Mining Student Data Captured from a Web-Based Tutoring Tool: Initial Exploration and Results

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Merceron, A. & Yacef, K. (2004). Mining Student Data Captured from a Web-Based Tutoring Tool: Initial Exploration and Results. Journal of Interactive Learning Research, 15(4), 319-346. Norfolk, VA: AACE.
Retrieved from http://www.editlib.org/p/6569.

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Journal Information

Journal of Interactive Learning Research
ISSN 1093-023X
Volume 15, Issue 4, October 2004
Association for the Advancement of Computing in Education (AACE)  Norfolk, VA

More Information on JILR

Authors

Agathe Merceron, ESILV - Pôle Universitaire Léonard de Vinci, France; Kalina Yacef, University of Sydney, Australia

Abstract

In this article we describe the initial investigations that we have conducted on student data collected from a web-based tutoring tool. We have used some data mining techniques such as association rule and symbolic data analysis, as well as traditional SQL queries to gain further insight on the students' learning and deduce information to improve teaching. In our work, applying data mining facilities serves two purposes: (a) understand better both how students grasp the tool and assimilate the knowledge they need to learn and (b) get pedagogically relevant information that may influence or help improve teaching.

Keywords

• Students

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