Understanding Who Stays in a STEM Scholar Program for Underrepresented Students: High-Achieving Scholars and Short-Term Program Retention

Abstract

This study highlights program retention among Science, Technology, Engineering, and Mathematics (STEM) students in a STEM Intervention Program (SIP) aimed at increasing the representation of underrepresented students in STEM fields. We applied London et al.’s STEM Engagement Framework to determine factors that distinguish who stays in a SIP and who leaves within the first two years of the program. Our sample was comprised of 129 high-achieving students enrolled in a multicomponent program at a large, research-intensive university in the mid-Atlantic. Our results suggest that identifying as a woman or gender non-conforming scholar, having a strong scientific identity, or reporting lower depressive symptoms, increase the likelihood of remaining in the SIP.

Keywords

STEM gender underrepresented retention postsecondary education well-being high-achieving

The success of minoritized populations in science, technology, engineering and mathematics (STEM) education is not just an ethical concern for higher education but is also relevant for the United States’ (U.S.) innovation and competitiveness in the global market (Langdon et al., 2011; Museus et al., 2011). Demand for careers in STEM continues to grow in the U.S. and the need to enroll and retain students in these fields has led to increased investment by industry and universities. Along with this increase in funding, a federal investment in STEM education programs of around 3 billion dollars per year has remained stable from 2010 to 2016 (Government Accountability Office, 2018).

In a report compiled by the national education statistics of 2013, 48% of bachelor’s degree seekers who entered as STEM majors between 2003 and 2009 had left these majors by 2009 (Snyder & Dillow, 2015). Around one-half of the students who left switched their major to a non-STEM field, and the rest exited college before earning a degree (Chen, 2013). The situation is even more concerning for underrepresented gender students (i.e., women and gender non-conforming students) and underrepresented racial/ethnic minoritized students (URMs), as retention in STEM for these groups is lower than for their counterparts (Espinosa, 2011; Hughes, 2018; Museus et al., 2011). One challenge in increasing the proportion of underrepresented students in STEM is the inability of colleges and universities to retain those who start until they have completed their programs. Given the limited literature on students who identify outside of the gender binary of woman or man, but available scholarship describing the challenges these students face navigating higher education (Atherton et al., 2016; Bilimoria & Stewart, 2009; Cech & Waidzunas, 2011; Hughes, 2018; Stout & Wright, 2016), we include them in this work and define this group with women to create a category we term underrepresented genders (UGs).

To address the barriers underrepresented genders (UGs) and underrepresented racial/ethnic minoritized groups experience when they enter these fields (Committee on Equal Opportunities in Science and Engineering, 2015), universities have implemented STEM intervention programs (SIPs) designed to increase the success of women and URMs in STEM (Chang et al., 2014; Maton et al., 2009; Sto Domingo et al., 2019). Researchers have shown that students who participate in SIPs are more likely than students with similar academic backgrounds to maintain an interest in STEM, earn better grades in STEM classes, complete STEM degrees and attend graduate school in STEM fields (Barlow & Villarejo, 2004; Maton & Hrabowski, 2004; Maton et al., 2000). Despite our knowledge that these programs work for URMs, less work has focused on the programs themselves and what distinguishes students that remain in the program from those students that leave. Studying program retention¹ in these types of programs may be a key to better understanding how to keep students on track towards STEM degree completion. In this sense, considering that the first two years of college are critical to retention and recruitment of STEM majors, as courses taken early in STEM fields are foundational courses and students begin to build connections with peers and faculty in these majors and the STEM field (President’s Council of Advisors on Science and Technology, 2012), understanding how students’ expectations and early experiences in SIP initiatives may be associated with their decision to leave SIP programs within their first two years of college represents a pressing research endeavor and is the focus of this paper.

This paper represents a unique examination into a SIP that is modeled after the success of the University of Maryland, Baltimore County’s (UMBC) Meyerhoff Scholars Program (MYSP) (Oseguera et al., 2019). The MYSP is nationally recognized for its remarkable effectiveness in sending underrepresented racial/ethnic minoritized groups and women to STEM Ph.D. programs (Maton et al., 2000). The aim of the current paper is to use a strength-based frame to better understand the key characteristics of those students who remained enrolled in this STEM intervention program through the first two years, as evidence suggests that remaining in these types of support programs have both short term (i.e., completing a STEM degree) and long term implications for securing a Ph.D. in STEM and maintaining a career in this field (Maton & Hrabowski, 2004; Maton et al., 2000; Merolla & Serpe, 2013). Our guiding research question is: what factors predict early SIP retention (i.e., within the first two years of study)?

We organize this paper by first providing a description of the SIP under study, and then review relevant literature on STEM-focused SIPs, and variables that are related to STEM engagement, such as interest, self-efficacy, sense of belonging, fewer experiences with discrimination, and STEM identity in relation to gender and racial/ethnic identities and well-being. We then introduce the theoretical framework that was used to guide variable selection and the analytic procedures. Finally, the results are presented, along with a discussion of the limitations and significance of this particular study.

This paper contributes to the field by examining the process of remaining engaged in a SIP, which requires high investment in terms of time, willingness to actively engage in research experiences early in one’s career, and willingness to expose oneself to intrusive advising. An additional contribution of this work is highlighting high-achieving underrepresented racial/ethnic minoritized (URM) groups and underrepresented gender (UG) groups in STEM and their race and gender salience.

The STEM Scholar Program

The SIP under study is a multicomponent program at a large, research-intensive university in the mid-Atlantic, called STEM scholar program (SSP).² The SSP is rooted in three asset-based areas: HBCU culture (i.e., family-like community), Black Greek organizations (i.e., Brotherhood/sisterhood atmosphere), and Black churches (i.e., uplift and inner strength) and is aimed at increasing the representation and academic achievement of URMs and UGs in STEM fields. While the current make-up of students in the SSP are not all Black-identified students, the program utilizes this framing given its success with diverse groups at the institution where the program originated (Maton et al., 2000).

To be considered for the SSP there is a three-step process: first, a student must be admitted to the university in a STEM college (e.g. Engineering, Science, Information Systems, etc.). Second, prospective participants are selected to interview based on their responses to a written application in which they are asked about their interest in pursuing STEM research, their potential in STEM, and why having a diverse group of scholars in STEM is important to the field. Third, during the selection period, prospective participants are invited to campus where they can interact with other SSP cohorts, faculty, and SSP staff. The responses to the written applications provide the discussion materials for the interviews that applicants have with faculty, staff, and current SSP scholars. Typically, several hundred applications are received, roughly 100 are invited for interviews, and ultimately 20–40 are selected. Students who are offered and accept admission to the program are awarded an annual scholarship for program participation. In instances where an admitted participant has greater financial need, as well as throughout the duration of the program if an unexpected financial hardship ensues, there are available provost and college funds for scholars to access.

SSP scholars also agree to participate and complete a summer bridge experience, an intensive six-week program that takes place the summer before the first year of college, in which students participate in team building activities, take rigorous math, writing, and science foundational courses and seminars, along with introduction to research, study habits, time management, and professional communication skills workshops.

The SSP provides financial, academic, and social support services to scholars for the four years of college. The SSP scholars live on campus during their first three years of study in a family-like community. During the four years of the SSP, scholars in the program learn not only to be accountable for their individual success, but also for the success of all the members in the program. The scholars from older cohorts provide mentoring to the new members (a practice that was modified for SSP’s first two cohorts as the program was too young to have upper-class students i.e., juniors or seniors within the program so utilized STEM upper-class students at the university as mentors) and all the scholars are encouraged to tutor other peers within the program. Mentoring not only takes place between scholars from newer and older cohorts throughout the entire duration of the program, but it also happens between alumni from the program and currently enrolled SSP scholars. In this sense, the program encourages its alumni to engage with SSP scholars by sharing their experiences in the STEM field, or by inviting current scholars to their research centers, universities, or businesses, among other mentoring practices. Before the SSP graduated its first class, it also modified this alumni practice by inviting alumni from the university to events. Also, scholars are encouraged to give back to the larger community outside the program, and they do so by tutoring students outside of the SSP.

The SSP scholars have substantial access to academic advisors and faculty mentors, with both scheduled appointment opportunities as well as extended drop in hours. The faculty mentors provide scholars with opportunities to participate in undergraduate research and to work in their laboratories. The advising team provides scholars with contacts to help them obtain summer internships and study abroad opportunities. In their fourth year, SSP scholars complete a research thesis, and they are encouraged to share their results at scientific conferences. SSP scholars also participate in GRE/MCAT prep classes, and are supported in their graduate school application process.

Literature Review

Although college student retention has been widely documented within higher education scholarship, for this review we focused mostly on STEM-related research areas, especially considering the documented challenges related to retention that students and programs face within STEM fields. Therefore, in this section, we focused first on the relevant research about SIPs, paying special attention to intervention programs that are STEM-focused. Then, in the STEM Retention Factors section, we highlighted variables that are related to STEM engagement: interest, self-efficacy, sense of belonging, fewer experiences of discrimination, and STEM identity in relation to gender and race identities. In understanding the SIP retention of URMs and UGs, it was important to consider the factors that have shown to be relevant for predicting these populations’ engagement levels in STEM, because of the relation between engagement in STEM and retention in STEM majors. STEM major retention is not equal to SIP retention but given the program’s primary purpose of retaining students in STEM majors, including literature around STEM engagement and major retention was justified.

Support and STEM Intervention Programs

The first U.S. colleges were designed to serve White males from privileged families preparing for the clergy. This traditional elitist college model remained until the American Civil War, when some limited attempts of providing access to other student populations began. Support programs appeared within higher education institutions as access to these institutions expanded in the late 1800s (Kezar, 2004), yet progress was primarily focused on increasing access to postsecondary education for White males from less wealthy backgrounds and geographically diverse places (Rudy & Brubacher, 1976). The situation for racial/ethnic minoritized groups and women only improved marginally and did not evolve without tension (Arendale, 2011).

According to Kezar (2004), the foundational goal of support programs was to facilitate the retention of the new populations and to support in leveling the playing field for the ones that were historically excluded from higher education opportunities, by increasing students’ preparation for success in college (Perna & Swail, 2001). However, discriminatory informal practices and discriminatory formal policies kept women (and other underrepresented genders) and racial/ethnic minoritized groups out of these support programs (Arendale, 2011). It was not until the Civil Rights legislation of the 1960s that federally-financed programs to provide appropriate services for URMs and UGs were created.

During the last forty years, support programs’ goals have expanded in response to the growth in the enrollment of historically underserved populations (e.g. women, first-generation, low-income, Black, and Latinx), and the new challenges that have arisen in the diverse fields within the higher education system (Kezar, 2010; Tierney et al., 2005).

According to George et al. (2019), SIPs began to appear in the higher education landscape in the 1980s, with diverse goals like increasing the enrollment and/or retention rates of women and URMs, supporting students in their transition to college, and improving undergraduates’ experiences and retention within their STEM majors (DePass & Chubin, 2008). Based on the needs and characteristics of the diverse college populations, SIPs provide various services, including summer bridge initiatives, undergraduate research opportunities, peer tutoring and mentoring, faculty mentoring, living learning communities, leadership training, professional development opportunities, and scholarships, to name some of them (George et al., 2019; Rincon & George-Jackson, 2016).

Racial and gender-based stereotyping and other kinds of microaggressions are particularly prevalent in STEM (McGee, 2016). Lane (2016) found that STEM classes were hostile environments in which women and URMs felt they needed to prove their intelligence in order to be respected. Seymour and Hewitt (1997) documented that competitive environments lack interpersonal and collaborative relationships crucial for women to thrive. Racial stereotypes also have consequences for URM students, such as increased anxiety, bouts of anger, and feelings of being an impostor, as well as compulsive work tendencies, which are related to URM students feeling forced to prove they are fully capable of achieving in STEM (McGee, 2016). Moreover, these negative features of STEM environments have been found to make women and URM students question their STEM identity (Rosenthal, London, Levy, & Lobel, 2011; Rosenthal, London, Levy, Lobel, & Herrera-Alcazar, 2011; Settles et al., 2009), which produces discipline disengagement (Estrada et al., 2018). With this in mind, SIPs aimed at supporting URMs and UGs work to curb the negative effects of the general STEM climate by cultivating a positive environment, facilitating interactions with faculty and peers, and fostering students’ self-efficacy in STEM fields, all of which contribute to their success in STEM education (Museus et al., 2011).

The research around SIPs has been relevant in highlighting the benefits of these interventions, emphasizing how they facilitate retention and academic success in the STEM field, foster graduate degree aspiration, and reduce the attainment gap for URMs and UGs. Along with this, researchers have also provided important critiques regarding the deficit ideology used in the design of some of these programs (Bowman in DePass & Chubin, 2015; Linley & George-Jackson, 2013). However, the literature that assesses the effectiveness of SIPs has not addressed the issue of SIP student retention. In academic literature, it is uncommon to find empirical evidence regarding SIP retention. To advance STEM support there is a need to understand what distinguishes those students who stay committed to a SIP from those who depart.

STEM Intervention Program Retention Factors

Engagement is defined as invested time and energy spent on academically purposeful activities that are linked to positive social and academic outcomes such as retention (Kuh, 2001). Considering SIPs usually require participants devote extra time and effort in activities related to the program, we use an asset-based engagement framing to guide this section of the literature review and further organize these sections of the literature review according to our guiding theoretical framework (see London et al., 2011). We also incorporate a well-being section, which scholarship has emphasized as a critical factor for students’ active participation in academia.

Scientific Interest, STEM Self-Efficacy, and Sense of Belonging

A substantial body of research about the retention in STEM majors has focused on understanding the role that interest and excitement play in facilitating student retention in the field (Crisp et al., 2009; Gasiewski et al., 2012; Lent et al., 2003; Perez, 2012; Seymour & Hewitt, 1997). Students’ lack of interest in STEM is frequently cited to explain their decision to switch from a STEM major to a non-STEM one (Seymour & Hewitt, 1997). SIPs aspire to raise students’ interest in STEM, with the expectation that increased interest will lead to increased retention (Ashley et al., 2017). A large body of literature has also highlighted that student participation in SIPs, such as summer bridge programs (Bruno et al., 2016; Kitchen et al., 2018; Lenaburg et al., 2012; Pritchard et al., 2016; Russomanno et al., 2010; Thompson & Consi, 2007) or undergraduate research programs (Doerschuk et al., 2016; Estrada et al., 2016; Russell et al., 2007), has a positive effect on STEM students, increasing their interest in STEM and their retention in the field.

As interest can influence STEM students’ persistence decisions, self-efficacy also influences STEM students’ academic behaviors, including the effort they put into their academic activities (Elliot et al., 2017). Academic self-efficacy has been defined as the confidence students have in their own capability to successfully complete academic tasks (Bandura, 1986; MacPhee et al., 2013), and it stands to reason that students with higher self-efficacy will be more likely to stay in a SIP. Research indicates that men in STEM have higher academic self-efficacy than women in the same field (Hardin & Longhurst, 2016; Lent et al., 2016; MacPhee et al., 2013; Vogt et al., 2007; Wilson et al., 2015), and also that non-URMs from upper SES backgrounds have higher self-efficacy than their peers from other social groups (MacPhee et al., 2013). MacPhee et al. (2013) explain that judgments about one’s own competency in a field are affected by social context cues. Therefore, it is reasonable to find that men and non-URMs from upper SES backgrounds have higher self-efficacy than UGs and URMs, since the latter have fewer role models of successful STEM graduates with their same gender or race/ethnicity, due to the residual effects of racism and gender bias on issues related to educational access and equity. Still today, many college-level STEM environments continue to be spaces that are dominated by White males (Beasley & Fischer, 2012; Bodzin & Gehringer, 2001; Corbett & Hill, 2015). An example of persisting inequities that affect self-efficacy can be seen in the access to research opportunities. In this sense, according to Robnett et al. (2015), a student’s participation in research opportunities is fundamental for acquiring science self-efficacy, yet, unfortunately, these experiences can be elusive for URM and UG students attending predominantly White institutions (PWIs).

In addition to the role that interest and self-efficacy play in relation to retention rates in STEM, research has shown that students’ social experiences, such as their sense of belonging and the experiences of discrimination they have encountered, are fundamental for their retention in STEM majors (Estrada et al., 2018; Freeman et al., 2007; Good et al., 2012; Hurtado et al., 2010; Inzlicht & Good, 2006; Strayhorn, 2018; Walton & Cohen, 2011). Sense of belonging has been defined as a person’s experience of integration within a system to the extent that this person feels she or he has a special function in that system (McLaren et al., 2008) and, equally, that the system is important for that individual (Strayhorn, 2018).

Evidence suggests that sense of belonging is especially relevant to the experiences and behaviors of those who “perceive themselves as marginal to the mainstream life of college” (Hurtado & Carter, 1997, p. 324). The numerical underrepresentation of URM, women, and lesbian, gay, bisexual, transgender, and queer (LGBTQ) students and faculty in STEM works as a cue priming these populations that they might not belong in the STEM field (Murphy et al., 2007; Strayhorn, 2009; 2018). Also, perceiving the campus or academic discipline as hostile or unwelcoming (Estrada et al., 2018), experiencing LGBTQ-biases (Stout & Wright, 2016), racial tension, a hostile racial climate (Hurtado et al., 2010; Locks et al., 2008), or suffering interpersonal discrimination (Dortch & Patel, 2017; Hurtado et al., 1996; Syed, 2010) reduces students’ sense of belonging and increases their odds of dropping out from their majors.

The racial climate on STEM departments has changed over time, but discrimination has not vanished. While overt discrimination has tended to disappear, more subtle, indirect, and covert discrimination practices (McGee, 2016), which usually take place in negative interpersonal encounters (Hebl et al., 2002), are still present in STEM departments (McGee, 2016). URM students are viewed from deficit ideologies, and they are considered as “unqualified, incompetent, and undeserving of opportunities in the STEM arena” (McGee, 2016, p. 1628). Similarly, despite overt practices of gender discrimination being less prevalent than they were decades ago, covert forms of gender bias and discrimination still exist and occur within the STEM field (Cooper & Brownell, 2016; Wang & Degol, 2017). Research has found that women in STEM math-intensive majors are particularly prone to experience gender bias (Robnett, 2016), and that women experience unequal treatment based on their gender within STEM (Steele et al., 2002). For instance, the same piece of scientific work gets a higher score from undergraduate students when it has a male name attached to it than when it has a female author (Knobloch-Westerwick et al., 2013), and similarly a curriculum vita of an undergraduate receives better scoring from faculty when it has a male name attached to it (Moss-Racusin et al., 2012). Likewise, research about LGBTQ students in STEM suggests that while overt anti-LGBTQ bias is not socially acceptable in the field, subtle anti-LGBTQ bias is still prevalent in STEM classrooms and other academic spaces, such as group project meetings (Cooper & Brownell, 2016), usually in the form of derogatory remarks or jokes and isolation (Cech & Waidzunas, 2011; Patridge et al., 2014).

Gender and Racial/Ethnic Identities in STEM

Just as the literature has shown that self-efficacy, interest, and sense of belonging influence URM and UG groups’ choices regarding their permanence in the STEM field, having a science or engineering identity has been recognized as being a significant predictor of retention in STEM (Carlone & Johnson, 2007; Chemers et al., 2011; Espinosa, 2011; Estrada et al., 2011; Graham et al., 2013; Merolla & Serpe, 2013). Since the strength and quality of students’ academic identification is related to their learning motivation (Cokley & Moore, 2007), students’ level of engagement and willingness to be active participants in their learning opportunities (Dean & Jolly, 2012) are influenced by these identities (White et al., 2019).

Research about students’ identities in STEM has posited that women and URMs are more inclined than other groups to question their STEM identity (Rosenthal, London, Levy, & Lobel, 2011; Rosenthal, London, Levy, Lobel, & Herrera-Alcazar, 2011; Settles et al., 2009) or experience fragmented academic, science, and personal identities (Beals, 2016; Hughes, 2018; Mahfood, 2014; Tran et al., 2011) because of the perceived stereotypes that STEM is a field for European or American males (Beasley & Fischer, 2012; Bodzin & Gehringer, 2001; Corbett & Hill, 2015), and because of gender and racial imbalance in the field (Atherton et al., 2016; Settles et al., 2016). This rigid stereotype about STEM being in nature a White masculine discipline is coupled with the assumptions that STEM is also a heterosexual enterprise, which also perpetuates problematic climates in STEM for LGBTQ students. As noted by Cooper and Brownell (2016), LGBTQ students in STEM perceived their faculty and peers as judging them as “unprofessional” if they made their LGBTQ identities explicit. LGBTQ students in STEM reported that they perceived pressures to “cover” their sexual orientation and/or gender identification (Bilimoria & Stewart, 2009) and that it was expected for them to “pass” as heterosexuals, as well as downplay cultural characteristics associated with LGBTQ identities (Cech & Waidzunas, 2011) to fit into the STEM environment.

When STEM students question their STEM identity, they have higher chances of experiencing discipline disengagement, which reduces students’ engagement in behaviors necessary for success in their career pathways (Estrada et al., 2018), such as participating in SIPs. Perceiving that both STEM and other salient psychosocial identities (gender or race identities) are compatible is fundamental for motivation in STEM (London et al., 2011; Rosenthal, London, Levy, & Lobel, 2011). For this reason, the idea that it is important to promote the development of a healthy science identity has become relevant in research (Carlone & Johnson, 2007; Lane, 2016; Ong et al., 2018). UGs and URMs who have successfully navigated the STEM environment frequently develop an identity that is a combination of their STEM and other salient and central identities, such as gender and racial/ethnic identity (McGee, 2016). In this identity development process, URM students redefine what it means to be a scientist and a person of color for them (Herrera et al., 2012; Tran et al., 2011), and UGs develop compatibility between their STEM and gender identities (Cech & Waidzunas, 2011; Rosenthal, London, Levy, & Lobel, 2011). Regarding the role of SIPs during the identity development process, researchers have posited that SIPs offer spaces where URMs and women fulfill their academic selves without being questioned in relation to their other identities (Lane, 2016; Ong et al., 2018).

Well-Being and STEM

Just as some researchers have suggested that having a science or engineering identity is a significant predictor of engagement in STEM, other scholars have found that students’ well-being and mental health are also associated with retention and engagement. College students’ well-being and mental health problems have become a rising concern for universities (Boyraz et al., 2017). According to the results of the National College Health Assessment (American College Health Association, 2018), 24% of the students reported that, during the last month or the last two weeks, they felt so depressed that it was difficult for them to function. Due to this concerning evidence, scholars have begun to integrate mental health or well-being variables in the study of college retention and dropout (Arria et al., 2013; Bachrach & Read, 2012; Boyraz et al., 2013, 2016; Bruffaerts et al., 2018; Eisenberg et al., 2009). Well-being and depression not only influence student retention, but also other undergraduate experiences. For instance, Byrd and McKinney (2012) found depression symptoms to be correlated with lower levels of students’ engagement with faculty and peers. One may expect that these patterns would also be found in relation to SIP retention.

In this literature review, we have shown how researchers have found a significant relationship between students’ engagement in STEM and their interest, self-efficacy, sense of belonging, experiences of discrimination, STEM identity and well-being. However, what remains constant across this wide array of topics in STEM research is that there is no work that analyzes how these variables influence student retention at the SIP level.

Theoretical Framework

The theoretical framework that guided this study was London et al.'s (2011) STEM Engagement Framework, developed and used to understand the first-year experiences of racially and ethnically diverse women at a coeducational university. London et al. (2011) define STEM engagement as “the academic and social variables that are essential not only for retention but also for sustained investment and satisfaction in STEM fields” (London et al., 2011, p. 305). In this model, the social variables are defined as the sense of belonging to the major and the educational environment, and the academic variables are motivation, confidence in STEM abilities, and the expectation of remaining in the STEM major. According to this framework, there are two psychosocial variables that function as facilitators of STEM engagement: perceived availability of social support and perceived identity compatibility.

We also added well-being measures to the model, considering the scholarship reviewed in the literature section that links engagement and well-being for minoritized groups in STEM (Arbona et al., 2018; Arria et al., 2013; Boyraz et al., 2016). The well-being measures included a low prevalence of depressive symptoms and a satisfaction with life measures. London et al. (2011) used this framework to predict women’s expectations of dropping out of STEM majors, but this paper adapted it to better understand students’ decisions to remain involved in a scholar program aimed at preparing undergraduates for STEM. Using an engagement framing is ideal, since this SIP has explicit expectations that participants will fully engage in the program and participate in academic and social activities.

Methodology

Data Source

Data for this study were collected using confidential web-based surveys administered during the summer of each cohort of the summer bridge program. Four surveys were designed to elicit information from participants about their backgrounds, the academic, social, and psychosocial aspects of their experiences within and outside the SSP. The first three surveys were administered early in the program, and they primarily collected information about students’ prior experiences in high school and their expectations for college. The fourth survey, which was administered at the end of the summer bridge program, collected information about participants’ experiences during the SSP and included selected measures asked in earlier surveys. All the independent variables used in this work were measured at the end of summer bridge program except gender identification, gender salience and race centrality scales, which were from the second survey administered. Scholars’ racial/ethnic identification was pulled from application data from the university's admission office.

Sample

The first five cohorts (2013–2017) of the SSP comprised the sample (n = 129) for this study. Cohort sizes ranged from 20–40 scholars per year. All scholars participated in the web-based surveys administered during their respective summer bridge programs.

The race and ethnicity categories were recoded to produce a variable with two mutually exclusive categories: URMs and non-URMs. Latinx/Hispanic, Black/African American, Native American, Alaskan Natives, Pacific Islanders, and scholars of two or more of these races were categorized as URMs. Asian, Asian American, White students, and scholars of two or more of these races were not considered URMs in STEM fields per program and university guidelines and were classified as non-URMs (see Table 1). Seventy-one percent of the students in this sample were identified as a member of a racial/ethnic minoritized group (see Table 1) and 59% as a member of an underrepresented gender group.

Table 1.

SSP Scholars’ Race/Ethnicity (Organized by Percent).

Race/ethnicity (n = 129)	Overall percent	Percent by sub-group
Total URM Students	71
Latinx/Hispanic		19
Black/African American		35
Native American or Pacific Islanders		1
Multi-Racial/Multi-Ethnic URM		17
Total Non-URM Students	29
Asian/Asian American		8
White		19
Multi-Racial/Multi-Ethnic Non-URM		2
Total^#	100	100

^#Due to rounding, percentages may not sum to 100.

The Free Application for Federal Student Aid (FAFSA) scores of both program retainers and leavers were found to be similar (see Table 2). Additionally, in terms of academic performance, the average high school grade point average (GPA) of the 129 SSP scholars was 4.02 (on a standard 4.0 scale with above a 4.0 representing extra points for advanced placement and honors courses), and the SAT math and verbal average scores of retainers (n = 118) were 684 (SD = 62) and 648 (SD = 71), respectively, and for the program leavers, the scores were 656 (math, SD = 50) and 598 (verbal, SD = 80). Also, among the 11 leavers, the average college GPA was 3.11 out of 4.00 with no SSP leavers falling below the general university standard of 2.0 for graduation and 55% remained in STEM fields. No scholars were dismissed for academic reasons. These GPA scores, along with the program’s flexibility and responsiveness to aid scholars academically when needed, indicate that scholars’ decisions to leave the program are more complicated than academics alone.

Table 2.

SSP Scholars’ Entering FAFSA Score by SSP Retention Status (Organized by Percent).

FAFSA Score	SSP Retainers (n = 118)	SSP Leavers (n = 11)
0 to 25	41	45
26 to 50	17	9
51 to 75	17	9
75 to 100	25	36
Total^#	100	100

Note. A FASFA Score of 0 represents 0% need, while a FAFSA score of 100 represents 100% need.^#Due to rounding, percentages may not sum to 100.

Variables in the Analysis

Outcome Variable

Our main outcome of interest, short-term retention in the first two years of the SSP program, was measured by a binary variable that distinguishes between retainers (SSP Retainer = 1) and leavers (SSP non-Retainer = 0).

Independent Variables

The independent variables were selected according to our adapted STEM Engagement Framework of London et al. (2011) and were operationalized using summer bridge experience measures. We opted to use measures from the summer bridge surveys as there was a 100% response rate for all SSP participants on the summer bridge surveys. Additionally, the SSP leadership described the summer bridge experience as a foundational aspect of the SSP and hence our decision to utilize variables collected during summer bridge. See Appendix for more detail concerning items from the constructs used in the analysis and corresponding alphas.

Academic Dimension Variables

Two academic scales were included. Scientific Research Interest was a 5-item scale that captured a respondent’s level of excitement about scientific research work and career. This scale had face validity (Slaughter et al., 2015). Respondents selected the extent to which they agreed with items such as: “I am excited about the idea of scientific research”. Scientific Self-Efficacy (Chemers, 2006) was a 14-item scale in which respondents marked their confidence in items such as: “Use technical science skills”.

Social Dimension Variables

Three social variables were used in the analysis. Since a major objective of the SSP program was to build a strong sense of program community, we included a 12-item construct that assessed the scholars’ sense of program community. This construct included items that asked scholars if they felt represented by statements like “Being a member of the SSP is a part of my identity”. The second social dimension variable used in the analysis was the Scientific Identity Scale, which was a 5-item modified version of the Chemers’ (2006) Scientific Identity Scale, in which students were asked the extent to which they consider accurate statements such as: “I derive great personal satisfaction from working on a team that is doing important research”. The final scale within social variables was the 10-item Everyday Discrimination Scale from Seaton et al. (2008). The scale included items that asked participants if they had experienced situations such as “People treat you as if you are not smart” and “You are treated with less respect than other people”.

Psychosocial Dimension Variables

Two psychosocial variables were used in this study. The first construct was a 6-item version of the MIBI-Teen scale (Sellers et al., 1998), adapted to capture gender identity centrality. The construct included items such as “Being [my gender] is an important part of my self-image”. The second construct used was the 3-item MIBI-Teen race centrality scale, which was used to determine the extent to which scholars viewed their race as central to their identity, and included items such as “I have a strong sense of belonging to others in [my race]”.

Well-being Dimension Variables

To capture subjective well-being, we used the 5-item Satisfaction with Life Scale (SWLS) (Diener et al., 1985). The second well-being measure used in this work was the 12-item version of the Center for Epidemiological Studies Depression Scale (CES-D), which asked respondents how frequently they had experienced symptoms associated with depression during the past week (e.g., feeling lonely, restless sleep, or poor appetite). The CES-D was a self-reported index of depressive symptoms (Kohout et al., 1993; Radloff, 1977) that we used as a proxy for depression or lack thereof. The CES-D was included as a dichotomous variable in our model, as used by Blank et al. (2004). The CES-D scale had demonstrated adequate reliability and validity in college student populations (Shean & Baldwin, 2008). In this regard, it is important to mention that all scales utilized in this study had an alpha reliability above .70, the recommended level of reliability (Nunnally, 1978).

Controls

We included UG and URM status as controls, given our interest in underrepresented genders and underrepresented racial/ethnic minoritized groups in STEM. Also, we compared retained and non-retained scholars' entering academic performance and found no significant difference among them, so we did not include a measure of academic performance in the control variables.

Analyses

We applied descriptive and multivariate analyses on our outcome. Specifically, we employed t-tests by UG and URM status to offer a description of the scholars in this sample prior to any higher order analyses. Since we hypothesized that our STEM engagement model would predict the SSP scholars’ decision to remain in the program, we entered predictors into the analysis based on our theoretical framework as hierarchical multiple regression does (Cohen, 2013). To better understand the factors that were related to retention in the SSP program, we conducted blocked, logistic regressions. By including independent variables into the regression models from controlling traits to the four dimensions of the conceptual frame in an additive way, we could see the net effect of each set of predictors on program retention. Missing data (less than 5%) were replaced individually with means of the non-missing construct items. When missing rates are lower than 20%, replacing missing data with means of non-missing items produce comparably sound results as other imputed data analyses such as multiple imputation (Shrive et al., 2006).

Limitations

While this work is a relevant contribution to understanding SIP retention, it is important to acknowledge some of its limitations. Our sample is drawn from a program at a single university; therefore, the conclusions presented here cannot be generalized. This program operates in two other research-intensive universities, and similar programs have grown at a variety of universities, so future work might include a multi-campus sample to identify whether there are unique campus effects on program retention rates. Additionally, the measures we applied are not designed for the conceptual framework, so we do not have a perfect representation of all the variables in the guiding framework.

Also, the small sample size led to lower statistical power, and prevented us from producing higher order statistical analyses, such as the examination of the conditional effects of the components of the STEM engagement model across more specific student subgroups. In our surveys, we have a response option, “other,” for any scholar who did not identify themselves with the binary gender category man or woman. Fewer than five students selected this option, which is a number too small to run any analyses separately, and thus we included them with women to produce the underrepresented gender (UG) category.

Finally, this work examines short-term retention in a SIP. We expect that in another two years, we can examine the program retention rates for the complete four years of the program and better link aspects of programming to long-term retention. Still, examining short-term program retention is critical, since attrition from STEM will typically occur within the first two years of study.

Findings

This section is divided in two parts. First, we present the t-test results by UG and URM status. Then, we review the results for the logistic regression analyses, by describing the significant results of our final complete model (model five), which contained all variables included in the analyses.

Table 3 presents means and standard deviations of the variables in the analyses by the overall sample and separately by UG. For most of the variables in the model, there were no differences between men and UGs except program retention and gender salience. Both groups reported strong scientific research interest, scientific self-efficacy, sense of program community, and scientific identity as well as reported similar levels of race centrality, satisfaction with life and depressive symptoms in their summer bridge experience. Our results of the t-test by UG showed that more men scholars left the program than UG scholars. The results also indicated that UG scholars tended to agree significantly more that their gender identity was important to their self-image.

Table 3.

Descriptive Statistics of Variables for the Overall Sample and by Gender.

Variable	Scale	Mean (SD)			T(df)
Variable	Scale	Men(N = 53)	UG(N = 76)	Total(N = 129)	T(df)
Outcome variable
Retention in the Program	0: non-SSP retainer after two academic years 1: SSP retainer	0.85 (0.4)	0.96 (0.2)	0.91 (0.3)	−2.05*(73)
Independent variables
AcademicDimension
Scientific Research Interest	From strongly disagree (1) to strongly agree (5)	4.00(0.7)	4.03(0.7)	4.02(0.7)	−0.28(127)
Scientific Self-Efficacy	From not at all confident (1) to absolutely confident (5)	4.10(0.6)	3.98(0.6)	4.03(0.6)	1.18(127)
SocialDimension
Sense of Program Community	From not at all (1) to completely (4)	3.16(0.6)	3.13(0.5)	3.14(0.5)	0.34(127)
Scientific Identity	From strongly disagree (1) to strongly agree (5)	4.19(0.6)	4.10(0.6)	4.14(0.6)	0.82(127)
LessDiscriminationExperiences	From almost everyday (1) to never (6)	4.72(0.9)	4.65(0.9)	4.68(0.9)	0.48(127)
PsychosocialDimension
Gender Salience	From strongly disagree (1) to strongly agree (5)	2.94(0.9)	3.39(0.6)	3.21(0.8)	−3.25**(91)
Race Centrality	From strongly disagree (1) to strongly agree (5)	3.45(1.0)	3.71(1.0)	3.60(1.0)	−1.44(127)
Well-being Dimension
Depressive Symptoms (CES-D scale)	0: low depressive symptoms1: high depressive symptoms	0.4(0.5)	0.5(0.5)	0.5(0.5)	−1.31(127)
Satisfaction with Life (SWL scale)	From strongly disagree (1) to strongly agree (7)	4.87(1.4)	4.78(1.5)	4.82(1.4)	0.35(127)
Control Variables
Underrepresented Racial/Ethnic Minoritized (URM) status	0: non-URM, 1: URM	0.74 (0.4)	0.70(0.5)	0.71(0.5)	0.47(127)

*p < .05; **p < .01.

Among the URM and non-URM groups, the t-test results showed that URM scholars exhibited a significantly lower program retention mean and completed summer bridge with a lower reported scientific research interest score, but they had a significantly higher race centrality mean than their non-URM counterparts (see Table 4). Given that students’ research interests play a critical role in promoting their academic engagement and retention in STEM (Ashley et al., 2017; Hunter et al., 2007 ), URM scholars’ lower mean on the scientific research interest variable might indicate a predisposition to discontinue their study in the SSP.

Table 4.

Descriptive Statistics of Variables by URM Status.

Variable	Scale	Mean (SD) (N = 129)		t(df)
Variable	Scale	Non-URM(N = 37)	URM(N = 92)	t(df)
Outcome variable	0: non-SSP retainer after two academic years1: SSP retainer
Retention in the Program	0: non-SSP retainer after two academic years1: SSP retainer	−0.95(0.2)	0.90(0.3)	0.80(127)
Independent variables
Academic Dimension
Scientific Research Interest	From strongly disagree (1) to strongly agree (5)	4.30(0.5)	3.91(0.7)	3.56**(98)
Scientific Self-Efficacy	From not at all confident (1) to absolutely confident (5)	4.08 (0.7)	4.00(0.7)	0.68(127)
Social Dimension
Sense of Program Community	From not at all (1) to completely (4)	3.14(0.5)	3.14(0.5)	0.69(127)
Scientific Identity	From strongly disagree (1) to strongly agree (5)	4.22(0.6)	4.10(0.6)	1.15(126)
Less Discrimination Experiences	From almost everyday (1) to never (6)	4.81(0.7)	4.63(0.9)	1.08(127)
Psychosocial Dimension
Gender Salience	From strongly disagree (1) to strongly agree (5)	3.15(0.6)	3.23(0.8)	−0.51(127)
Race Centrality	From strongly disagree (1) to strongly agree (5)	3.20(1.0)	3.76(0.9)	−3.05**(127)
Well-being Dimension
Depressive Symptoms (CES-D scale)	0: low depressive symptoms1: high depressive symptoms	0.43(0.5)	0.48(0.5)	−0.47(127)
Satisfaction with Life (SWL scale)	From strongly disagree (1) to strongly agree (7)	4.98(1.3)	4.75(1.5)	0.82(127)
Control Variables
Gender	1: Men, 2: UG	1.62( 0.5)	1.58(0.5)	0.47(127)

**p < .01.

We now move to the blocked logistic regression results, which predicted program retention after two years (see Table 5). In model 5, the full model where the well-being dimension variables of our model were added, scientific self-efficacy and the fewer incidents of discrimination were not significant predictors of short-term program retention, while gender was significant in the model. Underrepresented genders were 19.90 times (OR = 19.90, p < .01) more likely to remain in the program compared to their men counterparts.

Table 5.

Results of Logistic Regression Models for SSP Program Retention.

Variable	Model 1		Model 2		Model 3		Model 4		Model 5
Variable	B	OR	B	OR	B	OR	B	OR	B	OR
Control Variable
Gender	1.45*	4.27*	1.39†	4.01†	2.20*	9.05*	2.40*	11.06*	2.99**	19.90**
URM	−0.60	0.55	−0.26	0.77	−0.58	0.56	−0.55	0.58	−0.93	0.39
Independent Variables
Academic Dimension
Scientific Research Interest			0.68	1.98	0.54	1.71	0.50	1.65	0.22	1.25
Scientific Self-Efficacy			−0.50	0.61	−1.31†	0.27†	−1.34†	0.26†	−0.95	0.39
Social Dimension
Sense of Program Community					−0.36	0.70	−0.36	0.70	−0.62	0.54
Scientific Identity					2.30*	9.98*	2.29*	9.82*	2.34*	10.34*
Social DimensionLess Discrimination					0.79†	2.19†	0.78†	2.18†	0.70	2.01
Psychosocial Dimension
Gender Salience							−0.29	0.75	−0.50	0.61
Race Centrality							−0.11	0.90	0.05	1.05
Well−being Dimension
Life Satisfaction									−0.40	0.67
Depressive Symptoms									−1.94*	0.14*
Constant	0.74	2.09	−0.10	0.91	−8.60	0.00	−7.24	0.00	10.07	23677.32
Model fitPseudo R²	.07(p < .10)		.10(p > .10)		.24(p < .05)		.24(p < .05)		.31(p < .05)
R²			.03		.14		.00		.07

^†p < .10; *p < .05; **p < .01.

Scholars who had lower depressive symptoms during the SSP summer bridge program were 0.14 times more likely to remain in the program (OR = 0.14, p<.05). Model 5 included all dimensions of our framework, and it signals the need to pay attention to students’ mental health when examining who left the program. This result corresponds with research that correlates depression with university dropout (Arria et al., 2013).

According to the results of our final model, the scientific identity, in the social dimension, turned out to be a significant predictor of short-term program retention. Scholars who had higher scientific identity during the SSP summer bridge program were 10 times more likely to remain in the SSP (OR = 10.34, p < .05). The pseudo-R² of model 5 was .31, and the chi-square of the Hosmer-Lemeshow indicated that this model had a sound goodness-of-fit.

Discussion

Guided by an adapted STEM engagement framework, we discuss major findings in relation to early program retention in the STEM scholar program (SSP). First, UG scholars are more likely to remain in this program than their men peers, and URM scholars are as likely to remain in the program as their non-URM counterparts. URM and UG students found SIPs as counter-spaces against the racism and gender biases in the STEM academic culture; in these counter-spaces, they have a sense of belonging that they lack in the mainstream STEM field (Strayhorn, 2018). For instance, Ong et al. (2018) explain that URM women participated in STEM counter-spaces to seek support to “counter personal attacks, to get emotional support and strategies to counteract isolation” (p. 233).

This program is designed emphasizing the strengths of Black culture, Black churches and family-like supportive environments and it provides URM and UG scholars with a learning community in which they encounter a sense of belonging and supportive peer mentoring and tutoring. While this program emphasizes Black culture and was derived from a program at another institution which centered Black culture, the program nonetheless ensures that all scholars engage in global awareness conversations, and that invited speakers come from a wide array of racial/ethnic backgrounds and gender identities so as to integrate the diversity of students in the program.

The second finding relates to scientific identity, one of the social dimension variables, and it addresses what works for maintaining scholars in the program. Previous research has documented that students presenting a high level of scientific identity are more likely to find their ways in STEM fields (Perez et al., 2014) and matriculate in graduate schools (Merolla & Serpe, 2013). Our work identifies the significant association between students’ scientific identity and SIP retention. It resonates with other scholars’ findings that SIPs can serve as proximate social structures that enhance students’ development of scientific identities (Merolla & Serpe, 2013). College students’ identity development is influenced by day-to-day interactions with people and their reflections on the experiences in learning communities (Carrino & Gerace, 2016). The implemented activities during the six weeks of residential summer bridge programs, including taking college-level classes, professional development workshops, and lab tours, may have contributed to scholars’ interest in STEM professions, as well as they may have helped scholars build connections with senior mentors and faculty.

At the end of summer bridge, scholars did not show significant gaps in scientific identity by UG or URM status, indicating that UG and URM scholars maintain a scientific identity as high as their men and non-URM counterparts when beginning their freshmen year. As other scholars have demonstrated, early contact with faculty positively influences scientific identity formation and has long-term effects (Carlone & Johnson, 2007; Eagan et al., 2012); in our study, this effect is a high rate of program retention.

Another finding of our research highlights the connection between STEM scholars’ well-being dimension and their retention in the program. SSP scholars who report low depressive symptoms during the summer bridge programs are more likely to remain in the SSP than to leave the program during the first two years. This result confirms that college students’ mental health is a pressing issue in relation to their permanence in the academic program. Students’ sense of well-being cannot be overlooked, given poor well-being’s potentially destructive effects on academic performance and social interactions in life (Byrd & McKinney, 2012). Although research has indicated that certain subpopulations, such as Black and Latinx students, are sometimes more likely to undergo higher depressive symptoms, which causes lower levels of persistence intentions (Arbona et al., 2018; Boyraz et al., 2016), this was not the case for SSP scholars. In our data, measured at the end of summer bridge, URM and UG scholars did not show statistical differences in their well-being indexes. It is still important, however, to heed the overall wellness of these high-achieving scholars. The well-being dimension deserves to be integrated in both the guiding theoretical framework and the practical implementation of SIPs.

As shown by this discussion, while low academic performance is usually understood as the reason why URMs and UGs leave STEM areas, this study complicates the puzzle by highlighting the salience of other factors that relate to this issue, such as well-being and students’ social interactions. This work also suggests these SIPs are doing more for students than merely offering academic support.

Implications

This study has implications for the exploration of SIP retention, which is an unexplored area. Our findings are relevant for the design and implementation of SIPs. As noted in our literature review, URM students at PWIs tend to experience a more negative racial climate, which becomes a main barrier for adjusting to colleges and universities (Carter et al., 2013). In large, predominantly White, public research institutions, STEM courses tend to be taught in large classrooms with professors that subsequently “weed out” UG and URM students, which results in making highly competent students switch out to non-STEM majors (Seymour & Hewitt, 1997). This competitive environment lacks interpersonal and collaborative relationships, which are crucial for women to thrive (Seymour & Hewitt, 1997); it appears that the current program under study is working to keep UG students engaged. Therefore, institutional support, particularly for these students, can foster their adjustment and success. Good et al. (2002) discovered, in their mixed-method analyses, a significant effect of a SIP on African American students’ retention. They argue that the SIP could play a role as a protective factor from a hostile climate. In this respect, our work suggests that one way in which SIP leaders can orient their efforts is through the implementation of strategies that encourage the development of strong social identities.

Our results also highlight that it is prudent to pay attention to student well-being when aiming to increase student retention within a program. In particular, this finding signals that it is important to include depressive symptoms and well-being measures when studying high-achieving college students in STEM fields. Even though this has been an issue of public concern, it remains an under-researched topic; there is still little investigation on how mental health concerns affect students in highly competitive majors.

A critical finding of this study is that, in all our models, UGs had significantly higher odds of remaining in the SSP program, suggesting that UGs take advantage of these types of opportunities. Even though the SSP program is a very demanding one, UGs appear to be more willing to invest their time and effort when they are provided with a challenging, yet supportive and welcoming environment. It begs the question of whether men have already been socialized to expect to be successful without the assistance of a SIP, since many college STEM environments continue to be male-dominated spaces that advance male perspectives. For practitioners and institutions alike, these results indicate the need to create and implement SIPs for UGs in STEM that go beyond the traditional components of academic support, but that also include well-being components.

Conclusion

This study is one of the first to examine the relationship between STEM engagement dispositions and short-term retention in a SIP. While research using the London et al. (2011) framework has been relevant in the understanding of student retention in STEM majors, our findings suggest that this framework, which focuses on academic, social, psychosocial, and the addition of our suggested well-being dimension, has some utility for predicting SIP retention. The social and academic dimension variables did not relate to scholars’ program retention, but it might be that this result is due to the particularities of our sample. Since our sample was comprised of a group of high-performing students, it is possible that these variables are not relevant for a group that is more homogeneous in respect to variables related to academic achievement. Finally, it is important to mention that these are early findings in the study of SIP retention. More work in this area is necessary, given the impact that SIPs have in STEM retention.

The inclusion of the well-being variables in the model also represents an important contribution for understanding what could contribute to students remaining in a program that demands time, effort, and commitment to the success of other peers. Finally, we found that the students who remain in the SIP maintain higher grades and remain more committed to STEM than a group of those former SSP participants who had left the SIP. Future studies would benefit from including a comparison group of students in STEM majors who are not in a SIP, a comparison between academic SIPs across STEM fields, and a national representation of URM students.

Footnotes

Appendix: List of Survey Items in Each Construct

Construct	Number of items	Factor loadings
Scientific Research Interest	5
Q. Please mark your agreement for each of the following statements using the following scale:
• I enjoy doing research-related tasks.		0.84
• I expect that my career will focus on research rather than practice (or non-research work).		0.82
• I am excited about the idea of scientific research.		0.81
• I am firmly committed to pursuing a career in research.		0.79
• I look forward to working in a research lab.		0.47
Scientific Self-Efficacy	14
Q. Please select the best answer on the scale from not at all confident to absolutely confident.
• Use scientific literature and/or reports to guide research		0.83
• Create explanations for the results of the study		0.81
• Develop theories by integrating and coordinating results from multiple studies		0.77
• Figure out the methods I should use		0.75
• Figure out what data I should collect		0.75
• Be persistent in seeking an answer		0.72
• Collaborate with other scientists or engineers		0.70
• Generate a research question to answer		0.67
• Be open to criticism		0.65
• Report research results in an oral presentation		0.64
• Show integrity as a scientist or engineer		0.60
• Be a good lab citizen		0.57
• Be meticulous in record keeping		0.55
• Use technical science skills (use of tools, instruments, and/or techniques)		0.54
Sense of Community	12
Q. How well does each statement represent how you feel about the STEM scholar program?
• I am with the other STEM scholars a lot and enjoy being with them.		0.80
• When I have a problem, I can talk about it with members of the program.		0.79
• I can trust people in the program.		0.78
• If there is a problem in the program, members can get it solved.		0.77
• Program members and I value the same things.		0.77
• Members of the program care about each other.		0.73
• Being a member of the STEM scholar program is a part of my identity.		0.68
• I have influence over what the program is like.		0.66
• I expect to be a part of the program for a long time, even after graduation from this university.		0.60
• I get important needs of mine met because I am part of the STEM scholar program.		0.59
• I can recognize most of the members of the program.		0.38
• Most program members know me.		0.38
Scientific Identity	5
Q. Please select the best answer on the scale from strongly disagree to strongly agree.
• I feel like I belong in the field of science or engineering.		0.87
• I have come to think of myself as a ‘scientist' or ‘engineer.’		0.79
• I have a strong sense of belonging to the community of scientists or engineers.		0.79
• The daily work of a scientist or engineer is appealing to me.		0.78
• I derive great personal satisfaction from working on a team that is doing important research.		0.67
Everyday Discrimination	10
Q. In your day-to-day life, how often have any of the following things happened to you?
• You are treated with less respect than other people.		0.82
• People act as if they are better than you.		0.75
• You are treated with less courtesy than other people.		0.75
• You are threatened or harassed.		0.74
• People act as if they think you are not smart.		0.66
• You are called names or insulted.		0.65
• You receive poorer service than other people at restaurants or in stores.		0.62
• People act as if they are afraid of you.		0.61
• You are followed around in stores.		0.56
• People act as if they think you are dishonest.		0.55
Race Centrality	3
Q. Please read each statement below carefully and indicate the extent to which you agree or disagree.
• I have a strong sense of belonging with [own race/ethnicity] people.		0.91
• I feel close to other [own race/ethnicity] people.		0.87
• Being [own race/ethnicity] is an important part of who I am.		0.80
Gender Salience	6
Q. Please read each statement below carefully and indicate the extent to which you agree or disagree.
• Being [my gender] has a lot to do with how I think about myself.		0.89
• Being [my gender] is an important part of my self-image.		0.86
• Being [my gender] is unimportant to my sense of who I am.^a		0.81
• Being [my gender] has little to do with how I think about myself.^a		0.70
• I prefer to read books that are mostly read by [my gender].		0.38
• I prefer to watch movies or television programs that have been made to appeal to [my gender].		0.37
Satisfaction With Life Scale	5
Q. Below are five statements with which you may agree or disagree. Please be open and honest in your responding.
• I am completely satisfied with my life.		0.90
• In most ways, my life is close to my ideal.		0.87
• The conditions of my life are excellent.		0.83
• If I could live my life over, I would change almost nothing.		0.78
• So far, I have gotten the important things I want in life.		0.75
Center for Epidemiologic Studies Depression Scale (CES-D)	12
Q. Below is a list of ways you might have felt or behaved recently. Please tell me how often you have felt this way during the PAST WEEK
• I felt depressed.		0.79
• I was happy.^a		0.73
• I felt that I was just as good as other people.^a		0.70
• I enjoyed life.^a		0.70
• I could not get “going.”		0.69
• My sleep was restless.		0.64
• I felt hopeful about the future.^a		0.59
• I had crying spells.		0.54
• I felt that people disliked me.		0.52
• I felt that everything I did was an effort.		0.48
• I had trouble keeping my mind on what I was doing.		0.40
• People were unfriendly.		0.39

^aThis is a reverse coded item.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Data reported in this report were supported by the Howard Hughes Medical Institute (HHMI) under award number 52008089. The content is solely the responsibility of the authors and does not necessarily represent the official views of the HHMI.

1

We are intentional in the use of the word “retention” to reflect that our study centers on the program retention, which we assert is a function of the university’s effort to retain its students. While our analytic models include student-level measures, which would suggest there were reasons to use the word “persistence”, our aim is to keep the focus on the program’s ability to retain its students, so hence our preference for the word retention over persistence.

2

SSP is the pseudonym used in this study to protect the privacy of participants.

ORCID iD

Leticia Oseguera

Author Biographies

Leticia Oseguera is an associate professor in the Higher Education Program and senior research associate at the Center for the Study of Higher Education in the Department of Education Policy Studies in the College of Education at The Pennsylvania State University.

Javiera De Los Rios is a doctoral student in the Higher Education Program in the College of Education at The Pennsylvania State University.

Hyun Ju Park is a doctoral student in the Higher Education Program in the College of Education at The Pennsylvania State University.

Elyzza M. Aparicio is a doctoral student in the Higher Education Program in the College of Education at The Pennsylvania State University. She is also the associate director of The Office of Undergraduate Research Services at California State University, Long Beach.

Sridevi Rao is a recent doctoral graduate from the Higher Education and Comparative and International Education Programs at The Pennsylvania State University. She is currently working as a retention officer for UT for Me – Powered by Dell Scholars at The University of Texas (UT) at Austin.

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