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Abstract Title: Computational Modeling as a Promoter of Cognitive Transfer: Pilot Study
Abstract: We describe a study of the role of computational modeling in recognizing underlying similarities in different problems, a process called cognitive transfer. Previous studies have shown that this crucial process is highly sensitive to context, suggestion, and familiarity with the subject matter. We propose that courses emphasizing computational modeling, in which students repeatedly employ similar lines of code to model different physical systems, foster a more generalized cognitive transfer ability. We performed a think-aloud study on several students (some from a course involving computational modeling, others from a traditional physics course), exposing them to ordered pairs of problems of varying degrees of separation in specific details (molecular mechanics vs. projectile motion) and solution methods (numerical vs. analytical). With these data, we attempt to separate the influence of long-term instruction in computational modeling from the immediate priming effect of solving computational problems, and relate both to the promotion of cognitive transfer.
Abstract Type: Contributed Poster Presentation

Author/Organizer Information

Primary Contact: Scott S Douglas
Georgia Institute of Technology
Co-Author(s)
and Co-Presenter(s)
Marcos D Caballero
University of Colorado at Boulder

Michael F Schatz
Georgia Institute of Technology