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A diverse group of computing students and an instructor compare AI tutoring responses with a prerequisite map and scaffolded Python exercises
会议论文2026
会议论文 86

Pedagogical-fit feedback improved 51 of 62 weak AI-tutor responses, but scaffolding gains created trade-offs

Benjamin Barlog, Hudson Craig, Zedong Peng

IEEE 27th International Conference on Information Reuse and Integration for Data Science (IRI 2026)

Barlog, Craig and Peng evaluated ChatGPT, Gemini, Gemma 4 and Qwen 3 across 240 introductory-programming tutoring scenarios with a six-part Pedagogical Suitability Index. Baseline scores differed modestly, while targeted feedback improved 51 of 62 weak cases. The largest gain was scaffolding, but prerequisite ordering and Bloom-level alignment sometimes declined, showing why tutoring quality needs multiple measures rather than one composite score.

AI tutorspedagogical fitscaffolding
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AIEDHKAI in Education Hub of Knowledge

AIEDHK 是面向 AI in Education 研究、开发与负责任学习创新的多语言知识枢纽。

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