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

This paper evaluates ChatGPT's ability to solve decimal math problems, assess correctness of student self-explanations, and generate feedback within the Decimal Point learning game for middle school students, using over 5,000 real student responses. The study assesses ChatGPT's content knowledge in decimals, automated grading accuracy (75%), and pedagogical quality of generated feedback using a structured rubric.

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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