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Here the authors evaluateE various configurations of Llama 3.2 models (ranging from 1B to 8B parameters trained across 1 to 5 epochs) to serve as cost-effective math tutoring assistants for K-12 classrooms. Their findings show that while the largest 8B model trained for 5 epochs achieved peak accuracy, smaller fine-tuned models provide a viable, resource-efficient balance for practical educational deployment.

Authors examine the effectiveness of Large Language Models (LLMs) like BERT, MathBERT, and OpenAI GPT-3.5 in assisting middle school students with math word problems, particularly following the decline in math performance post-COVID-19.

Middle school math forms the basis for advanced mathematical courses leading up to the university level. Large language models (LLMs) have the potential to power next-generation educational technologies, acting as digital tutors to students. The main objective of this study was to determine whether LLMs like ChatGPT, Bard, and Llama 2 can serve as reliable middle school math tutoring assistants on three tutoring tasks: hint generation, comprehensive solution, and exercise creation.