  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.
