We believe handwriting input may be able to provide significant advantages over typing, especially in the mathematics learning domain. The use of handwriting may result in decreased extraneous cognitive load on students, and it may provide better support for the two-dimensional spatial components of mathematics when compared to existing typing-based tools. Here we report progress towards the application of a handwriting interface for mathematics learning. We introduce a prototype system that allows students to use handwriting input to solve algebraic equations in an intelligent tutor. We discuss strategies to improve the existing handwriting system and apply it to math learning. Although the recognition accuracy of current handwriting engines may not be at a level suitable for use by students, we hypothesize that this may be realistically improved via advance training of the engine on a large corpus, as well as via techniques similar to co-training.