2024 ASEE Annual Conference & Exposition

We present preliminary results from a scientific research study conducted at Texas A&M International University (TAMIU); a Hispanic-Serving Institution located along the U.S-Mexico border. Our study focuses on generating knowledge about learning strategies that improve and enhance undergraduate STEM education. As such, our study has both a programmatic and a research component. Through our project's programmatic component, we aim at increasing the quantity and improving the quality of retained and graduated TAMIU STEM-students. We do this by engaging 3 consecutive cohorts (one cohort per year) of students in a 4-semester pre-/early-college (i.e., pre-college summer; and freshman fall/spring/summer semesters) curriculum-based STEM-enrichment program called USTEM. Through USTEM, we implement high-impact and proven STEM-enrichment activities, practices, and strategies published in the STEM-education literature. Through our project’s research component, we examine how a set of creative video projects (CVPs) that we designed influences students’ psychosocial, scholastic, and persistence outcomes.

Casted as a longitudinal RCT-type experiment in generalized randomized block design (GRBD; with cohorts as complete blocks and students serving as replications within complete blocks), we randomly assign half of each cohort to participate in USTEM without CVPs (USTEM1); the other half of each cohort to participate in USTEM with CVPs (USTEM2). USTEM2 participants produced four CVPs in the form of: 1) a biography of a STEM scientist, 2) a position statement on a STEM controversy, 3) a tutorial on a STEM technique, and 4) a methodological critique of a STEM peer-reviewed research article. Outcomes were measured every end-of-semester.

The longitudinal data set generated allows us to compare and evaluate the efficacy of USTEM1 versus USTEM2, and to parametrically characterize trends across semesters; and to assess and evaluate USTEM as a STEM-enrichment program methodically and statistically. We performinferential analyses using SAS 9.4 (e.g., PROC MIXED) and SPSS 29 Premium Version (Generalized Linear Models). In consideration of the level of measurement and the empirical distribution of outcomes, and our objectives, the analytical techniques we use are in the form of analysis of variance, generalized linear models using normal (for scores) and logistic (for binary outcomes; e.g., graduated or not) link functions, and longitudinal analysis with trend analysis.

The intellectual merit of our research derives from our use of: 1) RCT-design, blocking and replication techniques, and GRBD-structured randomization to enhance internal validity and minimize extraneous variation; 2) longitudinal analytical techniques to examine trends in outcomes; and 3) empirically-validated and target-population-calibrated instruments to ensure the measurement reliability, reproducibility, and validity of the measures and indicators we use. Our research results and products advance a fundamental understanding of how STEM-oriented CVPs influence psychosocial outcomes and ultimately, persistence in STEM.