Due to the remarkable language understanding and generation abilities of large language models (LLMs), their use in educational applications has been explored. However, little work has been done on investigating the pedagogical ability of LLMs in helping students to learn mathematics. In this position paper, we discuss the challenges associated with employing LLMs to enhance students' mathematical problem-solving skills by providing adaptive feedback. Apart from generating the wrong reasoning processes, LLMs can misinterpret the meaning of the question, and also exhibit difficulty in understanding the given questions' rationales when attempting to correct students' answers. Three research questions are formulated.

翻译：鉴于大型语言模型（LLMs）在语言理解与生成方面展现出卓越能力，其在教育应用中的潜力已受到广泛探索。然而，关于LLMs在辅助学生数学学习方面的教学能力研究仍十分有限。本立场论文探讨了利用LLMs通过提供自适应反馈来提升学生数学问题解决能力所面临的挑战。除了可能生成错误的推理过程外，LLMs在理解题目含义、识别给定问题的逻辑依据以及纠正学生答案时均存在困难。据此，我们提出了三个研究问题。