Investigating Blended Math-Science Sensemaking with a diverse undergraduate population
Leonora Kaldaras, Carl Wieman

TL;DR
This study validates a cognitive framework for mathematical sensemaking in science among diverse undergraduates, revealing differences in engagement patterns and highlighting the effectiveness of PhET simulations in supporting learning.
Contribution
It extends the MSS framework to diverse populations, identifying distinct engagement patterns and demonstrating the utility of simulations for inclusive science education.
Findings
Diverse students develop mathematical relationships without pattern-focused MSS.
Diverse students use lower-level MSS to derive formulas.
PhET simulations enhance understanding and engagement for diverse students.
Abstract
Blended mathematical sensemaking in science (MSS) involves deep conceptual understanding of quantitative relationships describing scientific phenomena. Previously we developed the cognitive framework describing proficiency in MSS across STEM disciplines and validated it with undergraduate students from dominant backgrounds (White, middle class) using assessment built around PhET simulations. In this study we investigate whether the framework can characterize engagement in MSS among undergraduate students from diverse backgrounds and identify potential differences between the two populations. The framework is effective in characterizing engagement in MSS by undergraduate students from diverse backgrounds and largely functions as a learning progression. We have also uncovered a distinct pattern of engagement in MSS reflected in students successfully developing the mathematical…
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Taxonomy
TopicsInnovative Teaching and Learning Methods · Online Learning and Analytics · Innovative Teaching Methods
