Learning gain differences between ChatGPT and human tutor generated algebra hints
Zachary A. Pardos, Shreya Bhandari

TL;DR
This study compares the effectiveness of ChatGPT-generated algebra hints with human tutor hints, finding that human hints lead to significantly higher learning gains despite ChatGPT producing mostly acceptable hints.
Contribution
First evaluation of ChatGPT's algebra hints in a tutoring context, demonstrating its potential and limitations compared to human-authored hints.
Findings
ChatGPT hints passed 70% quality checks
Human hints resulted in significantly higher learning gains
ChatGPT performance was near ceiling in Intermediate Algebra
Abstract
Large Language Models (LLMs), such as ChatGPT, are quickly advancing AI to the frontiers of practical consumer use and leading industries to re-evaluate how they allocate resources for content production. Authoring of open educational resources and hint content within adaptive tutoring systems is labor intensive. Should LLMs like ChatGPT produce educational content on par with human-authored content, the implications would be significant for further scaling of computer tutoring system approaches. In this paper, we conduct the first learning gain evaluation of ChatGPT by comparing the efficacy of its hints with hints authored by human tutors with 77 participants across two algebra topic areas, Elementary Algebra and Intermediate Algebra. We find that 70% of hints produced by ChatGPT passed our manual quality checks and that both human and ChatGPT conditions produced positive learning…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsIntelligent Tutoring Systems and Adaptive Learning · Topic Modeling · Text Readability and Simplification
