Abstract
A particular challenge in the domain of student diagnosis concerns how to ‘recognize’ and ‘remediate’ student errors. Machine learning techniques have been successfully applied to identify categories of errors and then to discriminate a new error in order to provide feedback to the student. However, remediation very often requires interpreting student errors in terms of knowledge in the context of a specific learning situation. This work is mainly concerned with this problem area. In this sense, we present here an approach to student diagnosis founded on a cognitive framework, called Conception Model, developed in the domain of educational research. The main issue about the Conception Model is the fact that it allows representing student errors in terms of knowledge applied to a learning context. We describe the main aspects of the student diagnosis system we have implemented, and then we evaluate the diagnosis results by comparing them to human diagnoses.
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Webber, C. (2004). From Errors to Conceptions – An approach to Student Diagnosis. In: Lester, J.C., Vicari, R.M., Paraguaçu, F. (eds) Intelligent Tutoring Systems. ITS 2004. Lecture Notes in Computer Science, vol 3220. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30139-4_67
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DOI: https://doi.org/10.1007/978-3-540-30139-4_67
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22948-3
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