Grume, J.C., Miranda, J.P.P., De Leon, A.P., Salenga, J.L., Hernandez, H.E., Castro, M.A.A., Maniago, V.G.M., Canlas, J.D., Quiambao, J.B. (2026) — Pedagogical Innovations in CS Education (IGI Global).
Analysis
This book chapter presents a text mining analysis of how scholarly literature frames ChatGPT's role in programming education. Using term frequency analysis, phrase pattern extraction, and topic modeling, the authors identify four dominant themes: pedagogical implementation, student-centered learning, AI infrastructure, and assessment design.^[raw/papers/2605.00361.md]
The central finding is a dual positioning: ChatGPT is consistently framed as both a learning aid (enhancing explanation, feedback, efficiency) and a pedagogical risk (overreliance, unreliable outputs, academic integrity). This connects to academic-integrity, over-reliance, and hallucination-risk by documenting these as dominant framings in the research literature. Notably, research is skewed toward classroom practice while systematic assessment design and institutional governance remain underexplored.
Related Pages
- cognitive-shift-ai-education — 471 students surveyed 2020–2026 show shift from AI preference to human intellige
- over-reliance — Text mining reveals ChatGPT overreliance as key pedagogical risk
- academic-integrity — Academic integrity threat as dominant framing of ChatGPT in CS education
- stem-education — ChatGPT discussions in programming education across themes
- feedback-loop — ChatGPT as instant feedback provider and pedagogical implications
- student-experience — Student-centered learning as most-represented research theme
- hallucination-risk — Unreliable outputs as documented peril of ChatGPT in programming
Citation
APA: Grume et al. (2026). Pedagogical Promise and Peril of AI: A Text Mining Analysis of ChatGPT Research Discussions in Programming Education. arXiv:2605.00361. Pedagogical Innovations in CS Education (IGI Global).