Linda R. Kauffman

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Intelligent tutoring systems that utilize Bayesian Knowledge Tracing have achieved the ability to accurately predict student performance not only within the intelligent tutoring system, but on paper post-tests outside of the system. Recent work has suggested that contextual estimation of student guessing and slipping leads to better prediction within the(More)
This study examines the impact of integrating worked examples into a Cognitive Tutor for genetics problem solving, and whether a genetics process modeling task can help prepare students for explaining worked examples and solving problems. Students participated in one of four conditions in which they engaged in either: (1) process modeling followed by(More)
This paper describes two types of Conceptually Grounded Learning Activities designed to foster more robust learning in the Genetics Cognitive Tutor: interleaved worked examples and genetic-process reasoning scaffolds. We report three empirical studies that evaluate the impact of these learning activities on three diverse genetics problem-solving topics in(More)
In this paper, we examine the impact of three learning activities designed to foster more robust learning in a Genetics Cognitive Tutor module on pedigree analysis problem solving, in an experimental study. The three activities are (1) interleaved worked examples with student explanations; (2) enhanced feedback with tutor-provided explanations of problem(More)
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