May 13, 2024, 4:46 a.m. | Hunter McNichols, Jaewook Lee, Stephen Fancsali, Steve Ritter, Andrew Lan

cs.CL updates on arXiv.org arxiv.org

arXiv:2405.06414v1 Announce Type: new
Abstract: Intelligent Tutoring Systems (ITSs) often contain an automated feedback component, which provides a predefined feedback message to students when they detect a predefined error. To such a feedback component, we often resort to template-based approaches. These approaches require significant effort from human experts to detect a limited number of possible student errors and provide corresponding feedback. This limitation is exemplified in open-ended math questions, where there can be a large number of different incorrect errors. …

abstract arxiv automated cs.cl error experts feedback human intelligent language language models large language large language models math questions replicate students systems template tutoring type

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