Rate of Learning Models, Mental Models, and Item Response Theory

Computer Science – Learning

Scientific paper

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Scientific paper

We present three learning models that make different assumptions about how the rate of a student's learning depends on the amount that they know already. These are motivated by the mental models of Tabula Rasa, Constructivist, and Tutoring theories. These models predict the postscore for a given prescore after a given period of instruction. Constructivist models show a close connection with Item Response Theory. Comparison with data from both Hake and MIT shows that the Tabula Rasa models not only fit incomparably better, but fit the MIT data within error across a wide range of pretest scores. We discuss the implications of this finding.

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