Broadening Participation Research: Investigating the Role of Psychosocial Factors on Students Taking Gatekeeper Courses in STEM

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The project investigates the psychosocial factors that influence learning and performance for undergraduate students taking introductory science and mathematics courses at North Carolina Central University. The project extends prior research where the investigator found that among the factors measured on a learning motivation and strategies questionnaire, the students’ expressed self-efficacy was found to be the strongest predictor of course performance, and was the singular predictor when controlling for prior achievement. The current study will use a generalized latent subgroup approach to allow for a finer-grained analysis that could detail relationships or interactions that might be missed otherwise. The project illustrates the possibilities a generalized latent subgroup perspective yields for addressing the complexity and heterogeneity of broadening participation STEM education research.The research explores the intersection of the multiple dimensions of a generalized population, characterized by socioeconomic status, environmental and situational factors, personal and social identities, and motivational states of students, and corresponding relationships with behavioral and academic outcome variables associated with them taking gatekeeper STEM courses. The study will examine four research questions: (1) What generalized latent subgroups are determined from background characteristics, motivational, and psychological variables?, (2) Do background characteristics, motivational, and psychological variables interact to influence learning behavior in STEM courses?, (3) To what extent does the psychosocial and behavioral factors associated with learning determine academic outcomes, such as pass rates and retention in STEM courses? And (4) What differential effects are reflected on learning behaviors and academic outcomes in STEM courses from generalized subgroups? Survey data will be collected from students in introductory STEM courses and analyzed using Latent Class Analysis as a methodological approach. The research results can contribute to more effective interventions to improve retention of underrepresented groups in STEM.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.