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Abstract Title: Predicting the outcome of instruction: Examples with the contingency model of causal learning
Abstract: When teaching physics, instructors often use examples to illustrate concepts and to demonstrate the robustness of physical principles. The choice of particular examples is often left to intuition and instructional experience.  In this study, a more theoretical route to example choice is explored using concepts related to projectile motion and the balance-scale.  The contingency model is a computational model that proposes that certain patterns in the co-occurrence of two events can result in the learning of a causal association between the events. Our results demonstrate that different types of examples affect student answers in ways that are mostly consistent with the predictions made by the contingency model. Additionally, when asked to produce a physical "rule" to explain their answers, the students' self-reported rules were consistent with contingency model predictions. These responses, however, did indicate that examples alone were insufficient to teach complex functional relationships between physical dimensions, such as torque.
Abstract Type: Contributed Poster

Author/Organizer Information

Primary Contact: Thomas M. Scaife
University of Wisconsin - Platteville
One University Plaza
Platteville, WI 53818
Co-Author(s)
and Co-Presenter(s)
Andrew F. Heckler - The Ohio State University