Experimental Analysis of the Q-Matrix Method in Automated Knowledge Assessment

T.M. Barnes, D.L. Bitzer, and M.A. Vouk (USA)


Automated knowledge assessment, student modeling, remediation


An efficient and fault-tolerant method for modeling student learning is an essential component in computer assisted teaching and learning. The q-matrix method is a fault tolerant teaching tool that uses machine learning techniques to automatically assess and correct student knowledge. This method creates a concept model of an instructional topic, based solely on student responses to tutorial questions, and uses this model to evaluate and redirect student learning. We describe the q-matrix method and present an experiment to verify that the method can effectively predict which concepts need further review, and may identify areas of concern better than students do on their own.

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