Open Access
November 2013 Theory of self-learning $Q$-matrix
Jingchen Liu, Gongjun Xu, Zhiliang Ying
Bernoulli 19(5A): 1790-1817 (November 2013). DOI: 10.3150/12-BEJ430


Cognitive assessment is a growing area in psychological and educational measurement, where tests are given to assess mastery/deficiency of attributes or skills. A key issue is the correct identification of attributes associated with items in a test. In this paper, we set up a mathematical framework under which theoretical properties may be discussed. We establish sufficient conditions to ensure that the attributes required by each item are learnable from the data.


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Jingchen Liu. Gongjun Xu. Zhiliang Ying. "Theory of self-learning $Q$-matrix." Bernoulli 19 (5A) 1790 - 1817, November 2013.


Published: November 2013
First available in Project Euclid: 5 November 2013

zbMATH: 1294.68118
MathSciNet: MR3129034
Digital Object Identifier: 10.3150/12-BEJ430

Keywords: $Q$-matrix , classification model , cognitive assessment , consistency , diagnostic , self-learning

Rights: Copyright © 2013 Bernoulli Society for Mathematical Statistics and Probability

Vol.19 • No. 5A • November 2013
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