ChatGPT in Teaching-Learning and Research: A Systematic Review
Shaheena Aziz, Mohammad Ishfaq Mir, Mohammad Amin Dar, Faheem Syeed Masoodi · Asia Pacific Journal of Educators and Education · 2024
AI-generated evidence extraction, verified across multiple analytical personas. Not a substitute for the peer-reviewed original.
This is an AI analysis. Read the peer-reviewed original at the publisher: https://doi.org/10.21315/apjee2024.39.1.8
Methodology & findings
Study design
Systematic review following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.
Sample
N = 25, 4 groups
Primary method
Narrative synthesis of included studies. PRISMA guidelines utilized for systematic review methodology. Specific statistical analysis methods not detailed in abstract.
Main result
The review found that "ChatGPT can prove effective in teaching, learning and research." However, the systematic examination also revealed significant concerns: "The review also brought to light a lot of issues, such as plagiarism, manipulation, cheating and ChatGPT's trustworthiness." The findings underscore both the potential benefits and substantial ethical and practical challenges associated with ChatGPT integration in higher education.
Reports effect sizes.
Research paradigm
Interpretivist/Critical
Author conclusions
The authors conclude that "this review illuminates potential avenues for future studies and also presents a critical assessment, paving the way for improvements in the field." They emphasize that while ChatGPT offers effectiveness in educational contexts, "the findings also underscore the limitations in the use of ChatGPT and emphasise the ethical considerations involved."
Risk of bias
Selection bias from inclusion/exclusion criteria (25 of 106 studies selected); Publication bias potential from database-only search (Scopus, IEEE Xplore, ScienceDirect); Language bias possible if non-English articles excluded; Selection bias: Only 25 of 106 identified studies met inclusion criteria, which could result in selective inclusion of particular types of evidence; Database limitations: Search restricted to Scopus, IEEE Xplore, and ScienceDirect; other relevant databases may have been excluded; Publication bias: Systematic reviews of recent topics like ChatGPT may be subject to publication bias favoring positive or novel findings; Quality assessment methodology: Not specified in abstract whether quality appraisal tool was used; Selection bias: Only 25 of 106 initially identified studies met inclusion criteria; specific inclusion/exclusion criteria not detailed in abstract; Publication bias: Search limited to Scopus, IEEE Xplore, and ScienceDirect; potential grey literature not addressed; Language bias: Not specified whether non-English publications were included; Temporal bias: Rapid evolution of ChatGPT functionality may render earlier studies outdated
Limitations
- The review acknowledges that while it provides comprehensive analysis, the relatively small number of included studies (25 out of 106 identified) may limit generalizability
- The authors note "the limitations in the use of ChatGPT and emphasise the ethical considerations involved," though specific methodological limitations of the review itself regarding publication bias, heterogeneity assessment, or quality appraisal are not explicitly detailed in the abstract.
Open questions raised
- The authors identified a notable gap: "there is a notable gap in the literature regarding comprehensive review articles focusing on specific subtopics, such as the application of ChatGPT and its impact on higher-level teaching, learning and research." They also highlight future research directions by stating "this review illuminates potential avenues for future studies."
- The authors identified a notable gap in the literature: "there is a notable gap in the literature regarding comprehensive review articles focusing on specific subtopics, such as the application of ChatGPT and its impact on higher-level teaching, learning and research." The review itself points to future research directions related to ethical considerations and improvements in ChatGPT implementation in educational contexts.
- The review identifies a notable gap in comprehensive systematic review articles focusing on specific subtopics such as ChatGPT's application and impact on higher-level teaching, learning, and research. The authors note that prior to their work, "no thorough examination has been conducted to synthesise and critically analyse the existing studies in this particular domain." Future research directions include addressing ethical considerations, trustworthiness issues, and plagiarism/cheating concerns.
Explore related topics
Related papers
- Practical and ethical challenges of large language models in education: A systematic scoping reviewLixiang Yan · 2023 · 699 citations
- AI, agentic models and lab automation for scientific discovery — the beginning of scAInceThomas Hartung · 2025 · 14 citations
- LLM4SR: A Survey on Large Language Models for Scientific ResearchZonglin Yang · 2025 · 5 citations
- Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and EvaluationSteffen Eger · 2025 · 5 citations
- Artificial intelligence in higher education, opportunities, and challenges: a reviewSharifa AlBlooshi · 2026 · 4 citations
- AI for Auto-Research: Roadmap & User GuideLingdong Kong · 2026