qualitative research paper about education

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• Am J Pharm Educ
• v.74(8); 2010 Oct 11

Presenting and Evaluating Qualitative Research

The purpose of this paper is to help authors to think about ways to present qualitative research papers in the American Journal of Pharmaceutical Education . It also discusses methods for reviewers to assess the rigour, quality, and usefulness of qualitative research. Examples of different ways to present data from interviews, observations, and focus groups are included. The paper concludes with guidance for publishing qualitative research and a checklist for authors and reviewers.

INTRODUCTION

Policy and practice decisions, including those in education, increasingly are informed by findings from qualitative as well as quantitative research. Qualitative research is useful to policymakers because it often describes the settings in which policies will be implemented. Qualitative research is also useful to both pharmacy practitioners and pharmacy academics who are involved in researching educational issues in both universities and practice and in developing teaching and learning.

Qualitative research involves the collection, analysis, and interpretation of data that are not easily reduced to numbers. These data relate to the social world and the concepts and behaviors of people within it. Qualitative research can be found in all social sciences and in the applied fields that derive from them, for example, research in health services, nursing, and pharmacy. 1 It looks at X in terms of how X varies in different circumstances rather than how big is X or how many Xs are there? 2 Textbooks often subdivide research into qualitative and quantitative approaches, furthering the common assumption that there are fundamental differences between the 2 approaches. With pharmacy educators who have been trained in the natural and clinical sciences, there is often a tendency to embrace quantitative research, perhaps due to familiarity. A growing consensus is emerging that sees both qualitative and quantitative approaches as useful to answering research questions and understanding the world. Increasingly mixed methods research is being carried out where the researcher explicitly combines the quantitative and qualitative aspects of the study. 3 , 4

Like healthcare, education involves complex human interactions that can rarely be studied or explained in simple terms. Complex educational situations demand complex understanding; thus, the scope of educational research can be extended by the use of qualitative methods. Qualitative research can sometimes provide a better understanding of the nature of educational problems and thus add to insights into teaching and learning in a number of contexts. For example, at the University of Nottingham, we conducted in-depth interviews with pharmacists to determine their perceptions of continuing professional development and who had influenced their learning. We also have used a case study approach using observation of practice and in-depth interviews to explore physiotherapists' views of influences on their leaning in practice. We have conducted in-depth interviews with a variety of stakeholders in Malawi, Africa, to explore the issues surrounding pharmacy academic capacity building. A colleague has interviewed and conducted focus groups with students to explore cultural issues as part of a joint Nottingham-Malaysia pharmacy degree program. Another colleague has interviewed pharmacists and patients regarding their expectations before and after clinic appointments and then observed pharmacist-patient communication in clinics and assessed it using the Calgary Cambridge model in order to develop recommendations for communication skills training. 5 We have also performed documentary analysis on curriculum data to compare pharmacist and nurse supplementary prescribing courses in the United Kingdom.

It is important to choose the most appropriate methods for what is being investigated. Qualitative research is not appropriate to answer every research question and researchers need to think carefully about their objectives. Do they wish to study a particular phenomenon in depth (eg, students' perceptions of studying in a different culture)? Or are they more interested in making standardized comparisons and accounting for variance (eg, examining differences in examination grades after changing the way the content of a module is taught). Clearly a quantitative approach would be more appropriate in the last example. As with any research project, a clear research objective has to be identified to know which methods should be applied.

Types of qualitative data include:

• Audio recordings and transcripts from in-depth or semi-structured interviews
• Structured interview questionnaires containing substantial open comments including a substantial number of responses to open comment items.
• Audio recordings and transcripts from focus group sessions.
• Field notes (notes taken by the researcher while in the field [setting] being studied)
• Video recordings (eg, lecture delivery, class assignments, laboratory performance)
• Case study notes
• Documents (reports, meeting minutes, e-mails)
• Diaries, video diaries
• Observation notes
• Press clippings
• Photographs

RIGOUR IN QUALITATIVE RESEARCH

Qualitative research is often criticized as biased, small scale, anecdotal, and/or lacking rigor; however, when it is carried out properly it is unbiased, in depth, valid, reliable, credible and rigorous. In qualitative research, there needs to be a way of assessing the “extent to which claims are supported by convincing evidence.” 1 Although the terms reliability and validity traditionally have been associated with quantitative research, increasingly they are being seen as important concepts in qualitative research as well. Examining the data for reliability and validity assesses both the objectivity and credibility of the research. Validity relates to the honesty and genuineness of the research data, while reliability relates to the reproducibility and stability of the data.

The validity of research findings refers to the extent to which the findings are an accurate representation of the phenomena they are intended to represent. The reliability of a study refers to the reproducibility of the findings. Validity can be substantiated by a number of techniques including triangulation use of contradictory evidence, respondent validation, and constant comparison. Triangulation is using 2 or more methods to study the same phenomenon. Contradictory evidence, often known as deviant cases, must be sought out, examined, and accounted for in the analysis to ensure that researcher bias does not interfere with or alter their perception of the data and any insights offered. Respondent validation, which is allowing participants to read through the data and analyses and provide feedback on the researchers' interpretations of their responses, provides researchers with a method of checking for inconsistencies, challenges the researchers' assumptions, and provides them with an opportunity to re-analyze their data. The use of constant comparison means that one piece of data (for example, an interview) is compared with previous data and not considered on its own, enabling researchers to treat the data as a whole rather than fragmenting it. Constant comparison also enables the researcher to identify emerging/unanticipated themes within the research project.

STRENGTHS AND LIMITATIONS OF QUALITATIVE RESEARCH

Qualitative researchers have been criticized for overusing interviews and focus groups at the expense of other methods such as ethnography, observation, documentary analysis, case studies, and conversational analysis. Qualitative research has numerous strengths when properly conducted.

Strengths of Qualitative Research

• Issues can be examined in detail and in depth.
• Interviews are not restricted to specific questions and can be guided/redirected by the researcher in real time.
• The research framework and direction can be quickly revised as new information emerges.
• The data based on human experience that is obtained is powerful and sometimes more compelling than quantitative data.
• Subtleties and complexities about the research subjects and/or topic are discovered that are often missed by more positivistic enquiries.
• Data usually are collected from a few cases or individuals so findings cannot be generalized to a larger population. Findings can however be transferable to another setting.

Limitations of Qualitative Research

• Research quality is heavily dependent on the individual skills of the researcher and more easily influenced by the researcher's personal biases and idiosyncrasies.
• Rigor is more difficult to maintain, assess, and demonstrate.
• The volume of data makes analysis and interpretation time consuming.
• It is sometimes not as well understood and accepted as quantitative research within the scientific community
• The researcher's presence during data gathering, which is often unavoidable in qualitative research, can affect the subjects' responses.
• Issues of anonymity and confidentiality can present problems when presenting findings
• Findings can be more difficult and time consuming to characterize in a visual way.

PRESENTATION OF QUALITATIVE RESEARCH FINDINGS

The following extracts are examples of how qualitative data might be presented:

Data From an Interview.

The following is an example of how to present and discuss a quote from an interview.

The researcher should select quotes that are poignant and/or most representative of the research findings. Including large portions of an interview in a research paper is not necessary and often tedious for the reader. The setting and speakers should be established in the text at the end of the quote.

The student describes how he had used deep learning in a dispensing module. He was able to draw on learning from a previous module, “I found that while using the e learning programme I was able to apply the knowledge and skills that I had gained in last year's diseases and goals of treatment module.” (interviewee 22, male)

This is an excerpt from an article on curriculum reform that used interviews 5 :

The first question was, “Without the accreditation mandate, how much of this curriculum reform would have been attempted?” According to respondents, accreditation played a significant role in prompting the broad-based curricular change, and their comments revealed a nuanced view. Most indicated that the change would likely have occurred even without the mandate from the accreditation process: “It reflects where the profession wants to be … training a professional who wants to take on more responsibility.” However, they also commented that “if it were not mandated, it could have been a very difficult road.” Or it “would have happened, but much later.” The change would more likely have been incremental, “evolutionary,” or far more limited in its scope. “Accreditation tipped the balance” was the way one person phrased it. “Nobody got serious until the accrediting body said it would no longer accredit programs that did not change.”

Data From Observations

The following example is some data taken from observation of pharmacist patient consultations using the Calgary Cambridge guide. 6 , 7 The data are first presented and a discussion follows:

Pharmacist: We will soon be starting a stop smoking clinic. Patient: Is the interview over now? Pharmacist: No this is part of it. (Laughs) You can't tell me to bog off (sic) yet. (pause) We will be starting a stop smoking service here, Patient: Yes. Pharmacist: with one-to-one and we will be able to help you or try to help you. If you want it. In this example, the pharmacist has picked up from the patient's reaction to the stop smoking clinic that she is not receptive to advice about giving up smoking at this time; in fact she would rather end the consultation. The pharmacist draws on his prior relationship with the patient and makes use of a joke to lighten the tone. He feels his message is important enough to persevere but he presents the information in a succinct and non-pressurised way. His final comment of “If you want it” is important as this makes it clear that he is not putting any pressure on the patient to take up this offer. This extract shows that some patient cues were picked up, and appropriately dealt with, but this was not the case in all examples.

Data From Focus Groups

This excerpt from a study involving 11 focus groups illustrates how findings are presented using representative quotes from focus group participants. 8

Those pharmacists who were initially familiar with CPD endorsed the model for their peers, and suggested it had made a meaningful difference in the way they viewed their own practice. In virtually all focus groups sessions, pharmacists familiar with and supportive of the CPD paradigm had worked in collaborative practice environments such as hospital pharmacy practice. For these pharmacists, the major advantage of CPD was the linking of workplace learning with continuous education. One pharmacist stated, “It's amazing how much I have to learn every day, when I work as a pharmacist. With [the learning portfolio] it helps to show how much learning we all do, every day. It's kind of satisfying to look it over and see how much you accomplish.” Within many of the learning portfolio-sharing sessions, debates emerged regarding the true value of traditional continuing education and its outcome in changing an individual's practice. While participants appreciated the opportunity for social and professional networking inherent in some forms of traditional CE, most eventually conceded that the academic value of most CE programming was limited by the lack of a systematic process for following-up and implementing new learning in the workplace. “Well it's nice to go to these [continuing education] events, but really, I don't know how useful they are. You go, you sit, you listen, but then, well I at least forget.”

The following is an extract from a focus group (conducted by the author) with first-year pharmacy students about community placements. It illustrates how focus groups provide a chance for participants to discuss issues on which they might disagree.

Interviewer: So you are saying that you would prefer health related placements? Student 1: Not exactly so long as I could be developing my communication skill. Student 2: Yes but I still think the more health related the placement is the more I'll gain from it. Student 3: I disagree because other people related skills are useful and you may learn those from taking part in a community project like building a garden. Interviewer: So would you prefer a mixture of health and non health related community placements?

GUIDANCE FOR PUBLISHING QUALITATIVE RESEARCH

Qualitative research is becoming increasingly accepted and published in pharmacy and medical journals. Some journals and publishers have guidelines for presenting qualitative research, for example, the British Medical Journal 9 and Biomedcentral . 10 Medical Education published a useful series of articles on qualitative research. 11 Some of the important issues that should be considered by authors, reviewers and editors when publishing qualitative research are discussed below.

Introduction.

A good introduction provides a brief overview of the manuscript, including the research question and a statement justifying the research question and the reasons for using qualitative research methods. This section also should provide background information, including relevant literature from pharmacy, medicine, and other health professions, as well as literature from the field of education that addresses similar issues. Any specific educational or research terminology used in the manuscript should be defined in the introduction.

The methods section should clearly state and justify why the particular method, for example, face to face semistructured interviews, was chosen. The method should be outlined and illustrated with examples such as the interview questions, focusing exercises, observation criteria, etc. The criteria for selecting the study participants should then be explained and justified. The way in which the participants were recruited and by whom also must be stated. A brief explanation/description should be included of those who were invited to participate but chose not to. It is important to consider “fair dealing,” ie, whether the research design explicitly incorporates a wide range of different perspectives so that the viewpoint of 1 group is never presented as if it represents the sole truth about any situation. The process by which ethical and or research/institutional governance approval was obtained should be described and cited.

The study sample and the research setting should be described. Sampling differs between qualitative and quantitative studies. In quantitative survey studies, it is important to select probability samples so that statistics can be used to provide generalizations to the population from which the sample was drawn. Qualitative research necessitates having a small sample because of the detailed and intensive work required for the study. So sample sizes are not calculated using mathematical rules and probability statistics are not applied. Instead qualitative researchers should describe their sample in terms of characteristics and relevance to the wider population. Purposive sampling is common in qualitative research. Particular individuals are chosen with characteristics relevant to the study who are thought will be most informative. Purposive sampling also may be used to produce maximum variation within a sample. Participants being chosen based for example, on year of study, gender, place of work, etc. Representative samples also may be used, for example, 20 students from each of 6 schools of pharmacy. Convenience samples involve the researcher choosing those who are either most accessible or most willing to take part. This may be fine for exploratory studies; however, this form of sampling may be biased and unrepresentative of the population in question. Theoretical sampling uses insights gained from previous research to inform sample selection for a new study. The method for gaining informed consent from the participants should be described, as well as how anonymity and confidentiality of subjects were guaranteed. The method of recording, eg, audio or video recording, should be noted, along with procedures used for transcribing the data.

Data Analysis.

A description of how the data were analyzed also should be included. Was computer-aided qualitative data analysis software such as NVivo (QSR International, Cambridge, MA) used? Arrival at “data saturation” or the end of data collection should then be described and justified. A good rule when considering how much information to include is that readers should have been given enough information to be able to carry out similar research themselves.

One of the strengths of qualitative research is the recognition that data must always be understood in relation to the context of their production. 1 The analytical approach taken should be described in detail and theoretically justified in light of the research question. If the analysis was repeated by more than 1 researcher to ensure reliability or trustworthiness, this should be stated and methods of resolving any disagreements clearly described. Some researchers ask participants to check the data. If this was done, it should be fully discussed in the paper.

An adequate account of how the findings were produced should be included A description of how the themes and concepts were derived from the data also should be included. Was an inductive or deductive process used? The analysis should not be limited to just those issues that the researcher thinks are important, anticipated themes, but also consider issues that participants raised, ie, emergent themes. Qualitative researchers must be open regarding the data analysis and provide evidence of their thinking, for example, were alternative explanations for the data considered and dismissed, and if so, why were they dismissed? It also is important to present outlying or negative/deviant cases that did not fit with the central interpretation.

The interpretation should usually be grounded in interviewees or respondents' contributions and may be semi-quantified, if this is possible or appropriate, for example, “Half of the respondents said …” “The majority said …” “Three said…” Readers should be presented with data that enable them to “see what the researcher is talking about.” 1 Sufficient data should be presented to allow the reader to clearly see the relationship between the data and the interpretation of the data. Qualitative data conventionally are presented by using illustrative quotes. Quotes are “raw data” and should be compiled and analyzed, not just listed. There should be an explanation of how the quotes were chosen and how they are labeled. For example, have pseudonyms been given to each respondent or are the respondents identified using codes, and if so, how? It is important for the reader to be able to see that a range of participants have contributed to the data and that not all the quotes are drawn from 1 or 2 individuals. There is a tendency for authors to overuse quotes and for papers to be dominated by a series of long quotes with little analysis or discussion. This should be avoided.

Participants do not always state the truth and may say what they think the interviewer wishes to hear. A good qualitative researcher should not only examine what people say but also consider how they structured their responses and how they talked about the subject being discussed, for example, the person's emotions, tone, nonverbal communication, etc. If the research was triangulated with other qualitative or quantitative data, this should be discussed.

Discussion.

The findings should be presented in the context of any similar previous research and or theories. A discussion of the existing literature and how this present research contributes to the area should be included. A consideration must also be made about how transferrable the research would be to other settings. Any particular strengths and limitations of the research also should be discussed. It is common practice to include some discussion within the results section of qualitative research and follow with a concluding discussion.

The author also should reflect on their own influence on the data, including a consideration of how the researcher(s) may have introduced bias to the results. The researcher should critically examine their own influence on the design and development of the research, as well as on data collection and interpretation of the data, eg, were they an experienced teacher who researched teaching methods? If so, they should discuss how this might have influenced their interpretation of the results.

Conclusion.

The conclusion should summarize the main findings from the study and emphasize what the study adds to knowledge in the area being studied. Mays and Pope suggest the researcher ask the following 3 questions to determine whether the conclusions of a qualitative study are valid 12 : How well does this analysis explain why people behave in the way they do? How comprehensible would this explanation be to a thoughtful participant in the setting? How well does the explanation cohere with what we already know?

CHECKLIST FOR QUALITATIVE PAPERS

This paper establishes criteria for judging the quality of qualitative research. It provides guidance for authors and reviewers to prepare and review qualitative research papers for the American Journal of Pharmaceutical Education . A checklist is provided in Appendix 1 to assist both authors and reviewers of qualitative data.

ACKNOWLEDGEMENTS

Thank you to the 3 reviewers whose ideas helped me to shape this paper.

Appendix 1. Checklist for authors and reviewers of qualitative research.

Introduction

• □ Research question is clearly stated.
• □ Research question is justified and related to the existing knowledge base (empirical research, theory, policy).
• □ Any specific research or educational terminology used later in manuscript is defined.
• □ The process by which ethical and or research/institutional governance approval was obtained is described and cited.
• □ Reason for choosing particular research method is stated.
• □ Criteria for selecting study participants are explained and justified.
• □ Recruitment methods are explicitly stated.
• □ Details of who chose not to participate and why are given.
• □ Study sample and research setting used are described.
• □ Method for gaining informed consent from the participants is described.
• □ Maintenance/Preservation of subject anonymity and confidentiality is described.
• □ Method of recording data (eg, audio or video recording) and procedures for transcribing data are described.
• □ Methods are outlined and examples given (eg, interview guide).
• □ Decision to stop data collection is described and justified.
• □ Data analysis and verification are described, including by whom they were performed.
• □ Methods for identifying/extrapolating themes and concepts from the data are discussed.
• □ Sufficient data are presented to allow a reader to assess whether or not the interpretation is supported by the data.
• □ Outlying or negative/deviant cases that do not fit with the central interpretation are presented.
• □ Transferability of research findings to other settings is discussed.
• □ Findings are presented in the context of any similar previous research and social theories.
• □ Discussion often is incorporated into the results in qualitative papers.
• □ A discussion of the existing literature and how this present research contributes to the area is included.
• □ Any particular strengths and limitations of the research are discussed.
• □ Reflection of the influence of the researcher(s) on the data, including a consideration of how the researcher(s) may have introduced bias to the results is included.

Conclusions

• □ The conclusion states the main finings of the study and emphasizes what the study adds to knowledge in the subject area.

A systematic literature review of empirical research on ChatGPT in education

• Open access
• Published: 26 May 2024
• Volume 3 , article number  60 , ( 2024 )

Cite this article

You have full access to this open access article

• Yazid Albadarin   ORCID: orcid.org/0009-0005-8068-8902 1 ,
• Mohammed Saqr 1 ,
• Nicolas Pope 1 &
• Markku Tukiainen 1  

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

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1 Introduction

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

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

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

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

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

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

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

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

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

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

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

2 Methodology

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

2.1 Identify the purpose

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

2.2 Draft the protocol

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

2.3 Apply practical screen

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

2.4 Literature search

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

2.5 Quality appraisal

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

The study selection process

2.6 Data extraction

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

2.7 Synthesize studies

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

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

3.1 Part 1: descriptive analysis

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

3.1.1 The number of the reviewed studies and publication years

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

3.1.2 Educational levels and fields

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

Educational levels in the reviewed studies

Context of the reviewed studies

3.1.3 Participants distribution and countries contribution

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

The reviewed studies conducted in single or multiple countries

The Contribution of each country in the studies

3.1.4 Study population and sample size

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

3.1.5 Participants’ familiarity with using ChatGPT

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

3.1.6 Research methodology approaches and source(S) of data

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

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

Research methodologies in the reviewed studies

Source of data in the reviewed studies

3.1.7 The aim and objectives of the studies

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

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

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

The main findings in the reviewed studies

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

4.1 virtual intelligent assistant.

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

4.2 Writing and language proficiency assistant

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

4.3 Valuable resource for learning approaches

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

4.4 Enhancing students' competencies

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

4.5 Supporting students' academic success

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

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

5.1 valuable resource for teaching.

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

5.2 Improving productivity and efficiency

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

5.3 Catalyzing new teaching methodologies

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

5.4 Effective utilization of CHATGPT in teaching

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

6 Discussion

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

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

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

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

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

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

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

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

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

7 Conclusions

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

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

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

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

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

Data availability

The data supporting our findings are available upon request.

Abbreviations

• Artificial intelligence

AI in education

Large language model

Artificial neural networks

Chat Generative Pre-Trained Transformer

Recurrent neural networks

Long short-term memory

Reinforcement learning from human feedback

Natural language processing

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

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

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

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Published on 28.5.2024 in Vol 8 (2024)

Health Care Professionals’ Experiences With Using Information and Communication Technologies in Patient Care During the COVID-19 Pandemic: Qualitative Study

Authors of this article:

Original Paper

• Carly A Cermak 1, 2 , MClSc, PhD   ; 
• Heather Read 1 , PhD   ; 
• Lianne Jeffs 1, 2, 3 , RN, PhD  

1 Science of Care Institute, Sinai Health, Toronto, ON, Canada

2 Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada

3 Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada

Corresponding Author:

Carly A Cermak, MClSc, PhD

Science of Care Institute

Sinai Health

1 Bridgepoint Drive

Toronto, ON, M4M 2B5

Phone: 1 4165864800

Email: [email protected]

Background: The COVID-19 pandemic acted as a catalyst for the use of information and communication technology (ICT) in inpatient and outpatient health care settings. Digital tools were used to connect patients, families, and providers amid visitor restrictions, while web-based platforms were used to continue care amid COVID-19 lockdowns. What we have yet to learn is the experiences of health care providers (HCPs) regarding the use of ICT that supported changes to clinical care during the COVID-19 pandemic.

Objective: The aim of this paper was to describe the experiences of HCPs in using ICT to support clinical care changes during the COVID-19 pandemic. This paper is reporting on a subset of a larger body of data that examined changes to models of care during the pandemic.

Methods: This study used a qualitative, descriptive study design. In total, 30 HCPs were recruited from 3 hospitals in Canada. One-on-one semistructured interviews were conducted between December 2022 and June 2023. Qualitative data were analyzed using an inductive thematic approach to identify themes across participants.

Results: A total of 30 interviews with HCPs revealed 3 themes related to their experiences using ICT to support changes to clinical care during the COVID-19 pandemic. These included the use of ICT (1) to support in-person communication with patients, (2) to facilitate connection between provider to patient and patient to family, and (3) to provide continuity of care.

Conclusions: HCP narratives revealed the benefits of digital tools to support in-person communication between patient and provider, the need for thoughtful consideration for the use of ICT at end-of-life care, and the decision-making that is needed when choosing service delivery modality (eg, web based or in person). Moving forward, organizations are encouraged to provide education and training on how to support patient-provider communication, find ways to meet patient and family wishes at end-of-life care, and continue to give autonomy to HCPs in their clinical decision-making regarding service delivery modality.

Introduction

The health care workforce had to quickly adapt to the COVID-19 pandemic, with health systems grappling with the provision of COVID-19 care at the same time as non-COVID-19 care. Restrictions to reduce the spread of COVID-19 put an additional strain on the health care system. Health care providers (HCPs) were left to problem-solve how to continue providing compassionate, connected care among layers of personal protective equipment and visitor restrictions. Fortunately, the COVID-19 pandemic was a catalyst for digital health to support the ongoing response to the COVID-19 pandemic, with web-based care emerging as the primary innovation of information and communication technology (ICT) used in medical care [ 1 , 2 ]. Uses of ICT in medical care include remote consultations, digital noninvasive care, and digital platforms for data sharing [ 3 ].

ICT played an important role in supporting changes to clinical care within inpatient and outpatient health care settings. Within inpatient settings, ICT was integral in maintaining connectivity between patients, families, and providers when changes to visitor policies were implemented [ 4 ]. For example, the use of mobile devices and tablets allowed for connection between patient and family and supported knowledge transfer between provider and family [ 5 ]. Within outpatient settings, ICT was integral in continuing care when COVID-19 lockdown restrictions limited in-person visits [ 1 ]. For example, videoconference and telemedicine services (ie, web-based care) emerged as a platform for providers to use to allow for remote care [ 1 ]. In both facets, ICT facilitated connection, acting as an essential link between patients, families, and providers. However, we have yet to learn of HCPs’ experiences in using ICT to support clinical care.

Learning from the experiences of HCPs’ use of ICT will offer valuable insights into how innovative uses of ICT might continue to be used in inpatient and outpatient health care settings moving forward. From here, uses of ICT can inform organizational leadership of the systems or processes that may require further investigation to support ICT use in clinical care in a postpandemic world. The main objective of the study was to examine changes to models of care during the pandemic from the perspectives of HCPs, implementation team members, and leaders across 3 Canadian hospitals. For this paper, we report on a storyline that emerged from this work to describe the experiences of HCPs’ use of ICT that supported changes to clinical care during the COVID-19 pandemic.

Study Design

This qualitative descriptive study was undertaken from March 2022 to June 2023 to understand changes to models of care during the COVID-19 pandemic through the experiences of HCPs, implementation team members, and leaders across 3 hospitals in Canada. This paper is reporting on a subset of data related to HCPs’ experiences of using ICT in supporting changes to clinical care, drawn from the larger study that explored changes to models of care that took place during the COVID-19 pandemic. The reporting of this study was guided by the Standards for Reporting Qualitative Research [ 6 ].

Sampling and Participant Recruitment

In total, 30 HCPs were recruited from critical care, inpatient, and ambulatory services across 3 hospitals in Canada. A purposeful sampling strategy was used where recruiting took place in organizations that were known to have been affected by COVID-19 restrictions and policies. Site leads at participating institutions disseminated study information to HCPs (eg, nurses, physicians, and allied health disciplines) working within their respective health care organizations. From here, interview participants self-referred to this study. Inclusion criteria included current employment as an HCP working at the health care organization over the course of the pandemic and postpandemic recovery.

Data Collection

One-on-one, semistructured interviews were conducted by members of the research team (Kang Kang Margolese, Marina Morris, Lily Zeng, Marie Oliveira, Adebisi Akande, HR, Frances Bruno, or CAC) between December 2022 and June 2023. Demographic information, including age, gender, ethnicity, health discipline, time in profession, time in organization, and time in current role, was collected from all participants before the interview to ensure diversity within the sample. An interview guide was developed by the research team that explored the following five areas: (1) changes to care (eg, “What was your role like before the pandemic? How did care change over the course of the last 3 years?”), (2) provisions of care (eg, “What did you/your team start/stop doing? How did you prioritize care?”), (3) emotions (eg, “How did care change feel for you/your team? What supports were available to you?”), (4) implementation and evaluation (eg, “How were changes implemented and evaluated?”), and (5) lessons that were learned or future recommendations.

Data collection was completed by nonclinical research staff (Kang Kang Margolese, Marina Morris, Lily Zeng, Adebisi Akande, and HR) and clinical research staff (Marie Oliveira, Frances Bruno, and CAC). Data collection was concluded when saturation of themes was reached, meaning that limited new insights emerged from existing themes with the collected data sample [ 7 ]. The interviews were conducted via either a videoconferencing platform or in person and were approximately 45 to 60 minutes in length.

Ethical Considerations

Ethics was formally reviewed and approved by Sinai Health’s Research Ethics Board (REB# 22-0153-E), as well as at each participating site: Sunnybrook Health Sciences Centre (REB# 5571) and Providence Health Care (REB# H22-02792). Participants were informed that participation in this study was completely voluntary and that they could withdraw from the study at any time without penalty. Verbal informed consent was obtained before the start of the interviews, and participants were given an electronic gift card in recognition of their time. The honorarium for participants was CAD $20 (US $26.4). Demographic information was collected from all participants before the interview. These data were anonymized and stored separately from the transcripts, which were deidentified and stored on a secure server.

Data Analysis

The research design was conceived within an interpretivist paradigm, where the researchers’ purpose was to gather insight into how clinical care changed during the COVID-19 pandemic through the learning of the experiences of participants [ 8 ]. Interviews were analyzed using an inductive thematic analysis approach, which included openly coding line by line to organize data in a meaningful, systematic way; examining the codes to identify themes; and reviewing the themes [ 9 ]. Specifically, the entire research team openly coded a small group of interviews (n=3) independently, line by line, and then met as a group to review codes, discuss themes, and develop an initial codebook through consensus. From here, the research team coded the bulk of the interviews in pairs, meeting as needed to ensure the reliability of coding, using the primary investigator (LJ) to triangulate and resolve any discrepancies as needed.

Reflexivity was demonstrated through regular debriefs of interviews and a review of the codebook at 1- to 2-week intervals during the coding process. Primary adjustments were additions of new codes as interviews were collected from new participant subgroups. For example, the initial codebook was derived from nurse interviews, and new codes were required as the project expanded into allied health disciplines. Codes that related to HCPs’ experiences of ICT included disciplinary changes, technical changes and innovations, improvisation, problem-solving, tools, and technology recommendations. NVivo software (QSR International) was used to facilitate the cross-synthesis analysis. As a final step of analysis to ensure saturation and methodological rigor, the primary investigator for the study (LJ) reviewed the emergent coding schema with the original transcripts.

Participant Characteristics

A total of 30 participants (site A: n=4, site B: n=14, and site C: n=12) described their experiences of how ICT supported changes to clinical care. Table 1 presents the demographic characteristics. Themes generated from participants included the use of ICT (1) for supporting in-person communication with patients; (2) for enabling connection between patients, providers, and families; and (3) for providing continuity of care amid COVID-19 restrictions.

a HCP: health care provider.

b Participant self-identified; categories were not provided.

Supporting In-Person Communication With Patients

Participants described how tablets supported in-person communication to mitigate the impact that personal protective equipment (PPE) had on verbal interactions with patients. PPE such as masks, Plexiglas, and visors posed challenges in communicating effectively, particularly for patients who were hard of hearing or who had difficulties with comprehension. Efforts to support communication were essential as communication breakdowns created confusion for the patients with detrimental consequences:

And so when talking to elderly people, when they can’t read your lips or when they can’t really hear you through three layers of protective equipment, they get very confused and multiple confusing events leads to possible more agitation and agitation leads to an automatic write-off from a lot of health care providers as to a reason why not to provide a certain person with care. [Site B, 01, physiotherapist]

Participants described coming up with innovative ways to facilitate communication amid the layers of PPE, with tablets and phones used to break down communication barriers. Applications such as speech to text allowed live transcription of providers’ speech, which can be used as a tool to support comprehension for patients who were hearing impaired. Further, speech-to-text applications provided patients and families a model of how this tool can be used to support communication outside of the hospital setting:

And so, this [iPads] has been a huge help...it helps people, patients who haven’t heard of this...they go home with a brand-new strategy that makes their daily life so much easier. [Site C, 08, social worker]

In addition to using tablets to support communication with patients who were hard of hearing, participants also expressed the value of using tablets for translation services for patients who did not speak English. Benefits included the convenience of dialing translation services from an iPad:

We have translation services on them [iPads]...which has been so, so wonderful to have to just go into someone’s room who doesn’t speak English...And just call up this interpretation service, have a human being there and that was really a key. [Site C, 29, spiritual health practitioner]

Challenges surfaced when both a videoconferencing platform and translation services were required—specifically, the difficulties in handling 2 ICT tools simultaneously and the need to prioritize videoconferencing all the while hoping that family members were relaying information correctly:

...you can’t hold a Zoom, you know, iPad and then hold a translator phone to it, you know what I mean? So then it became family trying to find someone at their end who could relay information. [Site B, 13, occupational therapist]

Enabling Connection Between Patients, Providers, and Families

Participants described how digital devices facilitated the connection between provider to family and provider to patient during visitor restrictions. This included using phones and iPads to connect families to their loved ones in hospitals, especially at end-of-life care. Participants also described that providing a digital connection to families at end-of-life care was a service that could help families move through the grief process.

...we facilitated a FaceTime and all kinds of video calls for people to be able to talk to their loved ones. And even to their religious leaders in certain cases...Families were not able to be with a loved one when they were dying…we were a bridge between them. [Site B, 07, spiritual care]

...we recorded a memorial service that was generic and was put up on YouTube and we could send the link...And so many people just didn’t have the needed ritual to move through grief. And that was something that we could give them and that was—we received so much good feedback and gratitude for that. [Site C, 29, spiritual health practitioner]

While there were benefits of tablet use to connect families to patients at end-of-life care, a digital connection created an internal struggle for HCPs as they witnessed the lack of physical touch and difficulties in accommodating end-of-life rituals:

I feel like I struggled when I had to use an iPad to connect patients to family members and it could be in a very vulnerable situation, like a patient was dying, he doesn’t speak English, the daughter’s on the iPad, she’s crying, she can’t hold her dad, can’t hold his hand...I think we have to recognize that...there is a rite of passage before somebody dies. There are certain steps for religious people and families that need to happen to honour a dying body for them to move on to wherever that place is...So anointing, communion, confession. Those are not things that are amenable to a Zoom method. [Site B, 12, nursing]

Further, participants expressed the challenges with navigating the frequency of communication between patient and family, such as balancing family requests with staffing resources within the hospital:

...when you had multiple family members who each wanted their turn to visit once a week. Well, you know, you don’t have staff to be able to support five Facetimes per resident. So, we started to have to limit it and say...like two Facetimes a week for a family, or for a resident...So, that was a challenge. [Site B, 05, social worker]

Providing Continuity of Care

Participants described how the use of videoconferencing platforms such as Zoom (Zoom Video Communications) enhanced communication between providers and families, such as when needing to provide medical updates or discharge recommendations. Zoom provided accessible options for patients with hearing or comprehension challenges using closed captioning. Furthermore, Zoom enabled more efficient and faster communication between the care team and family, rather than being faced with the complexities of coordinating schedules of team members and families who may be coming in from out of town:

It [Zoom] optimized our efficiency for delivering family meetings...the specialist physicians were able to attend more of these family meetings than in the past, because of the ability to attend virtually. And then, more family were able to attend than...in the past. And it was able to happen faster because we could do it virtually versus waiting several days for a family member to arrive from another city. [Site B, 13, occupational therapist]

Participants also expressed the benefits of web-based care for patient access, particularly for patients with mobility challenges or lack of transportation:

I can actually say that shift [to virtual] was very positive because...it actually eliminated some of the concerns my patients have about transportation, or ways that they’re able to get out there, be it because of their physical impairment post-operation. Or simply just because they don’t have the resources to get transit for whatever reason. [Site A, 23, social worker]

Further, some participants expressed how web-based care positively changed clinical practice for counseling services:

And from all the patients I’ve intervened with...I’d say .01% want to come in person...I find that on Zoom you can sort of see the environment they’re in...I think that COVID has revolutionized social work intervention...I only have good things to say about it. COVID has opened up a whole new world for counseling. [Site B, 15, social worker]

Web-based care was not without its challenges. Clinicians described that greater access to care increased referrals from patients who would historically not come for in-person treatment, particularly for mental health services:

...we found that we were getting more referrals from ... all these different patients who would have not been able to come to hospital to do in-person groups...people with anxiety disorders, like agoraphobia. People who had not seen—have difficulty going outside the house. [Site A, 16, nursing]

...the workload increased enormously, and was impossible to keep up with because before people had to come in to [the hospital] to see me so that actually restricted the number of people that I could see to people who lived in [the city], or in some neighbouring communities. At times, people would come in and come drive like 90 to 120 minutes to come and see me but due to Covid, when we shifted to online therapy...now, everybody in [the province] had access to me who were part of these programs...many people wanted to see the psychologist because they wouldn’t have to drive in. [Site C, 16, psychologist]

Consequently, participants described that more visits over Zoom led to greater fatigue as a result of having to simultaneously navigate Zoom and in-person teaching, resulting in a reduction in group therapy frequency:

We noticed for us clinicians we were just getting so fatigued that it was just too much. Because running a group in-person, and running it over Zoom is very, very different. You’re staring at a screen, you’re looking at all the faces in the room. You’re trying to navigate the PowerPoint, there’s a lot of things happening simultaneously, that when we were doing four groups a week we just noticed this is not sustainable for us. So we had to shift it to three groups. So one less group a week. So I think that’s a huge change in terms of provision of care. [Site A, 16, nursing]

In terms of providing clinical care, clinicians described the challenges of conducting a physical assessment or providing counseling treatment via Zoom or by phone:

We do some physical examination. So it’s hard just to understand the status just by phone, even if you ask them “Any swelling?” Then they say no but actually they have, so the knowledge may not be there. [Site C, 10, registered dietician]

...in Zoom it’s very limited and you mostly see the face. Right? You don’t see what the person is doing with their hands, arms, with their legs, with their feet. [Site B, 07, spiritual care practitioner]

It’s just something about being in the same room with someone when their emotions are high that you don’t actually have to do anything in particular, but just the calming presence makes a difference. I think that people get some of that on Zoom...I don’t know how similar or different, but I’m just assuming that it’s probably a bit watered down...Whereas if I was just in the room, I think just being quiet with the person would be enough and might be even better at times. [Site C, 16, psychologist]

Finally, clinicians described the challenges of using web-based care when working with older patients due to limited experiences with technology or cognitive impairments. Interestingly, some participants felt that the reliance on web-based care reduced the attendance of older populations who were not familiar with the technology.

...our average age is 97, they’re not tech savvy, they’re not necessarily understanding, comprehending, you know, that, you know, as we would understand that you can actually talk to someone who’s not present here, but it’s in the same time...So, I would call it, you’re having a video call. I try and explain it’s that, you’re having a video telephone call. And then, they just think they’re looking at a television, you know, and they’re just watching kind of a show and stuff. [Site B, 10, recreation therapist]

Some of our clients—some people with dementia don’t understand...either they don’t recognize themselves, or they get agitated by the sight of themselves—so having the person facilitating the Zoom understand how to turn off the view that you can see yourself, was important...I think I lost a number of older spouses that used to come to the group, because they...had difficulty understanding the technology, or just their digital literacy, or access to technology wasn’t that great. So currently...and interestingly, that has changed the demographic of people who are coming in my Caregiver Group. [Site B, 08, social worker]

Principal Findings

The aim of this qualitative descriptive study was to describe the experiences of HCPs in how ICT supported changes to clinical care during the COVID-19 pandemic. Participant narratives revealed 3 key findings: the benefits of digital tools to support in-person communication between patient and provider, the need for thoughtful consideration for the use of ICT at end-of-life care, and the support for the continued use of web-based care, when appropriate. We discuss HCPs’ experiences as they relate to the literature and provide recommendations for health care organizations that can make use of ICT in a more collaborative way while reflecting on patient and family values.

Communication between patients and providers is essential for quality care and for reducing preventable adverse medical events [ 10 ]. Patients who have been appropriately supported in their communication have reported to be more satisfied in their hospital stay [ 11 ]. Devices to assist with communication, more commonly referred to as alternative augmentative communication (AAC), have existed in health care for decades. AAC is an intervention approach for individuals who require added support (augmentative) or a replacement (alternative) for their communication [ 12 ]. AAC can be low technology such as communication boards or pictures or high technology such as communication systems on iPads and speech-generation devices and can be used for a short or long period of time depending on the individual’s communication needs [ 12 ].

The COVID-19 pandemic spawned a rapid adoption of digital tools such as tablets, which became an available tool to reduce communication barriers experienced with mask-wearing when speaking to patients and families and allow for participation in conversation. Additionally, tablets enabled access to video language interpretation for patients who were mechanically ventilated and awake [ 13 ], a unique example of reducing language barriers when families were not able to be present for interpretation. However, participant narratives using digital tools within acute care and rehabilitation contrast the literature describing the experiences of patients and families in the intensive care unit. In the intensive care unit, HCPs and families reported barriers to the implementation of communication supports, particularly for patients who were mechanically ventilated and awake [ 14 ]. Nurses reported feeling inadequate and frustrated in trying to support patients [ 14 ], whereas families reported frustration with communication breakdowns, inconsistent availability of tools, and insufficient training by the HCP [ 15 ]. Patients described being mechanically ventilated as a vulnerable, lonely, and fearful experience [ 15 ], particularly as verbal communication was not an option.

The collective experiences of nurses, families, and patients emphasize the impact that a lack of communication supports can have at the bedside. Further, the experiences of nurses, families, and patients shed light on the education and training that is needed for successful patient-provider communication to support participation in conversation, particularly for patients on mechanical ventilation. Reports from speech-language pathologists working with patients who are critically ill revealed positive patient-provider communication outcomes when there was nurse collaboration and readily available communication supports at the bedside [ 13 ]. Thus, the experiences of patients, families, and HCPs highlight the integral role that leadership and hospital policies play in prioritizing communication access, tool availability, and organizational-wide training [ 13 , 16 ]. For system-level change, it is recommended that hospital leaders develop regular staff training on communication supports led by professionals with expertise in this area such as speech-language pathologists [ 14 ]. For increased awareness on the importance of communication supports in health care, it is recommended that education on patient-provider communication starts as early as the undergraduate and postgraduate level for health discipline (ie, clinical) programs [ 14 ].

Videoconferencing tools have been used to connect loved ones for over a decade and have been shown to have positive psychosocial outcomes for nursing home residents when used as an addition to in-person family visits [ 17 ]. Specifically, older residents in nursing homes who received videoconferencing visits with family in addition to in-person family visits had a greater mean change in baseline depressive symptoms and feelings of loneliness when compared to older residents who had in-person visits only [ 17 ]. During the pandemic, however, videoconferencing tools and digital devices were used as a substitute for in-person visits due to visitor restrictions imposed by the COVID-19 pandemic. Although this enabled a connection between patient and family, the reduced frequency of family connections created tensions between both HCPs and family members.

Similar tensions were described by HCPs in the United Kingdom including communicating devastating news to relatives without having ever met them in person and the moral dilemma of what is “best” end-of-life care versus what could be offered given the COVID-19 restrictions [ 18 ]. Further, clinicians in Canada reported that web-based visits at end-of-life care prevented meaningful conversations typically had between family members at the bedside [ 19 ]. One physician described the importance of family connection in end-of-life care: “I’m now convinced that family members at the bedside improves patients’ ability to get better” [ 19 ]. The experiences of bereaved relatives aligned with the internal conflicts of HCPs in the United Kingdom: families wanted frequent communication that was easy to understand, one last chance to say goodbye through physical touch, and speaking to their loved one at bedside [ 20 ]. Similarly in Canada, HCPs, patients, and families all felt that restrictive acute care visitor policies impacted the safety and quality of care, mental health of everyone involved, families as partners in care, and communication and advocacy [ 4 ].

Although COVID-19 visitor restrictions have lifted, the experiences described by clinicians and families highlight the considerations needed for a positive, meaningful, end-of-life experience. One example of an organizational-wide intervention for end-of-life care includes the 3 Wishes Project (3WP), an intervention that gathers 3 wishes from the patient and family to help personalize and humanize end-of-life care [ 21 ]. The 3WP has demonstrated a positive impact on families and clinicians; families had a significantly higher rating of emotional and spiritual support than families who did not receive the 3WP [ 22 ], while clinicians reported greater morale and collaboration in helping families move toward acceptance [ 23 ]. Further, the 3WP has shown to build capacity for compassion at the organization level by facilitating collective noticing, feeling, and responding [ 24 ]. In other words, the implementation of 3WP creates system-level processes and structures to facilitate compassionate care while promoting the connection between patients, families, and HCPs [ 24 ]. Thus, while the use of digital devices will likely continue to be a complement to care [ 25 ], it is important that organizations encourage collective, compassionate care to meet the wishes of patients and families.

Literature describing the benefits and challenges of web-based care aligned with participant narratives. Benefits included faster access to care, greater efficiency, and improved convenience for patients [ 26 ]; challenges included conducting assessments without the ability to complete in-person physical examinations [ 26 ] and offering web-based care to patients with poor digital literacy [ 27 - 29 ]. What was unique to this study’s findings was the increase in referral rates with the implementation of web-based care. Two reasons for an increase in referrals as described by participants included greater access for patients with significant mental health needs who otherwise would not come in for services and greater access for patients living far away from the hospital. Consequently, more referrals increased the workload of HCPs, demonstrating the dichotomy between patient access to care and provider workload. This emphasizes the considerations needed to balance clinician workload with patient preference of service modality as organizations move toward hybrid models of care [ 25 ].

A recent US study examined patient preference for service modality for nonurgent care and found that when out-of-pocket costs were not a factor, slightly more than half of the sample (53%) preferred in-person visits to web-based care, while one-fifth (21%) preferred web-based and one-quarter (26%) had no preference or did not know what they preferred [ 30 ]. For individuals who had video visit experience, this was associated with their preference for video visits [ 30 ]. A closer look at demographic factors revealed that those who did not feel that video calls had a role in their medical care were generally older people, who lived rurally, and who had a lower income and educational level [ 30 ]. Conversely, patients who were younger and had a higher income and education were more likely to choose a video visit over in-person care [ 30 ]. While choice of service modality may be an option for nonurgent care moving forward, some populations may not have the same ability to choose. Rather, it is up to the HCP to decide whether web-based care is appropriate.

HCPs, such as psychiatrists, who work with patients with significant mental health disorders have described the role that contextual factors contribute to decision-making of service modality [ 31 ]. Contextual factors in decision-making included if an in-person visit provided greater therapeutic benefit than a web-based visit, if a general examination was needed, if there were caregivers nearby who could provide information, if insight into the living environment was necessary, and if safety resources were required for in-person visits [ 31 ]. There was no consensus among psychiatrists on the mental health conditions that would best be served, as some respondents felt web-based care offered unique benefits such as improved patient safety and reduced likelihood of escalation [ 31 ]. Taken together, a combination of factors will need to continue to be considered for service delivery modality moving forward, such as patient preference, nature of service provided, and technology literacy. Furthermore, thoughtful planning for the accessibility of technology use for underserved populations will likely be an element of consideration for the field of health care [ 32 ].

Limitations

First, this study is limited to the experiences of the HCP from urban hospitals in Ontario and British Columbia and may not be transferable to the full scope of pandemic hospital worker experiences across the globe. Consequently, there may have been uses of ICT that happened during the pandemic that were particularly novel or interesting but may not have been captured due to the nature of this qualitative study. Second, participants were given an electronic gift card after the interview in recognition of their time, which may have impacted self-referral into the study. Third, there were several research team members involved in interviews, which may have impacted the depth of information provided by the participants across interviews.

Conclusions

Experiences from HCP highlight the uses of ICT to support changes to clinical care during the pandemic. The use of digital tools supported patient-provider communication, enabled a connection between patients and families at end-of-life care, and provided continuity of care amid COVID-19 lockdowns. Moving forward, organizations are encouraged to provide education and training on how to support patient-provider communication in clinical care; find ways to implement collaborative, compassionate, end-of-life care; and continue to give autonomy to HCPs in their clinical decision-making regarding service delivery modality.

Acknowledgments

This study was funded by a grant from the Canadian Institutes of Health Research (W12179927). The authors would like to thank the participants who took time to reflect on the difficult experiences they and their colleagues faced during the COVID-19 pandemic. The authors would also like to thank the research team of Kang Kang Margolese, Marina Morris, Lily Zeng, Marie Oliveira, Adebisi Akande, and Frances Bruno who contributed to the data collection and analysis.

Data Availability

An aggregate summary of data generated and analyzed during this study are included in this published manuscript. Individual data transcripts cannot be publicly shared because of confidentiality.

Authors' Contributions

LJ conceived and designed the study and assisted with data analysis. CAC and HR assisted with data collection and data analysis. CAC drafted the manuscript, and all authors critically reviewed it as well as read and approved the final manuscript.

Conflicts of Interest

None declared.

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Abbreviations

Edited by A Mavragani; submitted 24.09.23; peer-reviewed by A Ševčíková, H Pilabré, A Olsson; comments to author 02.12.23; revised version received 06.03.24; accepted 21.03.24; published 28.05.24.

©Carly A Cermak, Heather Read, Lianne Jeffs. Originally published in JMIR Formative Research (https://formative.jmir.org), 28.05.2024.

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