Attribute-mastery patterns from rule space as the basis for student models in algebra
✍ Scribed by Menucha Birenbaum; Anthony E. Kelly; Kikumi K. Tatsuoka; Yaffa Gutvirtz
- Book ID
- 102568225
- Publisher
- Elsevier Science
- Year
- 1994
- Tongue
- English
- Weight
- 407 KB
- Volume
- 40
- Category
- Article
- ISSN
- 1071-5819
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✦ Synopsis
Student models for procedural tasks in mathematics have relied heavily on analyses of bugs to guide their remediation. This paper reports on an analysis of data that first confirms the results of recent studies by finding a relatively large number of bugs to be unstable, with stable bugs tending to be infrequent. The paper then illustrates a method for classifying students according to higher-level (and presumably more stable) knowledge deficits using a psychometric classification technique, known as rule space. A rule space analysis is performed on the same test items. The resulting diagnoses (describing attribute-mastery patterns) are shown to demonstrate withintest stability. These patterns are then discussed in the light of their potential contribution to the design of machine-delivered remediation.