Student Retention Models in Higher Education: A Literature Review

May 16, 2019
  • AACRAO C&U
  • AACRAO Publications
  • Enrollment Management
  • Retention
  • Retention

By Adam Burke

Abstract

This literature review examines student retention in higher education institutions. Specifically, it looks at the background and history of student retention, three student retention theories, and current literature on student retention within the social system. The three theories are Spady’s (1970, 1971) Undergraduate Dropout Process Model, Tinto’s (1975, 1993) Institutional Departure Model, and Bean’s (1980, 1982) Student Attrition Model. These provide context for a literature review on current publications, focusing mainly on the social (as opposed to the academic) aspect of higher education. Major findings are that the topic of student retention is critical to higher education institutions, but it is highly complex and difficult to predict. The literature is clear that student engagement during the higher education experience leads to higher student retention rates and increased institutional commitment.

Student attrition rates have been one of the most critical issues in higher education for decades. As students fail to persist at higher education institutions, there are impacts on both the academic and social environments. Student persistence also plays a major impact in institutions’ financial planning, as student tuition and fees are major drivers of institutional income. With these facts in mind, it becomes increasingly important to understand what literature and theories exist relative to increasing student success and retention within higher education. The literature is rich with theoretical frameworks as well as qualitative and quantitative research to support understandings of student persistence. This article provides an overview of student retention, some of the theoretical models that exist in the literature, and some of the applied retention research within student affairs.

Definition of Retention

Student retention in higher education is typically defined as the continued enrollment of a student from the first year to the second year (Bean 1980, 1982; Cotton et al. 2017; Farrell 2009; Ishler & Upcraft 2005; Spady 1970; Tinto 1975, 1993). Another term that is used, sometimes interchangeably, is student persistence. However, persistence is typically used to define students’ continued enrollment from years two until graduation (Belch et al. 2001; Chambers & Paull 2008; Kerby 2015). Student retention is critical to the success of higher education institutions as the highest levels of student attrition are from year one to year two (Achinewhu-Nworgu 2017; Blue 2018; Tinto 1975, 1993). The higher the retention rate an institution can achieve, the more students it will maintain who will pay tuition and fees and generate academic achievements—all of which are imperative to institutional success.

Background of Retention in Higher Education

While student attrition has been a critical issue since the establishment of higher education institutions, the theoretical frameworks in which retention is studied are relatively new (Aljohani 2016a, 2016b). The majority of theories that relate to student retention were derived during the early 1970s and have since been added to, revisited, and revised (Tinto 2007, Tudor 2018, West et al. 2016).

Throughout the history of the education system, institutional goals and priorities have shifted away from building individual competencies in a few skill areas and toward the graduation of students (Aljohani 2016a; Bodin & Orange 2018). In the decades that preceded the 1950s, there was no systematic approach to student retention (Aljohani 2016b; Caruth 2018). Following World War II and the expansion of higher education, institutions had to deal with the influx of new students and the increased desire for a college education (Crosling et al. 2008, Logan 2017, Manyanga et al. 2017). The literature argues that during this expansion period, student retention became a global concern, with the result that student retention models were created (Aljohani 2016a, 2016b; Tinto 2007).

Prior to the 1970s the majority of student retention research and theories focused on characteristics of individual students (Aljohani 2016a; Reason 2003; Tinto 1975, 1993). Institutional research prior to the 1970s focused on traits such as gender, socioeconomic class, and race to determine whether any characteristics related directly to student attrition (Reason 2003; Tinto 1975, 1993). Interaction between individuals and institutions was rarely addressed, but beginning in the late 1960s and early 1970s, these relational variables began to be incorporated into student retention models (Aljohani 2016a, 2016b; Bean 1980; Spady 1970, 1971; Tinto 1975).

Methodology

This article has been constructed by reviewing literature and seminal works on student attrition and retention in higher education. The findings of this literature review are presented as two main sub-topics: the theoretical student retention models and current research that impacts and influences those models. Because the field of student attrition is rather extensive, this literature review focuses on the role of social interaction during students’ higher education experience. 

Theoretical Models

Although there are many student retention theoretical models, this literature focuses on three seminal works: Spady’s (1970, 1971) Undergraduate Dropout Process Model, Tinto’s (1975, 1993) Institutional Departure Model, and Bean’s (1980, 1982) Student Attrition Model. All are grounded in sociology and refer to the relationship between the individual and the institution. The majority of the literature expands or tests these theories in their specific setting or application, as in private, distance, and non-traditional learning environments (Guglielmetti 2011; Holmegaard et al. 2017; Page & Kulick 2016). This literature review is through the lens of a public, four-year institution.

Current Research

While student attrition is a major institutional concern, there is still work to be done in determining what an institution can do to improve retention. This literature review focuses on current research (from no later than 2010) on student engagement in higher education. In an attempt to relate the current research to student engagement within the field of student affairs (or non-academic units), many of the articles were attained either from the Recreational Sports Journal or the NASPA Journal.

Current research in the field typically takes specific applications or programs within higher education and tests them to determine their impact on student retention. Many of the articles that are reviewed are specific applications of student retention work and may not be transferrable to other applications or program areas within higher education. That said, one of the consistent themes is that when student engagement increases at an institution, attrition rates decrease (Bean 1980; Belch et al. 2001; Bowman & Culver 2018; Forrester et al. 2018; Grier et al. 2016; Ishler & Upcraft 2005; Kampf & Teske 2013; McElveen & Rossow 2014; Miller 2011; Mosholder et al. 2016; Weaver et al. 2017).

Findings

Theoretical models

The Undergraduate Dropout Process Model (Spady 1970, 1971)

The Undergraduate Dropout Process Model is widely considered to be one of the first theoretical models of student retention in the literature (Tinto 1970, Webb et al. 2017). Spady’s (1970) model was one of the first to incorporate Durkheim’s theory of suicide as it relates to student retention, as both suicide and attrition are forms of removing oneself from society (Spady 1970). This model was one of the first attempts to move toward an interdisciplinary approach to understanding student retention rates (as opposed to looking at the characteristics of individual students independent of the institution).

Spady’s (1970, 1971) starting point was the assumption that the student attrition process is best explained by an interdisciplinary approach that involves both the interaction between the individual student and the particular college environment in which the student’s characteristics are exposed to influences from a variety of sources. The theory assumes that students operate with two main institutional systems: the academic system and the social system. The theory relies on the idea that as students are challenged and exposed to various influences, the systems impact them differently; success in the academic system is measured by grades and in the social system by attitudes, interests, and personality dispositions that are in line with the institution (Spady 1970, 1971).

Durkheim maintains that the likelihood of suicide increases when two types of integration are absent: “insufficient moral consciousness and insufficient collective affiliation” (Spady 1970). Suicide clearly is much more serious and severe than student attrition, yet Spady argues that the social situations present in Durkheim’s theory form a parallel to institutional attrition in that poor performance in the academic system coupled with a lack of consistent, intimate relationships may lead to student attrition.

Spady’s (1970) first Undergraduate Dropout Process Model (which he revised in 1971) tied student attrition rates to four main variables: intellectual development, social integration, satisfaction, and institutional commitment. This model depends on the assumptions (1) that one’s satisfaction with the college experience will depend on the available social and academic rewards and (2) that sustaining one’s commitment to the college requires both integration into the system and a sufficient number of positive rewards (either academic or social) (Spady 1970, 1971). Figure 1 demonstrates how the multiple variables within Spady’s (1970, 1971) model interact with each other.

Figure 1. Spady’s Undergraduate Dropout Process Model (1970)

burke-f1

Institutional Departure Model (Tinto 1975, 1993)

Tinto’s (1975, 1993) Institutional Departure Model is perhaps the most cited and influential theory of student retention. Tinto’s (1975, 1993) theory builds upon Spady’s (1970, 1971) theory utilizing Durkheim’s suicide theory. Tinto (1975) also relies heavily on the social integration writings of Van Gennep (1960), who argued that in tribal societies, there are rituals and rites of passage that apply within social communities and that they must be followed.

Expanding on Van Gennep’s rites of passage in tribal societies, Tinto (1975, 1993) argues that the social transition for incoming, first-year students is essential to their success. During the stage of separation from one life (high school, hometown, etc.) to college, students must develop new relationships and a new community in order to be successful. This can be difficult to accomplish as there are potentially new values, priorities, and behaviors within the college community that students were not exposed to previously.

Like Spady (1970, 1971), Tinto (1975, 1993) acknowledges the presence of two main environmental factors: the academic system and the social system. Tinto (1975, 1993) argues that a student’s decision to leave an institution must be grounded in one of two realms: academic or social. In the academic system, a student must have a certain level of commitment to personal goals (grades, graduation, etc.) to continue to be motivated and persist. Conversely, a student must demonstrate a certain level of institutional commitment, typically evidenced through social network and school pride. The combination of personal goals and institutional commitment is what leads ultimately to a student’s decision to return to school (see Figure 2).

Figure 2. Tinto’s Institutional Departure Model (1975)

burke-f2 

In part because this model is the most cited (Tinto 1975, 1993) and perhaps the most well accepted, it has been repeated, tested, and reviewed repeatedly since its publication. Individuals have taken Tinto’s (1975, 1993) model and applied it to their own specific contexts, including for-profit, public, private, distance, and international education (Gansemer-Topf et al. 2018; Grier-Reed et al. 2016; Mansouri & Moumine 2017; Mosholder et al. 2016; Page & Kulick 2016). These studies have taken the basis of Tinto’s (1975, 1993) model and modified it to meet their and their populations’ needs, but the use of Tinto’s model in multiple contexts gives more credibility and validity (Aljohani 2016a).

Student Attrition Model (Bean 1980, 1982)

Bean’s Student Attrition Model (1980, 1982) postdates Spady (1970, 1971) and Tinto’s (1975, 1993) models and argues that none of the previous models is testable with a direct correlation (Bean 1980). Bean also argues that there is insufficient evidence to support the link between Durkheim’s theory of suicide and student attrition; this is a major difference between the models. Bean’s models (1980, 1982) strive to create a direct path of causality such that administrators can point to a specific variable that indicates why students drop out.

Spady (1970, 1971) and Tinto (1975, 1993) relied on characteristics of individuals and their relationships to their organizations to create their models, but Bean (1980, 1982) took an organizational workplace view. Bean (1980, 1982) argues that the factors that influence workforce turnover correlate directly with student attrition in higher education institutions (Aljohani 2016b). Bean (1980, 1982) argues that the same reasons that a staff member would leave an organization apply to a student leaving an institution.

Bean’s (1980, 1982) theory is grounded in statistical analysis and quantitative data; Spady (1970, 1971) and Tinto’s (1975, 1993) are grounded in sociology and philosophy. One major finding of Bean’s (1980, 1982) is that male and female students leave institutions for different reasons, but institutional commitment is the most important variable in explaining student attrition for both genders. One of the major differences between male and female students is that males leave an institution even though they are satisfied whereas females who are more satisfied are more committed to their institution and are less likely to leave (Bean 1980).

As Figure 3 indicates, Bean’s (1980, 1982) Student Attrition Model includes many variables that impact a student’s decision to persist; most are a function of the institutional structure and organization. Some of the confounding variables that Bean (1980, 1982) considered were university GPA, institutional satisfaction, value of education, student life engagement opportunities, and organizational rules, all of which can lead to a student dropping out or deciding to transfer to a different institution.

Figure 3. Bean’s Student Attrition Model (1980)

burke-f3

Current Research

Throughout Spady (1970, 1971), Tinto, (1975, 1993), and Bean’s (1980, 1982) models are two systems in which students operate: the academic system and the social system. (This is less true of Bean’s (1980, 1982) model, though many of the variables remain.) This review of the research focuses on the social system. Further, the research is considered according to two distinct realms: co-curricular programming, such as housing communities, honors programs, and academic communities outside the classroom, and service programming, which for the purposes of this article focuses on the impacts of campus recreation and related programming.

The literature makes it clear that when students’ sense of belonging increases, their likelihood of being retained from year one to year two increases (Ishler & Upcraft 2005, Logan 2017, Olbrecht 2016). In creating this sense of belonging, many institutions are moving toward cohort models, where students move through coursework together and—at some institutions—even live together. These cohorts often have a focus area, such as STEM, that serve as the common ground for connecting students. These cohort models have been shown to increase retention overall and have been particularly successful with female and minority students (Dagley et al. 2016, Sithole et al. 2017).

Students who participate in honors programs, intrusive advising, and living-learning communities within residence halls have higher retention rates and higher overall GPAs than their campus peers who do not (Bowman & Culver 2018, Reader 2018, Soria & Taylor 2016). Like academic cohort models, these co-curricular program areas provide students with opportunities to interact with like-minded peers and have been shown to improve students’ satisfaction with the institution (Bowman & Culver 2018; Reader 2018; Soria & Taylor 2016). Similar co-curricular programming can be more impactful in terms of retention of students from historically underrepresented groups (Bowman & Culver 2018, Grier-Reed et al. 2016, Mosholder et al. 2016).

Campus recreation is a known resource and service that is available at the majority of four-year higher education institutions. The presence of a recreation center has been shown to increase the retention of students as it impacts their sense of belonging and institutional commitment (Forrester 2015, Forrester et al. 2018, Kampf et al. 2018, Miller 2011). It has also been shown that the newer the campus recreation facility, whether new build or renovation, the greater the impact of the space and its programming on student retention (Kampf et al. 2018).

Campus recreation usage and programming has also been examined to determine whether participation affects student success and retention. The two areas that have been studied most are intramural sports and club sport participation. Intramural sports are defined as sports offered at an institution where students create teams to play other teams at their institution; club sports are teams that represent an institution and travel to compete against teams representing other institutions. The required level of commitment and dedication is one of the major differences between the two programs, with intramurals being more informal and club sports requiring a greater commitment.

In their investigation of the impact of intramural sports, McElveen & Rossow (2014) found no significant difference between the academic performance (GPA) of individuals who participate in intramurals “moderately to heavily” and those who do not participate at all. These results were interpreted to indicate that social interaction and participation in co-curricular activities do not impact a student’s academic success. McElveen & Rossow (2014) did find, however, that individuals who participate in intramurals were retained at a higher percentage than were those who did not.

Current research indicates that club sport members are retained at higher rates than non-members but generally finds no significant difference between their academic performance and that of non-participants (Forrester 2015, Kampf & Teske 2013). The authors suggest that participants’ increased retention is the function of social integration and that students who feel connected are more likely to persist. Kampf and Teske’s (2013) study also found that club sport participation remained the most significant predictor of persistence over most demographic characteristics, implying that social integration was more important than pre-college characteristics as an indicator. Weaver et al. (2017) noted that club sport programs can influence students’ choice of institution, and when community is created, students are more likely to persist.

Discussion

The theoretical models and literature agree that student retention is critical for higher education institutions and that student attrition is a complicated multivariate issue. While the Spady (1970, 1971), Tinto (1975, 1993), and Bean (1980, 1982) models focus on different aspects of higher education, they acknowledge that both the academic and social spheres influence students’ persistence. However, the models do not agree on how the different systems interact; Spady’s (1970, 1971) model is the most linear, and Bean’s (1980, 1982) model contains the most singular variables.

While the models disagree as to how different variables interact with one another, they agree that student retention is difficult to fully comprehend. Some of this difficulty can be attributed to students’ characteristics and lived experiences. Educational backgrounds, personality characteristics, and social norms all potentially impact a student’s ability to succeed in higher education and are extremely difficult to measure and account for in theoretical models. The number of controllable variables could limit the extent to which some of the theories can be applied.

Current research agrees that student engagement in co-curricular programming increases retention. The literature (Belch et al. 2001; Bowman & Culver 2018; Forrester et al. 2018; Kampf & Teske 2013; McElveen & Rossow 2014; Sithole et. al. 2017) suggests that type of engagement—whether living-learning community within a residence hall, campus recreation programming, or academic co-curriculars, such as an honors program—does not matter; students engaged in any of these areas demonstrated higher retention rates than did their “academic” peers. The literature and theoretical models also argue that creating positive social communities is vital to improving a student’s institutional commitment and decreasing the likelihood of dropping out.

The current research around student engagement, within the social sphere, directly influences one of the two main emphasis areas present in all three student retention models. Spady (1970, 1971), Tinto (1975, 1993), and Bean (1980, 1982) all rely on both academic and social factors within their models and that while a significant amount of current research focuses on the social sphere, student backgrounds, demographics and lived experiences all correspond to student academic success (Reason, 2013; Webb et.al., 2017).  The three models demonstrate the complicated interplay between social and academic variables and their impacts on student attrition. These models, when combined with current research show that students are more likely to persist when both their academic and social spheres are well developed and intentionally addressed.

Implications

The theoretical models and literature suggest that student retention rates need to be addressed within both the academic and social systems. Institutions striving to increase retention will need to invest in staff as well as programming. Providing professional development, increasing staff compensation, and creating a healthy culture to promote the services that lead to student retention efforts are all important. In addition, institutions will need to invest in new and innovative programming to engage students and increase their institutional commitment. Often, programming is limited by staff capacity or budgetary concerns, but institutions have the ability to address these issues if they choose.

The current research and theoretical models also suggest that higher education institutions must be cognizant of the demographics and backgrounds of incoming students. As institutions look to increase enrollment into the future, they will need a fundamental understanding of the demographic shift within higher education. From 1980 to 2020 the United States white, working-age population (25-64) is projected to decrease from 81.9% to 62.5% (Zumeta et. al., 2015). This decrease in white working-age individuals shows that the increase in ethnic minority individuals will increase, over the same time span from 18.1% to 37.5% (Zumeta et. al., 2015). This demographic shift in working-age individuals will have an impact on college enrollment demographics, and the three student attrition models from Spady (1970, 1971), Tinto (1975, 1993), and Bean (1980, 1982) argue that this should influence how higher education institutions are providing academic and social support. 

Conclusion

Among the several theoretical models explored in this literature review, there is consensus that greater understanding is needed as to why students choose to drop out of college. The models suggest that students’ pre-determined characteristics and interactions with the academic and social systems within their institutions influence their decisions to persist. Literature focused on the social system clearly communicates that students’ engagement during their higher education experience is extremely important to retention. The literature also shows that engagement creates a higher level of institutional commitment, which in turn increases students’ likelihood of persistence.

References

Achinewhu-Nworgu, E. 2017. Comparing student retention in a public and a private college: Implications for tackling inequality in education. In BCES Conference Books (Volume 15), Sofial, Bulgaria: Bulgarian Comparative Education Society. Available from: http://libproxy.uwyo.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=eric&AN=ED574199&site=ehost-live

Aljohani, O. 2016a. A comprehensive review of the major studies and theoretical models of student retention in higher education. Higher Education Studies, 6(2): 1–18.

———. 2016b. A review of the contemporary international literature on student retention in higher education. International Journal of Education and Literacy Studies, 4(1): 40–52.

Bean, J. 1980. Dropouts and turnover: The synthesis and test of a causal model of student attrition. Research in Higher Education, 12 (2): 155–87. Available at: https://doi.org/10.1007/BF00976194

———. 1982. Conceptual models of student attrition: How theory can help the institutional researcher. New Directions for Institutional Research, 1982(36): 17–33. Available at: http://dx.doi.org/10.1002/ir.37019823604

Belch, H. A., M. Gebel, and G. M. Maas. 2001. Relationship between student recreation complex use, academic performance, and persistence of first-time freshmen. NASPA Journal, 38(2): 254–68. Available at: https://doi.org/10.2202/1949-6605.1138

Blue, A. 2018. Exploring mentoring strategies needed by higher educational managers to increase student retention rates and decrease dropout rates in a higher education organization. ProQuest LLC. Ann Arbor, MI. Available at: https://eric.ed.gov/?id=ED585882

Bodin, R., and S. Orange. 2018. Access and retention in French higher education: Student drop-out as a form of regulation. British Journal of Sociology of Education, 39(1): 126–43.

Bowman, N. A., and KC Culver. 2018. When do honors programs make the grade? Conditional effects on college satisfaction, achievement, retention, and graduation. Research in Higher Education, 59(3): 249–72.

Caruth, G. D. 2018. Student engagement, retention, and motivation: Assessing academic success in today’s college students. Participatory Educational Research, 5(1): 17-30.

Chambers, D., and A. Paull. 2008. Landscape study of student lifecycle relationship management. Bristol, UK: JISC.

Cotton, D. R.E., T. Nash, and P. Kneale. 2017. Supporting the retention of non-traditional students in higher education using a resilience framework. European Educational Research Journal, 16(1): 62–79. Available at: https://doi.org/10.1177/1474904116652629

Crosling, G, L. Thomas, and M. Heagney. 2008. Improving Student Retention in Higher Education: The Role of Teaching and Learning. London: Routledge.

Dagley, M., M. Georgiopoulos, A. Reece, and C. Young. 2016. Increasing retention and graduation rates through a STEM learning community. Journal of College Student Retention: Research, Theory & Practice, 18(2): 167–82.

Farrell, P. L. 2009. Investing in staff for student retention. NEA Almanac of Higher Education, 85–92.

Forrester, S. 2015. Benefits of collegiate recreational sports participation: Results from the 2013 NASPA assessment and knowledge consortium study. Recreational Sports Journal, 39(1): 2–15. Available at: https://doi.org/10.1123/rsj.2015-0005

Forrester, S. A., K. McAllister-Kenny, and M. Locker. 2018. Association between collegiate recreational sports involvement and undergraduate student retention. Recreational Sports Journal, 42(1): 64–74. Available at: https://doi.org/10.1123/rsj.2017-0004

Gansemer-Topf, A. M., J. Downey, K. Thompson, and U. Genschel. 2018. Did the recession impact student success? Relationships of finances, staffing and institutional type on retention. Research in Higher Education, 59(2): 174–97.

Grier-Reed, T., F. Arcinue, and E. Inman. 2016. The African American student network: An intervention for retention. Journal of College Student Retention: Research, Theory & Practice, 18(2): 183–93.

Guglielmetti, S. G. C. 2011. University life of non-traditional students: Engagement styles and impact on attrition. The Journal of Higher Education, 82 (1): 33–53.

Holmegaard, H. T., L. M. Madsen, and L. Ulriksen. 2017. Why should European higher education care about the retention of non-traditional students? European Educational Research Journal, 16(1): 3–11.

Ishler, J. L., and M. L. Upcraft. 2005. The Keys to First-Year Student Persistence. Challenging and Supporting the First-Year Student. San Francisco: Jossey-Bass.

Kampf, S., S. G. Haines, and S. Gambino. 2018. The impact of new or renovated collegiate recreation centers on recruitment and retention. Recreational Sports Journal, 42(1): 18–32. Available at: https://doi.org/10.1123/rsj.2017-0005

Kampf, S., and E. J. Teske. 2013. Collegiate recreation participation and retention. Recreational Sports Journal, 37(2): 85–96. Available at: https://doi.org/10.1123/rsj.37.2.85

Kerby, M. B. 2015. Toward a new predictive model of student retention in higher education: An application of classical sociological theory. Journal of College Student Retention: Research, Theory & Practice, 17(2): 138–61.

Logan, M. L. 2017. Provisional admission in higher education: A case study in retention, persistence, and matriculation in academia. Ann Arbor, MI: ProQuest LLC. Available at: https://eric.ed.gov/?q=Clark&pg=5&id=ED578548  

Mansouri, Z., and M. El Amine Moumine. 2017. Outlook on student retention in higher education university reforms in Morocco. International Journal of Education and Literacy Studies, 5(2): 53–60.

Manyanga, F., A. Sithole, and S. M. Hanson. 2017. Comparison of student retention models in undergraduate education from the past eight decades. Journal of Applied Learning in Higher Education, 7 (January): 30–42.

McElveen, M., and A. Rossow. 2014. Relationship of intramural participation to GPA and retention in first-time-in-college students. Recreational Sports Journal, 38 (1): 50–54. Available at: https://doi.org/10.1123/rsj.2013-0024

Miller, J. J. 2011. Impact of a university recreation center on social belonging and student retention. Recreational Sports Journal, 35(2): 117–29. Available at: https://doi.org/10.1123/rsj.35.2.117

Mosholder, R. S., B. Waite, C. A. Larsen, and C. Goslin. 2016. Promoting Native American college student recruitment & retention in higher education. Multicultural Education, 23(3): 27–36.

Olbrecht, A. M., C. Romano, and J. Teigen. 2016. How money helps keep students in college: The relationship between family finances, merit-based aid, and retention in higher education. Journal of Student Financial Aid, 46(1). Available at: https://publications.nasfaa.org/jsfa/vol46/iss1/2/

Page, E., and M. Kulick. 2016. Student satisfaction as a predictor of retention in a professional online for-profit higher education institution. Online Journal of Distance Learning Administration, 19 (4). Available at: https://eric.ed.gov/?id=EJ1124529

Reader, C. M. 2018. The effectiveness of intrusive advising programs on academic achievement and retention in higher education. ProQuest LLC. Available at: https://eric.ed.gov/?id=ED585898

Reason, R. D. 2003. Student variables that predict retention: Recent research and new developments. NASPA Journal, 40 (4): 172–91. Available at: https://doi.org/10.2202/1949-6605.1286

Sithole, A., E. T. Chiyaka, P. McCarthy, D. M. Mupinga, B. K. Bucklein, and J. Kibirige. 2017. Student attraction, persistence and retention in STEM programs: Successes and continuing challenges. Higher Education Studies, 7 (1): 46–59.

Soria, K. M., and L. Taylor Jr. 2016. Strengths-based approaches in college and university student housing: Implications for first-year students’ retention and engagement. Journal of College and University Student Housing, 42 (2): 60–75.

Spady, W. 1970. Dropouts from higher education: An interdisciplinary review and synthesis. Interchange 1(1): 64–85. Available from: http://dx.doi.org/10.1007/BF02214313

———. 1971. Dropouts from higher education: Toward an empirical model. Interchange 2(3): 38–62. Available at: http://dx.doi.org/10.1007/BF02282469

Tinto, V. 1975. Dropout from higher education: A theoretical synthesis of recent research. The Review of Educational Research, 45(1): 89–125.

———. 1993. Leaving College: Rethinking the Causes and Cures of Student Attrition. 2nd ed. Chicago: University of Chicago Press.

———. 2007. Research and practice of student retention: What next? Journal of College Student Retention, 8(1): 1–19.

Tudor, T. R. 2018. Fully integrating academic advising with career coaching to increase student retention, graduation rates and future job satisfaction: An industry approach. Industry and Higher Education, 32(2): 73–79.

Van Gennep, A. (1960). The rites of passage. Chicago, IL: Chicago University Press.

Weaver, A. G., D. J. Forte, and C. W. McFadden. 2017. Perceptions of higher education administrators regarding the role of club sports in the recruitment and retention of male students. Recreational Sports Journal, 41(1): 42–54. Available at: https://doi.org/10.1123/rsj.2016-0023

Webb, O., L. Wyness, D. Cotton. 2017. Enhancing access, retention, attainment and progression in higher education: A review of the literature showing demonstrable impact. Heslington, York, UK. Higher Education Academy. Available at: https://www.heacademy.ac.uk/knowledge-hub/enhancing-access-retention-attainment-and-progression-higher-education

West, D., D. Heath, and H. Huijser. 2016. Let’s talk learning analytics: A framework for implementation in relation to student retention. Online Learning, 20(2): 30–50.

Zumeta, W., David W. Breneman, Patrick M. Callan, & Joni E. Finney. (2015). Financing American Higher Education in the Era of Globalization. (2nd ed.). Cambridge, MA: Harvard Education Press.

 

Adam Burke is the Assistant Director of Programs for the Department of Campus Recreation at the University of Wyoming. He is currently working on his Doctorate of Education in Higher Education Administration at the University of Wyoming. Previously, Adam attained his B.S. degrees at Colorado State University and his M.S. degree from Oregon State University. He has research interests in the areas of non-academic staff impacts on student success and the impacts and implications of non-academic staff on student attrition rates.