Pedagogical Promise and Peril of AI: A Text Mining Analysis of ChatGPT Research Discussions in Programming Education

TL;DR

This study uses text mining to analyze scholarly discussions on ChatGPT in programming education, revealing dominant themes, perceptions, and gaps in the literature.

Contribution

It provides a comprehensive mapping of research themes and perceptions of ChatGPT in programming education through systematic text analysis.

Findings

Four main themes: pedagogical use, student engagement, AI infrastructure, and assessment.

ChatGPT is seen as both a helpful learning tool and a pedagogical risk.

Literature emphasizes classroom practice but less on assessment and governance.

Abstract

GenAI systems such as ChatGPT are increasingly discussed in programming education, but the ways in which the research literature conceptualizes and frames their role remain unclear. This chapter applies text mining to publications indexed in a leading academic database to map scholarly discourse on ChatGPT in programming education. Term frequency analysis, phrase pattern extraction, and topic modeling reveal four dominant themes: pedagogical implementation, student-centered learning and engagement, AI infrastructure and human-AI collaboration, and assessment, prompting, and model evaluation. The literature prioritizes classroom practice and learner interaction, with comparatively limited attention to assessment design and institutional governance. Across studies, ChatGPT is positioned both as a learning aid that supports explanation, feedback, and efficiency and as a pedagogical risk linked to overreliance, unreliable outputs, and academic integrity concerns. These findings support responsible integration and highlight the need for stronger assessment and governance mechanisms.