Factors Affecting Student Retention At UVSC Affecting Student Retention At UVSC ... (1996) found...

Factors Affecting Student Retention At UVSC

Department of Institutional Research & Management Studies

December 1998

Prepared By Jeff Hoyt

Senior Research Analyst

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IntroductionThe present study was initiated as a component of a campus retention effort and focuses

on factors impacting attrition at Utah Valley State College (UVSC). The report begins with aliterature review of prior studies on student attrition and interventions used to improve the collegesuccess of students. Descriptive information on the relationship between retention and first termacademic performance, financial aid, and student characteristics is then presented. Several factorsare then analyzed in a regression analysis to identify those with the largest direct impact onstudent retention.

Literature ReviewThere are several theoretical models that attempt to explain student retention or college

persistence. In Tinto’s model, retention is impacted by a student’s pre-entry attributes, goals andcommitments, academic and social integration (Tinto, 1975, 1993). Bean and Metzner (1985)developed a model conceptualizing student persistence as dependent on a student’s background,academic variables, environmental variables including employment and finances, and socialintegration. Cabrera et al, (1992) integrated the Tinto model and the Bean and Metzner modelfinding that both provided unique insights, but also measured similar constructs. The presentstudy conformed more closely with the conceptual model proposed by Bean and Metzner.

An extensive amount of research has been conducted on retention in higher educationusing various different methods and approaches. Several studies used the Bean and Metzner orTinto models assessing the impact of various factors on student retention (Bers and Smith, 1991;Feldman, 1997; Windham, 1995; Voorhees, 1987). There were conflicting findings betweenmany of these studies as to whether gender, student goals, need for remedial education, studentgrade point averages, contact with faculty, or hours studied were related to student persistence. The studies were consistent in finding that older students, part-time students, minority students,and working adults had higher drop out rates.

These studies examined student retention over one year or two semesters, which was ashort time frame. Using a short time frame does not account for students who stop out and stillmay have a successful college experience (Bonham and Luckie 1993; Grosset, 1993). In addition,student transfer to other institutions was not considered in the studies. If successful students areincluded in the group that is not retained, it may confound the results of retention studies.

Pascarella, Smart, and Ethington (1993) studied the degree persistence of 825 studentsfrom 85 different colleges over a nine year period. Academic and social integration weresignificant predictors of persistence for males and females. Socioeconomic status was animportant factor for females, and institutional commitment or satisfaction was significant formales. However, less than 26 percent of the variation in degree attainment was explained in thestudy.

Other researchers used questionnaires to understand the extent to which a student’sexpectations about college were met and how this was related to retention (Bank, Biddle, andSlavings, 1992; Braxton, Vesper, and Hossler, 1995). If students expectations were met, itincreased persistence or intent to persist; however, expectations explained only a small percentageof the variance in student retention. In addition to predictive studies, survey and qualitative

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research was often used to understand the expectations, concerns, and needs of college students(Gallagher, Golin, and Kelleher, 1992; Levine and Cureton, 1993).

There is evidence that a student’s declaration of a college major or career has an impacton retention. Lewallen (1993) concluded that there was no relation between being initiallyundecided and retention. However, Foote (1980) found a significant relationship when looking ata student’s declared major during their experience at the institution. Although Foote showed thatstudents with undeclared majors had higher attrition rates; the relative importance of this variablein relation to other factors was not assessed in the study. Additional support is provided byPeterson (1993) who found that a student’s career decision making self-efficacy was related toacademic and social integration.

The institutional environment or organizational characteristics have been considered inother research. Studies indicate student feelings of alienation may be greater in larger institutions. Tomlinson-Clarke and Clarke (1996) found that men experienced more alienation and expressedmore uncertainty than women in their decision to continue their studies. Students who lived oncampus were shown to have a greater sense of community and higher retention rates in otherstudies (Lounsbury and DeNeui, 1995; Thompson, Smairatedu, and Rafter, 1993). Berger andBraxton (1998) showed that institutional communication, fairness in policy and decision making,and participation was positively related to social integration and had significant indirect effects onstudent retention (Berger and Braxton 1998). Others believed that the quality of a student’sexperience in the classroom was central to student retention (Tinto 1997; Ritschel 1995).

There have also been many studies conducted on special student populations that havehigher drop out rates. For older or non-traditional students, researchers reported that most werepart-time students and the large majority worked while attending college. However, persistencerates were still lower for non-traditional students who worked more hours and only attended part-time (Naretto, 1995). They also found that a supportive social environment was also important tothe retention of non-traditional students (Naretto, 1995; Ashar and Skenes, 1993). One authorasserted that there may be misconceptions about the lack of academic skills and abilities for non-traditional students. The withdrawal rates for non-traditional students in one study was notexplained by deficiencies in their academic ability (Richardson, 1994).

Numerous studies have also been conducted on minority student groups who are at highrisk of dropping out of college. For example, Nora and Cabrera (1996) found that students ofcolor often believed that the campus environment was discriminatory, and they were somewhatless prepared for their college studies than Caucasian students. Their cumulative GPA wasdirectly related to college persistence. Parental support, social integration, perceptions ofdiscrimination, and academic/intellectual development were indirectly related to student retention. Smedley, Myers, and Harrell (1993) used a series of instruments to assess sources of stress forminority students. They reported that student stress and additional stress associated with minoritystatus increased the risk for minority students. Students of color experienced stress related toacademic achievement which was correlated with lower grades. When matching Black andCaucasian students with similar academic achievement, Augelli and Hershberger (1993) foundthat students of color had greater concerns with finances, had lower satisfaction with theinstitution, and frequently experienced verbal harassment. About 10 percent were threatened, 3percent were assaulted, and 2 percent were spat upon. In a study of Hispanic students, Solis

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(1995) showed that satisfaction with instruction and academic experiences were related to astudent’s commitment to attend. Family support and future job prestige increased a student’smotivation to persist.

To reduce student attrition, colleges and universities have developed several programs orinterventions. College and universities often use inventories to assess student needs (Picklesimerand Miller, 1998; Himelstein, 1992; Ryland, Riordan, and Brack, 1994). If students are identifiedas high risk on the inventories, they are given additional assistance. Others have supported theuse of freshmen first year programs, seminars or orientation courses to help students learn studyskills, understand college expectations, and link them with student support services (Kluepfel,1994; Glass and Garrett, 1995; Singleton, Garvey, and Phillips, 1998; Wolfe, 1993; Fidler andGodwin, 1994).

Several other programs attempt to improve retention by focusing on a student’s academicperformance. Rutgers’ University identified high risk courses that student’s frequently failed atthe college (Kluepfel, Parelius, and Roberts, 1994). Each department developed gateway coursesto prepare students for these courses. At Oklahoma State University, students on academicsuspension took a study skills course and received additional advising, but the intervention did notimprove subsequent success (Schultz et. al, 1992). However, others demonstrated that studyskills programs were effective (Polansky, Horan, and Hanish 1993). Simmons (1994) believedthat data on the first term performance of remedial education students involved in a summertransition program supported the efficacy of the program.

Institutions also focused on assessing and improving academic advising (Kern and Engels,1996). At one institution, students requested access to advising in the evenings, desired moreinformation on career and job pursuits, needed more time with advisors, and wanted moreassistance in learning study skills.

Institutions sometimes establish a center or division for undeclared freshmen (Toder andHartsough, 1993; Jones and Schultz, 1992). Faculty volunteers were used in these programs toprovide advising to undeclared students. Toder and Hartsough used a control group design todemonstrate the effectiveness of the center at their institution.

Other programs used to increase retention include student orientation programs, supportcounseling groups, mentoring programs, honors programs, and service learning (Altizer andPatterson, 1994; Brown 1994; Perkins, Paradowski, and Hirchert, 1994; Sax and Astin, 1997;Rao, 1998; Kish and Rita, 1994; Capello, 1994). Some authors recommended mandatoryorientation programs and basic skills assessment, completion of remedial work before regularcollege level courses, abolishing late registration, establishing mentoring and peer supportprograms, reducing academic loads for working students, providing more financial aid, andconducting more program evaluations (Rouche and Rouche, 1994).

In summary, student retention is a very complex issue. There are many possible factorsthat can directly and indirectly influence a student’s decision to persist. For this reason, collegesand universities use several interventions in an attempt to reduce attrition. An effective studentretention program requires a campus-wide effort. In addition, it would be difficult, if notimpossible, to obtain the information from so many areas in any given study to comprehensivelystudy student retention. There are also many different student sub-populations. Specificinfluences may be different for each group.

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The present study is one effort to study factors affecting student retention. It contributesto the current literature by studying not only overall retention rates, but factors impacting theretention of remedial education students.

MethodsSeveral cohorts were tracked over time to determine how many students graduated,

transferred to other colleges and universities, were stilled enrolled, or dropped out of college. Fall entering freshmen were identified by obtaining a student’s first term taking a college courseon the UVSC campus. Students transferring in with credit from another college or universitywere eliminated from the cohorts. Information in the student information system, new studentsurvey, records from the Commissioner’s Office, and records from Brigham Young Universitywere used to identify students transferring to UVSC from other institutions. Students classified asreadmitted in the student information system were also excluded from the cohorts. Concurrent ordual enrolment students were included only if they attended a regular college course on the UVSCcampus.

Students who received a degree or certificate at UVSC were classified as graduates. Records from the Commissioner’s Office and Brigham Young University were used to identifystudents who transferred to another college or university in the state before earning a degree orcertificate at UVSC. Students may have transferred out of state, but records to determine thiswere not available for the study. Finally, students were categorized as still enrolled at the collegeif they were taking courses during fall 1998. All other students were considered drop outs ornon-continuing students.

A large number of students at UVSC stop out and later resume their studies. They maystop out due to finances, short term family situations, or other reasons, but they may still earn adegree or transfer. Many students serve a religious mission in the state, which lasts for 1 ½-2years. There is no accurate record of how many students at the college interrupt their studies toserve a a mission.

The mission factor was accounted for by looking at retention over at least a three-yearperiod of time. This allowed enough time for the large majority of students to return from amission and enroll in college. Because of the mission factor, only the cohorts for fall 1993, 1994,and 1995 were used to identify risk factors that predicted whether a student dropped out orsuccessfully completed their studies.

Descriptive statistics were used to examine the retention rates of students with specificcharacteristics mentioned in the literature review as important predictors of retention. Information from the new student survey was used for remedial education students, but was notused for all students because students with high ACT scores often did not complete the survey.

Overall Retention RatesIn general, the college has very low retention rates for students. Over half the students

drop out of college failing to earn a degree or transfer. The college generally loses 30 to 35percent of its students from fall to spring and nearly 60 percent of its students by the following fall(Tables 1 and 2). Up to 25 percent of the students not enrolled the following fall eventuallyreturned and resumed their studies on campus. Many of these students may have served a

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religious mission, returned, and enrolled in courses at the college. Other students may take atemporary break from their studies for other reasons.

Table 1: Fall to Spring Retention

Fall Cohort Continuing Next Spring Stop-Out Non-Continuing1

1993 2,140 1,605 (75.00%) 311 (14.53%) 224 (10.47%)

1994 2,659 1,733 (65.17%) 331 (12.45%) 595 (22.38%)

1995 2,888 1,898 (65.72%) 305 (10.56%) 685 (23.72%)

1996 2,886 1,880 (65.14%) 203 ( 7.03%) 803 (27.82%)

1997 3,017 2,037 (67.52%) 117 ( 3.88%) 863 (28.60%) Students who later returned and took courses at any time prior to fall 1998.1

Table 2: Fall to Fall Retention

Fall Cohort Continuing Next Fall Stop-Out Non-Continuing1

1993 2,140 1,064 (49.72%) 535 (25.00%) 541 (25.28%)

1994 2,659 1,010 (37.98%) 557 (20.95%) 1,092 (41.07%)

1995 2,888 1,076 (37.26%) 491 (17.00%) 1,321 (45.74%)

1996 2,886 1,147 (39.74%) 232 ( 8.04%) 1,507 (52.22%)

1997 3,017 1,195 (39.61%) 1,822 (60.39%) Students who later returned and took courses at any time prior to fall 1998.1

Because of the stop out behavior of students, student success at the college needs to beexamined over several years. This study found that up to 20 percent of students who attendedUVSC earned a degree or certificate (Table 3). Another 10 to 14 percent transferred to BYU orother public colleges and universities in the state. When accounting for students still enrolled atthe college, the drop out rate ranged from 54 to 64 percent.

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Table 3: Student College Success

Fall Cohort Graduated Transferred Enrolled Drop-Out1 2

1993 2,140 438 (20.47%) 298 (13.93%) 246 (11.50%) 1,158 (54.11%)

1994 2,659 338 (12.71%) 275 (10.34%) 392 (14.74%) 1,654 (62.20%)

1995 2,888 242 ( 8.38%) 195 ( 6.75%) 595 (20.60%) 1,856 (64.27%)Students transferring before earning a degree or certificate at UVSC.1

Students still enrolled during fall 1998.2

Factors Related to Student RetentionThe primary factors that impacted student retention in this study were related to academic

issues and financial support. Non-traditional students (those starting college when 25 years orolder) had the highest drop out rates. Students of color also had high drop out rates. The presentstudy did not focus on factors other than student characteristics, goal commitment, academicvariables, and financial support. Academic Issues

The most important influence on student retention identified in this study was theacademic performance of students. Grades for a student’s first term at the college wereassociated with whether a student persisted in their studies (Table 4). Drop out rates weresubstantially higher for students with GPA’s below a B- during their first term at the college. Fora more recent cohort (1997), about 40 percent of the students had first term GPA’s below a B-.

A student’s need for remedial education also affected their academic performance duringtheir first term at the college. In a prior study conducted by the department, Level of MathPreparation in High School and Its Impact on Remedial Education, a student’s high schoolpreparation determined their need for remedial education at the college (Institutional Research,1998). The college is dependent upon local high schools, and has limited control over theacademic preparation of students who attend UVSC.

Table 4: First Term GPA and Persistence

First Term GPA Fall Cohorts and Drop Out Rates1

1993 1994 1995

3.7 to 4.0 46% 46% 56%

2.7 to 3.69 48% 55% 55%

1.7 to 2.69 61% 66% 69%

0 to 1.69 78% 86% 84%

Drop out rates as of fall 1998.1

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Financial SupportIn addition to academic issues, the second most important factor that influenced student

retention was the financial support that students received or were offered by the college. Studentswho were offered any type of financial aid such as scholarships, grants, loans, or work study hadhigher retention rates than students who did not receive financial aid (Table 5). Students whowere offered scholarships had the highest retention rates. Scholarships at the college are awardedusing several criteria such as community service, grades, or major, and may be targeted to specialstudent populations.

Table 5: Financial Aid Offered and Persistence

Category Fall Cohorts and Drop Out Rates1

1993 1994 1995

Scholarships 43% 39% 49%

Loans 45% 57% 56%

Grants 47% 57% 58%

Any Financial Aid 45% 52% 55%

No Financial Aid 63% 69% 70%


About 33 percent of the students in the fall 1997 freshmen cohort were offered financialaid. Virtually all students accepted grants, scholarships, and loans offered by the college. About89 percent accepted work study when it was offered. The college offered work study to 1percent of the students, grants to 15 percent, scholarships to 19 percent, short-term loans to 14percent, and long term loans to 9 percent of the students.

Total aid offered by the college in academic year 1997 included $2.2 million in short termloans, $5.8 million in long term loans, $5.1 million in grants, $1.4 million in scholarships, and$206,070 in work study. The average amount of financial aid offered to students was $1,921 forthe year. About 49 percent of all students (15,994) attending the college in fall 1997 were offeredfinancial aid.

Student Populations The research literature highlights several sub-populations of students who may be at

greater risk of dropping out of college. These groups include students of color, non-traditionalstudents (over 24 years of age when starting college), disabled students, remedial educationstudents, first generation students, single parents, working adults, part-time students, and so on. Students with greater persistence included concurrent enrolment students, full-time students, andthose with higher family incomes.

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Students may be included in more than one sub-population, making it difficult to createhomogeneous groups. However, these classifications are still useful in understanding studentretention. Each of these groups have their own risk factors and challenges to overcome whenearning a college degree. Nontraditional students had a drop out rate of nearly 80 percent ormore (Table 6). The drop out rate for students of color was 73 percent or higher.

Table 6: Student Populations and Retention


1993 1994 1995

Concurrent Enrolment 42% 46% 46%

Full-Time 48% 57% 60%

Non-Remedial 51% 59% 60%

Disabled 56% 64% 75%

Remedial 58% 65% 67%

Part-Time 61% 67% 68%

Students of Color 73% 74% 77%

Non-Traditional 79% 79% 86%2

Drop out rates as of fall 1998. 1

Students older than 24 when starting college.2

Each of these groups make up a different percentage of the overall student population. Although retention for disabled, students of color, and non-traditional or older students is lower,they make up a smaller percentage of the overall student population (Chart 1). On the other hand,remedial education students and part-time students make up a large percentage of the studentpopulation on campus.

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*Estimated from prior years.

Remedial EducationThere are no admission requirements to attend UVSC because the college is an open

admissions institution. Due to this, many students attending the institution are underprepared forcollege. This requires the college to operate a large remedial education program. The collegeoffers several remedial math, English, and reading courses to bring students up to a college levelof performance.

Remedial education rates were based on the COMPASS and DRP test scores of students. A student’s test was used to determine remedial placement if it was taken three months beforetheir first regular term or within two months after the start of the term. This ensured that the testwas taken after a student completed their high school studies, except for a few early admissionstudents. It also excluded other instances where students retake tests after attending courses oncampus. The 1993 and 1995 cut scores were used to identify remedial education students foreach version of the test.

In another study conducted by the department, Competency Test Analysis, there was aweak relationship between COMPASS writing test scores and grades in College Writing courseson campus. The test scores were used in this analysis to determine if their was a relationshipbetween remedial education and student retention (Institutional Research, 1997). The prior study

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indicated that the low correlation could be due to several factors such as possible grade inflationfor unprepared students in English classes, a student’s study skills or effort in the course, etc.

The present study indicated that about half the students at the college required remedialeducation in at least one area (Table 7). The low level of academic preparation for many studentsat the college has a negative impact on student retention. Remedial education students maybecome discouraged taking several remedial courses and may have difficulty in their academicsubjects.

Table 7: Remedial Education Students

Fall Cohort Remedial Non-Remedial Total

1993 1,110 52% 1,030 48% 2,140

1994 1,415 53% 1,244 47% 2,659

1995 1,583 55% 1,305 45% 2,888

1996 1,240 43% 1,646 57% 2,886

1997 1,459 48% 1,558 52% 3,017

Remedial education students had lower retention rates than students prepared for college

level work (Table 8). As the number of remedial areas for students increased, their drop out ratesconsistently increased. For example, 64 to 72 percent of students who required remedialeducation in three areas (math, English, and reading) eventually dropped out of college.

Table 8: Remedial Education and Persistence


1993 1994 1995

Non-Remedial 51% 59% 60%

One Area 55% 60% 63%

Two Areas 58% 67% 70%

Three Areas 64% 68% 72%


Many remedial education students needed remediation in several areas. For the fall 1997cohort, 21 percent of students required remedial education in two areas, and 11 percent requiredremedial education in three areas. About 44 percent needed remedial math courses, 34 percentneeded remedial English, and 12 percent needed remedial reading courses.

The need for remedial education was also related to a student’s GPA during their firstterm at the college. For the 1997 cohort, the average first term GPA for non-remedial students

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was 2.8. Remedial education students had an average first term GPA of 2.54, with most studentsearning “C” grades in courses. Those needing two areas of remedial education had a first termGPA of 2.47, and those needing remedial courses in all three areas had an average first term GPAof 2.30. In other words, a lack of preparation for college substantially reduces a students’chances of college success by decreasing their ability to perform academically. With such a largeremedial population at the college, it creates a considerable challenge for the faculty and theinstitution.

Students of ColorAlthough students of color are only about 5 percent of the student population, they are an

important group within the college and increase diversity. For the fall 1997 cohort, 3 percent ofthese students were Black, 53 percent were Hispanic, 20 percent were American Indian/AlaskanNative, and 24 percent were Asian. Although academic factors explained higher drop out ratesfor students of color, other factors such as racism or not feeling accepted on campus may be otherinfluences that impact their retention.

There were some important differences between students of color and other students atthe college. First of all, there were substantially more males (66 percent) than females (34percent) in the minority student group. About 46 percent received financial aid, which was higherthan most students. About 27 percent received grants compared with only 15 percent of allstudents on campus.

Students of color had higher remedial placement rates than students in general. Therewere 62 percent that tested into remedial education, with 57 percent requiring remedial math, 51percent remedial English, and 26 percent remedial reading. More than twice as many (24percent) needed remedial education in three areas, compared with all students in general (11percent). Their average first term GPA was 2.41, similar to students requiring remedial educationin two areas.

There were similarities and differences among the ethnic groups in the 1997 cohort. Blacks, Hispanics, and American Indians/Alaskan Natives were similar in their levels ofremediation, and first term GPA. The average first term GPA for Asian students was 2.76. Thiswas substantially higher than the other groups. The difference in first term GPA for Asianstudents was consistent over time. However, the remedial placement rate for Asian students washigher than most students, but lower than the remedial placement rate for other ethnic groups.

Non-Traditional StudentsFor the 1997 cohort, about 6.5 percent were non-traditional students. Their high drop out

rate was not explained by academic factors. For example, their average first term GPA was 3.0,and their remedial placement rate of 42 percent was slightly lower than most students at thecollege. There were more part-time students in the non-traditional student group (63 percent). The major difference was that 55 percent were married compared with 7 percent of youngerstudents.

It is uncertain why non-traditional students had such high drop out rates. There was littledifference in their drop out rates by gender. It is possible that many of these students areworking, have families, and other commitments. These students may take much longer to earn

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their degrees. More information about these students needs to be gathered before a determinationcan be made.

Disabled StudentsThe college does not have complete records to identify all disabled students at the college.

The number identified for the fall 1997 cohort in the SIS system, was substantially smaller than inprior years. Because of this, all disabled students identified since 1993 were used to obtaindescriptive information. There were slightly more full-time students in this group (53 percent). The percentage of disabled students receiving financial aid was higher (48 percent).

A major difference with disabled students was their high remedial placement rates. Of the510 students, 72 percent required remedial education, 28 percent in two areas, and 22 percent inthree areas. About 64 percent needed remedial math, 53 percent remedial English, and 27 percentremedial reading.

The average first term GPA for disabled students was 2.61. With such high remedialplacement rates, one would expect their first term GPA’s to be lower (similar to other studentsrequiring remedial education). Their higher GPA could be due to the additional services that areoffered to them.

Part-Time StudentsThere was not a big difference between full-time and part-time students in most areas.

Their first term GPA’s were slightly lower (an average of 2.54), but they did not have remedialplacement rates that were substantially higher than full-time students or other students in general. So, their slightly lower GPA was probably not due to academic preparation.

A substantial difference for this group was that only 20 percent received financial aid. Many of these students may work to pay for their college education, which may explain theirlower grades. More information is needed on these students as well, to understand why theirdrop out rates were somewhat higher than full-time students.

Regression ModelThe descriptive information in the study illustrated that academic factors, financial

support, and other characteristics impact retention rates at the college. For a more completeunderstanding of student retention, these factors should be studied in combination rather thandescriptively. Each subgroup or population of students also needs to be studied individually togain a better understanding of the differences between different student groups on campus. Apath analysis model would be the preferred method to understand the causal links betweendifferent factors.

The present study was limited for several reasons. First, the data available did not satisfythe statistical assumptions of a path analysis model. Second, all the relevant information thatimpacts student retention on campus was not available on all students. One exception to this wasthe new student survey data that was available for the majority of remedial education students. Although the data did not satisfy the assumptions for a path analysis model, logistic regressionwas used to gain some understanding of which variables had the strongest direct relationship withstudent retention. Because of indirect relationships, and inter-correlation among the variables, it

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is difficult to assess the importance of individual factors. However, the regression still gives arough indication of which factors are likely to have the largest direct impact. Other researchershave supported the use of logistic regression in retention studies (Dey and Astin, 1993).

The 1993 to 1995 cohorts were combined in the regression for remedial educationstudents to identify significant factors that impacted retention over these years (Table 9). Asecond regression was also run for the data available on all students to see if findings were similar. Regression analysis is impacted by the variables that are included in the model; however, thedirection of the relationships were consistent for all students and remedial education students. The regression equation for the remedial population included 2,534 students, and the overallequation included 7,683 students. Students who dropped out as of 1998 were coded with a 1,and students who graduated, transferred, or were still enrolled were coded with a 0.

Several variables used in the model were entered as categorical variables. In theseinstances, a comparison group was created. For example, separate dummy variables (coded as 0or 1) were created for students who needed remedial education in one area, two areas, and threeareas. These variables were entered into the regression separately and compared with studentsnot requiring any remedial education (i.e. the comparison group coded as 0).

This same method was used for student first term GPAs, income groups, and workingstudents. Students with GPAs in the B range, C range, and below a C were compared withstudents earning A grades. Students from the lowest, second, and third income groups werecompared with students with the highest incomes. Students working full-time and part-time werecompared with students who did not work. See the appendices for a more detailed explanation ofthe variables and additional descriptive information on graduation, transfer, and drop-out rates foreach cohort.

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Table 9: Estimates of Retention Equations (*Significant p<.05)

Variables Remedial Students All Students

Background Characteristics Coefficients R Coefficients R

Non-Traditional .2017 .0000 .8413* .0684

Students of Color .4428* .0323 .5215* .0407

Disabled .1216 .0000 .1175 .0000

Single Parent .4541 .0065

First Generation Student -.1874* -.0254

Concurrent Enrolment -.6076* -.0731 -.5397* -.0755

Married .1738 .0000 .2634* .0232

Children -.0348 .0065

Attempted Hours -.0393* -.0612 -.0411* -.0708

Goal Commitment

Bachelor Degree Commitment .0128 .0000

Planned Semesters .0753* .0517

Academic Variables

Remedial One Area .0835 .0000

Remedial Two Areas .0833 .0000 .2482* .0335

Remedial Three Areas .0643 .0000 .2551* .0234

GPA B Range -.0095 .0000 -.0113 .0000

GPA C Range .3930* .0436 .4425* .0557

GPA Below C 1.2585* .1247 1.2788* .1224

Financial Support

Received Aid -.4780* -.0838 -.5358* -.1029

Lowest Income Group .4264* .0324

Second Income Group -.0320 .0000

Third Income Group .3998* .0401

Work Part-Time .1354 .0000

Work Full-Time .4875* .0407

Live Parents -2.464* .0952

Constant .5004 .7394*

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There were several findings that were consistent for all students and remedial educationstudents. The variable that had the largest partial correlation in both equations involved astudent’s GPA during their first term at the college. Because the distribution for GPA wasbimodal, grade information was entered in the equation as categorical data. The retention ratesfor students with GPA’s in the B range were not significantly different from A students. However, the positive coefficients indicated that students with GPA’s in the C range and below aC during their first term were at a significantly higher risk of dropping out of college, whencontrolling for all the other factors in the model. In other words, academic performance appearsto be the most important factor. As shown in the descriptive statistics presented above, remedial education was associatedwith lower first term GPA’s. When controlling for other variables in the overall model, studentswho needed remedial education in two and three areas had significantly higher drop out rates thanstudents who did not need remedial education.

The dummy variable measuring receipt of financial aid had the second largest partialcorrelation in both models. The Wald statistic was significant and negative, indicating that thereceipt of financial aid reduced dropout rates when controlling for the other factors in the model.

Other variables related to the financial support of students indicated that this area wasimportant in predicting student retention. For remedial education students, living at home had asignificant and negative relationship with student drop out rates. Living at home may be lessexpensive for students and their families, resulting in higher persistence rates. Students thatworked full-time, and were from lower income groups had significantly higher drop out rates. Working part-time did not appear to have a significant impact.

Student demographics were also significant predictors of student retention rates. Whencontrolling for first term GPA, remedial placement rates and other variables, minority status stillsignificantly increased a student’s chances of dropping out of college. Although these studentshad higher remedial education needs, there are likely to be other factors that impact their retentionat the college. Being a non-traditional student and marriage was significant in the overall modelbut not for remedial education students. This may be the case because the equation for remedialeducation students included the hours that students worked while attending college. For remedialeducation students, single parents had high drop out rates ranging from 66 to 87 percentdepending on the cohort, but single parenthood was not significant in the regression. Otherfactors in the model may have accounted for their higher drop out rates. Gender was not includedin the model because descriptive statistics only showed a small difference in retention betweenmales and females.

The number of semesters that a student planned to attend the college was also a significantpredictor of retention. It was interesting to note that students who planned to attend more termsat UVSC had lower retention rates. This finding could be due to several possible reasons.Students who planned to complete short term certificate programs may have been moresuccessful. Transfer students, who planned to only attend a few terms, may have been less likelyto drop out of the college. Students planning to attend more semesters may also be part-time andplanning to take longer to earn their degree.

Other student characteristics increased a student’s chances of college success. Studentswho completed concurrent enrolment courses in high school or took a larger number of credit

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hours at the college during their first term had higher retention rates. Taking concurrentenrolment courses may prepare students for college or demonstrate a stronger commitment toearning a degree. Full-time students may also have a greater commitment or more financialsupport for pursuing their studies.

The remedial student equation, and overall equation correctly classified only 66 and 65percent of the students respectively. When including all the variables in the remedial studentequation, 85 percent of students who dropped out were classified correctly; however, only 37percent of those did not drop out were classified correctly. The model had difficulty identifyingstudents who persisted at the college. This poor classification illustrates the difficulty inpredicting student retention.

Summary and ConclusionThe present study examined information from the new student survey and information in

the student information system to understand factors that impact student retention at the college. The study found that student retention is difficult to predict because there are so many factors thatimpact a student’s college success. However, the study did find that student academicperformance is a major predictor of student retention. The high remedial population of thecollege significantly increased drop out rates. Non-traditional students had the highest drop outrates. Students of color also had high drop out rates. Receiving financial aid or being in higherincome brackets had a positive impact on student retention.

In general, the college has a student population that is at a high risk of dropping out ofcollege. Numerous factors impact student retention, which requires several programs andinterventions. Improving student retention does not have a simple easy answer, and it requires acampus-wide effort.

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Appendix A: Definition of Terms

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Table 10: Definition of Terms

Demographic Characteristics

Non-Traditional Students who were over 24 years old when they started their firstregular term at the college (0=No, 1=Yes)

Students of Color Black, Hispanic, Asian, American Indian, and Alaskan Native studentsidentified in the Student Information System (0=No, 1=Yes).

Disabled Students identified as disabled in the Student Information System(0=No, 1=Yes)

Single Parent Students identified as single parents on the New Student Survey(0=No, 1=Yes).

First Generation Student On the New Student Survey, students said that their mother or fatherdid not complete a four year college degree or higher (0=No, 1=Yes).

Concurrent Enrolment Students who took concurrent enrolment courses while in high schoolas identified in the Student Information System (0=No, 1=Yes).

Married Students identified as married in the Student Information System(0=No, 1=Yes).

Children Students with children as listed on the New Student Survey (0=No,1=Yes).

Attempted Hours The number of attempted credit hours during a students first regularterm at the college as identified in the Student Information System.

Goal Commitment

Bachelor Degree Commitment Five point Likert scale from very likely to very unlikely on the NewStudent Survey answering wether students are likely to pursue a four-year degree.

Planned Semesters The number of semesters that a students plans to attend as listed on theNew Student Survey. Numbers 1 through 7 are entered with thehighest category ending at 8 or more.

Academic Variables

Remedial One Area Students who tested into only one remedial area based on COMPASSand DRP test scores (0=No, 1=Yes).

Remedial Two Areas Students who tested into only two areas based on COMPASS and DRPtest scores (0=No, 1=Yes).

Remedial Three Areas Students who tested into three areas based on COMPASS and DRP testscores (0=No, 1=Yes).

GPA B Range Students earning a first term GPA ranging from 2.7 to 3.69.

GPA C Range Students earning a first term GPA ranging from 1.7 to 2.69

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GPA Below C Students earning a first term GPA below 1.7

Financial Support

Received Aid Received short-term loans, long terms loans, grants, or scholarships asidentified in the Student Information System (0=No, 1=Yes).

Lowest Income Group Family income under $12,000 on the New Student Survey

Second Income Group Family income $12,000-$24,999 on the New Student Survey

Third Income Group Family income $25,000-$29,999 on the New Student Survey

Work Part-Time Students working 1 to 30 hours each week while attending school aslisted on the New Student Survey.

Work Full-Time Students working 31 or more hours each week while attending schoolas listed on the New Student Survey.

Live Parents Students living with parents as indicated on the New Student Survey(0=No, 1=Yes).

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Appendix B: Retention Tables1993-1995

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Table 11: Student Academic Success 1993 Cohort

Category Students Graduated Transferred Enrolled Dropout


Non-Traditional 196 26 13.27% 9 4.59% 7 3.57% 154 78.57%

Students of Color 119 15 12.61% 11 9.24% 6 5.04% 87 73.11%

Disabled 146 33 22.60% 18 12.33% 13 8.90% 82 56.16%

Concurrent Enrolment 276 83 30.07% 32 11.59% 45 16.30% 116 42.03%

Full-Time 1061 276 26.01% 169 15.93% 112 10.56% 504 47.50%

Part-Time 1079 162 15.01% 129 11.96% 134 12.42% 654 60.61%

Academic Variables

Non-Remedial 1030 250 24.27% 157 15.25% 103 10.00% 520 50.49%

Remedial One Area 600 118 19.67% 79 13.17% 76 12.67% 327 54.50%

Remedial Two Areas 283 38 13.42% 41 14.49% 39 13.78% 165 58.30%

Remedial Three Areas 227 32 14.10% 21 9.25% 28 12.33% 146 64.32%

GPA A Range 402 123 30.60% 58 14.43% 37 9.20% 184 45.77%

GPA B Range 1016 261 25.69% 150 14.76% 117 11.52% 488 48.03%

GPA C Range 423 47 11.11% 56 13.24 63 14.89% 257 60.76%

GPA Below C 166 3 1.81% 19 11.45% 15 9.04% 129 77.71%

Financial Support

Scholarships 654 210 32.11% 84 12.84% 79 12.08% 281 42.97%

Loans 377 96 25.46% 52 13.79% 61 16.18% 168 44.56%

Grants 648 163 25.15% 86 13.27% 94 14.51% 305 47.07%

Any Financial Aid 1044 295 28.26% 146 13.98% 132 12.64% 471 45.11%

No Financial Aid 1096 143 13.05% 152 13.87% 114 10.40% 687 62.68%

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Non-Traditional 230 16 6.96% 16 6.96% 16 6.96% 182 79.13%


Disabled 151 21 13.91% 13 8.61% 20 13.25% 97 64.24%


Full-Time 1299 220 16.94% 163 12.55% 176 13.55% 740 56.97%

Part-Time 1360 118 8.68% 112 8.24% 216 15.88% 914 67.21%

Academic Variables

Non-Remedial 1244 211 16.96% 134 10.77 160 12.86% 739 59.41%




GPA A Range 448 114 25.45% 68 15.18% 58 12.95% 208 46.43%

GPA B Range 1098 187 17.03% 114 10.38% 195 17.76% 602 54.83%

GPA C Range 509 35 6.88% 51 10.02% 87 17.09% 336 66.01%

GPA Below C 399 1 .25% 26 6.52% 31 7.77% 341 85.46%

Financial Support

Scholarships 451 158 35.03% 39 8.65% 78 17.29% 176 39.02%

Loans 451 72 15.96% 42 9.31% 79 17.52% 258 57.21%

Grants 636 106 16.67% 60 9.43% 105 16.51% 365 57.39%


No Financial Aid 1639 118 7.20% 177 10.80% 216 13.18% 1128 68.82%

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Non-Traditional 221 6 2.71% 7 3.17% 17 7.69% 191 86.43%


Disabled 193 8 4.15% 7 3.63% 34 17.62% 144 74.61%


Full-Time 1450 163 11.24% 110 7.59% 306 21.10% 871 60.07%

Part-Time 1438 83 5.77% 85 5.91% 289 20.10% 981 68.22%

Academic Variables

Non-Remedial 1305 158 12.11% 90 6.90% 269 20.61% 788 60.38%




GPA A Range 443 71 16.03% 34 7.68% 92 20.77% 246 55.53%

GPA B Range 1254 153 12.20% 93 7.42% 317 25.28% 691 55.10%

GPA C Range 584 21 3.60% 36 6.16% 122 20.89% 405 69.35%

GPA Below C 413 0 0.00% 22 5.33% 43 10.41% 348 84.26%

Financial Support

Scholarships 579 121 20.90% 34 5.87% 140 24.18% 284 49.05%

Loans 388 48 12.37% 25 6.44% 97 25.00% 218 56.19%

Grants 589 66 11.21% 36 6.11% 146 24.79% 341 57.89%


No Financial Aid 1778 79 4.44% 132 7.42% 328 18.45% 1239 69.69%

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