Evaluating ChatGPT's Decimal Skills and Feedback Generation in a Digital Learning Game

This paper evaluates ChatGPT's ability to solve decimal problems, grade student self-explanation responses, and generate instructional feedback within the Decimal Point learning game, using over 5,000 real student responses from middle school students. The study finds ChatGPT can accurately assess 75% of student answers and generate high-quality feedback, though it struggles with specific decimal place value problems.

While open-ended self-explanations have been shown to promote robust learning in multiple studies, they pose significant challenges to automated grading and feedback in technology-enhanced learning, due to the unconstrained nature of the students' input. Our work investigates whether recent advances in Large Language Models, and in particular ChatGPT, can address this issue. Using decimal exercises and student data from a prior study of the learning game Decimal Point, with more than 5,000 open-

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