What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature
Abstract
:1. Introduction
- RQ1: How does ChatGPT perform in different subject domains?
- RQ2: How can ChatGPT be used to enhance teaching and learning?
- RQ3: What are the potential issues associated with ChatGPT, and how can they be addressed?
2. Methods
2.1. The Rapid Review Approach
2.2. Search Strategies
2.3. Inclusion and Exclusion Criteria
2.4. Content Analysis
- Open coding: Open coding is the initial stage of coding in which the researcher examines the data and generates codes to describe and categorise the data. It allows a deep exploration and understanding of the data without imposing preconceived ideas.
- Axial coding: After the initial process of open coding, axial coding is used to analyse the relationships and connections between the codes generated during open coding. It involves organising the codes into broader categories or themes and establishing the relationships between them.
- Selective coding: Selective coding is the final stage of coding. It involves further refining and integrating the categories or themes identified during open and axial coding to develop a comprehensive picture. It identifies the core category or central phenomenon that emerged from the data.
3. Findings
3.1. General Description of the Literature
3.2. RQ1: How Does ChatGPT Perform in Different Subject Domains?
3.3. RQ2: How Can ChatGPT Be Used to Enhance Teaching and Learning?
3.4. RQ3: What Are the Potential Issues Associated with ChatGPT and How Can They Be Addressed?
4. Discussion
4.1. Leveraging ChatGPT in Teaching and Learning
4.2. Challenges and Threats Posed by ChatGPT in Education
4.3. Immediate Action in Response to the Impact of ChatGPT
4.4. Limitations and Recommendations for Future Research
4.4.1. Limitations of this Rapid Review
4.4.2. Limitations of the Included Articles
5. Conclusions
Supplementary Materials
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Criterion | Inclusion | Exclusion |
---|---|---|
Article topic | Discuss ChatGPT in the field of education | Do not discuss GhatGPT in the field of education |
Article type | Academic articles | Non-academic articles, such as articles from mass and social media |
Time period | 1 January 2022 to 28 February 2023 | Articles outside the time period |
Language | English | Non-English |
Subject Domain | Studies | Overall Performance | Representative Researcher Comments |
---|---|---|---|
Critical and higher-order thinking | [21] | Outstanding | “The generated responses can be assessed as being clear in exposition, precise with respect to examples used, relevant to the requests…” [21] (p. 13). |
Economics | [22] | Outstanding | In TUCE, “ChatGPT ranks at the 99th percentile in macroeconomics and the 91st percentile in microeconomics, when compared to [other] students” [22] (p. 7). |
Programming | [35,36,37] | Outstanding to satisfactory | “Nearly all answers of ChatGPT were completely correct and nicely explained… the explanations by ChatGPT were amazingly clear and goal-oriented” [35] (p. 1). “The lecturer graded the assignment submission with a total score of 71 out of 100 points, resulting in a grade of ‘Satisfactory’” [36] (p. 4). |
English language comprehension | [20] | Satisfactory | “the mean grade achieved by ChatGPT according to official norms was 7.18, which is similar to the mean grade of all students in the Netherlands” [20] (p. 1). |
Law | [10,23] | Barely satisfactory to unsatisfactory | “ChatGPT performed on average at the level of a C+ student, achieving a low but passing grade” [10] (p. 1). “It performed worst on exams that featured problem-style or ‘issue spotting’ questions” [23] (p. 1) |
Medical education | [24,25,26,27,28,29,30,31,32] | Barely satisfactory to unsatisfactory | “ChatGPT yields moderate accuracy approaching passing performance on USMLE” [24] (p. 4). In American Heart Association BLS and ACLS exams, “ChatGPT did not reach the passing threshold for any of the exams” [26] (p. 109732). |
Mathematics | [33] | Unsatisfactory | “ChatGPT’s mathematical abilities are significantly below those of an average mathematics graduate student” [33] (p. 1). |
Software testing | [38] | Unsatisfactory | “ChatGPT is not able, by itself, to pass a software testing course. In total, ChatGPT was able to correctly answer 37.5% of the questions we posed” [38] (p. 8). |
Sports science and psychology | [39] | Unsatisfactory | “ChatGPT gave several correct answers to 20 questions but failed the test with [a score of] 45%” [39] (p. 2). |
MCQ-based exams across subjects | [34] | Unsatisfactory | “ChatGPT fails to meet the passing grade on almost every MCQ exam that it is tested against, and performs significantly worse than the average human student” [34] (p. 1). |
Aspect | Function | Representative Quotes | Other Representative Support |
---|---|---|---|
Teaching preparation | Generating course materials | “we asked ChatGPT to create one of the dialogues above in a format that can be imported into DialogFlow. ChatGPT was able to generate it successfully” [42] (p. 37). | [43,44,45] |
Providing suggestions | “I told ChatGPT that the learner was with dyslexia, and eventually ChatGPT recommended specific learning materials for the learner” [41] (p. 1). | [8,27,37] | |
Performing language translation | “ChatGPT can be used to translate educational materials into different languages” [46] (p. 8). | [45,47,48] | |
Assessment | Generating assessment tasks | “Another use of ChatGPT is its ability to generate exercises, quizzes, and scenarios which can be used in the classroom to aid in practice and assessment” [29] (p. 5). | [27,45,49] |
Evaluating student performance | “ChatGPT can be trained to grade student essays, providing teachers with more time to focus on other aspects of teaching” [29] (p. 8). | [46,50,51] |
Aspect | Function | Representative Quotes | Other Representative Support |
---|---|---|---|
Learning | Answering questions | “The answer[s] given by ChatGPT were relevant and accurate… The tool can used as quick reference and self-studying instrument” [28] (p. 1). | [25,46,53] |
Summarising information | “it is very good at processing information, distilling it, and presenting it verbally” [54] (p. 92). | [23,29,44] | |
Facilitating collaboration | “The ChatGPT application has the potential to serve as a means of generating different scenarios for students to work together to solve problems and achieve goals” [52] (p. 13). | [25,44,50] | |
Assessment | Concept checking and exam preparation | “ChatGPT has shown promising results in becoming a powerful reference and self-learning tool for preparing for the life support exams” [26] (p. 1). | [10,28,32] |
Drafting assistance | “students could be encouraged to use AI to give a ‘first draft’ answer, and then asked to improve upon that answer manually” [23] (p. 21). | [10,25,55] | |
Providing feedback | “ChatGPT could be used to grade assignments and provide feedback to students in real-time” [50] (p. 2). | [46,48,56] |
Aspect | Issues | Representative quotes | Other Representative Support |
---|---|---|---|
Accuracy and reliability | Relying on biased data | “These biases stem from research performed in high-income countries and textbooks [i.e., the training data of ChatGPT]” [57] (p. 2). | [40,46,54] |
Having limited up-to-date knowledge | “ChatGPT has no idea of the world after 2021 and hence it could not add any references or information after 2021” [46] (p. 14). | [25,45,56] | |
Generating incorrect/fake information | “ChatGPT included a make-up article which does not exist and even provided full bibliographic details of the article with a non-functional URL” [46] (p. 14). | [32,38,58] | |
Plagiarism prevention | Student plagiarism | “Our experimental group [with ChatGPT support] had slightly more problems with plagiarism than the control group [without ChatGPT support]” [59] (p. 7). | [40,51,60] |
Bypassing plagiarism detectors | “Of the 50 essays inspected, the plagiarism-detection software considered 40 of them with a high level of originality, as evidenced by a similarity score of 20% or less” [61] (p. 10). | [36,52,62] |
Aspect | Strategies | Representative Quotes | Other Representative Support |
---|---|---|---|
Task design | Incorporating multimedia resources | “Embedding images to exam questions can make it more difficult for students to cheat and for ChatGPT to generate accurate responses” [21] (p. 16). | [22,34,52] |
Adopting novel question types | “[Instructors] might also reconsider the types of questions they pose to students, focusing on those that require analysis rather than those that simply require [a] recall of legal rules” [10] (p. 12). | [8,22,63] | |
Employing digital-free assessment formats | “blanket solution would be to make all assessments of the ‘in-class’ variety… it will be essentially impossible for ChatGPT to be leveraged in an unscrupulous fashion” [23] (p. 19). | [21,31,36] | |
Identification of AI writing | Using AI-based writing detection tools | “Plagiarism detectors could not identify the AI-originated text, but AI detectors did” [39] (p. 2). | [21,55,56] |
Checking references | “Although in text citations and references were provided…, these were all fabricated… This does open a potential avenue of detection by academic staff” [56] (p. 5). | [39,50,52] | |
Institutional policy | Establishing anti-plagiarism guidelines | “Administrations should consider how to reshape honor codes to regulate the use of language models in general” [10] (p. 12). | [52,56,61] |
Providing student education | “Our recommendations for students are to… be aware of academic integrity policies and understand the consequences of academic misconduct… provide training on academic integrity for students” [52] (pp. 14–15). | [54,64,65] |
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Lo, C.K. What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature. Educ. Sci. 2023, 13, 410. https://doi.org/10.3390/educsci13040410
Lo CK. What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature. Education Sciences. 2023; 13(4):410. https://doi.org/10.3390/educsci13040410
Chicago/Turabian StyleLo, Chung Kwan. 2023. "What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature" Education Sciences 13, no. 4: 410. https://doi.org/10.3390/educsci13040410