Date of Award

6-10-2024

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Applied Science

First Advisor

Mark Baillie

Abstract

Multiple national calls centered on critical thinking and social justice have been made to improve and reform higher education in science, technology, engineering, and mathematics (STEM) courses to increase the representation of students from marginalized groups in the STEM workforce and equip all students for success. To help answer this call, our project has two overarching goals: 1) Identify pathways to increase student success in STEM courses at a moderately selective metropolitan institution with a diverse population that can be generalized to similar institutions, and 2) determine how instructional practices influence perceptions of the learning environment, especially for marginalized students. Grounded in a Social Cognitive Theory framework, this work uses structural equation modeling (SEM) to identify how student perceptions of the instructor mindset influence their affect (student mindset, sense of belonging) and how that, in turn, impacts their performance in STEM courses. The lens of diversity, equity, and inclusion (DEI) was used to determine how these pathways are moderated by demographic factors (race, gender, age, generational status). Additionally, we uncover how instructional practices shape student perceptions of faculty mindset based on student and instructor demographic characteristics. Lastly, we will present tailored recommendations based on our findings to improve student success at institutions that serve a demographically diverse student population with varying levels of prior preparation.

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