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  1. ; ; ; ; ; (, LAK 2024 (submitted, in review))
    We present a conversational AI tutor (CAIT) for the purpose of aiding students on middle school math problems. CAIT was created utilizing the CLASS framework, and it is an LLM fine-tuned on Vicuna using a conversational dataset created by prompting ChatGPT using problems and explanations in ASSISTments. CAIT is trained to generate scaffolding questions, provide hints, and correct mistakes on math problems. We find that CAIT identifies 60% of correct answers as correct, generates effective sub-problems 33% of the time, and has a positive sentiment 72% of the time, with the remaining 28% of interactions being neutral. This paper discusses the hurdles to further implementation of CAIT into ASSISTments, namely improved accuracy and efficacy of sub-problems, and establishes CAIT as a proof of concept that the CLASS framework can be applied to create an effective mathematics tutorbot. 
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