Luo Si and Yan Ping Xin, Purdue University

Mathematics is integral to all areas of daily life. However, assessments conducted at state, national, and international levels over the past 30 years indicate that U.S. students are “notably deficient” in their ability to solve mathematical problems [National Research Council, 2001].

Differentiated instruction plays a critical role in today’s inclusive classrooms to meet the diverse needs of individual students.

The proposed research will utilize cutting-edge computer science techniques to construct an exploratory but fully functioning differentiated instructional system of mathematical word problem solving with the following functionalities.

1. The system maintains a pool of instructional materials generated by pre-defined templates or shared from students/teachers; features such as readability and the noise level of irrelevant information will be automatically extracted from instructional materials by proposed statistical natural language processing techniques.
2. The system provides computer-assisted instruction to train students’ abilities for analyzing and solving mathematical word problems.
3. It enables formative evaluation to monitor students’ progress.
4. The system provides the recommendation of differentiated instructional materials for a specific student by utilizing a student performance-driven recommendation algorithm.
   

This project is supported by National Science Foundation and Purdue University.