growth in the past few years has been very impressive (and indicative of future trends). Between 2012 and 2018 , the number of MOOCs available increased by more than 683%, while the total number of students enrolled went from 10 million (in 2013) to 81 million, and the number of universities offering them increased by 400% (from 200 to 800).

Between 2020 and 2050 , the number of people without any formal education will decline from 10% to 5% of the global population. While the number of people with a primary and lower secondary education is expected to remain largely the same, the number of people with secondary education is projected to go from 21% to 29% and post-secondary education from 11% to 18.5%.

For developing nations, distributed learning systems will offer a degree of access and flexibility that traditional education cannot. This is similar to the situation in many remote areas of the world, where the necessary infrastructure doesn’t always exist (i.e., roads, school buses, schoolhouses, etc.).

New Technologies & New Realities

Along with near-universal internet access, there are a handful of technologies that will make education much more virtual, immersive, and hands-on. These include augmented reality (AR), virtual reality (VR), haptics , cloud computing, and machine learning (AI). Together, advances in these fields will be utilized to enhance education.

By definition, AR refers to interactions with physical environments that are enhanced with the help of computer-mediated images and sounds, while VR consists of interacting with computer-generated simulated environments. However, by 2050, the line between simulated and physical will be blurred to the point where they are barely distinguishable.

This will be possible thanks to advances in “haptics,” which refers to technology that stimulates the senses. Currently, this technology is limited to stimulating the sensation of touch and the perception of motion. By 2050, however, haptics, AR, and VR are expected to combine in a way that will be capable of creating totally realistic immersive environments.

These environments will stimulate the five major senses (sight, sound, touch, taste, smell) as well as somatosensory perception — pressure, pain, temperature, etc. For students, this could mean simulations that allow the student to step into a moment in history and to see and feel what it was like to live in another time and place — with proper safety measures (let’s not forget that history is full of violence!).

This technology could extend beyond virtual environments and allow students the opportunity to visit places all around the globe and experience what it feels like to actually be there. It’s even possible that this technology will be paired with remote-access robotic hosts so students can physically interact with the local environment and people.

Cloud computing will grow in tandem with increased internet access, leading to an explosion in the amount of data that a classroom generates and has access to. The task of managing this data will be assisted by machine learning algorithms and classroom AIs that will keep track of student tasks, learning, retention, and assess their progress.

New & Personalized Curriculums

In fact, AI-driven diagnostic assessments are likely to replace traditional grading, tests, and exams as the primary means of measuring student achievement. Rather than being given letter grades or pass/fail evaluations, students will need to fulfill certain requirements in order to unlock new levels in their education.

The ease with which students can connect to classrooms will also mean that teachers will no longer need to be physically present in a classroom. By 2050, “ virtual teacher ” is likely to become an actual job description! Ongoing progress in the field of AI and social robotics is also likely to result in classrooms that are led by virtual or robotic teachers and education assistants.

Speaking of robotics, emerging technologies and the shifting nature of work in the future will be reflected in the kinds of tasks students perform. For this reason, students are sure to spend a significant portion of their lessons learning how to code and build robots , take apart and reassemble complex machines, and other tasks that will enhance their STEM skills.

Other professions that emerge between now and 2050 are also likely to have an impact on student education. Given their importance to future generations, students are sure to learn about additive manufacturing (3D printing), space travel, renewable energy, and how to create virtual environments, blockchains , and digital applications .

In addition to adapting to new demands, school curriculums are likely to become a lot more decentralized as a result of technological changes. On the one hand, schools are likely to abandon compartmentalized study — math, science, language, literature, social studies, etc. — in favor of more blended learning activities that cut across these boundaries.

Gaming, Problem Solving, & Incentives

Another major change is the way education is expected to become “gamified.” This is the philosophy behind Ad Astra , a private school created by Elon Musk and educator Joshua Dahn for Musk’s children and those of SpaceX’s employees. Since then, this school has given way to Astra Nova , which follows the same philosophy, but is open to the general public.

With their emphasis on destructured learning and focus on problem-solving, these schools provide something of a preview for what education will look like down the road. As Musk remarked in a  2013 interview with Sal Khan, founder of the online education platform Khan Academy :

“What is education? You’re basically downloading data and algorithms into your brain. And it’s actually amazingly bad in conventional education because it shouldn’t be like this huge chore… The more you can gamify the process of learning, the better. For my kids, I don’t have to encourage them to play video games. I have to pry them out of their hands.”

This approach is similar to the Montessori method of education , where students engage in self-directed learning activities in a supportive and well-equipped environment. While many practices have come to be included under the heading of “Montessori school,” the general idea is to avoid using highly structured and transmission-based methods.

Combined with cutting-edge technology, this same philosophy is projected to become far more widespread and will be possible without the need for physical classrooms, schools, textbooks, etc. In this respect, it is the Synthesis School , another spin-off of Ad Astra, that provides the closest approximation of what the future of education will be like.

The Synthesis School is an open-access educational platform that takes the problem-solving and gamified approach of Ad Astra and Astra Nova and makes it available as an enrichment activity to the entire world (for a fee). In the future, children and youths from all over the world could be following the same process: Logging in from just about anywhere, forming groups, and playing games that develop our faculties.

The growing use of cryptocurrencies and non-fungible tokens (NFTs) will also have an effect on schooling. In terms of the future economy, these technologies could replace traditional fiat money and banking. But in education, they could facilitate an entirely new system of reward and punishment.

Here too, Ad Astra and Astra Nova offer a preview of what this might look like. In these schools, students are encouraged to earn and trade a unit of currency called the “ Astra .” This system is designed to reward students for good behavior while also teaching them about money management and entrepreneurship.

By 2050, the majority of students around the world may no longer have to physically go to school in order to get an education. Instead, they will be able to log in from their home, a common room in their building, or a dedicated space in their community. From there, they will join students from all around the world and engage in problem-solving tasks, virtual tours, and hands-on activities.

For hundreds of millions of students, this will represent a chance to at a brighter future for themselves and others. For many children, it will be an opportunity to learn about the world beyond their front door and how to facilitate the kind of changes that will benefit us all.

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For others, the transformation of education that is anticipated in the coming decades is a chance to fulfill the dream of countless generations. As long as education has existed as a formal institution, educators have wrestled with questions regarding the best way to impart knowledge, foster intellectual acumen, and inspire future leaders.

As Socrates famously said, “Education is the kindling of a flame, not the filling of a vessel.” Through technology that allows us to create education that is tailored to the individual, universal in nature, and decentralized in structure, we may finally have found the means for ensuring that every student finds their path to success.

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ABOUT THE EDITOR

Matthew S. Williams Matthew S Williams is an author, a writer for Universe Today, and the curator of their Guide to Space section. His works include sci-fi/mystery The Cronian Incident and his articles have been featured in Phys.org, HeroX, Popular Mechanics, Business Insider, Gizmodo, and IO9, ScienceAlert, Knowridge Science Report, and Real Clear Science, with topics ranging from astronomy and Earth sciences to technological innovation and environmental issues. He is also a former educator and a 5th degree Black Belt Tae Kwon Do instructor. He lives on Vancouver Island with his wife and family.  

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The future of educational technology

Dan Schwartz is a cognitive psychologist and dean of the Stanford Graduate School of Education.

He says that artificial intelligence is a different beast, but he is optimistic about its future in education. “It’s going to change stuff. It’s really an exciting time,” he says. Schwartz imagines a world not where AI is the teacher, but where human students learn by teaching AI chatbots key concepts. It’s called the Protégé Effect, Schwartz says, providing host Russ Altman a glimpse of the future of education on this episode of Stanford Engineering’s The Future of Everything podcast.

Listen on your favorite podcast platform:

Related : Dan Schwartz , professor of educational technology

[00:00:00] Dan Schwartz: You know, the tough question for me is, should you let the kid use ChatGPT during the test? Right? And we had this argument over calculators, right? And finally they came up with ways to ask questions where it was okay if the kids had calculators. Because the calculator was doing the routine stuff and that's not really what you cared about. What you cared about was, could the kid be innovative? Could they take another, a second approach to solve a problem? Things like that.

[00:00:33] Russ Altman: This is Stanford Engineering's The Future of Everything, and I'm your host, Russ Altman. If you're enjoying The Future of Everything podcast, please hit the follow button in the app that you're listening to now. This will guarantee that you never miss an episode. 

[00:00:46] Today, Dan Schwartz will tell us how AI is impacting education. He studies educational technology and he finds that there's a lot of promise and a lot of worries about how we're going to use AI in the classroom. It's the future of educational technology. Before we get started, please remember to follow the show in the app that you listen to. You'll be alerted to all of our episodes and it'll make sure that you never miss the future of anything.

[00:01:16] You know, the rise of AI has been on people's minds ever since the release of ChatGPT. Especially the powerful one that started to do things that were scary good. We've seen people using it in business, in sports, in entertainment, and definitely in education. When it comes to education, there are some fundamental questions, however, are we teaching students how to use AI? Or are we teaching students? How do we assess them? Can teachers grade papers with AI? Can students write papers with AI? Why is anybody doing anything? Why don't we just have the AI talk to itself all day? These are real questions that come up in AI. 

[00:01:55] Fortunately, we're going to be talking to Dan Schwartz, who's a professor of education and a dean of the School of Education at Stanford University about how AI is impacting education.

[00:02:06] Dan, the release of ChatGPT has had an impact all over the world, people are using it in all kinds of ways. And clearly one of the areas that AI, especially generative AI has made impact is in education. Students are clearly using it, teachers are thinking about using it or using it. You're the Dean of Education at Stanford. What's your take on the situation right now for AI in education? 

[00:02:33] Dan Schwartz: Okay, so lots of answers to that, but, but, you know, the thing I've enjoyed the most is, uh, showing it to people and watching their reaction. So I'm a cognitive psychologist. I study creativity, learning, what it means to understand. And you show this to people and you just see them go, oh my lord.

[00:02:53] And then the next thing you see is they begin to say, uh, what's left for humans? Like what's left? And then they sort of say, wait a minute, will there be any jobs? And then finally they sort of say. Oh my goodness, education needs to change. And as a dean who raises money for a school, this is the best thing to ever happen. No, whether it's good or bad, it doesn't matter. Everybody realizes it's going to change stuff. And so it's really an exciting time. 

[00:03:22] Russ Altman: So that is really good news. I have to say going into this and I have to reveal a bias. I have often wondered if technology has any place in a classroom. And I think it's because I was, uh, I was injured as a youth.

[00:03:37] This is in the 1970s when some teachers tried to put a computer program in front of me and I was a pretty motivated student and I worked with this computer for about six minutes, and I should say, I'm not an anti-computer person. I literally spent all my time writing algorithms and doing computation work. But I just felt as a youth that I wanted to have a teacher in front of me, a human telling me things. Uh, and so that is clearly not the direction, I hear you laughing. So talk to me about the appropriate way to think about computers. Because I really have a big negative reaction to the idea of anything standing between me and a teacher.

[00:04:18] Dan Schwartz: You must have had very good teachers. 

[00:04:19] Russ Altman: I might have. 

[00:04:19] Dan Schwartz: So Russ, you sound like someone who doesn't play video games. 

[00:04:23] Russ Altman: I do not play video games. 

[00:04:24] Dan Schwartz: So there's this world out there where people can experience things they could never experience, uh, directly. And no teacher can deliver this immersive experience of you in the Amazon searching for anthropological artifacts. There's also something called social media that people use. 

[00:04:43] Russ Altman: I've heard about this. 

[00:04:43] Dan Schwartz: Yeah. Yeah. 

[00:04:44] Russ Altman: I think we disseminate the show using it. 

[00:04:46] Dan Schwartz: So back in the day. 

[00:04:47] Russ Altman: Okay. So I'm a dinosaur. 

[00:04:49] Dan Schwartz: Uh, back in the day, you got the Apple 2 maybe, and it's about 64 K, maybe. It's got a big floppy drive and it takes all its CPU power to draw a picture of a two plus two on the screen. So I think things have changed a little bit Russ. But I appreciate your desire to be connected to teachers. I don't think we're replacing them. 

[00:05:14] Russ Altman: I'm not going to give you a lecture about teaching. But I will say this one sentence that was reverberating through my brain when I was getting ready for our interview, which was when I'm in a classroom, and this has been since I've been in third grade. I am watching the teacher trying to understand, how they think about the information and how they struggle with it to like understand it and then try to relay it to me.

[00:05:34] And so it is, that's where I'm learning. I'm, it's not even what they're saying. It's they're painting a picture for their cognitive model of what they're talking about. And that's what I'm trying to pull out to this day. And so that's why I have such a negative reaction to anything standing between me and this other human who has a model that is more advanced than mine about the material that we're struggling with and I just, I'm trying to download that model. 

[00:06:01] Dan Schwartz: Wow. You're, you are a cognitive psychologist, Russ? 

[00:06:03] Russ Altman: I don't know. 

[00:06:05] Dan Schwartz: Like I had a buddy who sort of became a Nobel laureate. And he talked about how he loved take apart cars, and I'd say I love to watch you take apart cars, just to figure out what you're doing. No, so I think, let's separate this. There's the part where you think the interaction with the teacher is important. I don't know that you need it eight hours a day. You know, that's an awful lot of interaction. I'm not sure I want to be with my mom and dad for eight hours a day trying to figure out their thinking. So you don't need it all the time.

[00:06:34] On the other side, you know, we can do creative things with the computers. So for example, I wrote a program where students learn by teaching a computer agent. And so they're trying to figure out how to get the agent to think the way it should in the domain. Turns out it's highly motivating. The kids learn a lot. The problem was the technology quickly became obsolete. Because after kids used it for a couple of days, they no longer needed it, 'cause they'd figured out sort of how to do the kind of reasoning that we wanted them to teach the agent to do for reasoning. 

[00:07:06] Russ Altman: That's exactly what I was talking about before, about my relationship with my teacher. And you just flipped it, but it's the same idea, which is that there's a cognitive model that you're trying to transfer. And by doing that transfer, you get in, you introspect on it and you understand what it is that you're thinking about. 

[00:07:22] Dan Schwartz: I think that's right. You know, so the concern is the computer does all the work, right? And so I'm just sitting there pressing a button that isn't relevant to the domain I'm trying to learn. But you know, uh, one of the things computers are really good at, like as good as casinos, is motivation. So some computer programs, they gamify it. I'm not sure that's a great use of it. Because you, you know, you try and you learn to just beat the game for the reward. 

[00:07:49] Russ Altman: Right.

[00:07:49] Dan Schwartz: As opposed to learn the content. But things like having, teaching an intelligent agent how to think. There's something called the protege effect, which is you'll try harder to learn the content to teach your agent than you will to prepare for a test. Right? So we can make the computer pretty social. 

[00:08:08] Russ Altman: Okay. So you are clearly a technology optimist in education. And in addition to the amazing fundraising and like, there's so many questions to be answered. What I think a lot of people are worried about is, are we at risk of losing a gen. We've already lost a few generations of students, some people argue, because of the pandemic and the terrible impact it had, especially on, uh, on people who weren't privileged in society and in their education.

[00:08:34] Are we about to enter yet another shock to the system where, because of the ease of having essays written and having, and grading papers, that we really don't serve a generation of students well? Or do you think that's a overhyped, unlikely to happen thing? 

[00:08:51] Dan Schwartz: No, it's a good question. You know, that part of this is people's view about cheating, you know? And so it's too easy for students to do certain things. But there's another response that I want to hang on to. I want to ask you, Russ, are you using, you teach. 

[00:09:07] Russ Altman: Yeah. 

[00:09:07] Dan Schwartz: Are you like putting in all sorts of rules to prevent students from cheating, or are you saying, use it, do whatever you can. I'm going to outsmart your technique anyway.

[00:09:17] Russ Altman: It's a little bit more on the latter. So we, uh, I teach an ethics class, which is a writing class. And we allow ChatGPT because the, my fellow instructor and I decided, and this was the quote, we want to be part of the future, not part of the past. So we said to the students, 

[00:09:33] Dan Schwartz: Sorry, The Future of Everything, Russ.

[00:09:34] Russ Altman: Thank you. Thank you. Thank you. And thanks for the plug. So, uh, we allow it. We asked them to tell us what prompt they used and to show us the initial output that they got from that prompt. And then we, of course, have them hand in the final thing. And we instruct the TAs and ourselves, when we grade that we're grading the final product with or without a declaration of whether ChatGPT is used.

[00:09:56] We do have engineers as TAs, which means that they did a careful analysis. Students who used ChatGPT, and I don't think this is a surprise, got slightly lower grades, but spend substantially less time on the assignment. So if you're a busy student, you might say, I will make that trade off because the grades weren't a ton worse. It was like two points out of a hundred, like from a ninety to an eighty-eight, and they completed it in like half the time. 

[00:10:25] Dan Schwartz: Uh, do you think they learned less? 

[00:10:28] Russ Altman: So we don't know. We don't know. And, uh, the evaluation of learning is something that I'm looking to you, Dan. Uh, how do I tell? So, um, so we do try to use it. But we are stressed out. We have seen cases where people say they used ChatGPT, but tried to mislead us in how they use it. They said, I only used it for copy editing, but it was clear that they did more than copy editing with it. And so there's at the edges, there are some challenges. But in the end, we said motivated students who want to learn will use it as a tool and we'll learn. And the students who we have failed to motivate, and it is our failure, you could argue. They're just going to do whatever they do, and we're not going to be able to really impact that trajectory very much. 

[00:11:12] Dan Schwartz: Yeah, you know, you sort of see the same thing with video, video-based lectures. So I'm online. I've got this lecture. Do I really want to sit and listen to the whole thing? Not really. I'm going to skim forward to find the information. I skim back. I'm probably going to end up doing the minimum amount if it's not a great lecture. 

[00:11:29] Russ Altman: Yeah.

[00:11:29] Dan Schwartz: So I'm not sure this is a ChatGPT phenomenon. It's just, it's sort of an enabler. I think the challenge is thinking of the right assignment. So like, you can grade things on novel and appropriateness. So, are they novel? You know, if they use ChatGPT like everybody else, they won't be novel. They'll all produce the same thing. 

[00:11:48] Russ Altman: It's incredibly, yes. It, so it is, um, there's the most common type of, uh, moral theory is called common morality. And it turns out that ChatGPT does pretty well at that one because there's so many examples that it has seen. And it's terrible at Kant. Deontology, it really can't do. Okay, so let me. 

[00:12:07] Dan Schwartz: So let me get back to your question. 

[00:12:09] Russ Altman: Yeah. 

[00:12:09] Dan Schwartz: So here's what I see going on right now. There, there are like, uh, big industry conferences. Because they're going to, they're producing the technology that schools can adopt. Right? And there's a lot of money there. And twenty years ago, there were zero unicorns, and about, uh, I think last year, fifty-four billion dollar valuation companies in ed tech. So this is a big change. So what are they doing? They're basically creating things to do stuff to students, right? 

[00:12:42] So maybe they're marketing to the teachers, but it's, you know, it's, I'll make a tutor that, uh, is more efficient at delivering information to the students. Or, I will make a program that can correct their math very quickly. And so what's happening is the industry is sort of using the AI in the way that nobody else uses it.

[00:13:04] Because everybody who's got this tool wants to create stuff, right? Like, uh, my brother. It's my birthday, what does he do? He has ChatGPT to write me a poem about Dan Schwartz at Stanford. What he doesn't know is that there's a lot of Dan Schwartz's and so evidently I wear colorful ties, but this is what everybody wants to do. They want to create with it. Meanwhile, the field is trying to push towards efficiency. Can we get the kids done faster? Can we get them through the curriculum faster? Can we correct them faster? In which case the kids are going to optimize for being really efficient, right? As opposed to just trying to be creative, innovative, use it for deeper kinds of things. So this is my big fear. 

[00:13:42] Russ Altman: And so you're watching these companies and I'm guessing that they don't always ask your opinion about what's, what would you tell, so let's say a, one of these unicorn billion dollar or more companies comes to you and says, we want to do this right. We want to use the best educational research to create AI that can bring education to people who might otherwise not have quality education. What would you tell them? 

[00:14:04] Dan Schwartz: So this is a challenge, right? This is something we're actively trying to solve. So we've created a Stanford accelerator for learning to kind of figure out how to do this. 'Cause I've been in this ed tech position for quite a while. And the companies come in and they say, we really want your opinion. And then they present what they're doing. And I go, uh, have you ever thought of, and they go, wait, let me finish. And this goes on for fifty-five minutes. Where they're telling me what they want to do. And I'm trying to say, you know, if you just did this. And the way it ends is I say to them, look, you, if you do these three things, I'll consider being an advisor.

[00:14:42] Russ Altman: Right.

[00:14:42] Dan Schwartz: They never come back. 

[00:14:45] Russ Altman: So the message you're sending them is just not in their worldview. 

[00:14:50] Dan Schwartz: It's because they have a vision. Everybody wants to start their own school. 

[00:14:53] Russ Altman: Yeah. 

[00:14:53] Dan Schwartz: They have their vision of what it should be and they're urgent to get it done. And you know, it's a startup mentality. So trying to figure out how can we educate them? You know, I think we know a lot about how people learn that, uh, that we didn't know twenty years ago when they went to school. And the AI, you know, one of the things it can do is implement some of these theories of learning in ways that don't exist in textbooks and things like that.

[00:15:17] So that's the big hope. And the question is, how can you take advantage of industry? You know, education is a public good, but they still buy all their products. And so going through those companies is one way to sort of bring a positive revolution. But again, I'm a little worried that the companies are, and they're sort of optimizing for local minima.

[00:15:41] Russ Altman: Yeah. 

[00:15:41] Dan Schwartz: You know, to accommodate the current schools and things like that. 

[00:15:44] Russ Altman: Should we take, so what, should we take solace in the teachers? So many of us are fans of teachers, grammar school teachers, middle school teachers, high school teachers, but many of these folks are incredibly dedicated. Will they be a final, um, uh, a final filter that looks at these, uh, educational technologies and says, absolutely not. Or yeah, we'll use that, but we're going to use that in a way that makes sense for my way of teaching. Or are they not in a position to make those kinds of, what you could call courageous decisions, about kind of modifying the use of these tools to make them as good as possible in, uh, on the ground? 

[00:16:21] Dan Schwartz: So it's pretty interesting. The surveys I've seen, uh, sort of over the last year, the different groups do different surveys. It, it sort of, if I take the average, about sixty percent of K 12 teachers are using GenAI, right? And about thirty percent of the kids. If I go to the college level, about thirty percent of the faculty are using GenAI in teaching and about eighty percent of the kids are using it. So I do think in the pre K to 12 space, the teachers are making decisions. They do a lot of curriculum. There are, so a great application is, um, project-based learning. So project-based learning is a lot of fun. Kids learn a lot. They sort of develop a passion, a certain depth. As opposed to just mastering sort of the requirements, but it's really hard to manage. You know, when I was a high school teacher, I had a hundred and thirty kids, right?

[00:17:11] If all of them have a separate project, I have to help plan them and make them goal, you know, learning goal appropriate. So the GenAI can help me do that. It can help me, uh, have the kids sort of help use it to help them design a successful project. Uh, it can help me with a dashboard that helps manage them, hitting their milestones, things like that.

[00:17:31] And there, you know, it's, it, the, teacher is like, I can do something I just couldn't do before. 

[00:17:35] Russ Altman: Yeah. Yeah. 

[00:17:36] Dan Schwartz: It's different than the model where you put the kids in the back of the room who finished early and say, go use the computer. I think, you know, most schools, kids are carrying computers in classes. So it's a little different. It's more integrated than it used to be. 

[00:17:52] Russ Altman: This is the Future of Everything with Russ Altman. More with Dan Schwartz, next.

[00:18:06] Welcome back to The Future of Everything. I'm Russ Altman and I'm speaking with Dan Schwartz, professor of education at Stanford University. 

[00:18:12] In the last segment, Dan told us about AI, education, some of the promises and some of the pitfalls that he's looking at on the ground, thinking about how to educate the next generation.

[00:18:23] In this segment, I'm going to ask him about assessment, grading. How do we do that with AI and how do we make sure it goes well? Also going to ask him about physical activity, which turns out physical ness is an important part of learning. 

[00:18:39] I want to get a little bit more detailed, Dan, in this next segment, and I want to start off with assessment, grading. I know you've thought about this a lot. People are worried that um, AI is going to start to doing, be doing all the grading. Everybody knows that a high school teacher with a big, couple of big classes can spend their entire weekend grading essays. It is so tempting just to feed that into ChatGPT and say, hey, how good is this essay? How should we think about, maybe worry about, but maybe just think about, assessment in education in the future? 

[00:19:11] Dan Schwartz: Yeah, this was, uh, you remember the MOOCs? 

[00:19:14] Russ Altman: Yes. 

[00:19:14] Dan Schwartz: Massively online, open courses. And, uh, you're hoping you have ten thousand students, and then you gotta grade the papers for ten thousand students. So what do you do? You give a multiple-choice tests, which can be machine coded, right? So, so I think that's always there. I'm going to take it a slightly different direction, which is, uh, I'm interacting with a computer system and while I'm interacting with it, it's, it can be constantly assessing in real time, right?

[00:19:41] And so there's a field that's sometimes called educational data mining or learning analytics. And there's thousands of people who are working on, how do I get informative signal out of students interactions. Like, are they trying to game the system? Are they reflecting? And so forth. So this is something the computer can do pretty well, right?

[00:20:02] It can sort of track what students are doing, assess, and then ideally deliver the right piece of instruction at the moment. So yours, you could use the assessments to give people a grade, but really the more important thing is, can you use the assessments to make instructional decisions? So I think this is a big area of advancement, but here's my concern.

[00:20:25] We've gotten very good at assessing things that are objectively right and wrong. Like did you remember the right word? Did you get two plus two correctly? For most of the things we care about now, they're like strategic and heuristic, which means it's not a guaranteed right answer. And so what you really want to do is assess students choices for what to do. So for example, uh, creativity, it's just for the most part, it's a large set of strategies. Right? There's a bunch of strategies that help you be creative. The question is, do the students choose to do that or do they take the safe route? 'Cause creativity is a risk, right? 'Cause you're not sure.

[00:21:02] So I think this is where the field needs to go. Is being willing to say that certain kinds of choices about learning are better than others. Uh, and it's a, it becomes more of an ethical question now. Instead of saying two plus two equals four, there's no ethics to it. 

[00:21:16] Russ Altman: Are you going to be able to convince non educators who hold purse strings, let's call them the government, that these kinds of assessments are important and need to be included? Because my sense is that when it filters up to boards of education or elected leaders, a lot of that stuff goes out of the window. And they just want to know how good are they at reading comprehensive and can they do enough math to be competitive with, you know, country X? 

[00:21:43] Dan Schwartz: Yeah. Yeah. So different assessments serve different purposes. Like the big year end tests that kids take, those aren't to inform the instruction of that child. They're not even for that teacher. They're for school districts to decide are our policies working. And so it's really a different kind of assessment than me as a teacher trying to decide what should I give the kid next. So I think it's going to vary. You know, the tough question for me is should you let the kid use ChatGPT during the test? Right?

[00:22:14] And we had this argument over calculators, right? And finally they came up with ways to ask questions where it was okay if the kids had calculators. Because the calculator was doing the routine stuff. And that's not really what you cared about. What you cared about was, could the kid be innovative? Could they take a, another, a second approach to solve a problem? 

[00:22:34] Russ Altman: Yeah. 

[00:22:34] Dan Schwartz: Things like that. 

[00:22:34] Russ Altman: We, so I teach another class where it's a programming class, the students write programs, and we have switched, um, and we've actually downgraded the value. So as you know, very well, just as background, there is now an amazing, ChatGPT can also write computer code essentially. And so a lot of coding now is kind of done for you and you don't need to do it. We are trying to make sure that they understand the algorithms that we ask them to code. And so what we're doing is we're downgrading the amount of points you get for working code.

[00:23:04] You still get some, but we're upgrading the quiz about how the algorithm works. Do you understand exactly why this happened the way it did? Why is this data structure a good choice or a bad choice? And so it's forcing us, and you could have argued that we should have done this twenty years ago in the same class, but this is making it a more urgent issue, because if we don't, people can just get an automatic piece of code. They can run it. It'll work. They have no understanding of what happened. And so it's really a positive. It's putting more of a burden on us to figure out why the heck did we have them write this code in the first place? 

[00:23:39] Dan Schwartz: No, this was my point. It makes you sort of rethink what is valuable to learn. And you stop doing what was easy to grade. So I have an interesting one. This is a little nerdy. 

[00:23:51] Russ Altman: Okay. I love it. I love it. 

[00:23:52] Dan Schwartz: I teach the intro PhD statistics course in education. And lots of students say, I took statistics, right? And I'm sort of like, well, that's great. Let me ask you one question. And I say, I'm going to email you a question and you'll have five minutes to respond. You let me know when you're ready for it. And I ask them, uh, this is just for you, Russ. But why is the tail of the T distribution fat in small sample sizes? And I, what I get back usually is because they're small sample sizes.

[00:24:24] Russ Altman: Right. Or because it's the T distribution. 

[00:24:27] Dan Schwartz: Or it's, yes, even better. And then I come back and I sort of say, well, have you ever heard of the standard error? And I begin to get at the conceptual stuff, right? And, uh, I suspect if I gave it, uh, so there are ways to get conceptual questions that are really important. But you know, being able to prompt or write R code, you know, that's a good thing. You want them to learn the skills as well. 

[00:24:50] Russ Altman: Exactly. 

[00:24:51] Dan Schwartz: So I don't know, you know, when the calculator showed up, there's a big debate, right? What should students learn? Can they use the calculator? The apocryphal solution was you had to learn the regular math and the calculator now. You just had to learn twice as much. And so maybe that's what it's going to be. 

[00:25:08] Russ Altman: And that's a very likely transitional strategy and then we'll see where we end up. Okay. In the final few minutes, I, this seems like it's unrelated to AI, but I bet it's not. You've done a lot of work on physical activity and learning. You've even been on a paper recently where you talk about having a walk during a teaching session and whether you get better outcomes than if you were just standing or sitting. So tell me about that interest and tell me if it has anything to do with today's topic. 

[00:25:37] Dan Schwartz: I can make the bridge. I can do it, Russ. Right. So we did some studies. Um, I've done a lot of it. It's called embodiment where, yeah, there was, I got clued into this where, uh, I was asking people about why, about gears. And I say, you know, you have three gears in a line, and you turn the gear on the left clockwise. What does the gear on the right do? Far right. And I'd watch them, and they'd go like this with their hands. They'd model with their hands. And then I was sort of like, well, what's the basis of this? And I'd say well why? And they say because this one's turning that way that one, I go but why. And in the end, they just bottom out. They just show me their hands. They didn't say things like one molecule displaces another. 

[00:26:20] Russ Altman: Right. 

[00:26:21] Dan Schwartz: So that sort of clued me in. 

[00:26:22] Russ Altman: This pinky is going up and this other pinky is going down. 

[00:26:26] Dan Schwartz: Yes. 

[00:26:26] Russ Altman: What don't you understand about that? 

[00:26:28] Dan Schwartz: Pretty much. Well, it was nonverbal. 

[00:26:31] Russ Altman: Yeah. 

[00:26:31] Dan Schwartz: So we went on, you know, we discovered that the basis for negative numbers, right? Is actually perceptual symmetry. And we did some neuro stuff. And so the question is sort of how does this perceptual apparatus, which some people, we're just loaded with perception, right? The brain's just one giant perceiving. So how do you get that going? So part of the embodiment is my ability to take action, right? And so this is where we started, right? Right now, the AI feels very verbal, very abstract. Even the video generation, it's amazing, but it's pretty passive for me. So enter virtual worlds, they're still working on the form factor where I can move my hand in space. 

[00:27:16] Russ Altman: Yeah. 

[00:27:17] Dan Schwartz: And something will happen in the environment in response to that. You know, I think medicine is, you know, really been working on haptics so surgeons can practice. Uh, there was a great guy who made a virtual world for different heart congenital defects, and you could go in and practice surgery and see what would happen to the blood flow. So I think, uh, that embodiment where you get to bring all your senses to bear, it's not just words, but it's everything, can really do a lot for learning, for engagement, uh, not just physical skills. 

[00:27:49] Russ Altman: So that's a challenge to, I'm hearing a challenge to AI, which is as an educator, you know that this physicality can be an critical part of learning. And by the way, would this be a surprise? I mean, we're, we've been on earth evolving for several hundred million years. And, uh, you would be surprised if our ability to manipulate and look at three dimensional situations wasn't critical to learning, and yet that's not what AI is doing right now. So this is a clear challenge to AI among other things. 

[00:28:17] Dan Schwartz: Right. So, uh, I have a colleague, Renate Fruchter. And, uh, she teaches architecture, and she has students make a blueprint for the building, right? And then she feeds the blueprint to a CAD system that creates the building. She then takes the building and puts it into a physics engine, it can basically render the building and make walls so you can't move through them, and it has gravity and things like that.

[00:28:42] She then puts the, uh, original student who designed the building in a wheelchair and has them try to navigate through that environment. At which point they sort of understand, oh this is why you need so much space so they can turn around, so they can navigate near the door. I am sure that is an incredibly compelling experience that allows them to be generative about all their future designs.

[00:29:03] So yeah, this is a challenge and part of the co-mingling of the AI and the virtual worlds, I think this is a big challenge. It's computationally very heavy, but it will open the door for lots of ways of teaching that you just couldn't do before. 

[00:29:17] Russ Altman: Thanks to Dan Schwartz. That was the future of educational technology.

[00:29:21] You've been listening to The Future of Everything and I'm Russ Altman. You know what? We have an archive with more than 250 back episodes of The Future of Everything. So you have instant access to a wide array of discussions that can keep you entertained and informed. Also, remember to rate, review, and follow. I care deeply about that request. 

[00:29:41] And also, if you want to follow me, you can follow me on X @ @RBAltman, and you can follow Stanford Engineering @ StanfordENG.

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How technology is reinventing education

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.”

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How technology will change education in the future.

Featured article by Sebastian Miller, Independent Technology Author

Photo credit: Pixabay.com

Technology has affected our lives one way or the other. It has also improved many sectors. However, education remains one the key sectors that have and would benefit more as technology continues to grow. With cheap broadband, improved infrastructure, among others, there is a high possibility that education will become more accessible and simpler for students and teachers. We have already experienced these changes in the last couple of years. Now you can do your math assignment or find help with ease, something that was a bit difficult in the past. Here is how technology is changing education and what we can expect in the future.

1.   The use of Virtual Reality in schools will likely increase

Virtual reality is not a new topic in the tech world. It’s one of the tech advancements that have the potentials to transform education massively in the future.

Samsung, Google, and other tech heavyweights have already started investing heavily in VR projects. So we can expect more improvements in this technology in the future.

Virtual reality has had a tremendous impact in the gaming world. It has also proven itself as an impressive learning tool that can make teaching fun and engaging. Instead of teaching students the history of ancient Rome from a textbook, they can just put on the VR headset and experience Rome for themselves.

However, accessibility is one of the things that will make widespread acceptance and use of this VR technology possible. Many schools and students will adopt it to foster effective teaching and learning. With a mobile device and an app, one can make use of this technology. And since the number of teenagers who have access to a mobile device is dubbed to increase in the future, it won’t take long before every student has it on their device.

There will also be more innovations like the virtual science lab that is currently available. This lab allows students to perform experiments using harmful chemicals and flames without having contact with any of them. But the result remains the same as a real-life experiment conducted with the same materials. Such innovations will also give rise to discoveries because students and aspiring scientists will be able to experiment with ease.

2.   Artificial intelligence

AI is one tech innovation that will have more impact on education in the future. It will not only make learning effective for students but help teachers to perform their duties efficiently. Artificial intelligence such as Professor Einstein (a robot) is already making waves in the educational sector.

The robot helps science students by lecturing and helping them to understand science subjects. It has the potential to make complex science subjects look so easy for students, too. In addition to that, the robot has the capacity to make learning fun and engaging. It does not only provide answers to questions but uses a funny facial expression that makes learning less of a chore for students.

Chatbots and grading assistants are already helping teachers with their complex administrative work. The latter assist teachers to grade their students’ work, allowing them to focus more energy on teaching their students.

3.   Improved way of storing and delivering contents

There is a call by environmentalists to reduce human activities that contribute to global warming. And that includes the reduction of tree felling. Schools depend heavily on paper for writing, which in turn leads to tree felling, which doesn’t support the agenda of environment-conscious governments. But this will likely change in the future. And it will happen will the help of technology.

In other words, technology will change how teachers and students receive and send information. There will be a shift from the traditional system of using pen and paper to digital. Cloud services which provide a smooth, safe and cost-effective way of storing information will continue to gain relevance. It will become the best option for teachers and students to store data of any size. The advantage of storing and delivering contents digitally besides preservation of trees or reduction of paper waste is that there will be no need for re-printing. And it would be easier to update documents whenever one pleases.

The future of education will see a significant shift towards visual learning techniques, enabled by advancements in technology. Online platforms and interactive tools will allow students to engage with educational content in a more visual and immersive way, enhancing their learning experience. Students will have access to a wide range of visual aids, including diagrams, infographics, and videos, to support their learning. These visual tools will help students to better understand complex concepts and retain information.

According to the weekly essay , education will experience massive changes in the future because of tech advancements. Teachers will have access to technology that will enable them to teach effectively. Students will also have access to technology that would make learning more effective too. The only thing that is of great concern is for teachers and students to embrace educational tech tools and learn how to use them. If that can happen, then the world can expect a massive transformation of education in the future.

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