Automated Error Analysis through Parsing Mathematical Expressions in Adaptive Online Learning
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Livne, N., Livne, O. & Wight, C. (2006). Automated Error Analysis through Parsing Mathematical Expressions in Adaptive Online Learning. In T. Reeves & S. Yamashita (Eds.), Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2006 (pp. 1321-1325). Chesapeake, VA: AACE.
Retrieved from http://www.editlib.org/p/23892.
World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (ELEARN) 2006
Honolulu, Hawaii, USA
Thomas Reeves & Shirley Yamashita
More Information on ELEARN
Table of Contents
A novel mathematical expression parser is presented as the core of a free, unlimited-use online adaptive learning system for improving student college readiness. In addition to standard expression matching, the parser is capable of comparing the student's response with a reference string (the correct answer) provided by instructors. It evaluates whether they are mathematically equivalent using a fast numerical approach rather than a complicated symbolic computer algebra logic, and classifies expression elements to correct, wrong, unrecognized, missing and redundant. The accuracy of our parsing algorithm has been demonstrated on real-world examples from an introductory college calculus course.
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