ChatGPT-Assisted Data Analysis in Mathematics Education Research (CADAMER): A Scoping Review in the Post-Modern Scholarly Milieu

Abstract

This study investigated the role of ChatGPT-assisted data analysis in mathematics education research within the post-modern scholarly milieu using a scoping review approach. This examined how ChatGPT contributes to ethical, reliable, rigorous, and context-sensitive data analysis in mathematics education research. The findings reveal five (5) emergent themes that define ChatGPT’s role in this domain: (1) ChatGPT for Quantitative Analysis; (2) ChatGPT for Qualitative Coding; (3) ChatGPT and Research Ethics; (4) ChatGPT in Literature Reviews; and (5) ChatGPT on the Future of Research. Based on the findings, the study extracted the ChatGPT-Assisted Data Analysis in Mathematics Education Research (CADAMER) model, positioning ChatGPT as a versatile research assistant that enhances analytical efficiency while upholding scholarly rigor. Although ChatGPT streamlines data analysis, human oversight and ethical safeguards remain crucial to ensuring accuracy and academic integrity. The integration of ChatGPT with expert validation strengthens the rigor, ethics, and reliability of mathematics education research.

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