ICLS 2000 Proceedings


The Use of Artificial Neural Nets (ANN) to Help Evaluate Student Problem Solving Strategies

Terry Vendlinski & Ron Stevens
5601 W. Slauson Avenue #255
Cluver City, CA 90230
Tel: 310-649-6568, Fax: 310-649-6591
Email: vendlins@mit.edu, immex_ron@hotmail.com

Abstract: This paper describes a technique for developing and analyzing detailed models of complex student problem solving, and methods to measure the reliability and validity of these models. Specifically, we use the Interactive Multi-media Exercises (IMMEX) system to record the specific steps students use to solve open-ended problems. While IMMEX has been used in numerous academic disciplines, the research documented in this paper relies on biology and chemistry students. We analyze thousands of such performances using artificial neural networks as a data-clustering tool that aggregates student performances without a priori knowledge of those performances and without the limitations imposed by comparing these performances to "experts." The resulting clusters serve as a rich source of assessment information, and can provide students and educators with the meaningful practical feedback necessary to improve learning. Finally, we analyze these clusters and explore the data features that influence the reliability and usefulness of such a tool.

Keywords: assessment, science education, artificial intelligence, meta-cognition


Preferred Citation Format:
Vendlinski, T., & Stevens, R. (2000).The Use of Artificial Neural Nets (ANN) to Help Evaluate Student Problem Solving Strategies. In B. Fishman & S. O'Connor-Divelbiss (Eds.), Proceedings of the Fourth International Conference of the Learning Sciences (pp. 108-114). Mahwah, NJ: Erlbaum.

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