Investigating Blended Math-Science Sensemaking with a diverse undergraduate population

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 relationship describing their observations without engaging in a type of MSS focused on quantitative pattern identification. Unlike students from dominant backgrounds, diverse students leverage lower level MSS to develop the formula for the phenomenon. Further, diverse students use PhET simulations to make sense of the phenomenon more and are more successful in using the simulations to find the correct mathematical relationship compared to students from dominant backgrounds. Math preparation has a stronger effect at level 1 compared to levels 2 and 3 of the framework. The framework can guide the development of instructional and assessment strategies to support students from diverse backgrounds in building MSS skills. Further, PhET simulations provide a suitable and effective learning environment for supporting engagement in and learning of MSS skills, and their capabilities should be leveraged for designing learning experiences in the future.