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Mixed results from a multiple regression analysis of supplemental instruction courses in introductory physics.

ABSTRACT: Providing less prepared students with supplemental instruction (SI) in introductory STEM courses has long been used as a model in math, chemistry, and biology education to improve student performance, but this model has received little attention in physics education research. We analyzed the course performance of students enrolled in SI courses for introductory mechanics and electricity and magnetism (E&M) at Stanford University compared with those not enrolled in the SI courses over a two-year period. We calculated the benefit of the SI course using multiple linear regression to control for students' level of high school physics and math preparation. We found that the SI course had a significant positive effect on student performance in E&M, but that an SI course with a nearly identical format had no effect on student performance in mechanics. We explored several different potential explanations for why this might be the case and were unable to find any that could explain this difference. This suggests that there are complexities in the design of SI courses that are not fully understood or captured by existing theories as to how they work.

SUBMITTER: Burkholder E

PROVIDER: S-EPMC8016292 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Modeling Instruction (MI) for University Physics is a curricular and pedagogical approach to active learning in introductory physics. A basic tenet of science is that it is a model-driven endeavor that involves building models, then validating, deploying, and ultimately revising them in an iterative fashion. MI was developed to provide students a facsimile in the university classroom of this foundational scientific practice. As a curriculum, MI employs conceptual scientific models as the basis for the course content, and thus learning in a MI classroom involves students appropriating scientific models for their own use. Over the last 10 years, substantial evidence has accumulated supporting MI's efficacy, including gains in conceptual understanding, odds of success, attitudes toward learning, self-efficacy, and social networks centered around physics learning. However, we still do not fully understand the mechanisms of how students learn physics and develop mental models of physical phenomena. Herein, we explore the hypothesis that the MI curriculum and pedagogy promotes student engagement via conceptual model building. This emphasis on conceptual model building, in turn, leads to improved knowledge organization and problem solving abilities that manifest as quantifiable functional brain changes that can be assessed with functional magnetic resonance imaging (fMRI). We conducted a neuroeducation study wherein students completed a physics reasoning task while undergoing fMRI scanning before (pre) and after (post) completing a MI introductory physics course. Preliminary results indicated that performance of the physics reasoning task was linked with increased brain activity notably in lateral prefrontal and parietal cortices that previously have been associated with attention, working memory, and problem solving, and are collectively referred to as the central executive network. Critically, assessment of changes in brain activity during the physics reasoning task from pre- vs. post-instruction identified increased activity after the course notably in the posterior cingulate cortex (a brain region previously linked with episodic memory and self-referential thought) and in the frontal poles (regions linked with learning). These preliminary outcomes highlight brain regions linked with physics reasoning and, critically, suggest that brain activity during physics reasoning is modifiable by thoughtfully designed curriculum and pedagogy.

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Mixed results from a multiple regression analysis of supplemental instruction courses in introductory physics.

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