2018 BFY III Abstract Detail Page

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Abstract Title: Challenges with proposing causes for unexpected experimental results
Abstract: Models are representations used to explain and predict experimental results and observations. When students encounter discrepancies between the actual versus expected behavior of a system, they revise their models to include the newly acquired observations, or change their apparatus. The Modeling Framework For Experimental Physics (Modeling Framework) describes the iterative process of matching measurements and observations to models, and the process of making revisions to undertake to resolve discrepancies. We used the Modeling Framework to develop and code think-aloud problem-solving interviews centered on troubleshooting an inverting amplifying circuit out of its operation limits. We observed that a few of our participants will iteratively and continuously conduct diagnostic measurements and revisions if they are unable to immediately propose a cause for an observed discrepancy. In this paper, we discuss two episodes where students undergo this process to converge on a proposed cause. One student converges on a phenomenological description of the observed behavior, while the other reasons incorrectly even while revising their model adequately. We conclude by discussing implications for a modeling assessment.
Abstract Type: Poster

Author/Organizer Information

Primary Contact: Laura RĂ­os
CU Boulder/JILA
Duane Physics, E1B32
2000 Colorado Avenue
Boulder, CO 80309
and Co-Presenter(s)
Benjamin Pollard, Dimitri R. Dounas-Frazer, H.J. Lewandowski
all affiliated with CU Boulder/JILA