thesis

The Influence of Conscientiousness

on the Dynamics of Institutional Departure

Alicia R. Damia

An Abstract of a Thesis

Submitted in Partial Fulfillment of the

Requirements for the Degree of

Master of Arts

In

Psychology

Department of Psychology

Central Connecticut State University

New Britain, Connecticut

October 2003

Thesis Advisor

Dr. Marc Goldstein


Key Words: College Students, College Dropout, Personality Traits

Influence of Conscientiousness Page numbers



Over the years concerns have increased about retention and attrition in higher

education. In order to develop and improve retention services it is important to

understand the underlying dynamics associated with institutional departure.

As opposed to research on college performance, much less research exists

regarding the ability of personality characteristics to predict college retention. Such pre-

entry characteristics have been surmised to indirectly affect departure by influencing a

person’s intentions and commitments regarding future educational activities.

The purpose of this study was to explore the dynamics of institutional departure at

a medium-sized northeastern university among a convenience sample of first-time, first-

semester students. Specifically, the study investigated the possible impact of

conscientiousness on the dynamics of college student departure. It was suspected that

more conscientious students would have a higher commitment to educational goals,

become more academically integrated into the university, have a higher grade point

average, and be less likely to depart from the university.

Fifty-six participants completed the conscientiousness subscale of the NEO-FFI

and the goal commitment subscale of the Student Adaptation to College Questionnaire,

along with a demographic questionnaire within the first two weeks of the semester.

Approximately nine weeks later, participants completed the goal commitment subscale

(for a second time), along with the academic integration subscale of the Student

Adaptation to College Questionnaire. At the beginning of the spring semester grade point

average and registration status were accessed via the university’s computerized student

records system.


Structural equation modeling was used to analyze the data. Some, but not all, of

the original hypothesized paths within the model were supported. Overall, the results

indicated that conscientiousness does significantly impact departure via academic

integration. The results suggest the utility of incorporating personality traits into studies

of institutional departure. Widening the investigation will help generate a more complete

picture of students at risk for departure, and can thereby help shape future intervention

programs geared toward retention.



Alicia R. Damia

A Thesis

Submitted in Partial Fulfillment of the

Requirements for the Degree of

Master of Arts in Psychology


Central Connecticut State University

New Britain, Connecticut

October 2003

Thesis Advisor

Dr. Marc Goldstein





Concerns about retention and attrition in higher education have increased over the

years both on a national and international level (Brawer, 1996; Kowalski, 1982; Yorke,

1998). According to Brawer (1996), approximately 50% of freshmen enrolled in colleges

and universities drop out before completing their degree. American College Testing (as

cited in Whitbourne, 2002) reported that one in four students leave college before

sophomore year. Retention has implications for both the university and to the future

labor market.

Importance of retention

Improving retention rates has fiscal implications for an institution (Glennen,

Farren, & Vowell, 1996; Yorke, 1998). Retention affects funding patterns, facilities

planning, student services available and academic programs offered (Heisserer & Parette,

2002). All of the above typically rely heavily on tuition revenue (Braunstein & McGrath,

1997). To taxpayers and legislators, improved retention and graduation rates demonstrate

the accountability of the institution and can help lead to increased funding in the case of

public institutions. The added fiscal resources generated by increased retention rates

enable institutions to improve and maintain programs and services (Glennen, Farren, &

Vowell, 1996).

Retention also affects the future labor market, because students who do not have

proper training for the workforce are generally unprepared to meet the expected roles and

responsibilities associated with certain professions (Heisserer & Parette, 2002).

Individual students who attain their academic goals improve their chance of success in

today’s competitive society (Glennen, Farren, & Vowell, 1996).


In order to develop and improve retention services it is important to understand

the underlying dynamics associated with institutional departure. This study explores the

role of personality, specifically the trait of conscientiousness, in college student departure.

As Tross, Harper, Osher, and Kneidinger (2000) state, research examining personality

and institutional departure provides additional insight into potential predictors of college

performance and retention and can assist institutions "in providing better services to

diverse constituents, including the student themselves, parents, taxpayers, and future

employers" (p. 332).

Tinto’s theory of attrition

To begin, it is pertinent to discuss the theoretical framework driving much of the

student attrition research. One of the most dominant models of college student departure

is that of Tinto (Okun & Finch, 1998). Tinto’s model (1987) revolves around four

primary components: pre-entry characteristics, goals and commitments, external

commitments, and academic and social experiences (see Figure 1). In this model

institutional departure arises out of a longitudinal process of complex interactions.

According to Tinto (1987), the “goodness of fit” between the individual and the

institution shapes two underlying commitments: commitment to educational goals and

commitment to the specific institution. Goal commitment refers the person’s willingness

to work toward the attainment of educational and occupational goals. Institutional

commitment refers to how loyal a person feels toward a specific college/university.

Institutional commitment is strongly associated with social integration, whereas goal

commitment is more strongly associated with academic integration. Further, both goal

and institutional commitment are posited to be the most proximate causes of institutional

departure. In other words, the higher the goal of college completion and/or level of


commitment to a specific institution the greater the probability of college persistence.

Individuals enter institutions of higher education from a wide range of: family and

community backgrounds, personal attributes, intellectual and social skills, and pre-college

educational experiences and achievements (Tinto, 1987). These pre-entry characteristics

have been shown to influence initial levels of goal and institutional commitment, which

in turn, interact with the institution’s academic and social system and lead to varying

degrees of academic and social integration (Tinto, 1987). Experiences within the

institution’s academic and social systems continually modify the individual’s intentions

and commitments.

Additionally, institutions of higher education do not exist in a vacuum. An

institution, and the academic and social communities within it, is nested within a larger

external environment. This larger environment is also comprised of multiple

communities, such as family, peers, work, and culture, each with its own set of values,

expectations, and requirements. Tinto’s model (1987) recognizes that for many students

going to college is just one of many commitments they have to balance over the course of

a college career. External commitments alter the person’s intentions as well as goal and

institutional commitments at entry and throughout the college career (Tinto, 1987).

Past Research

Several studies have investigated the correlates of college student

withdrawal/persistence. What appears most evident is the absence of a single causal

factor (Snell & Makies, 1993), and that persistence is the result of a complex set of

interactions over time (Cabrera, Nora & Casteneda, 1993).

In 1975, Kowalski (as cited in Kowalski, 1982) identified a variety of factors

differentiating persisting from non-persisting students. Persisting students were more


mature, flexible, selective in choice of school, and certain about their educational goals.

They had a greater sense of self-awareness, more self-motivation, better study habits,

more self-discipline, greater parental support, more financial security, less parental

pressure, higher aspirations, greater endurance, more interest in school, and greater

intellectual and academic abilities. Conversely, Kowalski found non-persisting students

suffer from poor motivation, inadequate work habits, uncertain goals, general lack of

interest in school, and immaturity in their attitudes and perceptions. They had low

achievement drives, lacked initiative, had financial difficulties, were indecisive and

disorganized, and were lacking in intellectual independence. In addition, they were often

unlikely to identify with or become involved in college life and related campus activities.

These findings point to many of the important aspects of Tinto’s (1987) attrition model:

pre-entry characteristics, academic and social integration, commitment, and external

environmental factors.

While Kowalski’s research only hinted at aspects of Tinto’s model, Pascarella and

Terenzini (1983) attempted to validate the model using a path-analytic approach with data

collected from a sample of 763 residential university freshmen. In general, the analysis

yielded results consistent with the model’s expectations. And, according to Pascarella and

Terenzini (1983), the classification analyses correctly identified approximately 80% of

the persisters and voluntary withdrawals.

Initial goal commitment was influenced by pre-college characteristics and

schooling, and in turn, had a direct influence on both academic and social integration, and

subsequent commitment to graduation from college. Although initial institutional

commitment had a direct effect on subsequent institutional commitment, it did not

influence social integration. Academic integration directly influenced goal commitment,


which in turn, had a direct effect on persistence. Social integration directly influenced

institutional commitment, which in turn, directly affected persistence. Unexpectedly,

academic integration also had a direct influence on institutional commitment. Although

the direct effects of academic and social integration on persistence were approximately

equal, the effect of institutional commitment was nearly three times that of goal

commitment.

Interestingly, none of the background characteristics or initial commitment

variables had a direct influence on persistence. Rather, their effects were indirect,

transmitted via social and academic integration or subsequent institutional and goal

commitment. Thus, it appears that the influence of differences in pre-college

characteristics and levels of commitment are mediated predominantly by variations in

students’ actual freshmen year experiences.

When the sample was separated by gender, Pascarella and Terenzini (1983) found

notable differences. For women, the results indicated social integration had a somewhat

stronger direct effect on voluntary freshmen year persistence/withdrawal decisions than

academic integration, whereas the reverse was found for males. Further analysis

suggested a significant compensatory interaction between social and academic integration

and between institutional and goal commitment. Academic integration was most

important for students with low levels of social integration, and vice versa. Similarly,

goal commitment was most important for students with low levels of institutional

commitment, and institutional commitment was most salient for students with low levels

of goal commitment.

Also in 1983, Pascarella and Chapman conducted a multi-institutional, path

analytic validation of Tinto’s model of attrition. In this longitudinal study, data were


collected from 2,326 freshmen from 11, 2-year and 4-year institutions (both residential

and commuter). Again, the results generally supported the predictive validity of the

model. However, unlike the results of Pascarella and Terenzini (1983), the direct effects

of institutional and goal commitment on persistence were approximately equal. Social

and academic integration, while not directly influencing persistence, did have an indirect

effect through their direct influence on institutional commitment (social integration) and

both institutional and goal commitment (academic integration). Only two other variables

had direct effects: living on campus (positive) and attending a 2-year institution

(negative). The results indicated that background variables such as socioeconomic status

and high school grades, as well as institutional factors such as size, were mainly indirect,

with their effects transmitted via social and academic integration and institutional and

goal commitment.

The data supported much of Tinto’s model. The results also suggested that there

are differences in the patterns of influence depending on the type of institution. These

differences concerned social and academic integration. Social integration played a

stronger role in influencing persistence at 4-year residential institutions, while academic

integration was more salient at 2- and 4-year commuter institutions. The influence of

background characteristics on persistence was also different for each type of institution.

High school achievement had a direct effect on persistence for the 4-year commuter

sample, and affiliation needs had a direct negative effect in the 2-year commuter sample.

The authors note that goal commitment, which had the strongest direct effect on

persistence at the 2-year commuter sample, was strongly influenced by background traits

and uninfluenced by integration.

According to Aitken (1982), most studies of retention have not estimated formal-


structural models, but rather attempted to test for association between retention and a

series of potential explanatory variables. Aitken (1982) commented that the Pascarella

and Terenzini (1982) study is an exception, but that the researchers included sixteen pre-

college characteristics in their single equation with little theoretical justification. In a

desire for a more mathematical approach to the study of student persistence, Aitken

(1982) presented a four equation structural model of student satisfaction, performance

and retention. His formal, mathematically-derived model includes variables that capture

the impact of various aspects of the physical environment and the quality of services

provided at the institution, and is specified in such a way that identifies where these

variables have their major impact. Each equation measures major aspects of student’s

experience: retention, academic satisfaction, living satisfaction, and academic

performance.

Aitken’s model was developed from data gathered from 892 first-year students at

the University of Massachusetts. For retention, results showed that poor grades play the

largest relative role in explaining non-retention. This was followed by satisfaction with

residential living experience and academic experience. For external factors impacting

retention, concern with family/personal problems was statistically significant

(negatively). Interestingly, concern with financial problems was not significant, indicating

that financial constraints do not appear to be as important a factor in causing student

withdrawal as previously assumed. Activity involvement was also not significant. Aitken

explained however that since this variable has been found to be significant in explaining

nationwide retention over four years, its major impact might come after the first year.

Regarding academic satisfaction, four variables were identified; in order of

importance they were perceived GPA, followed by course satisfaction, a measure of


isolation, satisfaction with major, and rating of instructors. Aitken (1982) stated that

academic performance appears to be even more important in determining retention rates

since it not only has a direct effect on retention, but an indirect one as well through

academic satisfaction.

Results demonstrated that peer relationships are important predictors for living

satisfaction. Liking people on the floor or corridor, satisfaction with the behavior of other

students in the dormitory as a whole, and roommate satisfaction were all highly

significant and rank as the top three variables in terms of importance. Older students were

less satisfied with dormitory living than younger students, indicating this may be due to a

proportionately smaller group of students their age with whom they associate.

However, peer relationships were not the only important determinant of living

satisfaction. At a staff level, the more effective the student dorm counselor the greater the

students’ satisfaction with their living environment. Satisfaction with dorm physical

condition, study facilities, dorm security and delay in room assignment were also all

statistically significant. On the other hand, dorm size, satisfaction with university food

service, and satisfaction with dorm head of residence did not significantly impact living

satisfaction.

A multitude of variables had a significant effect on academic performance,

measured by GPA at the end of the first academic year. Higher GPA was associated with

higher high school rank, higher SAT verbal and math score, gender (female), positive

rating of instructors, fewer sick days, enrollment in more small-sized courses, and fewer

personal problem days. Contrary to theoretical expectations, student satisfaction with

study facilities was negatively related to GPA. Aitken (1982) stated because this variable

is positively related to dorm living satisfaction but negatively to GPA, it appears to be


picking up two effects: variation in the actual quality of study facilities and variation in

the students’ perceived need for study facilities. He surmised that students with high

academic motivation may tend to rate study facilities lower than those with less academic

motivation, and therefore the variable appears, in part, to be a measure of motivation.

Another interesting result regarding academic performance relates to the

significant negative effect of peer relationships. The results suggest that peer relationships

play a dual role in retention. On the one hand, peer relations are essential for students’

satisfaction with their campus living experience, which in turn positively affects the

prospects for retention. On the other hand, the more time spent on social relations, the

less is available for study, which tends to lower both the student’s grades and academic

satisfaction. “The prospects for retention would appear to be improved, therefore, by

programs that can integrate the students’ academic and social experiences” (Aitken, 1982,

p. 45).

In a longitudinal study, Cabrera, Nora, and Castaneda (1993) tested an integrated

model of student retention, combining Tinto’s model with that of Bean (1985, as cited in

Cabrera, Nora, & Castaneda, 1993), which places a greater emphasis on factors external

to the institution. Their goal was to examine to what extent the two theories could be

merged in order to improve understanding of the underlying processes of persistence in

college. Their research examined two environmental variables and four endogenous

variables. Encouragement from friends and family and attitudes towards their financial

situation comprised the environmental variables, while the endogenous variables included

measures of academic integration, social integration, institutional commitment and goal

commitment.

The largest total effect on persistence was accounted for by intent to persist,


followed by GPA, institutional commitment, encouragement from friends and family,

goal commitment, academic integration, finance attitudes, and social integration. The

largest total effect on intent to persist was accounted for by institutional commitment,

followed by encouragement from friends and family, goal commitment, academic

integration, social integration, and finance attitudes. Thus, whereas Tinto’s model

constrained the role of environmental variables to shaping commitments, Cabrera et al.

(1993) found that these factors exert an influence in the socialization and academic

experiences of the students. This supports Bean’s propositions that environmental

variables should be taken into account in explaining persistence processes.

As indicated by Cabrera, Nora, and Castaneda (1993), intention to persist appears

to be an important variable in predicting college student withdrawal. Okun, Benin, and

Brandt-Williams (1996) examined moderators of the relation between intention and

institutional departure. They hypothesized that the magnitude of the relation between

intention and subsequent enrollment behaviors varied with grades, commitment, and

encouragement from others to stay. Specifically, they posited that as semester GPA

increases, the intent-departure relation will increase. For students who earn good and

excellent grades, intention (to stay or transfer) should be strongly related to institutional

departure because the grades should not undermine their intentions. In contrast, for those

who intend to transfer, fair grades may reduce the probability of success in college in

general; and for those who intend to stay, fair grades may reduce the probability of

success at their current college. Thus, intention should be moderately related to

institutional departure among those with fair grades. For students who do poorly, the

intentions of both those who intend to stay and to transfer are undermined. In these cases,

intention should be weakly related to institutional departure.


The second hypothesis of the Okun et al 1996 study was that as commitment

increases, the intent-departure relation would increase. It was expected that when students

assigned the highest priority to their grades, they would be most likely to enact their

intentions. Thus, the relation between intention and departure behavior would be strong

when doing well in college was the highest priority. In contrast, for students who made

doing well in college their second or third highest priority, it was expected that some of

them would shift their intentions in the face of unforeseen events, such as job changes.

For students who did not make doing well in college one of their three highest priorities,

the researchers predicted that the association between intention and departure would be

weak. These students lack commitment to the academic component of college and hence

should be most susceptible to shifting their intentions.

And, the third hypothesis was that as encouragement to stay increases, the intent-

departure relation would decrease. Despite low encouragement to stay, students intending

to stay are expected to re-enroll, whereas low encouragement to stay should lead to high

departure rates among those intending to transfer. Thus, intention should be strongly

related to persistence among students with low encouragement to stay. According to

Okun et al, high encouragement to stay should undermine the intention of students

planning to transfer, because changing colleges often is contingent on the support of

significant others. Consequently, intention should be weakly related to departure among

students high in encouragement to stay.

Researchers drew a random sample from introductory psychology courses,

stratified proportionately by day versus evening courses, offered at a community college

in Phoenix, Arizona. In total, there were 652 students included in the final analyses. The

sample only differed from the rest of population in that it was somewhat biased towards


students who earned some credit hours and at least a “C” average.

In general, the findings indicated that for students who intend to stay and to

transfer alike, credit loads of 1-3 hours and semester GPAs below 2.0 are associated with

increased risk of institutional departure. The intention to transfer appears to be

undermined by high encouragement to stay and by moderate commitment to the goal of

doing well in college. Contrary to the first hypothesis, poor academic performance, did

not moderate the intention-departure relation. One explanation was that nonacademic

events such as work and family attenuate the relation between intention and institutional

departure.

In support of the second hypothesis, the intention-departure relation was higher

among students who place a high priority in doing well in college as compared to students

who place a moderate priority on doing well. A moderate as opposed to high priority on

doing well in college may contribute to unintended persistence among students intending

to transfer. Surprisingly, the intention-departure relation was also strong among student

who placed a low priority on doing well in college. The authors are cautious about this

result, as it may be an anomaly, in that only 9 students in the sample intended to transfer

and assigned a low priority to doing well in college.

The results also confirmed the third hypothesis, in that for students who intended

to transfer, encouragement from others to stay exhibited a strong, inverse linear relation

with institutional departure. When encouragement to stay was high, over 80% of students

intending to transfer subsequently re-enrolled in the same college. Thus, encouragement

may play a vital role in unintended persistence among students intending to transfer. Pre-

college variables such as gender, age, ethnicity, marital status, number of children, and

hours working did not exert a direct effect on institutional departure.


In 1998, Kern, Fagley, and Miller focused on the relationship between retention

and GPA and academic-related variables including learning, study and test-taking

strategies, students’ attitudes about college, and ACT scores. The study asked the

following questions: What variables are related to GPA and to attrition? Do different

variables predict attrition than predict GPA? What variables predict GPA and attrition

after controlling for subject differences in ACT and the other variables? The sample

consisted of 102 undergraduate students enrolled in a career planning and development

course at a southwestern state university.

Multiple regression analyses revealed that GPA has a direct effect on attrition and

that ACT scores as well as certain study skills like information processing, selecting main

ideas, self testing, and the composite of motivation, time management, and concentration

have indirect effects on attrition through GPA. The authors comment that these findings

suggest that GPA and retention should be considered distinct outcomes. In bivariate

correlations, only motivation was significantly related to both GPA and attrition.

Therefore, although prior academic achievement was significantly related to college

GPA, other variables also were significantly related to GPA. These variables, especially

information processing, time management strategies and test strategies, are amenable to

intervention. Moreover, the finding that attrition was more strongly correlated to

motivational self-ratings than to learning and study skills may be useful in alternative

intervention strategies as opposed to those concentrating on enhancing study skills alone.

On an international level, Mackie (2001) explored student withdrawal behavior

during the first year of an undergraduate modular program in the business school of a new

university in England. This qualitative study examined the reasons why some students

voluntarily left the university, while others, who share similar experiences and


difficulties, stayed. Special attention was given to the complex interplay of factors

(personal, institutional and external), which lead up to the decision by a student to

withdraw.

Mackie (2001) found that individual commitment plays a critical role in the

decision to persist or withdraw. Based upon the data, Mackie developed a model of the

first year experience. In this model, the major hurdles of the first year are social and

organizational integration. Initial commitment, long-term objective, and continued

motivation are identified as the driving forces that push or pull the student over these

hurdles. “The height of the hurdles is not as important a factor as the willingness of the

student to jump” (Mackie, 2001, p. 273). Initial commitment is the push, and long-term

objective and sustained motivation are the pull.

Social integration feedback from peers and organizational integration feedback

from professors increases or decreases the commitment to stay. Progress is further

fostered or impeded by external factors. Departure results from a failure of social or

organizational integration, insurmountable external problems or failure in individual

commitment. Either commitment levels are strong enough to overcome the problems, or

feedback is negative and commitment decreases. Departure early in the year is most likely

the result of a failure in social integration, particularly in making friends and supportive

relationships. Departure later in the year is most likely the result of a failure in

organizational integration and is concerned with the type and content of courses.

While individual commitment emerged as a central factor, Mackie emphasized

that the intention is not to place blame for departure with students themselves. Students

arrive with some level of commitment and intention to complete and that by the

beginning of the second term universities succeed, for some, “in turning this ‘expectant


hope’ into ‘fears realized’ and may have failed to exploit the potential within that initial

commitment” (Mackie, 2001, p. 275).

Personality, College Performance, and Attrition

Spurred by a drop what they considered a predictive validity of the Scholastic

Aptitude Test (SAT), Wolfe and Johnson (1995) investigated the utility of using

personality variables in predicting college GPA. Data was collected from 201 students

enrolled in psychology courses at SUNY Geneseo. Subjects completed the Jackson

Personality Inventory, a scale compiled from the Multidimensional Personality

Questionnaire representing each basic dimension on the original questionnaire, the 35-

item Big 5 Inventory, and additional items representing need for cognition, general self-

efficacy, self-handicapping, and academic procrastination. SAT scores were obtained

from the college’s records office.

The study supported Wolfe and Johnson’s assertion that personality dimensions

can, in fact, predict college performance. Specifically, self-control emerged as the most

robust predictor. Multiple regression analyses revealed that in predicting GPA, it does not

matter how self-control is defined or measured. Organization, control, conscientiousness

and self-efficacy all accounted for roughly equal portions of GPA variance, and all

entered their respective analyses ahead of SAT.

Musgrave-Marquart and Bromley (1997) also found that personality dimensions

could predict college performance. One hundred sixty-one university students enrolled in

psychology courses completed the Revised NEO Personality Inventory measuring

neuroticism, extroversion, openness, agreeableness and conscientiousness, the Academic

Attributional Style Questionnaire, and the Substance Use Questionnaire. The analyses

revealed that conscientiousness, openness and neuroticism stood out as the best predictors


of academic achievement using stepwise multiple regression. In support of the

hypothesis, conscientiousness was the best predictor of high GPA. Costa and McCrae

(1992, as cited in Musgrave-Marquart and Bromley, 1997) explained that openness is

modestly related to intelligence and somewhat more strongly related to measures of

divergent thinking. The results of this study appear to confirm this contention.

Unexpectedly, neuroticism was also positively correlated with GPA. The authors deduced

that the study’s timing was central in this finding. The survey was administered at the end

of the semester when students typically are more aroused and anxious. This result raises

the question as to whether neuroticism, with its multiple components (anxiety,

anger/hostility, depression, self-consciousness, impulsiveness, and vulnerability), is an

element of academic success within a temporal context.

As opposed to research on college performance, much less research exists

regarding the ability of personality characteristics to predict college retention (Tross et al.,

2000). However their importance is no less than that of other predictors. According to

Tinto (1987), pre-entry characteristics indirectly affect departure by influencing a

person’s formulation on intentions and commitments regarding future educational

activities. In this sense, Tinto (1987) asserted that commitments mirror aspects of

personality, which predispose an individual toward goal attainment. And, though

intuitively it would make sense that personality must play a role in student withdrawal,

“we are unable to say just how different elements of personality affect student leaving”

(Tinto, 1987, p. 79).

Okun and Finch (1998) investigated the role of the “Big Five” personality

dimensions in the dynamics of institutional departure. Their hypothesized path model of

institutional departure focused on four variables: subjective social integration, changes in


institutional commitment, cumulative GPA, and institutional departure. For social

integration, they proposed that extraversion and agreeableness would indirectly affect it

through their influence on organizational involvement and number of friends.

Conscientiousness was expected to exert an indirect effect on social integration via initial

institutional commitment and also via organizational involvement. Openness to

experience was posited to exert an indirect effect on social integration via its influence on

living in a dorm.

They predicted that institutional commitment at time 2 would be affected by

institutional commitment at time 1 and subjective social integration. They reasoned that

institutional commitment would exert a direct effect on cumulative GPA, and that

students with high conscientiousness would attain higher grades than students with low

conscientiousness. A similar prediction was made in reference to openness to experience.

And finally, they hypothesized that the likelihood of institutional departure would

decrease as cumulative GPA and institutional commitment increased.

Their sample consisted of 240 first-time, first-semester students enrolled in

introductory psychology course at a large Southwestern state university. Participants

completed the 44-item version of the Big Five Inventory and 4-items measuring

institutional commitment from the Student Adaptation to College Questionnaire. Seven

weeks later the participants completed the subjective integration scale and the

institutional commitment scale of the Student Adaptation to College Questionnaire.

Cumulative GPA and enrollment status was extracted from the university’s student

records system at the end of the spring semester.

Overall, Okun and Finch (1998) found that personality dimensions contribute

substantially to the prediction of institutional departure. The sensitivity rate for detecting


students who departed, using cumulative GPA, institutional commitment at time 2 and

conscientiousness as predictors was 78.6%, higher than previous studies using a

minimum of six predictors. In terms of their specific hypotheses, some were confirmed,

while others were not supported by the data.

For subjective social integration, neuroticism and initial institutional commitment

were the strongest predictors. As neuroticism increased, first time, first-semester students

were less likely to have made an adequate adjustment to the social demands of starting

college. This stands in somewhat of a contrast to Musgrave-Marquart and Bromley’s

findings that found neuroticism to be a positive indicator of academic adjustment.

Consistent with past research, those with higher levels of institutional commitment were

more likely to perceive themselves as being integrated into the university’s social system.

Involvement in organizations, conscientiousness, and extraversion were

significant positive predictors of subjective social integration. Conscientiousness

appeared to influence initial institutional commitment and organizational involvement,

which, in turn, exert direct effects on subjective social integration. Extraversion was

positively related to number of friends and to organizational involvement, thereby,

indirectly effecting subjective social integration via organizational involvement. Contrary

to the hypothesis however, neither number of friends nor living in the dorm were

predictors of subjective social integration. Openness to experience was positively related

to living in a dorm; however, it did not exert an indirect effect on subjective social

integration. Also, contrary to predictions, agreeableness did not predict number of friends,

which in turn, did not predict subjective social integration.

Regarding institutional commitment at time 2, significant effects were associated

with initial institutional commitment, neuroticism, and conscientiousness. As


hypothesized, institutional commitment at time 1 exerted both a direct and indirect effect

via subjective social integration on institutional commitment at time 2. Neuroticism had a

negative indirect effect on institutional commitment at time 2 through its influence on

subjective social integration. In contrast, conscientiousness had a positive indirect effect

on institutional commitment at time 2 via its influence on organizational involvement and

initial institutional commitment.

In support of the hypothesis for cumulative GPA, conscientiousness was found to

exert a direct effect. However, contrary to expectations, openness to experience and

institutional commitment at time 2 did not exert a direct effect on cumulative GPA. Less

than 4% of the variance in cumulative GPA was accounted for in the study.

As predicted, the strongest predictor of institutional departure was cumulative

GPA. As GPA increased, the likelihood of institutional departure decreased. Also as

expected, institutional commitment at time 2 was inversely related to institutional

departure. Although not part of the original predictions, conscientiousness was found to

exert a direct effect on institutional departure. As conscientiousness increases, first-time,

first-semester students were more likely to persist at the institution.

In review, in Okun and Finch’s (1998) study of the Big Five personality

dimensions, conscientiousness exerted a much larger total effect on institutional departure

than either institutional commitment at time 2 or subjective social integration.

Conscientiousness exerted both a direct effect as well as indirect effect via organization

involvement, initial institutional commitment, and grades upon departure.

In 2000, Tross et al. investigated the influence of a somewhat different set of

personality characteristics on student persistence. They examined the impact of

conscientiousness, achievement, and resiliency in predicting college performance and


college retention. There were two primary hypotheses for this study. First, individuals

possessing higher levels of achievement, conscientiousness, and resiliency would

subsequently earn higher college GPAs than would individuals possessing lower levels of

these characteristics. Second, individuals possessing more achievement,

conscientiousness and resiliency should be more likely to stay than individuals with lower

levels of these characteristics.

The sample consisted of 844 first-year students enrolled in psychology courses at

a large, public southeastern university. During the first week of classes, participants

completed the Achievement, Academic Commitment, and Resilience scales of the

College Adjustment Inventory. Additional information, including high school GPA, total

SAT score and first-year cumulative college GPA, was gathered from the college’s

student records. Retention was operationally defined by whether or not the participants

were enrolled in the college’s subsequent academic year.

The findings supported the hypothesis that conscientiousness significantly

predicts both college GPA and college retention. Conscientiousness predicted both

involuntary and voluntary attrition. They surmised that more conscientiousness

individuals may be more likely to feel commitment to their chosen college and less likely

to consider other academic or professional options, and hence are more likely to stay

enrolled. However, the personality dimensions of achievement and resiliency were not

significant predictors.

The zero-order correlations between achievement and college performance and

retention were significant, but these effects were lowered significantly when

conscientiousness was entered into a combined regression equation. In essence, the

predictive ability of achievement was used by conscientiousness. The authors noted that


the predictive ability of achievement was restricted by apparent range restriction, as

evidenced with a high mean and low standard deviation. Additionally, Tross et al. (2000)

point out that the institution where the study was conducted was highly selective, which

may have contributed to the possible range restriction on the achievement measure.

There were no significant results for resiliency. One explanation posited by the

researchers is that individuals must face a significant challenge before resiliency can be

demonstrated. Given that the study was conducted at the beginning of the students’ first

foray into higher education, they may not have yet experienced the adversity necessary to

adequately gauge resiliency.

Limitations of Previous Research

The majority of previous research on college performance and retention has

primarily focused on what Tross et al. (2000) call the “usual cast of characters,” with an

over-reliance on “can do” and an under-reliance on “will do.” Tross et al. (2000) stress

that there is a difference. According to Wolfe and Johnson (1995) as the SAT continues

to show signs of predictive weakness, promising alternatives should be explored. For

these reasons, the characteristic of conscientiousness and personality variables in general,

deserve more research attention. Widening the investigation to examine these personality

characteristics will help generate a more complete picture of students at risk for

departure, and can thereby help shape future intervention programs geared toward

retention.

Possible Predictor: Conscientiousness

There exists a host of potentially relevant personality characteristics that may

provide additional insight into the dynamics of institutional departure. To further build

upon research in this arena the current study will examine the role of a specific


personality trait, conscientiousness.

Conscientiousness can be defined as the tendency to carry out tasks in a careful

manner until their completion (Tross et al., 2000). A more conscientious person is

diligent, careful, and organized, whereas a less conscientiousness person is unreliable,

imprecise, disorganized, and impetuous. It has been found to be a valid predictor of

occupational performance (Barrick & Mount, 1991; Mount, Barrick, & Strauss, 1999) and

of academic performance (Okun & Finch, 1998; Tross et al., 2000; Wolfe & Johnson,

1995). Research demonstrates that the personality characteristic of conscientiousness

adds significant variance to the prediction of subsequent college GPA (Wolfe & Johnson,

1995).

In addition, conscientiousness does not appear susceptible to response distortion

or social desirability (Ellingson, Sackett, & Hough, 1999; Hough, Eaton, Dunnette,

Kamp, & McCloy, 1990) and is a relatively stable, personality-based characteristic

(Hough & Schneider, 1996). Research such as that of Wolfe and Johnson (1995), Okun

and Finch (1998), and Tross et al. (2000) provides additional support for the use of

conscientiousness in the academic setting and the inclusion of this characteristic in

models that seek to explain academic performance and retention. However, additional

research is needed to further investigate the dynamics between conscientiousness and

retention (Tross, et al., 2000), specifically regarding commitment and integration.

Individuals possessing higher levels of conscientiousness may be more likely to

stay than individuals with lower levels of this characteristic. Individuals who are more

responsible, reliable, and driven, will be more involved and committed to the college and

obtaining good grades, and hence, less likely to withdraw.


Current Study

The present study explores the question: What is the impact of conscientiousness

on college student departure? To investigate this question, participants completed two

self-report questionnaires: the Student Adaptation to College Questionnaire and the

conscientiousness subscale of the NEO-FFI along with a demographic questionnaire.

Figure 2 illustrates the hypothesized path model of institutional departure being

tested in the current study. Following are the specific predictions for four endogenous

variables: academic integration, goal commitment, grade point average (GPA), and

institutional departure.

Academic Integration

It was anticipated that two variables, conscientiousness and initial goal

commitment, would have direct effects on academic integration. Conscientious students,

those who want to excel and who are organized and diligent, will become more involved

in the academic system of the college, as opposed to students who are disorganized,

impetuous and who do not want to put in extra effort. As posited by Tinto’s model

(1987), initial goal commitment is an antecedent to academic integration. It is reasoned

that those students committed to educational attainment will invest themselves in the

academic life at the university. Conscientiousness should also exert an indirect effect on

academic integration via goal commitment.

Goal Commitment

It was hypothesized that there will be a significant path from conscientiousness to

initial goal commitment. Those who are diligent and planning will have a strong

commitment to educational goals. Initial goal commitment in turn, is expected to directly

influence goal commitment at time 2. Likewise, academic integration will directly


influence goal commitment at time 2. The more integrated into the academic system of

the university, the more committed the student will become to educational goals.

Moreover, conscientiousness will indirectly impact goal commitment at time 2 via its

connection to academic integration and initial goal commitment.

First Semester GPA

As previous research has demonstrated conscientiousness predicts academic

performance (Okun & Finch, 1998; Tross et al., 2000). Therefore, it was expected that

conscientiousness will directly impact first semester GPA. Being organized, hardworking,

and persistent, conscientious students are expected to obtain better grades than low

conscientious students. The amount of academic integration should directly impact grades

as well. Greater involvement in academic endeavors leads to increased knowledge, which

is then reflected in academic performance.

Institutional Departure

Grades were expected to predict institutional departure. Previous research has

indicated that poor grades (Aitken, 1982; Okun & Finch, 1998) are strongly associated

with institutional departure. Based upon the study by Okun and Finch (1998)

conscientiousness was also hypothesized to exert a direct influence of institutional

departure.

If these hypotheses are supported, the results would suggest the utility of

incorporating personality dimensions into studies on the dynamics of institutional

departure.


Method

Participants

Fifty-six first-year, first-semester college students (19 males, 37 females), age 18

and older, served as participants. Table 1 provides a complete description of the sample’s

demographic characteristics. Participants were solicited from the incoming freshmen

student population at Western Connecticut State University, with 43 of the participants

residing in campus residence halls. This institution is a non-selective predominantly

commuter university.

Materials

Table 2 provides a description of the measured variables. A demographic

questionnaire was used to gather information on the characteristics of the sample (see

Appendix A for copy of questionnaire). The questionnaire asked for age, gender,

ethnicity, number of hours worked at a job, number of credits being taken, and if the

student’s parents and siblings have attended college.

Conscientiousness was assessed with a subscale of the NEO-FFI (Costa &

McCrae, 1985). The NEO-FFI was developed to meet the needs of researchers and

professionals who need a brief, comprehensive measure of the five domains of

personality. This instrument is a shortened version of Form S of the NEO-PI. The

conscientiousness subscale consists of 18-items. In each case the participant responds

using a 5-point scale. Examples of items on the subscale include: I think twice before

answering a question; I strive for excellence in everything I do; I have a clear set of goals

and work towards them in an orderly fashion. In the current study, the conscientiousness

subscale of the NEO-FFI had an alpha reliability of .78.


The Student Adaptation to College Questionnaire (Baker & Siryk, 1984) is a self-

report questionnaire containing items that are rated on a 9-point scale (1 = doesn’t apply

to me at all, 9 = applies very closely to me). Goal commitment was measured with items

from the Institutional Attachment/Goal Commitment subscale. The items relate to the

students’ feelings about being in college in general. The three items from this subscale

were: I am pleased now about my decision to go to college; Lately I have been giving a

lot of thought to dropping out of college altogether and for good; and, I find myself giving

considerable thought to taking time off from college and finishing later. With the present

sample, the three goal commitment items had an alpha reliability of .64 at time 1 and an

alpha reliability of .69 at time 2. The correlation between goal commitment scores at time

1 and time 2 was .325, p<.05.

Academic integration was measured using the Academic Adjustment subscale of

the Student Adaptation to College Questionnaire. It consists of 24 items referring to

various facets of the educational demands characteristic of the college experience.

Example items from this subscale include: Recently I have had trouble concentrating

when I try to study; I am enjoying my academic work at college; I have been keeping up

to date on my academic work. The academic integration subscale had an alpha reliability

of .89 in the current study.

Grade point average (GPA) and enrollment status were extracted from the

computerized student information system at the start of the spring semester. Enrollment

status was coded 1 if the student was not registered for classes at the beginning of the

spring semester, and was coded 2 if the student was registered for classes at the beginning

of the spring semester.


Procedure

This study was approved by the Human Subjects Review Committee of Western

Connecticut State University as well as the Human Studies Council at Central

Connecticut State University (see Appendix B for approval forms).

Data were collected in two waves. Initial data collection (time 1) was conducted

in groups in the lounge areas of the various residence halls at Western Connecticut State

University following a mandatory meeting for freshmen residents within the first two

weeks of the fall semester. Participants completed an informed consent form. Once the

forms were completed and handed in, participants were given a packet consisting of:

demographic questionnaire, conscientiousness subscale of the NEO-FFI, and the goal

commitment subscale of the Student Adaptation to College Questionnaire, in that order.

Approximately nine weeks later, at time 2, participants were contacted individually to

complete the goal commitment subscale (for a second time), along with the academic

integration subscale of the Student Adaptation to College Questionnaire. Students either

completed the measurements at the researcher’s office, or they completed them over the

telephone with the researcher.

Participants were instructed to complete each scale thoroughly and to take as

much time as necessary. It took approximately 40 minutes to complete the questionnaire

packet at time 1, and approximately 15 minutes to complete the packet at time 2. At the

initial data collection 64 students completed the informed consent and survey packet.

Fifty-six of those students completed the packet at time 2.

Fall semester GPA and enrollment status for the spring semester were extracted

from the student information system by matching students with either their student

identification number or their full name, as some students did not feel comfortable


providing the researcher with their identification number.

There were no missing data.

Results

Prior to analysis, means and standard deviations were obtained for all variables to

determine if the distributions for each were normal. With the exception of goal

commitment, the variables did not violate the assumption of normality. Both goal

commitment at time 1 and time 2 were highly negatively skewed. In order to use the data

for goal commitment appropriately, the variable, at time 1 and time 2, was reverse-coded

to make it positively skewed. Then, log base 10 transformations were done to reduce

skewness. It should be noted that this process does create a restricted range.

Correlations

Table 3 presents the correlations among the six measured variables.

Structural Equation Analysis

Structural equation modeling (SEM) via LISREL VIII (Joreskog & Sorbom, 2000)

was used to test the hypothesized model of the influence of conscientiousness on the

dynamics of institutional departure (see Figure 2). Single indicators were used in this

study due to the small sample size. If the measurement model with multiple indicators

were used, number of estimated parameters would have been too large for the sample

size. The covariance matrix was analyzed for the six indicators using maximum

likelihood estimation. For each indicator the error variance was fixed at one minus the

alpha times the total variance of the indicator. Additionally, the factor loading was fixed

at the square root of the total variance minus the error variance. The structural component

of the model was specified in keeping with the anticipated direct and indirect effects on

institutional departure as shown in Figure 2. Conscientiousness and goal commitment at


time 1 were allowed to correlate.

In the current study, three indices were employed to assess model fit: the Chi

Square goodness-of-fit test, the Tucker Lewis Index (or non-normed fit index; NNFI), and

the Root Mean Square Error of Approximation (RMSEA). A non-significant chi-square

value, that is with a probability greater than .05, indicates that the data fit the

hypothesized model. For the Tucker-Lewis Index values of .90 or greater reflect an

adequate fit of a specified model to the data. For the Root Mean Square Error of

Approximation values less than .05 indicate a good model fit.

The fit of the initially specified model was weak, 2(6, N)=9.23, p=.19,

NNFI=.88, RMSEA=.26. Inspection of the modification indices revealed that adding a

path from goal commitment at time 2 to departure would significantly improve the fit of

the model to the data. The addition of this path corresponds to previous research by

Pascarella and Chapman (1983) as well as Pascarella and Terenzini (1983), who found

that the lower the goal of college completion (goal commitment), the greater the

likelihood of college withdrawal. Therefore, this path was specified in the revised model.

The fit of the revised model was satisfactory, 2(5, N)=4.13, p=.53, NNFI = 1.04,

RMSEA =0.0. The t-values associated with four of the structural paths in the original

hypothesized model were not statistically significant. Accordingly, these paths were

deleted from the model. Also, the path from academic integration to goal commitment at

time 2 was only significant at the .10 level. While this is a low standard, it is not

unreasonable to include the path given the small sample size.

The trimmed model was then re-estimated with only the significant paths. Figure

3 presents the standardized path coefficients associated with the trimmed model.

Discussion


The present study explored whether the personality dimension of

conscientiousness has an influence on the dynamics of institutional departure. Using

multiple goodness of fit criteria, and with an added path, the model was shown to provide

a satisfactory fit to the data. Overall, it appears conscientiousness does increase the

prediction of institutional departure. Nevertheless, before elaborating on the findings, it is

important to discuss several limitations of the present study.

Study Limitations

Limitations of the present study revolve predominantly around sample issues.

Lack of student interest to participate in the study caused much of the difficulty in data

analysis. Any results obtained from a sample of only 56 participants must be interpreted

with great caution. This small sample may in part, explain why goal commitment at time

1 was not significantly linked with goal commitment at 2 or academic integration as

previous research has repeatedly demonstrated.

The sample is also relatively homogeneous in terms of race and gender. The

majority are white non-Hispanic women, followed by white non-Hispanic men. The fact

that the study was conducted at only one medium-sized university limits generalization.

Additionally, there was a relatively low dropout rate within the small sample. Due to time

constraints on the study, enrollment status was obtained after only a single semester of

college had been completed. This may not have been enough time to accurately gauge the

dynamics at play in decisions to persist or depart. The majority of studies in this area

obtain enrollment status at the end of the spring semester, when departure typically

occurs. For all these reasons, as stated above, caution must be taken in making

generalizations of the research findings to different types of students and different types

of higher education institutions.



Academic Integration. It was originally hypothesized that conscientiousness and

initial goal commitment would each exert a direct effect on academic integration. Only

conscientiousness had a significant direct effect. The positive sign associated with the

beta for conscientiousness indicates that as conscientiousness increases, first-semester

students are more likely to become integrated into the academic system of college. This

suggests that those students who are more diligent, organized, and have a drive to excel,

will become more involved in the academic life and activities of college, as opposed to

students who are disorganized, impetuous, and who do not want to put in extra effort.

According to Tinto’s model (1987) and previous research (Pascarella & Terenzini,

1983; Pascarella & Chapman, 1983), initial goal commitment is an antecedent of

academic integration. However, the findings of this study do not indicate that connection.

It may be that the sample size was just too small to garner an effect.

Goal Commitment. As suspected, conscientiousness was found to have a

significant direct effect on initial goal commitment. The negative sign associated with the

beta is somewhat deceiving. Recall that initial goal commitment was recoded making it

positively skewed, as opposed to negatively skewed, in order to transform the data to

reduce skewness. Therefore, a lower number then became associated with stronger

commitment. Thus, the significant path means that more conscientious students have, at

least initially, a stronger commitment to educational goals.

Regarding direct effects on goal commitment at time 2 once again the results are

mixed. It was hypothesized that initial goal commitment and academic integration would

each directly effect goal commitment at time 2. Consistent with Tinto’s model (1987),

academic integration directly effected goal commitment at time 2. Because goal


commitment at time 2 was recoded to reduce skewness, greater commitment became

associated with a lower score. Thus, the negative sign associated with the path from

academic integration should be interpreted to mean that the more integrated into the

academic system of the university, the more committed the student becomes to

educational goals.

Contrary to expectations, initial goal commitment did not influence subsequent

goal commitment. Again, this may be due to the very small sample size.

In terms of indirect effects, conscientiousness had a positive indirect effect on

goal commitment at time 2, via its influence on academic integration. More

conscientiousness students have greater integration into the academic life of college and

thereby have a greater commitment to educational goals.

First Semester GPA. It was hypothesized that conscientiousness and academic

integration would each directly impact first semester grade point average. In support of

the hypothesis, academic integration exerted a significant positive direct effect on first

semester GPA. The more integrated students become into academic activities at the

university, the better their grades.

Conscientiousness did not have a significant direct impact on first semester GPA.

This is not consistent with previous research demonstrating that conscientiousness

directly influences grades (Wolfe & Johnson, 1995; Okun & Finch, 1998; Tross, et al,

2000). However, via its connection to academic integration, conscientiousness exerted a

significant indirect effect on GPA. More conscientious students become more involved in

academic life at the university and this then translates into a higher GPA.

Institutional Departure. Confirming the hypothesis, GPA had a significant direct

effect on institutional departure. As GPA increased, the more likely a student was to re-


enroll at the institution. Or, to say it another way, as GPA increased, the likelihood of

institutional departure decreased. This finding is consistent with previous research

indicating that poor grades strongly predict institutional departure (Aiken, 1982; Kern,

Fagley, & Miller, 1998; Okun & Finch, 1998).

Although not predicted, goal commitment at time 2 was inversely related to

institutional departure. As a student’s commitment to educational goals increases, the less

likely they are to leave the university. This corresponds to previous research by Pascarella

and Chapman (1983) as well as Pascarella and Terenzini (1983), who found that the

lower the goal of college completion (goal commitment), the greater the likelihood of

college withdrawal.

Contrary to expectations, conscientiousness did not exert a direct effect on

departure. On one hand, this result confirms findings by Pascarella and Chapman (1983)

which demonstrated that background characteristics indirectly influence departure. On the

other hand, this contrasts with the findings of Okun and Finch (1998) and may warrant

further investigation.

Overall, the results of the present study suggest that conscientiousness does in fact

influence the dynamics of institutional departure. Conscientiousness, a pre-entry variable

in Tinto’s model (1987), appears to influence the process of departure by exerting an

indirect effect on institutional departure via academic integration. More conscientious

students become more involved in academic activities or situations at college, greater

academic integration leads to a higher GPA and greater commitment to educational goals,

which decrease the likelihood of institutional departure.

Implications

The results of the present study suggest the utility of incorporating personality


traits into the study of institutional departure. Who a student is, based on background

characteristics as well as personality, does appear to play an important role in shaping

commitment and integration into university life. It may not be enough to provide students

only with the necessary skills to perform well in college. As Tross et al (2000) contend it

is not always an issue of “can do,” but rather “will do.” A student who is not

conscientious may indeed know the skills for college success, but simply may not be

using them. Widening the college departure investigation to include variables such as

personality can help generate a more complete picture of students at risk for departure,

and can thereby help shape future programs geared toward retention.

Practical Implications

In a practical sense this study’s findings reiterate the importance of early

engagement by the university to first-year students. Though specific student attributes,

such as conscientiousness, are largely beyond the control of the university, the institution

can control the settings in which students find themselves. While conscientious students

make the effort and become involved in their educational endeavors, the key for

universities is also to engage those students at the other end of the conscientiousness

spectrum. The path for these students, who are not particularly conscientious, does not

have to lead to departure. The university can foster educational commitments and

integration thereby diverting the path to institutional departure. The primary place for this

to occur is in the classroom.

Tinto (1999) points out that most freshmen experience education as isolated

learners. Their learning experiences resemble a spectator sport, in which faculty talk

dominates and where only a few students actively participate. By rethinking the structure

of the freshmen year classroom it may be possible to engage both conscientious and


unconscientious students. One suggestion is to build learning communities which

transform students from spectators into participants (Tinto, 1999).

At a basic level, learning communities involve block scheduling and/or linking

courses with a common theme. Learning communities enroll the same students in several

classes so they get to know each other quickly and fairly well and in a way that is an

integral part of their academic experience. Shared knowledge is another key aspect of

learning communities. Learning communities seek to involve students in ways, both

socially and intellectually, that promote cognitive development. They try to foster “an

appreciation for the many ways in which one’s own knowing is enhanced when other

voices are part of the learning experience” (Tinto, 1999, p. 7). Learning communities also

ask students to become responsible to each other in the learning process. Students

participate in collaborative groups, which require them to be mutually dependent on one

another. “This dependency ensures that the learning of the group does not advance

without each member doing her or his part” (Tinto, 1999, p. 7).

In addition, academic advising should be a fundamental part of learning

communities. Advising should be woven into the fabric of the freshmen year. Regular

contact with an academic advisor can foster commitment to educational goals and

increase academic integration among unconscientious students, who according to this

study, do not appear to actively do this independently.

Future Research

Most importantly, the results of the present study need to be replicated, as well as

extended. The sample size issues faced in this study alone make replication a necessity.

One direction for future research involves examining the narrow traits, such as

achievement-striving and self-discipline, which comprise the broader personality


dimension of conscientiousness. Although achievement and conscientiousness have been

treated similarly in some personality taxonomies, research by Hough et al. (1990)

indicates that achievement and conscientiousness are conceptually distinct personality

characteristics. The narrow traits defining the Big Five factors can surpass those broad

dimensions themselves in prediction of course grades (Paunonen & Ashton, 2001). Much

important information may be lost when focused solely at the broad Big Five factor level.

It seems plausible that the different aspects comprising the Big Five dimension of

conscientiousness may impact the dynamics of institutional departure in different ways.

For instance, self-discipline and deliberation may have a greater influence on goal

commitment, whereas competence and achievement-striving may have a greater impact

on academic integration.

Another important direction for future research is to differentiate among first-

time, first-semester students who persist, transfer, and drop out. What factors differentiate

drop-outs, transfer students and persisters? As Okun and Finch (1998) surmise, dropouts

will likely have low GPA, low institutional and goal commitment, compared to transfer

students who should exhibit moderate to high GPA, moderate to high goal commitment,

and low institutional commitment. Persisters should exhibit moderate to high grades, high

goal and institutional commitment. Also, are there changes in the way personality

dimensions influence the dynamics of institutional departure for drop-outs, transfer

students, and persisters?

Lastly, much of the research conducted on institutional departure appears to have

been conducted at relatively selective, if not highly selective, institutions of higher

education. The average GPA in the Tross, et al (2000) study was 3.64 and the average

SAT score was 1232. The 4 year retention rate of the university used in Okun and Finch


(1998) was 82.4%. This stands in contrast to the university used in the present study

where the average SAT score is 940 and where the freshmen retention rate is 70.6%.

More research in this area needs to be conducted at universities which are not so

selective. Typically, these are the institutions facing serious retention rate issues. It is at

these institutions where a better understanding of departure needs to take place.


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Table 1

Description of Demographic Variables

________________________________________________________________________

Variable Frequency % M SD Description code/scales

________________________________________________________________________

Age

18 50 89.3

> 19 6 10.7

Gender

Men 19 66.1

Women 37 33.9

Ethnicity

White 47 83.9

Afr. American 4 7.1

Latino 3 5.4

“Other” 2 3.6

Attended College

Mother 0 = No, 1 = Yes

Yes 28 50.0

No 25 44.6

No answer/NA 3 5.4

Father 0 = No, 1 = Yes

Yes 27 48.2

No 26 46.4


No answer/NA 3 5.4

Sister 0 = No, 1 = Yes

Yes 13 23.2

No 30 53.6

No answer/NA 13 23.2

Brother 0 = No, 1 = Yes

Yes 9 16.1

No 37 66.1

No answer/NA 10 17.9

Work Hours

0 40 71.4

8-10 8 14.3

11-20 6 10.8

21+ 2 3.6

Credit Hours 13.51 1.85

< 12 3 5.4

12 22 39.3

13-14 5 9.0

15 19 33.9

> 15 7 10.7

________________________________________________________________________


Table 2

Description of Measured Variables

________________________________________________________________________

Description

Variable M SD Reliability code/scales

________________________________________________________________________

Conscientiousness 66 7.66 .78 1 = Strongly Disagree

9 = Strongly Agree

Goal Commitmenta 1 = Strongly Disagree

9 = Strongly Agree

Time 1 .58 .62 .64

Time 2 .41 .54 .69

Academic Integration 1 = Strongly

Disagree

9 = Strongly Agree

Time 2 156.44 25.36 .89

Cumulative GPA 2.65 .94 0 = All F’s

4 = All A’s

Institutional Departure 1 = Not registered

2 = Registered

________________________________________________________________________

Note: Reliability was estimated by coefficient .

aDue to skewed data log transformations were performed on goal commitment at time 1

and time 2.


Table 3

Correlations among Study Variables

________________________________________________________________________

Variable 1 2 3 4 5 6

_______________________________________________________________________

1. Conscientiousness -- .429** .569** -.326* .419* .278*

2. Goal Commitment time 1 -- -.350** .325* -.391** .212

3. Academic Integration -- .385** .512** .263*

4. Goal Commitment time 2 -- -.166 -.373**

5. Grade Point Average -- .407**

6. Departure --

________________________________________________________________________

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


Figure 1. Tinto’s longitudinal model of institutional departure. FromLeaving college: Rethinking the causes and cures of student attrition(p. 114), by Vincent Tinto, 1987, Chicago: The University of ChicagoPress. Copyright 1987 by The University of Chicago Press. Reprintedwith permission.


Figure 2. Hypothesized model of the influence of conscientiousness on institutional

departure.

Conscientiousness

AcademicIntegration

Goal Commitment(Time 1) Goal Commitment

(Time 2)

GPA

Departure


Figure 3. Trimmed model with standardized path coefficients.

.55

-.37-.48

Conscientiousness

AcademicIntegration

Goal Commitment(Time 1)

GPA

Departure-.62


Appendix A

Demographic Questionnaire

AGE: _________________________GENDER: (circle one)

Male Female

ETHNICITY: (check one)_____ White Non-Hispanic_____ Black or African American_____ Latino or Hispanic_____ Asian_____ Pacific Islander_____ Native American_____ Native Hawaiian_____ Other: ___________________________

NUMBER OF CREDITS YOU ARE TAKING THIS SEMESTER: ___________NUMBER OF HOURS YOU WORK PER WEEK: _____________________(If you do not work then write 0 hours.)

HAVE ANY OF THE FOLLOWING MEMEBERS OF YOUR FAMILY ATTENDEDCOLLEGE:

Yes NoMother _______ ________Father _______ ________Brothers _______ ________Sisters _______ ________


Appendix B

Approval Forms



Prior to completing her Master’s Degree in Psychology at Central Connecticut State

University, Alicia R. Damia earned a B.A. in Psychology at Western Connecticut State

University in Danbury, CT and a B.A. in Communications at Marist College in

Poughkeepsie, NY. After a brief career as a newspaper editor and technical writer, Alicia

decided to take a position as an academic advisor to undeclared freshmen at Western

Connecticut State University. She makes her home in Danbury, CT.

thesis

Documents

college students

college retention

college questionnaire

college dropout

college performance

underlying dynamics

conscientiousness subscale

semester students