AI evidence extraction

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.

9/10

Relevance

Evidence

Citations

0.41

FWCI

Top 10%

Impact

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, 3 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; 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; specific inclusion/exclusion criteria not detailed in abstract; 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."

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