impact of employment on student retention at four-year … · 2016. 6. 20. · tuttle, mckinney...

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Author: Krueger, Brenda K.

Title: Impact of Employment on Student Retention at Four-Year Universities

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Krueger, Brenda K. Impact of Employment on Student Retention at Four-Year Universities

Abstract

Despite 40 years of research on student retention, additional research is needed given the shifting

experience of college students who now spend a large amount of time working while attending

college. The objective of this paper was to determine if the location of employment and number

of hours worked predicted retention, and if this relationship was moderated by student

involvement and type of position. A nationally representative dataset was used from the

National Center of Education Statistics (NCES). The population included first time, full-time

students attending four-year public, non-doctoral granting institutions in the United States and

Puerto Rico (N = 1,308) from 2003-2005. Results of the study indicated that students working

long hours, and off-campus were less likely to be retained. The interaction between hours

worked and location showed similar results. Students working a moderate number of hours, on-

campus, were more likely to be retained, and students employed off-campus were more likely to

drop out. Social involvement did moderate the relationship between students working long hours

and retention, but no difference was found for students working a moderate number of hours.

Type of employment was not related to student retention.

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Acknowledgments

I would like to thank my family, friends, advisor and committee for listening to

me, encouraging me, being patient with me, guiding me, and pushing me to keep working

hard to finish my thesis. A special thank you to my husband, Dan, for your non-stop

encouragement. Thank you to my three children, Alayna, Bennett, and Kenna, for your

patience and listening ear. Thank you to my parents, Sherry & Allie, for always being

there for me. Thank you to my advisor, Alicia Stachowski, for your guidance, patience,

and gentle nudges when needed. Thank you to Meridith Drzakowski and Sarah Wood for

being a part of my thesis committee. Thank you to my friends and family who supported

me, encouraged me, and most of all just listened to me. I appreciate all of you.

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Table of Contents

Abstract ............................................................................................................................................2

List of Tables ...................................................................................................................................7

Chapter I: Literature Review ...........................................................................................................8

Theories Related to Student Retention ................................................................................9

Conservation of Resources Theory ......................................................................... 9

Student Involvement Theory................................................................................... 9

Impact of Student Employment on Retention ....................................................................10

Number of Hours Worked .................................................................................... 11

Employment Location ........................................................................................... 13

Social Involvement as a Moderator of Employment and Retention ..................... 15

Type of Employment as a Moderator of Employment and Retention .................. 15

Chapter II: Methodology................................................................................................................17

Participants .........................................................................................................................17

Measures ............................................................................................................................17

Number of Hours Worked .................................................................................... 17

Employment Location ........................................................................................... 18

Social Involvement ............................................................................................... 18

Job Type ................................................................................................................ 18

Retention ............................................................................................................... 18

Demographics ....................................................................................................... 18

Procedures ..........................................................................................................................19

Chapter III: Results ........................................................................................................................20

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Demographic ......................................................................................................................20

Number of Hours Worked .................................................................................................21

Hypothesis 1.......................................................................................................... 21

Employment Location ........................................................................................................22

Hypothesis 2.......................................................................................................... 22

Hypothesis 3.......................................................................................................... 23

Social Involvement as a Moderator of Employment and Retention ..................................24

Hypothesis 4.......................................................................................................... 24

Type of Employment as a Moderator of Employment and Retention ...............................26

Hypothesis 5.......................................................................................................... 26

Supplemental Analysis.......................................................................................................28

Number of Hours Worked .................................................................................................29

Hypothesis 1.......................................................................................................... 29

Employment Location ........................................................................................................29

Hypothesis 2.......................................................................................................... 30

Hypothesis 3.......................................................................................................... 30

Social Involvement as a Moderator of Employment and Retention ..................................31

Hypothesis 4.......................................................................................................... 31

Type of Employment as a Moderator of Employment and Retention ...............................32

Hypothesis 5.......................................................................................................... 32

Chapter IV: Discussion ..................................................................................................................34

Implications........................................................................................................................35

Limitations and Future Directions .....................................................................................36

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References ......................................................................................................................................38

Appendix A: Data License and Use ...............................................................................................43

Appendix B: Breakdown of Variables ...........................................................................................45

Appendix C: Supplemental Analysis Detail .................................................................................47

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List of Tables

Table 1: Demographics - Age, Gender, Race/Ethnicity ................................................................20

Table 2: Breakdown of Student Retention by Hours Worked .......................................................21

Table 3: Breakdown of Student Retention by Location.................................................................22

Table 4: Breakdown of Student Retention by Hours Worked by Location ...................................24

Table 5: Logistic Regression - Hours Worked and Social Involvement .......................................26

Table 6: Logistic Regression - Hours Worked and Job Related to Major .....................................27

Table 7: Supplemental Demographics - Age, Gender, Race/Ethnicity .........................................28

Table 8: Supplemental Breakdown of Student Retention by Hours Worked ................................29

Table 9: Supplemental Breakdown of Student Retention by Location ..........................................30

Table 10: Supplemental Breakdown of Student Retention by Hours Worked by Location ..........31

Table 11: Supplemental Logistic Regression - Hours Worked and Social Involvement ..............32

Table 12: Supplemental Logistic Regression - Hours Worked and Job Related to Major ............33

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Chapter I: Literature Review

A variety of stakeholders are interested in the retention (and completion rates) of college

attendees. First, over the course of their lifetime, students who earn a college degree earn twice

as much as employees without one (Alarcon & Edwards, 2013). Students also create revenue

for the institutions they attend. The challenge is that retention rates are decreasing. Retention

rates measured from year one to year two have dropped 3.4% over the last five years (ACT,

2009; 2014). The current retention rate is 64.2%, meaning that 35.8% of students at public

universities drop out in the first year of attendance (ACT, 2014). Given this alarmingly large

number of students that leave the university after one year, learning more about the demands of

college students is important.

Employment while at college has increased – with the growing cost of attending college,

the majority of students must work while attending school. The rate of student employment

increased steadily from 1960 (40%) through 2006 (80%; Cuccaro-Alamin, Choy & MPR

Associates, 1998; Riggert, Boyle, Petrosko, Ash & Rude-Parkins, 2006; Stern & Nakata, 1991;

Tuttle, McKinney & Rago, 2005). Since 2006, the student employment rate has dropped to

approximately 72% for ages 16 to 24 (Davis, 2012). At present, research has not consistently

shown how student employment influences retention rates. The purpose of the current study is to

explore whether variables related to work and involvement are related to student retention from

the first year to the second year. Specifically, this study examines whether the location of

employment and number of hours worked impact retention. In addition, this study explores

whether the relationship between retention and hours worked is moderated by student

involvement and position type.

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Theories Related to Student Retention

There are a large number of theories referenced in the student retention research, as

retention has been explored from numerous disciplines. For instance, there are theories focused

on prompt feedback and interventions for at-risk students (Tinto, 1993), academic self-efficacy

(Bandura, 1997), and institutional commitment (Bean & Eaton, 2001). Given the specific

interest in employment-related variables and student involvement, the two theories that will best

guide predictions include: Conservation of Resources Theory and Student Involvement Theory,

both of which are described below.

Conservation of Resources Theory. Comprehension of how working impacts students’

ability to stay in school starts with understanding the resources students have at their disposal.

Hobfoll’s (1989) Conservation of Resources Theory (COR) is one way to explain the retention

decisions of students who are working while attending school full-time. Hobfoll (1989)

describes the COR theory in relation to resources that are available, gained and lost. Individuals

are born with resources, have a desire to gain additional resources, and try to limit the loss of

existing resources. Resources are described as those assets needed for life and happiness, and the

things that help to maintain those resources. Self-confidence, housing, health, self-efficacy,

employment, and reputation are all examples of resources. When an individual’s resources are

threatened, stress is experienced. If the stress lasts for an extended period of time, resources can

be depleted, and individuals may withdraw from the stressor (Gorgievski & Hobfall, 2008).

Balancing resources can be a struggle for students who have competing obligations in their

school, work, family and social life.

Student Involvement Theory. Balancing competing obligations can also impact how

involved a student is on campus. Social involvement has been identified as a critical component

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of student success in the research over the past 30 years (Astin, 1984; Demetriou & Schmitz-

Sciborski, 2011; Furr & Elling, 2000; Lobo, 2012; Tinto, 2006). Student involvement is the

extent to which a student devotes time and energy to the college experience by studying,

socializing with peers, participating in university activities, and connecting with faculty and

staff. The Student Involvement Theory indicates that students that are more involved in

university life will learn more and develop additional skills and abilities (Astin, 1984). In

addition, students that are more involved in university life will be more likely to be retained

(Astin, 1984). According to this theory, time and energy are limited resources and the student

decides where they want to spend those resources (Astin, 1984). Similar to the Conservation of

Resources Theory, students decide what they want to be involved with, how much effort they

will put in, and what they will do when met with adversity (Weng, Cheong, & Cheong, 2010).

Impact of Student Employment on Retention

College students need to attend class, study, work, and find time to socialize with peers.

They may need tutoring to do well in class and they must find time to complete all of their class

readings. There may be conflicts that arise that require students to choose between working and

studying. They need to study to do well in school, but many students need to work in order to

finance their studies. Lansdown (2009) found that, at times, working while attending school

created a barrier to academic performance when students were asked to work additional hours, or

lacked time to study. Students may feel unable to change their work situation because they have

financial obligations that must be met (Lansdown, 2009). This conflict threatens their resources,

causing stress. The stress depletes their resources, and if this stress cannot be resolved, the

student may withdraw from school. Thus, working while attending school may be detrimental

unless a student can find ways to gain additional resources.

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Through the years, many studies have explored the impact of employment on students’

ability to stay in school. Unfortunately, results from empirical studies on the impact of student

employment on retention are inconsistent and contradictory (Riggert et al., 2006). First, there is

a body of research to support the positive impact of student employment on retention (Dundes &

Marx, 2006; Horn & Malizio, 1998; King, 2003; Nonis & Hudson, 2006; Stern & Nakata, 1991).

The positive impacts of student employment fall into three categories: 1) increased academic

performance leading to retention (Dundes & Marx, 2006; Nonis & Hudson, 2006), 2) increased

student retention from part-time employment (Horn & Malizio, 1998; King, 2003), and 3)

increased student retention when employment is related to a student’s major (Stern & Nakata,

1991).

There are also researchers that discuss the negative impacts related to employment on

student retention (Cuccaro-Alamin, 1997; Lau, 2003; Tinto, 2006). The negative consequences

of student employment fall into two categories. First, students working a high number of hours

are more apt to drop out before receiving a degree (Cuccaro-Alamin, 1997). Second, working

gives students less time to study and attend classes, which can ultimately impact whether a

student stays in school (Lau, 2003; Tinto, 2006). When examining the results, two factors

emerge as indicators of retention: number of hours worked and where the employment is located

(on-campus versus off-campus).

Number of hours worked. The number of hours students work plays an important role

in whether or not employment has a positive or negative impact on academic success. Results

demonstrate that students are less likely to graduate if they attend college part-time and work

full-time compared to students that attend college full-time and work part-time (Cuccaro-Alamin,

1997; Lobo, 2012). Students that devote 40 hours a week to work have less time, energy and

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resources to devote to school, thus making them less likely to graduate. It is difficult to fulfill

school commitments when such a large percentage of time is spent working. Ehrenberg and

Sherman’s (1987) study of male students indicated that those working 20 or more hours per

week during their freshman year increased their likelihood of dropping out by 3.2%. King’s

(2003) study of 12,000 undergraduates showed that students working over 15 hours each week

were less likely to graduate in four years. However, those working 15 or fewer hours were more

likely to graduate in four years than nonworking students (King, 2003). Thus, working a

moderate number of hours appeared to be the key to student success. The National Center for

Education Statistics (NCES) also found that students working 1-15 hours per week were the most

likely to be retained, even compared to nonworking students (Horn & Malizio, 1998). Dundes

and Marx (2006) found that students who worked 10-19 hours a week performed better

academically than all other students (working or non-working).

According to the Conservation of Resources Theory, the employment atmosphere can

provide opportunities to gain additional resources through successful job performance or can

cause resource depletion through job pressures (Gorgievski & Hobfall, 2008). Successful job

performance increases self-efficacy, allowing for resource gain (Gorgievski & Hobfall, 2008).

This helps explain why students who work perform better than students who do not work.

However, students need to balance work demands with school demands. Limiting the number of

hours worked will decrease the chance of depleting students’ resources. Working additional

hours while balancing the required course work adds increased demands and more stress, thus

depleting more resources. The stress may push students to the threshold of dropping out of

school. In order to confirm findings in the previous studies, the following hypothesis is studied:

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Hypothesis 1. Students that work 1-15 hours per week are more likely to be retained than

students who work over 15 hours per week or those who do not work at all.

Employment location. In addition to considering the number of hours worked, existing

research supports the notion that working on-campus is more beneficial to students than working

off-campus in relation to academic performance (Ehrenberg & Sherman, 1987; Kulm & Cramer,

2006; Wenz & Yu, 2010) and student retention (Beeson & Wessel, 2002; Ehrenberg & Sherman,

1987; Noel-Levitz, 2010; Tinto, 1993). Beeson and Wessel (2002) found that students working

on-campus persisted at slightly higher rates (78%) from year one to year two than non-working

students (77%) and overall retention rates (77%). Results from Ehrenberg & Sherman’s (1987)

study also indicated that working off-campus had a negative impact on student retention;

however, students working on-campus were retained at approximately the same rate as those

who did not work at all. The Conservation of Resources Theory helps to explain the reason that

students that work on-campus are more likely to be retained than those who work off-campus.

Off-campus employment requires students to expend more time and resources. For example,

students may need additional time to drive home, change into different clothing and drive to their

off-campus employment. In addition, more financial resources may be required for

transportation. Scheduling may also be more challenging for off-campus employment when

employers call students to take on extra shifts or refuse to honor schedule change requests due to

homework or finals schedules. On-campus employment, however, is an extension of the

university. Students can simply move from class to work without time or energy needed for

adjustment. On-campus employers also understand the nature of the academic schedule and

offer more schedule flexibility. To investigate the differences between on-campus and off-

campus employment, the following hypothesis is examined:

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Hypothesis 2. Students that work on-campus are more likely to be retained than students

who work off-campus.

The inconsistent results found in the empirical studies on the impact of student

employment on retention indicate that the situation may be more complex than just looking at

number of hours worked and location separately. Number of hours worked may interact with

location, and other work-related variables to influence student retention. Social involvement may

help to explain these sometimes contradictory findings. More specifically, it is possible that the

interaction of hours and location impacts students that are working a moderate number of hours

differently than those working extended hours. According to the Student Involvement Theory,

students choose where they want to devote their resources. Working a moderate number of

hours on-campus requires students to expend the least amount of resources, and gives them the

opportunity to gain new resources through experiencing success on the job, learning through

interactions with others, and being involved in a supportive environment. In contrast, students

working off-campus utilize extra resources because of the additional time it takes to get to and

from work, and the added resource demands of paying for transportation. Students who do not

work are also impacted, as they do not have the opportunity to gain additional resources from

experiencing success on the job. Finally, working longer hours requires the most resources to be

expended, which ultimately increases students’ stress levels as they have less time and energy to

devote to their course work. If resources are depleted, there is increased risk of dropping out of

school. To understand the interaction between hours worked and location of employment, the

following hypothesis is explored:

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Hypothesis 3. Students working on-campus 1-15 hours per week are more likely to be

retained than students working 1-15 hours per week off-campus, and students who work over 15

hours per week (on or off-campus), and those who do not work at all.

Social involvement as a moderator of employment and retention. Tinto (1993)

indicated that employment negatively impacted social involvement, as students had less time to

devote to on-campus activities, connect with faculty, and interact with peers. Other research

contradicts Tinto’s findings. Surprisingly, students that worked part-time on-campus were found

to be more involved with student life on-campus and had more interactions with faculty, staff,

and peers (Furr & Elling, 2000). The Student Involvement Theory suggests that involved

students are more likely to be retained (Astin, 1984). On-campus employment is another way to

be involved and may help students feel more connected to the university (Noel-Levitz, 2010).

Kulm and Cramer (2006) indicated that on-campus employment helped students to be more

socially involved on-campus, which helps to explain the positive correlation found between on-

campus employment and persistence. Those working on-campus are likely to be more involved,

and connected to the campus, and thus more likely to stay regardless of the number of hours

worked per week. Therefore, the fourth hypothesis predicts:

Hypothesis 4. Social involvement will moderate the relationship between hours worked

and retention, such that students that are more involved will be more likely to be retained

regardless of the number of hours worked.

Type of employment as a moderator of employment and retention. Riggert et al.

(2006) indicate that the majority of working students are employed in unskilled labor positions to

pay basic living expenses, rather than working in positions related to their majors to gain job

experience. Stern and Nakata (1991) reported that when students were working in positions

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related to their major, there was a stronger positive relationship with school performance. Blau

and Snell (2013) advocated for professional development engagement to help students secure

positions in their field after graduation. Professional development engagement is defined as

involving students outside their learning environment. One example is gaining experience

associated with their majors through an internship, co-op, or other job-related experience (Blau

& Snell, 2013). Trede and McEwen’s (2015) pilot study recently advocated for early workplace

learning experiences for students during their first year of college to improve retention. Students

in the pilot study indicated that early introduction to employment in their chosen field was vital

to understanding career options within their field and confirming their career choice (Trede &

McEwen, 2015). Success in a position related to a student’s major increases self-efficacy.

Conservation of Resources Theory would predict that increased self-efficacy is another way to

restore students’ reserves and extend their resources, which helps them to stay in school

(Gorgievski & Hobfall, 2008). To probe into this topic more, the final hypothesis states:

Hypothesis 5. Type of employment will moderate the relationship between hours worked

and retention, such that students working in a job related to their major will be more likely to be

retained if they are working, regardless of the number of hours worked.

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Chapter II: Methodology

This study addresses three areas related to the impact of student employment on retention

at public four-year baccalaureate non-doctoral universities (doctoral-granting, and private

universities will be excluded): the number of hours worked on-campus compared to off-campus,

the impact of social involvement on the relationship between hours worked and retention, and

the influence of type of employment, related or unrelated to major, on the relationship between

hours worked and retention.

A national, archival dataset was used for the purpose of this study. The Beginning

Postsecondary Longitudinal Study (BPS:04/09) restricted dataset was utilized from the NCES.

This dataset contains information on a sample of students considered to be nationally

representative, who started postsecondary education for the first time in 2003-2004 (Wine,

Janson, Wheeless, & Hunt-White, 2011).

Participants

The population of interest is traditionally-aged (18-25), first-time, full-time freshman

attending 4-year institutions (limited to public, baccalaureate, non-doctoral universities) in the

United States and Puerto Rico. The total sample size was 1,308 students (Wine et al., 2011).

Permission was received to use the BPS:04/09 restricted dataset for this study (See Appendix A).

Measures

The variables used for this study are defined below and included: number of hours

worked, employment location, social involvement, job type, retention, and demographics.

Number of hours worked. The number of hours students worked per week was self-

reported during the 2003-2004 academic year and included all regular jobs and work-

study/assistantship jobs.

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Employment location. The location of the students’ employment was self-reported

during the 2003-2004 academic year and detailed where the student worked the majority of hours

while enrolled: on-campus, off-campus, or both on and off campus.

Social involvement. The social involvement index tracked social involvement of the

students during the 2003-2004 academic year by asking students to self-report the number of

activities they participated in. Social involvement is a derived continuous variable indicating the

average frequency of attendance at fine arts activities, intramural sports, varsity sports and

school clubs.

Job type. Job type was self-reported by the student during the 2003-2004 academic year,

and this variable also documented if the job was related to his/her field of study.

Retention. Retention was measured in the traditional manner and follows the definition

used by IPEDS (Integrated Postsecondary Education Data System): first-time bachelor’s degree-

seeking undergraduates from the previous fall who are again enrolled in the current fall. A

derived variable investigating fall-to-fall freshmen retention was created using monthly

enrollment indicators. Variables for enrollment in October 2003 and October 2004 was used to

determine retention. Students enrolled full-time in October 2003, but not enrolled in October

2004 were considered non-retained.

Demographics. Three demographic variables were included: gender, age, and race,

which were self-reported during the 2003-2004 academic year. Gender was self-reported as

male or female. Age was a continuous variable that was entered the first year the student was

enrolled and race was self-reported based on designated categories. See Appendix B for a

breakdown of each variable with their response options.

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Procedures

The original data was gathered using a two-step process. The National Postsecondary

Student Aid Study (NPSAS) eligible institutions were selected in step one. Eligible students

included all first-time, full-time freshmen who were attending an NPSAS eligible institution for

the 2003-2004 school year. Students with complete data were selected based on stratified and

cluster sampling for step two. The response rate was 82% among the eligible sample.

Participants were surveyed three times during their first year and transcripts were collected from

eligible institutions where participants were in attendance. The transcripts were entered and

coded and included quality control checks to ensure reliability. A subset of this previously

collected dataset which included first-time, full-time freshmen that attended four-year, public,

non-doctoral granting institutions starting in 2003was used here to determine the impact of

student employment on retention.

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Chapter III: Results

The objective of this paper was to determine if the location of employment and number

of hours worked predicted retention, and if this relationship was moderated by student

involvement and type of position.

Demographic

The sample included 1,308 first-time, full-time freshmen at public non-doctoral

universities that began college in 2003. The majority of students in the sample were 18 years old

(63.1%) with an ethnicity of white (71.7%). The sample included slightly more females (56.7%)

than males (43.1%). The demographic information is shown in Table 1. The group was tracked

over their first year and into their second year. Students that were enrolled full-time in fall 2003,

and enrolled full-time or part-time in fall 2004, were considered retained. There were 972 (74%)

students who were retained and 336 (26%) students who were not retained into their second year.

Table 1

Demographics - Age, Gender, Race/Ethnicity

Demographic Variable Total M SD

Age 18.93 3.36 Gender N % Male 564 43.1 Female 742 56.7 Race/Ethnicity White 938 71.7 Black or African American 122 9.3 Hispanic or Latino 137 10.5 Asian 49 3.7 American Indian or Alaska Native 9 .7 Native Hawaiian / other Pacifica Islander 1 .2 Other 21 1.6 More than one race 31 2.4

Note. N = 1,308 participants.

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Number of Hours Worked

In order to assess the impact of the number of hours worked on retention, the following

hypothesis was studied:

Hypothesis 1. Students that work 1-15 hours per week are more likely to be retained

than students who work over 15 hours per week or those who do not work at all.

A chi-square test of independence was performed to examine the relationship between

hours worked and student retention. The relationship between student retention and hours

worked was statistically significant (2 (2, N = 1,308) = 26.52, p < .001). The breakdown of

student retention by hours worked is shown in Table 2. Follow-up tests were conducted by

examining the standardized residuals. Compared to the expected null, non-working students

were retained at a higher rate than expected and students working long hours were retained at a

much lower rate than expected. Hypothesis 1 was partially supported. Students working long

hours were less likely to be retained; however, non-working students were more likely to be

retained.

Table 2

Breakdown of Student Retention by Hours Worked

Hours Worked Student Retention Not Retained Retained 2

0 Hours (not working) 101 401 26.52** (-2.5) (1.4) 1-15 Hours (moderate) 67 238 (-1.3) (.8) 16+ Hours (long) 168 333 (3.5) (-2.0) Note. ** p < .001. Adjusted standardized residuals appear in parentheses below

group frequencies.

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Employment Location

In order to determine the effect of the employment location on retention, the following





employment location and student retention. The relationship between student retention and

employment location was statistically significant (2 (2, N = 715) = 31.83, p < .001). The

breakdown of student retention by location is shown in Table 3. Follow-up tests were conducted

by examining the standardized residuals. Compared to the expected null, students that worked

off-campus were retained at a lower rate than expected and students that worked on-campus were

retained at a higher rate than expected. Hypothesis 2 was supported. Students working off-

campus were less likely to be retained.

Table 3

Breakdown of Student Retention by Location


On-Campus 10 49 31.83** (-1.3) (.8) Off-Campus 213 443 (3.4) (-2.0) Note. ** p < .001. Adjusted standardized residuals appear in parentheses below

group frequencies.

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A chi-square test of independence was also performed to examine the blended

relationship between hours worked, employment location, and student retention. The

relationship between hours worked, employment location, and student retention was statistically

significant for moderate hours worked (2 (2, N = 715) = 8.92, p < .012). The breakdown of

student retention by hours worked by location is shown in Table 4. Follow-up tests were

conducted by examining the standardized residuals for the working students. Compared to the

expected null, students working on-campus were more likely to be retained than students

working off-campus; however, results were only statistically significant for students working

moderate hours. In addition, the relationship between hours worked and student retention was

also statistically significant for non-working students (2 (1, N = 502) = 179.28, p < .001). Non-

working students were also less likely to drop out than expected. Hypothesis 3 was partially

supported. Students working a moderate number of hours, on-campus and non-working students

were less likely to drop out than expected and off-campus students were more likely to drop out

than expected.

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Table 4

Breakdown of Student Retention by Hours Worked by Location

Hours Worked Student Retention

Employment Location

Not Retained

Retained 2

0 Hours (not working) 101 401 179.28** 1-15 Hours (moderate) On-Campus 5 33 8.92* (-1.2) (.6) Off-Campus 53 141 (1.6) (-.8) 16+ Hours (long) On-Campus 5 16 3.44 (-.8) (.5) Off-Campus 160 302 (.4) (-.3) Note. ** p < .001, * p = .01. Adjusted standardized residuals appear in parentheses

below group frequencies.

Social Involvement as a Moderator of Employment and Retention

In order to establish if social involvement influences employment and retention, the

following hypothesis was studied:




A logistic regression analysis was performed to explore the interaction between social

involvement and hours worked on the likelihood that students will be retained. Data from 1,308

students was available for analysis: 502 students who were not working, 305 students who were

25

working a moderate number of hours (1-15 hours per week), and 501 students who were working

long hours (16+ hours per week).

The referent category was non-working students. A test of the full model with two

predictors and the interaction against a constant-only model was statistically significant, 2(5, N

= 1,308) = 53.66, p < .001 indicating that hours worked and social involvement impacted student

retention. The full model including the hours worked and social involvement variables was

slightly better at predicting student retention than the constant only model, and explained 5.9%

(Nagelkerke R2) of the variance in student retention. The classification table indicates 74.3% of

students were correctly classified, although this percentage was not an improvement over the

constant only model.

Logistic regression - hours worked and social involvement is shown in Table 5 and

includes b-weights, standard errors, Wald tests, significance, and odds ratios of the individual

predictors in the model. The interaction between long hours and the social involvement index

was statistically significant (p = .03) suggesting that there is a relationship between student

retention and the combination of social involvement and working long hours. Students that were

working long hours and socially involved on-campus were 1.01 times more likely to be retained

than non-working students. Social involvement positively impacted students working long

hours; however, there was no benefit to social involvement for those working moderate hours.

Hypothesis 4 was partially supported. Social involvement did moderate the relationship between

students working long hours and retention, but it did not moderate the relationship between

students working a moderate number of hours and retention.

26

Table 5

Logistic Regression - Hours Worked and Social Involvement (N = 1,308)

Student Retention B SE B Wald Sig. Odds

ratio 95% CI

Constant 0.75 0.10 54.87 .000** 2.12 Non-Working

18.45 .000**

Moderate Hours 0.61 0.15 16.25 .000** 1.84 1.37, 2.47 Long Hours 0.52 0.18 8.52 .004* 1.67 1.18, 2.37 Social Involvement 0.00 0.00 4.56 .033* 1.00 1.00, 1.01 Non-Working*Social Involvement

5.27 .072

Moderate Hours*Social Involvement 0.00 0.00 0.08 .776 1.00 1.00, 1.01 Long Hours*Social Involvement 0.01 0.00 5.02 .025* 1.01 1.00, 1.02

Note. ** p < .001, * p < .05. CI = confidence interval. Nagelkerke R2 = .06.

Type of Employment as a Moderator of Employment and Retention

In order to gauge the impact of type of employment on student retention, the following


Hypothesis 5. Type of employment will moderate the relationship between hours

worked and retention, such that students working in a job related to their major will be more

likely to be retained if they are working, regardless of the number of hours worked.

A logistic regression analysis was performed to explore the interaction between type of

employment and hours worked on the likelihood that students would be retained. Of the 1,308

students, the majority of students (1,001) declared a major. In addition, 104 were working in a

job related to their major and 1,204 were working in a job unrelated to their major.



= 1,308) = 26.59, p < .001. The full model including the hours worked and type of employment

27

variables is slightly better at predicting student retention than the constant only model. The

model explained 3.0% (Nagelkerke R2) of the variance in student retention. The classification

table indicates 74.3% of students were correctly classified, although this percentage was not an

improvement over the constant only model.

Logistic regression - hours worked and job related to major is shown in Table 6 and

includes b-weights, standard errors, Wald tests, significance, and odds ratios of the individual

predictors to the model. The main effect for moderate hours worked (p < .001) was statistically

significant, suggesting that there is a relationship between student retention and moderate hours

worked. Students working a moderate number of hours per week were 1.96 times more likely to

be retained than non-working students. However, an interaction between hours worked and type

of employment was not found. Thus, Hypothesis 5 was not supported. Type of employment and

the interaction between type of employment and hours worked was not shown to be related to

student retention.

Table 6

Logistic Regression - Hours Worked and Job Related to Major (N = 1,308)


ratio 95% CI

Constant 0.55 0.25 4.96 .026* 1.73 Non-Working

21.24 .000**

Moderate Hours 0.67 0.15 19.70 .000** 1.96 1.46, 2.63 Long Hours 0.59 0.48 1.55 .214 1.81 0.71, 4.58 Job Related to Major 0.16 0.27 0.35 .552 1.17 0.70, 1.98 Non-Working*Job Related to Major

0.00 .978

Moderate Hours*Job Related to Major -0.01 0.51 0.00 .978 0.99 0.36, 2.67

Note. ** p < .001, * p < .05. CI = confidence interval. Nagelkerke R2 = .03.

28

Supplemental Analysis

Supplemental analyses focused on employment impacts of student retention of first-time,

full-time freshmen at all four-year universities (public, private, doctoral and non-doctoral) as a

comparison to the primary sample that focused only on public, non-doctoral 4-year institutions.

See Appendix C for a more elaborate explanation of these findings.

The broader sample included 7,202 first-time, full-time freshman at all four-year

universities (public, private, doctoral and non-doctoral) that began college in 2003. The majority

of students in the sample were 18 years old (63.3%) with an ethnicity of white (72.1%). The

sample included slightly more females (56.2%) than males (43.7). The supplemental

demographics – age, gender, race/ethnicity is shown in Table 7. There were 5,774 (80%)

students who were retained and 1,428 (20%) students who were not retained into their second

year.

Table 7

Supplemental Demographics – Age, Gender, Race/Ethnicity

Demographic Variable Total M SD

Age 18.67 2.51 Gender N % Male 3148 43.7 Female 4048 56.2 Race/Ethnicity White 5164 72.1 Black or African American 656 9.1 Hispanic or Latino 622 8.6 Asian 396 5.5 American Indian or Alaska Native 27 .4 Native Hawaiian / other Pacifica Islander 14 .2 Other 101 1.4 More than one race 192 2.7 Note. N = 7,202 participants.

29


In order to assess the impact of the number of hours worked on retention in the broader

sample, the following hypothesis was studied:

Hypothesis 1. Students that work 1-15 hours per week are more likely to be retained

than students who work over 15 hours per week or those who do not work at all.

The supplemental breakdown of student retention by hours worked is shown in Table 8.

The pattern of findings was similar to the primary analysis; however, with the broader sample,

students working a moderate number of hours were the most likely to be retained. This is

different than what was found in the primary analysis where non-working students were most

likely to be retained.

Table 8

Supplemental Breakdown of Student Retention by Hours Worked


0 Hours (not working) 494 2472 145.13** (-3.9) (1.9) 1-15 Hours (moderate) 359 1894 (-4.2) (2.1) 16+ Hours (long) 575 1408 (9.2) (-4.6) Note. ** p < .001. Adjusted standardized residuals appear in parentheses below

group frequencies. Employment Location

In order to determine the effect of the employment location on retention in the broader


30



The supplemental breakdown of student retention by location is shown in Table 9. The

pattern of results was similar to that found in the primary analysis. Students working off-campus

were less likely to be retained than those working on-campus.

Table 9

Supplemental Breakdown of Student Retention by Location


On-Campus 79 414 110.50** (-1.9) (.9) Off-Campus 705 1983 (7.5) (-3.7) Note. ** p < .001. Adjusted standardized residuals appear in parentheses below

group frequencies




The supplemental breakdown of student retention by hours worked by location is shown

in Table 10. Using this broader sample, students working long hours on-campus were less likely

to drop out than those working a moderate number of hours. This is different than the primary

analysis where students working a moderate number of hours on-campus were less likely to be

drop out.

31

Table 10

Supplemental Breakdown of Student Retention by Hours Worked by Location

Hours Worked Student Retention

Employment Location

Not Retained

Retained 2

0 Hours (not working) 494 2472 1319.11** 1-15 Hours (moderate) On-Campus 57 292 10.60* (.2) (-.1) Off-Campus 182 802 (2.0) (-.9) 16+ Hours (long) On-Campus 22 122 18.55** (-3.1) (2.0) Off-Campus 523 1181 (1.3) (-.8) Note. * p = .005, ** p < .001. Adjusted standardized residuals appear in parentheses

below group frequencies.


In order to establish if social involvement influences employment and retention in the

broader sample, the following hypothesis was studied:




The supplemental logistic regression - hours worked and social involvement in shown in

Table 11. Social involvement did not moderate the relationship between hours worked and

retention. This is different than in the primary analysis where social involvement did moderate

the relationship between hours worked and retention.

32

Table 11

Supplemental Logistic Regression - Hours Worked and Social Involvement (N = 7,202)


ratio 95% CI


100.19 .000**

Moderate Hours 0.63 0.07 76.28 .000** 1.87 1.62, 2.15 Long Hours 0.65 0.08 68.68 .000** 1.92 1.65, 2.24 Social Involvement 0.01 0.00 33.09 .000** 1.01 1.00, 1.01 Non-Working*Social Involvement

.89 .640

Moderate Hours*Social Involvement -0.00 0.00 0.86 .355 1.00 1.00, 1.00 Long Hours*Social Involvement -0.00 0.00 .38 .540 1.00 1.00, 1.00

Note. ** p < .001. CI = confidence interval. Nagelkerke R2 = .05.


In order to gauge the impact of type of employment on student retention in the broader


Hypothesis 5. Type of employment will moderate the relationship between hours

worked and retention, such that students working in a job related to their major will be more

likely to be retained if they are working, regardless of the number of hours worked.

The supplemental logistic regression - hours worked and job related to major is shown in

Table 12. Again, type of employment and the interaction between type of employment and

hours worked was shown to be unrelated to student retention.

33

Table 12

Supplemental Logistic Regression - Hours Worked and Job Related to Major (N = 7,202)


ratio 95% CI


110.31 .000**

Moderate Hours 0.70 0.07 93.77 .000** 2.02 1.75, 2.33 Long Hours 1.01 0.25 16.55 .000** 2.75 1.69, 4.47 Job Related to Major 0.07 0.14 0.28 .599 1.08 0.82, 1.42 Non-Working*Job Related to Major

1.06 .304

Moderate Hours*Job Related to Major -0.27 0.26 1.06 .304 0.77 0.46, 1.28

Note. ** p < .001. CI = confidence interval. Nagelkerke R2 = .03.

34

Chapter IV: Discussion

The objective of this paper was to determine the impact of employment on student

retention for first-time, full-time freshmen at public, non-doctoral universities. Specifically,

location of employment and number of hours worked were explored to determine their impact on

student retention, and whether this relationship was moderated by student involvement and type

of position.

Results of this study were consistent with previous research in several cases: 1) students

working a moderate number of hours were more likely to be retained than students working long

hours, 2) students working on-campus were more likely to be retained than students working off-

campus, 3) students working a moderate number of hours, on-campus were less likely to drop

out than students working off-campus, and 4) social involvement did moderate the relationship

between students working long hours and retention. However, results were contrary to prior

research in the following areas: 1) non-working students were found to be slightly more likely to

be retained than students working a moderate number of hours, 2) social involvement (at least as

defined by frequency of experience) did not impact students working a moderate number of

hours, and 3) type of position did not moderate the relationship between hours worked and

retention.

Supplemental analyses were conducted on a broader sample for comparative purposes –

the sample of students chosen was expanded to include students from all 4-year universities

(public, private, doctoral, non-doctoral) to explore contrasts to the primary study that only

included public, four-year, non-doctoral granting universities. A few differences were found.

Students working a moderate number of hours were the most likely to be retained in comparison

to students working long hours or those not working at all. When looking at the broader sample,

35

the study also indicated that students working long hours on-campus were the most likely to be

retained. In addition, the supplemental study did not support the research that students that are

more socially involved on-campus are more likely to be retained.

Implications

The broad implications from this study suggest that students should limit the number of

hours that they work each week (to 1 – 15 hours) while attending college during their freshman

year, and should explore on-campus employment options. This supports the Conservation of

Resources theory in that students need to balance their resources. Limiting the number of hours

worked and working on-campus gives students more time and resources to devote to coursework.

This also reduces the chance of depleting students’ resources and lessening the chance of

students dropping out of school.

In addition, students that must work long hours, should consider becoming socially

involved on-campus. Social involvement may act as a protective factor for students working

long hours, keeping them involved in the university and increasing their odds of staying in

school. Being involved on-campus keeps school at the top of a student’s priorities list. And

finally, this study was specifically focused on first-time, full-time freshmen. Many students have

not yet declared a major when they are a freshman, and many do not have enough background or

education to be working in a job related to their major freshman year. Perhaps sophomore year

would be a better time to offer field experience related to their major. As students gain more

knowledge through coursework, they are more apt to declare a major and as they gain more

knowledge in their field, more students would have an opportunity to work in a job related to

their major through an internship or coop.

36

Limitations and Future Directions

This study has several limitations worth noting. First, the results should be interpreted

carefully, as the number of hours worked and social involvement only accounted for 6% of the

variance in student retention and the hours worked variable and job type variable only accounted

for 3% of the variance in student retention. Most people in the sample were retained (74.3%).

Including hours worked and social involvement variables was only slightly better at predicting

student retention than the base model. This indicates that there are other variables that were not

studied that have a larger impact on student retention. It also supports past research indicating

that student retention is a very complex topic which still requires additional research.

Another limitation was the hours worked ranges. For this study, moderate hours was

defined as 1-15 hours a week as that showed up most in the previous literature. A small subset

of literature (Dundes & Marx, 2006; Ehrenberg & Sherman, 1987) used different combinations

of hours in their research. It is recommended that future research look at hours per week as a

continuous variable and review other possible ranges to determine the threshold of number of

hours per week that benefits retention for students.

A third limitation was the small number of students that worked in a job related to their

major. The impact of a job related to a student’s major is more apt to be seen as students are

further along in their degree program. More students would have declared a major and as they

gain more knowledge in their field, would have an opportunity to work in a job related to their

major through an internship or coop. A longitudinal study is recommended to follow students

across multiple years to address this question.

The fourth limitation was the differences found in the study when comparing four-year

public non-doctoral universities to all four-year universities (public, private, doctoral, and non-

37

doctoral). This suggests that the characteristics of the institution may influence the relationship

between employment and retention. It is recommended that institutional characteristics be

included when studying the impact of employment on retention in future studies.

The final limitation deals with the definition of retention. The primary and supplemental

studies defined retention as full-time for year one and then full-time or part-time for year two. A

final recommendation is to explore the impact of employment on retention of students that are

full-time for year one and continue full-time into year two. These full-time students could be

compared to those that decrease their credit load to part-time for their second year. Looking at

the retention in this way will help to better understand the impact that employment is having on

students staying in school and the length of time it is taking to complete school. As the majority

of undergraduate students work while attending college; it is important to continue to look for

ways to help students balance the competing demands of school, work, and family to help

improve the retention of students not only for the first year, but until graduation.

38

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43

Appendix A: Data License and Use

From: <[email protected]> Date: December 17, 2014 at 9:27:06 AM CST To: <[email protected]> Cc: Bethany Ring <[email protected]>, Marilyn Seastrom <[email protected]>, Jason Browning <[email protected]>, "Jesse Rine" <[email protected]>, Tami Le <[email protected]> Subject: Approved- #12120006 Application number: 12120006 Principal Project Officer (PPO) Name Meridith Drzakowski Title Assistant Chancellor Organization University of Wisconsin-Stout Address 802 Broadway Street South Building Bowman Hall Room 124 City Menomonie State/Zip Code WI 54751 Phone (715) 232-5312 Fax (715) 232-5406 Email [email protected] Dear Meridith Drzakowski, Your request to extend the time period for your License has been approved. Your License now expires on: 1/15/2020 1:33:33 PM Please place a copy of this approved License extension amendment in your License file. If you have any questions, please contact us. IES Data Security Office Department of Education/IES/NCES 1990 K. Street, NW, Room 9060 Washington, DC 20006 202-502-7307 IES Data Security Office

45

Appendix B: Breakdown of Variables

Independent Variables Description Response Options JOBHOUR2 Average number of hours

worked per week for all jobs while enrolled.

Continuous – Divide into 3 categories. 1-Non-Working (0 Hours) 2-Moderate Hours (1-15 Hours) 3-Long Hours (16+ Hours)

JOBONOFF Specifies the location of the job where the respondent worked most hours.

1-On-campus 2-Off-campus 3-Both on and off campus

SOCINX04 Social involvement index, is a derived continuous variable revealing frequency of attendance at fine arts activities, intramural sports, varsity sports, or school clubs.

Continuous

MAJORS12 A condensed version of 12 majors or fields of study that shows the students major.

0-Undeclared or not in a degree program 1-Humanities 2-Social/behavioral sciences 3-Life sciences 4-Physical sciences 5-Math 6-Computer/information science 7-Engineering/engineering technologies 8-Education 9-Business/management 10-Health 11-Vocational/Technical 12-Other technical/ professional

JOBMAJOR Signifies if the job is related to his/her major.

0-No 1-Yes

46

Dependent Variables Description Response Options ENR0310 Enrollment in October 2003 0-Not Enrolled

1-Enrolled Full-time 2-Enrolled Part-time

ENR0410 Enrollment in October 2004 0-Not Enrolled 1-Enrolled Full-time 2-Enrolled Part-time

RETAINED Derived Variable to determine if student was retained from October 2003 to October 2004

0-No 1-Yes

Demographic Variables Description Response Options GENDER Gender 1-Male

2-Female AGE Age first year enrolled Continuous RACE Race / ethnicity 1-White

2-Black or African American 3-Hispanic or Latino 4-Asian 5-American Indian or Alaska Native 6-Native Hawaiian or Pacific Islander 7-Other 8-More than one race

FSECTOR09

Indicates the type of the first institution attended during the 2003-2004 academic year

1-Pulic less-than-2-year 2-Public 2-year 3-Public 4-year nondoctorate granting 4-Public 4-year doctoral granting 5-Private nfp less than 4-year 6-Private nfb 4-year nondoctorate granting 7-Private nfp 4-year doctorate granting 8-Private for-profit less than 2-year 9-Private for-profit 2-years or more

47

Appendix C: Supplemental Analysis Detail

Supplemental Analyses

Supplemental analyses focus on employment impacts of student retention of first-time,

full-time freshman at all four-year universities (public, private, doctoral and non-doctoral) as a

comparison to the primary sample that focused only on public, non-doctoral 4-year institutions.

The broader sample included 7,202 first-time, full-time freshman at all four-year

universities (public, private, doctoral and non-doctoral) that began college in 2003. The majority

of students in the sample were 18 years old (63.3%) with an ethnicity of white (72.1%). The

sample included slightly more females (56.2%) than males (43.7). The detailed demographic

information is shown in Table 7. There were 5,774 (80%) students who were retained and 1,428

(20%) students who were not retained into their second year.


Hypothesis 1. Students that work 1-15 hours per week are more likely to be retained than

students who work over 15 hours per week or those who do not work at all.


hours worked and student retention. The relationship between student retention and hours

worked was statistically significant (2 (2, N=7,202) = 145.13, p < .001). The breakdown of

student retention by hours worked is shown in Table 8. Follow-up- tests were conducted by

examining the standardized residuals. Compared to the expected null, non-working students and

students working moderate hours were retained at a higher rate than expected and students

working long hours were retained a much lower rate than expected. Students working a

moderate number of hours were the most likely to be retained. This pattern differs from the

48

sample including only public, non-doctoral-granting institutions where non-working students

were most likely to be retained.

Employment Location




employment location and student retention. The relationship between student retention and

employment location was statistically significant (2 (2, N=3,181) = 110.50, p < .001). The

breakdown of student retention by employment location is shown in Table 9. Follow-up tests

were conducted by examining the standardized residuals. Compared to the expected null,

students that worked off-campus were retained at a lower rate than expected and students that

worked on-campus were retained at a higher rate than expected. Similar to the primary sample,

students working off-campus were less likely to be retained.




A chi-square test of independence was also performed to examine the blended

relationship between hours worked, employment location, and student retention. The

relationship between hours worked, employment location, and student retention was statistically

significant for moderate hours worked (2 (2, N=3,181) = 10.60, p = .005) and long hours

worked (2 (2, N=3,181) = 18.55, p < .001). The breakdown of student retention by hours

worked by employment location is shown in Table 10. Follow-up tests were conducted by

examining the standardized residuals for the working students. Compared to the expected null,

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students working on-campus were more likely to be retained than students working off-campus.

In addition, the relationship between hours worked and student retention was also statistically

significant for non-working students (2 (1, N = 2966) = 1319.11, p < .001). Non-working

students were also less likely to drop out than expected. Students working long hours on-campus

were less likely to drop out than those working a moderate number of hours. This is different

than the pattern found in the primary analysis where students working a moderate number of

hours on-campus were less likely to be drop out.





A logistic regression analysis was performed to explore the interaction between social

involvement and hours worked on the likelihood that students will be retained. Data from 7,202

students was available for analysis: 2,966 students who were not working, 2,253 students who

were working a moderate number of hours (1-15 hours per week), and 1,983 students who were

working long hours (16+ hours per week).



= 7,202) = 213.65, p < .001, indicating that hours worked and social involvement impacted

student retention. The full model including the hours worked and social involvement variables

was slightly better at predicting student retention than the constant only model, and explained

4.6% (Nagelkerke R2) of the variance in student retention. The classification table indicates

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80.2% of students were correctly classified, although this percentage was not an improvement

over the constant only model.

Table 11 shows b-weights, standard errors, Wald tests, significance, and odds ratios of

the individual predictors to the model. There were four main effects which were all significant

suggesting that there is a relationship between student retention and the combination of

independent variables: not working (p < .001), moderate hours (p < .001), and long hours (p <

.001), and the social involvement index (p < .001). Students working a moderate number of

hours were 1.87 more likely to be retained than non-working students and students working long

hours were 1.92 times more likely to be retained than non-working students. In addition,

students that were more socially involved were 1.01 times more likely to be retained. However,

an interaction between hours worked at any level and social involvement was not found. Social

involvement did not moderate the relationship between hours worked and retention. This is

different than in the primary analysis where social involvement did moderate the relationship

between hours worked and retention.


Hypothesis 5. Type of employment will moderate the relationship between hours worked

and retention, such that students working in a job related to their major will be more likely to be

retained if they are working, regardless of the number of hours worked.

A logistic regression analysis was performed to explore the interaction between type of

employment and hours worked on the likelihood that students would be retained. Of the 7,202

students, the majority of students (5,106) declared a major. In addition, 467 were working in a

job related to their major and 6,735 were working in a job unrelated to their major.

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= 7202) = 138.47, p < .001. The full model including the hours worked and type of employment

variables was slightly better at predicting student retention than the constant only model. The

model explained 3.0% (Nagelkerke R2) of the variance in student retention. The classification

table indicates 80.2% of students were correctly classified, although this percentage was not an

improvement over the constant only model.

Table 12 shows b-weights, standard errors, Wald tests, significance, and odds ratios of

the individual predictors to the model. There were three main effects that were statistically

significant suggesting that there is a relationship between student retention and hours worked:

not working (p < .001), moderate hours (p < .001), and long hours (p < .001). Students working

a moderate number of hours were 2.02 times more likely to be retained than non-working

students and students working long hours were 2.75 times more likely to be retained than non-

working students. However, an interaction between hours worked and type of employment was

not found. Like in the primary analysis, hypothesis 5 was not supported. Type of employment

and the interaction between type of employment and hours worked was shown to be unrelated to

student retention.

impact of employment on student retention at four-year … · 2016. 6. 20. · tuttle, mckinney...

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