By Kimberly R. Schneider, Uday Nair, Rachel Straney, Patrice Lancey, and Mary Tripp
Close to one-third of students entering United States universities will leave after their first year, regardless of academic discipline, and the average five-year graduation rates for students attending four-year institutions is 52% throughout the United States (ACT, 2018; Tinto, 1993). For Hispanic and African American students, the five-year graduation rates are even lower, at 35% and 45%, respectively (Brower, 1992; Tinto,1993). While underrepresented minorities make up 33% of the population of the United States in 2017, underrepresented minority students earn only 21.6% of the science and engineering bachelor’s degrees. This trend remains consistent across most minority groups (NSF, 2015). While the number of underrepresented minority students who earn science and engineering degrees has steadily increased over the past two decades (NSF, 2019), additional work needs to be done to retain these students and usher them to graduation in these majors. To address this national need, institutions of higher education need effective and innovative programs to increase STEM retention and graduation rates.
Lowering the barriers for STEM student success toward graduation remains a challenge. Students leave STEM majors for various reasons such as the classroom climate, lack of mentoring, and general discrimination on university campuses (reviewed in Fouad & Byars-Winston, 2005; Estrada et al., 2016). A wide variety of interventions have been shown to increase retention for students. Supportive environments such as living-learning communities where students live and take classes together and receive mentoring from staff and faculty, have been shown to increase retention and improve the university experience for countless students including those in STEM disciplines (Estrada et al., 2016; Lane, 2016; Stassen, 2003; Tinto, 2007). These supportive environments seem particularly effective for underrepresented minorities and students hoping to matriculate into STEM graduate programs (Estrada et al., 2016; Lane, 2016; Myers & Pavel, 2011).
The Learning Environment and Academic Research Network (LEARN) model was developed in 2011 at the University of Central Florida (UCF) to lower the barriers to student success in STEM. The goals of the program were to (1) recruit, retain, and graduate underrepresented students; (2) provide an early research experience; and (3) pipeline students into other undergraduate research programs. The LEARN program combines a living-learning community with mentored undergraduate research experiences. Creating these types of programs can take substantial effort and results of these programs take significant time to generate. In 2015, we reported in this journal the planning and implementation of this STEM learning community (Schneider et al., 2015). In this current report, we share data collected from another five years as we have continued to monitor the program.
LEARN accepts 28 First Time in College Students (FTIC) students annually, providing them with an opportunity to live together in a learning community, take coursework together, and work as apprentices in research laboratories. The required courses are Introduction to Research I (fall) and Introduction to Research II (spring), developed specifically to meet the goals established for the program. What makes the LEARN program unique is the type of research mentorship available to the students through an apprenticeship model. In the program, students are matched with a graduate student mentor in the same or related academic discipline and conduct and are exposed to research for three hours a week over a 12-week period (see Schneider et al., 2015 and Schneider & Bickel, 2015). Additionally, students are paired with an upperclass peer mentor who has completed the LEARN program.
LEARN does not target the highest achieving students at UCF; instead, the program focuses on High-Impact Educational Practices (HIPs) for underserved students. The average SAT scores for LEARN students closely match the average scores of the incoming (FTIC) UCF population. For example, in the fall of 2018 the UCF incoming class had an average SAT score of 1328 and high school GPA of 4.12 (weighted). The fall 2018 LEARN cohort had an average SAT score of 1267, and high school GPA of 4.12 (weighted).
The goal of the LEARN Program is to recruit admitted students who have not had the opportunity to benefit from other academic programs (e.g., honors program). Results from the first three cohorts demonstrated early signs of success, including but not limited to, increased year-to-year retention, improved GPA, and documented critical-thinking gains (Schneider et al., 2015). Over the last five years, assessment data have shown the continued known benefits of this program while highlighting some new areas to strengthen. Here we review data on graduation rates, movement into other HIPs, and overall student success.
There have been 231 LEARN participants total over eight cohorts (between 2011–12, cohort 1, and 2018–19, cohort 8). A little over half (51%, n = 117) of LEARN participants were female students, compared to only 36% of all FTIC students in STEM majors. About 25% of LEARN participants were Black/African American (n = 57) and 32% were Hispanic/Latino (n = 74) compared to 9% Black/African American and 25% Hispanic/Latino for all FTIC students in STEM majors. Taken together, over half of our participants usually are from underrepresented minority populations, evidence that the LEARN program has successfully recruited students from these populations. Representation of students from first-generation and underrepresented populations are typically 10% to 20% higher than the applicant pool and the university population.
Each year, a systematic process was undertaken to create a comparison group (a working ‘control’ group). This work follows best practices typically employed to identify a comparison group (Fraenkel et al., 2012). Over the eight years, 802 students were identified as comparison group students for the 231 LEARN students. It should be noted that the LEARN comparison groups are similar to the LEARN cohorts on three characteristics: gender, ethnicity, and high school GPA (see Table 1). Each LEARN cohort was compared with the formal comparison group identified at the start of each fall term after enrollment was complete.
To identify the comparison group, specific variables were held constant and a stratified sample of students were identified based on select student characteristics (Fraenkel et al., 2012). A stratified sample was achieved by dividing the student population into different subgroups or strata, then randomly selecting within those strata to obtain a final sample that looks similar to the LEARN group. The comparison group was restricted to FTIC students who: (1) entered the university during the same academic year as their LEARN counterparts, (2) were STEM majors, and (3) had not participated in any other formal learning communities (i.e., honors college, leadership community). From this population of interest, approximately 100 comparison students were selected using the stratified sampling method (see Table 1).
The all-university STEM FTIC students for every entry year (see Table 1) comprises of three sub-groups: (a) LEARN group, (b) LEARN comparison group, and (c) nonLEARN FTIC STEM group. These three sub-groups were identified, tracked, and reported separately (see Tables 2 and 3). A test of proportions was done on these data sets between the LEARN cohorts and the comparison group. The test of proportions is a statistical test that employs proportions to assess whether two variables are associated.
We have continued to monitor the retention rates reviewed in our first paper and, after eight years, we are tracking trends in graduation rates, as well. The cohort, comparison, and non-LEARN students all started as STEM majors. Some students change majors to other STEM or non-STEM disciplines. Note that first-year retention and graduation outcomes are reported based on the students’ major at the point of retention or graduation, which could be either STEM or a non-STEM major.
First-year retention: As noted in Table 2, retention continues to be higher for our cohort than the selected comparison group and the university FTIC STEM population. First-year retention rates for LEARN participants were comparable to that of FTIC comparison group students, 90% and 88%, respectively. No statistical difference found in overall first-year retention rates for these two groups (p > 0.05). However, for students retained at the university, 84.1% of LEARN students remained in STEM compared to 76.1% of the comparison group students. For students who were retained at the university, retention in STEM is statistically higher for LEARN participants compared to the comparison group (p = .012). It should be noted that our institution already has strong first-year retention rates campuswide (see Table 2).
Graduation: Table 3a reviews the graduation data over eight years since the program began in 2011, showing a difference between the first four cohort years of LEARN and their respective comparison groups (Table 3a). Only four out of eight LEARN cohorts are included in this analysis since these are the only students who have had enough time to graduate (at least four years).
For the first four cohort years, 71.2% of LEARN students graduated compared to only 55.3% of the comparison groups. These differences are statistically different at a significance level of α = 0.05, with graduation rates of LEARN students being higher than that of a group of students with similar genders, ethnicities, and academic abilities (p = 0.001). Furthermore, of the students who graduated, LEARN students graduated in STEM disciplines at a statistically higher rate (68.4%) compared to their comparison group peers (56.8%; p = 0.036; Table 3a). Similar differences were also noted for female and under-represented minority students.
Though statistically significant differences were not found for female students, it should be noted that of the female students who graduated, female students in LEARN graduated in STEM disciplines at a higher rate (56.9%) compared to their comparison group peers (48.1%; Table 3b).
For underrepresented minority students who graduated, students in LEARN graduated in STEM disciplines at a statistically higher rate (70.2%) compared to their comparison group peers (57.3%; p = 0.0427; Table 3c). Underrepresented minority (URM) groups reported in Table 3c consists of Black/African-
American, Hispanic/Latino, Multi-racial, American Indian/Alaskan Native, and Hawaiian native/Pacific Islander students.
Thus, the graduation rates indicate the long-term success of this first-year program. Not only are LEARN students more likely to graduate, but they are also more likely to graduate with STEM degrees.
At UCF student involvement with undergraduate research is closely monitored (see Schneider et al., 2016) along with other HIPs through a centralized SAS database. The database allows us to track only documented undergraduate research experiences (e.g., paid experiences, credit programs) providing an opportunity to study the impact of early exposure through this program. LEARN participants and their comparison groups were tracked in undergraduate research and internships beyond the one-year program via this centralized database. We found that 30.1% of LEARN participants had documented involvement in undergraduate research post-LEARN. In our comparison group, only 9.4% were involved in research at some point during their undergraduate career. Thus, LEARN students were 3.2 times more likely than the comparison group students to participate in research post LEARN. We documented comparable participation in internships (8.7% compared to 8.9%), highlighting an area where we can provide increased opportunities for our students.
One outcome of early exposure to undergraduate research is an awareness of other available opportunities (e.g., paid summer programs, prestigious fellowships). Two reasons LEARN students apply for additional opportunities at UCF is that they are informed of these opportunities (i.e., general awareness), and students in good standing may receive a letter of recommendation from the program. At a large research institution, it can be difficult to secure letters from university officials early in an undergraduate career. During the academic year 2017–18, for example, the LEARN program provided 70 letters of recommendation to current or former LEARN participants. Even with database information, it is difficult to monitor all placements or successes (our database only tracks documented internal experiences); however, we are aware that students have moved into Ivy League summer programs and graduate programs. For example, LEARN students participated in paid summer research programs at a variety of competitive summer research programs, several immediately after their first year (e.g., Stanford University, NIH). LEARN students also pipelined into other programs at our university and have secured prestigious fellowships such as the Goldwater Scholarship and the National Science Foundation, Graduate Research Fellowship.
The LEARN program continues to refine the model each year to ensure the program meets the changing needs of students and program coordinators. As our 2015 paper highlights, challenges remain: (1) students leaving the program or the university; (2) significant variation in mentor quality for both peer mentor and graduate student mentors; and (3) maintaining university partnership with close stakeholders. With each cohort there is a percentage of students who leave the program. There are typically two reasons for this attrition: (1) students remain at the university but are not interested in the program; and (2) students leave the university due to poor academic performance, health-related issues, or transfer to another academic institution.
Our one-on-one peer mentoring system continues to remain a consistent strength. Using peer mentors who are LEARN alumni ensures that student leaders know the program and value their leadership opportunity. Additionally, we continue to strengthen our model of training the graduate research mentors, recruited each year from the graduate student population (Schneider & Bickel, 2015). For the most part, the graduate student mentors are strong mentors and good role models for our new researchers. However, we have received reports of graduate mentors who are not mentoring effectively. In response we have improved communication and started to work more closely with faculty to request nominations of their strongest graduate students who are most well suited to mentor undergraduate students.
With the success of LEARN at UCF, we have now adapted the program at two other universities, as new pilot programs, with federal support for our FTIC population (now F- LEARN). In addition, we are currently running a parallel program for transfer students to meet a growing need at institutions of higher education (T-LEARN). Through these collaborations we are learning how a successful model can be adapted to other student populations and other campuses. Additionally, a detailed review of the cost of running this wraparound program for first-year students should be developed and compared to other retention programs at the three institutions (and nationally).
Creating a comprehensive retention program that builds pipelines for student success requires critical resources. Here, we reviewed the benefits of a first-year formal research living-learning community. The gains reviewed are valuable to a wide variety of stakeholders, but the most important are the individual students who have moved forward to successful careers in medical school, graduate programs, and industry. Through careful planning this model can be expanded to all disciplines and to other student populations to increase the integration of undergraduate research for first-year students. ■
We acknowledge National Science Foundation for sponsorship of the program development (Grant #0941980 to K. R. Schneider and A. Morrison-Shetlar and #to K. R. Schneider and M. Aldarondo-Jeffries). The authors appreciate the continued support of our LEARN partner, UCF Housing and Residence Life. We also acknowledge Michael Aldarondo-Jeffries, Divya Bhati, Amy Bickel, Donna Chamely-Wiik, Shannon Colon, Evelyn Frazier, William Kwochka, Alison Daniel Meeroff, Morrison-Shetlar, Kathy Rovito, Colleen Smith, and Jesse Sunski for support of the program over the years.
Kimberly R. Schneider (KRS@ucf.edu) is the interim assistant vice provost and assistant dean in the Division of Student Learning and Academic Success, Uday Nair is the director of Operational Excellence and Assessment Support (OEAS), Rachel Straney is an applications programmer II with OEAS, Patrice Lancey serves as the assistant vice president of OEAS, and Mary Tripp is an instructional specialist in the Office of Undergraduate Research, all at the University of Central Florida in Orlando, Florida.
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