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1. STEM Bridge Program Participation Predicts First- and Second-Semester Math Performance

   https://doi.org/10.18260/1-2--32296  

   Bradford, Brittany ; Beier, Margaret ; Wolf, Michael ; McSpedon, Megan ; Taylor, Matthew ( July 2019 , American Society for Engineering Education)

   To combat math underperformance among incoming STEM majors, Rice University designed a summer bridge program with National Science Foundation (NSF) S-STEM funding that included an intensive calculus course. Students invited to participate in the program were identified as being underprepared for STEM classes based on their standardized test scores, high school STEM coursework, and socioeconomic status. One of the program’s goals is to improve students’ preparation for the advanced math courses required for all STEM majors at Rice. The bridge program is designed to teach the material that has historically been most challenging for underprepared students, meaning the math content covered primarily second-semester calculus topics. We explored the impact of bridge program participation on math performance in first and second-semester math. First, we examined group differences in math preparation. Though program administrators attempt to create equivalent bridge and comparison groups, the bridge program is optional, meaning group assignment is not completely random. Bridge students were less prepared than comparison students on number of high school calculus AP (or equivalent) credits received. We analyzed group differences in final class grades from 2012-2017 among the comparison group, the bridge group, and the rest of the class (i.e. non-comparison and nonbridge), standardizing grades using Z-scores. Planned contrasts found that bridge students performed slightly better than, but not significantly different from, comparison students in first semester math. Conversely, planned contrasts found that the bridge group significantly outperformed the comparison group in second-semester math. These results suggest that bridge program exposure to calculus may improve performance relative to a comparison group, which is especially noteworthy because bridge students are the least math-prepared STEM students entering the university. Future research will analyze outcomes in more advanced math classes. We will use these findings to refine the bridge program’s approach to teaching students how to succeed at collegiate-level math classes and, ultimately, as STEM majors at Rice. 

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2. Promoting Success Through Building Community for Computer Science and Computer Engineering Undergraduates

   Harris, S. L. ; Jiang, Y. ; Clark, C. ; Jorgensen, E. ; Garza, T. ; Marrun, N. A. ; & Taylor, V. L. ( June 2023 , ASEE Annual Conference proceedings)

   Building on prior studies that show a sense of belonging and community bolster student success, we developed a pilot program for computer engineering (CpE) and computer science (CS) undergraduates and their families that focused on building a sense of belonging and community supported by co-curricular and socioeconomic scaffolding. As a dually designated Hispanic-Serving Institution (HSI) and Asian American and Native American Pacific Islander-Serving Institution (AANAPISI) – two types of federally designated Minority-Serving Institutions (MSI) – with 55% of our undergraduates being first-generation students, we aimed to demonstrate the importance of these principles for underrepresented and first-generation students. Using a student cohort model (for each incoming group of students) and also providing supports to build community across cohorts as well as including students’ families in their college experiences, our program aimed to increase student satisfaction and academic success. We recruited two cohorts of nine incoming students each across two years, 2019 and 2020; 69% of participants were from underrepresented racial or minority groups and 33% were women. Each participant was awarded an annual scholarship and given co-curricular support including peer and faculty mentoring, a dedicated cohort space for studying and gathering, monthly co-curricular activities, enhanced tutoring, and summer bridge and orientation programs. Students’ families were also included in the orientation and semi-annual meetings. The program has resulted in students exceeding the retention rates of their comparison groups, which were undergraduates majoring in CpE and CS who entered college in the same semester as the cohorts; first- and second-year retention rates for participants were 83% (compared to 72%) and 67% (compared to 57%). The GPAs of participants were 0.35 points higher on average than the comparison group and, most notably, participants completed 50% more credits than their comparison groups, on average. In addition, 9 of the 18 scholars (all of the students who wanted to participate) engaged in summer research or internships. In combination, the cohort building, inclusion of families, financial literacy education and support, and formal and informal peer and faculty mentoring have correlated with increased academic success. The cohorts are finishing their programs in Spring 2023 and Spring 2024, but data up to this point already show increases in GPA, course completion, and retention and graduation rates, with three students having already graduated early, within three and a half years. The findings from this study are now being used to expand the successful parts of the program and inform university initiatives, with the PI serving on campus-wide STEM pipeline committee aiming to recruit, retain, and support more STEM students at the institution. 

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3. Building Capacity: Enhancing Undergraduate STEM Education by Improving Transfer Success

   Brown, P. ( August 2022 , 2022 ASEE Annual Conference & Exposition, Minneapolis, MN)

   A combination of strategies was implemented to reduce barriers to transfer from associate to baccalaureate programs, and baccalaureate degree completion. These strategies include creation of the STEM Transfer Collaborative (STC). an adaption of the CUNY Pathways articulation initiative. Components of the STC include articulation agreements, shared professional development to align pedagogy and curriculum, outreach and collaboration by both the sending and receiving college faculty to begin transfer preparation and support before transfer occurs, and regular updates to community college faculty on the success of their transfer students. The second strategy employed is Momentum to the Baccalaureate (MB), an adaption of the CUNY Accelerated Study in Associate Programs (ASAP). MB provides support for junior and senior-level transfer students who are either community colleges associate degree graduates (external transfer) or associate degree graduates who transferred to bachelor’s programs at the same comprehensive college they earned their associate degree at, which has a 2+2 degree structure (internal transfer). Components of MB include personalized mentoring, advisement, and monthly stipends to students who maintain full-time enrollment and good academic standing. Participating majors include computer engineering technology, computer systems technology, construction management and civil engineering technology, electrical engineering technology, and applied chemistry. Propensity matching was used to evaluate the effectiveness of these strategies. Participating campuses are part of the City University of New York (CUNY), and include six community colleges (Borough of Manhattan Community College, Bronx Community College, Guttman Community College, Hostos Community College, Kingsborough Community College, and LaGuardia Community College), five of which are Hispanic Serving Institutions (HSIs), and New York City College of Technology (City Tech), also an HSI, which offers associate and bachelor’s programs (2+2 structure). Our first cohort of 40 students started upper-level studies in fall 2019, and has completed 2 years (four semesters) of post-associate degree study. The second cohort of 40 students, started in fall 2020, and has completed one year (two semesters) of post-associate degree study. Cohort 1 students receiving MB, supports had a significantly higher graduation rate after two years than the college average. Additionally, for cohort 1, the STC seems to have reduced “transfer shock,” the typical drop in GPA the first semester after transfer. There was no statistical difference in GPA, credits completed and semester-to-semester persistence of internal and external transfers in the MB program. Cohort 1 external transfer students who received support though MB also had a statistically significant improvement in their semester GPAs for their first 3 semesters at City Tech compared to matched students who were not provided support in the junior and senior years. There was no statistically significant difference by the 4th semester. Cohort 2 internal transfers receiving MB supports in their junior year had a statistically significant improvement in credits earned and persistence compared to a matched cohort without MB supports. There was no statistically significant improvement of external transfers compared to a matched cohort, who did not receive MB supports The inability of external transfer students to come to campus due to the pandemic, may have negated the sense of community and belonging that MB was intended to create. Overall, these preliminary results suggest that targeted pre-transfer and post-transfer supports improve transfer student outcomes. This project (NSF grant #1832457) was funded through the NSF Division of Education, Improving Undergraduate STEM Education: Hispanic-Serving Institutions Program. 

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4. Examining STEM Diagnostic Exam Scores and Self-efficacy as Predictors of Three-year STEM Psychological and Career Outcomes

   https://doi.org/10.18260/1-2--34614  

   Bradford, Brittany ; Beier, Margaret ; McSpedon, Megan ; Wolf, Michael ( June 2020 , American Society for Engineering Education)

   In this research-based paper, we explore the relationships among Rice University STEM students’ high school preparation, psychological characteristics, and career aspirations. Although greater high school preparation in STEM coursework predicts higher STEM retention and performance in college [1], objective academic preparation and college performance do not fully explain STEM retention decisions, and the students who leave STEM are often not the lowest performing students [2]. Certain psychosocial experiences may also influence students’ STEM decisions. We explored the predictive validity of 1) a STEM diagnostic exam as an objective measure of high school science and math preparation and 2) self-efficacy as a psychological measure on long-term (three years later) STEM career aspirations and STEM identity of underprepared Rice STEM students. University administrators use diagnostic exam scores (along with other evidence of high school underpreparation) to identify students who might benefit from additional support. Using linear regression to explore the link between diagnostic exam scores and self-efficacy, exam scores predicted self-efficacy a semester after students’ first semester in college; exam scores were also marginally correlated with self-efficacy three years later. Early STEM career aspirations predicted later career aspirations, accounting for 21.3% of the variance of career outcome expectations three years later (β=.462, p=.006). Scores on the math diagnostic exam accounted for an additional 10.1% of the variance in students’ three-year STEM career aspirations (p=.041). Self-efficacy after students’ first semester did not predict future STEM aspirations. Early STEM identity explained 28.8% of the variance in three-year STEM identity (p=.001). Math diagnostic exam scores accounted for only marginal incremental variance after STEM identity, and self-efficacy after students’ first semester did not predict three-year STEM aspirations. Overall, we found that the diagnostic exam provided incremental predictive validity in STEM career aspirations after students’ sixth semester of college, indicating that early STEM preparation has long-lasting ramifications for students’ STEM career intentions. Our next steps include examining whether students’ diagnostic exam scores predict STEM graduation rates and final GPAs for science and math versus engineering majors. 

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5. GPA Patterns of Black Mechanical Engineering Students

   Manning, Jessica ; Mobley, Catherine ; Orr, Marisa ; Brawner, Catherine ; Brent, Rebecca ; Tidwell, Michael L. ( August 2022 , Proceedings of the 2022 Annual Conference of the American Society for Engineering Education. https://peer.asee.org/41089)

   In recent years, research has associated grade point average (GPA) with a variety of student outcomes during their undergraduate careers. The studies link higher GPAs to students being more likely to graduate in their major, while lower GPAs have been linked to students switching majors or leaving the institution. Further research, which focuses on how Black female and male students remain successful in different engineering degrees, is necessary to identify the underlying elements contributing to their entrance into and exit from engineering disciplines. This quantitative examination of trends among the GPAs of Black women and men is part of a larger NSF-funded mixed-methods study that includes in-depth student interviews of Black students who persisted in and switched from ME. In this quantitative paper, we examine the GPA patterns of Black students in Mechanical Engineering (ME). Students who have ever enrolled in ME have four potential, mutually exclusive, outcomes: 1) they can persist for 12 semesters without graduating; 2) they can graduate in ME within 12 semesters; 3) they can switch to another major; or 4) they can leave school. In this research, we identify the most common GPA patterns associated with graduated ME students. We hypothesize a relationship between distinct GPA patterns and whether a student persists in ME, graduates in ME, switches away from ME, or leaves the institution altogether. This quantitative investigation uses the Multiple-Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD) to collect the cumulative GPA of ME students at each term. We use a functional cluster analysis approach to group similar patterns. First, a function is fit to each student record. Then a cluster analysis is conducted on the function parameters to identify natural groupings in the data. Once students are grouped according to their GPA profile, we examine the other characteristics and outcomes of the group. We present a visual quantitative analysis of the patterns in the GPAs of Black women and men who enroll in ME. Clustering analysis suggests that first-time-in-college (FTIC) Black female students in ME who graduated have a higher proportion of students in the higher GPA clusters than the proportion of FTIC Black male students who graduated in ME. A higher proportion of the male student population is clustered in the lower GPA cluster groups as compared to women in the lower GPA cluster groups. A higher proportion of students who graduated are in the higher GPA clusters than the proportion of graduated students in the lower GPA clusters. 

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