Clustering students to help evaluate learning

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Abstract

In this paper we show how clustering techniques can be applied to student answers generated from a web-based tutoring tool. In particular we are interested in extracting clusters of students based on the mistakes they made using the tool, with the aim of obtaining pedagogically relevant information and providing this feedback to the teacher. The data we used comes from the Logic-ITA, a webbased tutoring tool to practice formal proofs currently in use in the School of Information Technologies at the University of Sydney. © 2005 by International Federation for Information Processing.

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APA

Merceron, A., & Yacef, K. (2005). Clustering students to help evaluate learning. In IFIP Advances in Information and Communication Technology (Vol. 171, pp. 31–42). Springer New York LLC. https://doi.org/10.1007/0-387-24047-0_3

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