Student congruence with academic major: Do hours worked and attitude affect satisfaction and success?

Holland’s theory and person–environment fit

According to Holland’s theory, individuals and environments can be understood and defined through the RIASEC areas, often referred to as the hexagon or interest areas. Details regarding the RIASEC components are beyond this paper but can be found in many places (Holland, 1997; Gottfredson & Johnstun, 2009). Person–environment fit, or congruence, has been defined as the compatibility in the relationship between an individual’s characteristics and the characteristics of his or her environment (Kristof-Brown, Zimmerman, & Johnson, 2005). When individuals are paired with a certain environment, the interaction between their RIASEC personality and the environment (i.e. P–E fit or congruence) can be used to predict outcomes of success, satisfaction, vocational choice, stability, achievement and overall well-being (Broadbridge & Swanson, 2006; Holland, 1997). If an individual’s personality matches the characteristics of his or her environment, he/she should experience positive outcomes (Holland, 1997). For college students, environments are determined by major (e.g. Allen & Robbins, 2010). Since various factors that influence college student outcomes are determined by major, it is important to understand how students’ fit with their major affects satisfaction and success.

Person–environment fit has been most often studied within the world of work and less often in the college environment. In the college environment, fit between personality and major is related to higher grade point averages (GPAs) and persistence in major and career field (Tracey, Allen, & Robbins, 2012). Satisfaction and persistence in one’s major are important outcomes of P–E fit, as they lead to commitment to college and timely degree attainment (e.g. Allen & Robbins, 2008). As such, the goal of academic advisors and career counselors is often to aid students in finding a major that matches their interests (Crookston, 2009). However, some research has shown contradictory evidence on the importance of P–E fit, or congruence (specifically fit between students’ interests and academic major). Some studies and meta-analyses have found only small to moderate correlations between academic major congruence and outcomes of satisfaction and success (e.g. Assouline & Meir, 1987; Tranberg, Slane, & Ekeberg, 1993; Tsabari, Tziner, & Meir, 2005). The inspiration for this research is the idea that extraneous variables influence the strength of relations between congruence and academic outcomes. This study seeks to understand the role that students working and cognitive influence might play in this relationship.

Academic major satisfaction and success

Academic major satisfaction has been defined as the “enjoyment of one’s roles or experiences as a student” (e.g. Lent, Singley, Sheu, Schmidt, & Schmidt, 2007, p. 87). Although this construct has gained its own definition, academic major satisfaction has also been referred to as a way to measure the decision-making outcomes of college students in place of job satisfaction (Nauta, 2007). Nauta (2007) asserted that academic major satisfaction is like job satisfaction for college students in that different academic settings lead to different opportunities to utilize skills and interests.

Academic success is also an important factor that influences the college experience. Many researchers have studied academic success by using GPA or exam results (e.g. Dollinger & Orf, 1991). However, Welles (2010) noted that “the concept of academic success in college is complex and multifaceted” (p. 2). A meta-analysis by Robbins et al. (2004) found that psychosocial and study skills explained variance in academic outcomes above and beyond standardized tests scores and GPA when predicting academic outcomes in college students. Therefore, it is important to consider factors in addition to GPA when examining academic success. The current study made such efforts by measuring academic success through a multifaceted self-report measure in addition to GPA.

Additionally, academic success is directly related to degree attainment. This is troubling considering that over 50% of students will leave an institution without attaining a degree (Watson, 2013). Leaving college without a degree can cause students to earn less money, be financially unstable, and have fewer career opportunities (Martinez, Sher, Krull, & Wood, 2009). Understanding factors affecting academic success could aid higher education institutions in preventing academic failure.

Some work has been done to explore the relationship between congruence and satisfaction. One meta-analysis conducted by Tranberg et al. (1993) found that congruence and satisfaction were not significantly correlated, and other meta-analyses have also found weak or negative results (Assouline & Meir, 1987; Spokane, 1985). However, Holland (1997) argued that the inconsistency of results is partially explained by the methods by which congruence is measured. He noted that the integrity of the studies used in the meta-analyses varied greatly and most correlations were positive and supportive of the congruence construct (Holland, 1997). Additionally, not all of these studies assessed other life roles and work-relevant factors that moderate congruence or lack of congruence between a person and his/her work. Despite the varying research on congruence in the work context, Feldman, Smart, and Ethington (1999) found that college students’ congruence with their majors was a good predictor of academic major satisfaction.

Research that has been conducted on congruence and academic success has produced relatively weak relationships. Feldman et al. (1999) noted that the weak relationship between congruence and academic success could be due to poorly defined or differentially operationalized constructs, such as academic success itself. Despite these inconsistencies, some research has shown positive results between congruence and academic success, especially when success is defined through GPA. Students’ higher congruence with his or her major has been associated with higher GPA (Posthuma & Navran, 1970; Tracey & Robbins, 2006) and likelihood to remain in major (Tracey et al., 2012).

Students as employees

There has been research focused on applying Holland’s theory of vocational personalities and work environments to higher education settings (e.g. Feldman, Ethington, & Smart, 2001). There is, however, less research on how interest-major congruence is affected in students who serve in roles aside from their academic role. Working reflects time away from school and multiple priorities. Students with work obligations might not have adequate time or focus to benefit from congruence with their academic environment (Hawkins, Smith, & Hawkins, 2005). The impact of work on college students is substantial, as a growing number of college students are employed in addition to being enrolled in a full academic course load. The U.S. Census Bureau (2011) reported that 72 percent of college students held a job. Of those students, 20 percent held full-time, year-round positions. The remaining 52 percent held year-round jobs that averaged between 20 and 26 hours of work per week. However, Perna (2010) reported that higher education administrators suggested full-time college students work no more than ten to fifteen hours per week in an on-campus (rather than off-campus) job. Therefore, it would be beneficial to a large number of students to examine how working might affect congruence in college students. The relationships between success, satisfaction, and congruence have been explored in typical students (Tracey & Robbins, 2006; Tracey et al., 2012). Investigating students’ work roles is important to gain more insight into factors that moderate the congruence relationship.

The increasing cost of higher education, coupled with the lessening of government funding to universities, leaves many students with no other choice than to work during full-time enrollment in college (State Higher Education Executive Officers, 2013). Hall (2010) found that students were struggling in dealing with balancing work and school responsibilities. Park and Sprung (2013) identified work–school conflict as a notable stressor and found a negative relationship between work–school conflict and psychological health. Additionally, Furr and Elling (2000) found that the number of hours worked were positively related to students’ reports of employment interfering with academic advancement. Because college student employment is a trend that appears to be on the rise (U.S. Census Bureau, 2011), its effects on academic performance and well-being is crucial in understanding how to serve an increasingly employed college student body.

Cognitive influence

In addition to work hours, cognitive influences (e.g. positive thinking and negative career thoughts) are factors that could affect the benefits of congruence. Bekhet and Zauszniewski (2013) defined positive thinking as “a cognitive process that creates hopeful images, develops optimistic ideas, finds favorable solutions to problems, makes affirmative decisions, and produces an overall bright outlook on life” (p. 1076). Research has shown a link between factors related to positive thinking, such as hope and academic optimism, and positive academic outcomes such as GPA (Snyder et al., 2002) and academic achievement (e.g. student performance in courses; Hoy, Tarter, & Hoy, 2006). However, not all instances of positive thinking are beneficial. Boyraz and Lightsey (2012) noted that in some individuals, positive automatic thoughts could be indicative of unhealthy denial. In this case, data from those individuals might affect possible causal inferences about the true nature between positively thinking and positive outcomes. This is especially true for students who may be highly positive in spite of poor academic performance or satisfaction (i.e. low GPA with no chance of improving before graduation).

Career thoughts are defined as “outcomes of one’s thinking about assumptions, attitudes, behaviors, beliefs, feelings, plans, and/or strategies related to career problem solving and decision making” (Sampson, Reardon, Peterson, & Lenz, 2004, p. 91). The literature indicates a variety of negative outcomes related to negative career thoughts, including anxiety, poor job satisfaction, poor self-efficacy, and academic undecidedness (e.g. Sampson et al., 2004). As an example, Walker and Peterson (2012) found that dysfunctional career thoughts and occupational undecidedness were positively related to depressive symptoms in college students. These outcomes of negative career thoughts could be influential in understanding students’ congruency with their academic majors as negative career thoughts might affect major choice, major satisfaction, and academic success. Because of the aforementioned evidence in the literature that positive thinking and negative career thoughts affect or potentially interrupt the relationships between congruence, academic satisfaction, and academic success, positive thinking and negative career thoughts will be included as covariates in the current study to assure a purer look at the congruence, satisfaction, and success relationship.

Present study

The current study examined how working while in college might impact the relationship between students’ congruence with their major and academic major satisfaction and academic success while accounting for cognitive influences. The present study hypothesized that (a) when accounting for positive thinking and negative career thoughts, the relationship between congruence and academic major satisfaction will be moderated by number of work hours worked; (b) when accounting for positive thinking and negative career thoughts, the relationship between congruence and academic success as measured by GPA will be moderated by number of work hours worked; and (c) when accounting for positive thinking and negative career thoughts, the relationship between congruence and academic success as measured by self-report will be moderated by number of work hours worked.

Participants

The current study included 233 undergraduate students from a mid-sized southeastern university. The participant sample included 42 males (18%) and 191 females (82%). In terms of employment, 113 participants (48.5%) reported studying as well as working and 120 participants (51.5%) reported studying and not working. More details about the participants can be seen in Table 1.

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Table 1.

Demographic characteristics of sample.

Characteristic	n	%
Race
American Indian/Alaskan Native	3	1.3
Asian/Pacific Islander	1	.4
Black or African American	69	29.6
Hispanic	5	2.1
White	154	66.1
Other	1	.4
Year in college
Freshman	72	30.9
Sophomore	56	24.0
Junior	55	23.6
Senior	18	20.6
Other	2	.9
Hours worked per week
1–10	20	17.9
11–20	50	44.6
21–30	24	21.4
31–40	16	14.3
41–50	1	.9
51–60	1	.9

Procedure

Participants were recruited with the approval of the university’s Institutional Review Board. An online survey consisting of an informed consent statement, a demographics form, and measures of the study was advertised on the psychology department’s research recruitment website. The survey was hosted on Qualtrics, a data collection website, and linked to the recruitment website. Because the psychology department participant pool is largely female, additional male participants were recruited by emailing predominantly male student groups at the university which contributed approximately 15 participants total. Validity of data was addressed using validity check items, recommended by Meade and Craig (2012). Data were evaluated to determine validity of answers and participants who answered either validity item incorrectly were eliminated from the sample.

Measures

The Demographic Form prompted participants to provide their age, gender, race/ethnicity, year in college, college major, GPA, information on their work, including job status, type of job, number of hours worked per week, and the purpose for their jobs.

The O*NET Interests Profiler Short Form (National Center for O*NET Development, 1999) determined participants’ congruence with their college major. The 60 item measure includes 10 items for each of Holland’s RIASEC types (realistic, investigative, artistic, social, enterprising, and conventional) that reflect work activities within that type. Scores are determined by the number of self-reported “likes.” An interest or personality summary code is created using the three highest scoring RIASEC types. Congruence was calculated using the Iachan Agreement Index (Iachan, 1984), which assesses how well two codes match through weighted scores for certain pairings. For the current study, a participant’s code from the interest profiler was matched with the code associated with their major using the Educational Opportunities Finder (Rosen, Holmberg, & Holland, 1997). Iachan (1984) indicated what scores on the Iachan Agreement Index mean in regard to level of match between interests and environment. Scores range from 1 to 28. A score of 13 or below indicates a poor match, a score between 14 and 19 indicates a “not close” match, a score between 20 and 25 indicates a “reasonably close” match, and scores between 26 and 28 indicate a very close match. Recent studies still use this classification of congruence (e.g. Zanskas & Strohmer, 2010). In the current study, 50% of participants had a poor match, 10% had a not close match, 28% had a reasonably close match, and 12% had a very close match. Alpha coefficients of the RIASEC types in the O*NET Interests Profiler Short Form indicated acceptable levels of internal consistency (α = .78–.87; Rounds, Su, Lewis, & Rivkin, 2010).

The Academic Success Inventory for College Students (ASICS; Prevatt et al., 2011) was used to assess students’ level of academic success in areas other than GPA. The measure consists of 50 items, all scored on a 7-point Likert-type scale (1 = strongly disagree; 7 = strongly agree). Cronbach alpha for the 50-items was .93 (Welles, 2010). A total score was used in the current study but scores can be separated into 10 subscales. Higher scores indicate greater academic success.

The Academic Major Satisfaction Scale (AMSS; Nauta, 2007) was used to assess participants’ level of college major satisfaction. The measure consists of six items, all scored on a 5-point Likert-type scale (1 = strongly disagree; 5 = strongly agree). Scores from the six items are averaged to produce a score from one to five. Higher scores indicate a higher level of academic major satisfaction. Nauta (2007) reported high internal consistency for the six items (α = .90).

The Positive Automatic Thoughts Questionnaire (ATQ-P; Ingram & Wisnicki, 1988) was used to assess participants’ positive thinking. The measure consists of 30 items, all of which are scored on a 5-point Likert-type scale ranging from (1) never to (5) all the time (Ingram, Kendall, Siegle, Guarino, & McLaughlin, 1995). Total scores were used in the current study and can range from 30 to 150. Higher scores indicate more positive thinking. Burgess and Haaga (1994) found the coefficient alpha of the ATQ-P to be .95.

The Career Thoughts Inventory (CTI; Sampson, Peterson, Lenz, Reardon, & Saunders, 1996a) was used to determine the level of negative career thoughts experienced by participants. The measure consists of 48 items, all scored on a 4-point Likert-type scale (SD = Strongly Disagree, D = Disagree, A = Agree, SA = Strongly Agree), ranging from 0 to 4, respectively. The CTI yields a total score, which is the score that was used in the current study, as well as three subscale scores that measure specific areas of career related dysfunctional thinking. The subscales of the CTI are Decision Making Confusion (DMC), Commitment Anxiety (CA), and External Conflict (EC). Higher scores indicate more negative career thoughts. The CTI total score has evidence of high internal consistency in its college student normative group (α = .96; Sampson et al., 1996a).

Intercorrelations among all variables were computed and are presented in Table 2. Additionally, internal consistency alphas yielded for the current study’s measures were within the expected range based on the measures’ past internal consistency reports, and all alpha coefficients exceeded .77. This information is detailed in Table 3. Hierarchical multiple regressions were used to test the hypotheses in the current study. Preliminary analyses were conducted to ensure no violations of the assumptions of normality, linearity, multicollinearity, and homoscedasticity. Control variables and moderators were centered to reduce multicollinearity. All analyses were conducted with the full sample and a subsample including only those participants that indicated working. Results did not differ across sample/subsample analyzed for any hypothesis.

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Table 2.

Intercorrelations among variables.

	1	2	3	4	5	6	7	8
1. ATQ-P	1	−.48**	.05	−.05	.12	.29**	.19**	−.09
2. CTI	–	1	.06	.02	.05	.39**	.53**	.11
3. Congruence	–	–	1	−.07	−.20**	.10	.01	.01
4. Hours worked	–	–	–	1	.06	.06	−.16	−.36**
5. Profile elevation	–	–	–	–	1	.06	−.03	−.07
6. ASICS	–	–	–	–	–	1	.26**	.16*
7. AMSS	–	–	–	–	–	–	1	.07
8. GPA	–	–	–	–	–	–	–	1

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Table 3.

Scale reliabilities, means, and standard deviations.

Variable	α	M	SD	Range	Possible range
IP-SF	.93	.38	.46	0–1	0–1
Realistic	.89	.21	.41	0–1	0–1
Investigative	.84	.33	.46	0–1	0–1
Artistic	.88	.44	.49	0–1	0–1
Social	.77	.60	.48	0–1	0–1
Enterprising	.82	.43	.47	0–1	0–1
Conventional	.87	.25	.43	0–1	0–1
ASICS	.89	641.01	92.56	406.98–913.92	1–1000
AMSS	.92	3.43	.46	1–5	1–5
ATQ-P	.96	118.99	19.70	30–150	30–150
CTI	.98	105.04	29.91	0–144	0–144

ASICS: Academic Success Inventory for College Students; AMSS: Academic Major Satisfaction Scale; ATQ-P: Positive Automatic Thoughts Questionnaire; CTI: Career Thoughts Inventory.

Practical implications

The findings of the current study are of importance to career counseling professionals working with college students. The data in this study did not support the hypotheses that work influences the relationships between congruence, academic satisfaction, and academic success. Regardless, students find themselves holding multiple roles during their college careers and dealing with the balance of these roles. It might seem that students with majors that fit with their personality would prosper academically regardless of obstacles (e.g. poor time management) when faced with multiple roles. Yet, the frustration related to role conflicts might lead to additional problems such as poor psychological health which could affect academic performance (Park & Sprung, 2013). The current study provides little clarification on the effects work or interest level have on congruence with major or success. Yet, analyses do show that how an individual thinks about career development impacts some of these outcome variables. This area of research requires continued attention to better support interventions for these issues. Additionally, assessing congruence with college major is still a salient task for clinicians working with college students. Congruence with college major is related to positive outcomes such as persistence (Tracey et al., 2012). Therefore, students who are struggling with issues such as persisting in their major or degree might benefit from an intervention after the assessment of major fit.

The current study provides some correlational support for the impact of work on academic success. However, until there is more empirical support for the existence and strength of this relationship, interventions on related issues (e.g. finances) might be more justifiable and helpful. In the current study, 77% of working participants reported that they worked to support themselves (i.e. paying bills, buying groceries, maintaining transportation, etc.). Students who work to support themselves would be unable to terminate their employment to further focus on their academics without other financial support. Broton, Goldric-Rab, and Benson (2016) found that low-income students who were offered financial aid worked less and their work experience was improved (e.g. worked less undesirable shifts). Thus, college student development staff could aid students struggling with work–school balance in investigating other options to finance their educations. Because of the potential positive impact of financial aid, all university staff assisting working students should be aware of proper referrals to college financial aid departments to help the student better understand his/her options. Another option that professionals might explore is discussing course load with clients struggling with work–school balance. Students that work to support themselves and are either ineligible for financial aid or choose to decline it might have to decrease their enrollment to maintain employment. However, some findings indicate that students at the part-time enrollment level experience less satisfaction with their higher education experience (Moro-Egido & Panades, 2010). Clinicians should be cautious in their recommendations to help students make the decision best for their financial and educational goals.

Additionally, clinicians might need to target dysfunctional thinking to help students with work–school balance. The current study indicated that cognitive influences such as positive and negative thinking explained much of the variance in academic success and satisfaction. Although formal testing and feedback should not be used as a standalone intervention, gaining information about students’ cognitive influence could be useful in deciding on an approach to students’ presenting problems. For instance, students who strongly agree to items such as “I will be successful” and “There’s nothing to worry about” (ATQ-P; Ingram & Wisnicki, 1988) might have less dysfunctional thinking than students who strongly agree with items such as “I'm afraid if I try out my chosen occupation, I won't be successful” (CTI; Sampson et al., 1996a). Students who strongly agree to such statements might struggle with low self-confidence or career indecisiveness. Clinicians could assist students by using psychoeducation, modalities of therapy that the clinician deems appropriate, and career counseling, as addressing these issues is likely to impact academic satisfaction and success. One way to address these items would be to utilize the CTI workbook (Sampson, Peterson, Lenz, Reardon, & Saunders, 1996b), which can help students understand and challenge their negative thoughts.

Limitations and directions for future research

The lack of support for some aspects of the current study’s hypotheses highlight the generalizability limitation and prompts the need to explore these proposed relationships in a more diverse college student population as some research suggests that values regarding work vary across cultures (e.g. Iosua et al., 2014). The current study’s participants did represent some areas of diversity (e.g. 48% were low income; 10% non-traditional college students; 29.6% of participants identified as Black); yet were limited in several ways (e.g. all from the same university, heavily female, and many ethnic minority groups not represented). As previously mentioned, the U.S. Census Bureau (2011) reported that 72% of college students held a job with half of those averaging more hours than the recommendations for working college students (Perna, 2010). In the current study, 48.5% of participants held a job with 53.5% working more than 20 hours per week. Almost one-third of the sample was freshmen. Freshman may not hold jobs now but might at some point in their collegiate career. Outside of working rates, there are notable differences between the current sample and the population found in the U.S. Census. The current sample might differ from the sample of the U.S. as a whole regarding degree completion. As noted in the introduction, approximately 40% of students will leave an institution without attaining a degree (Watson, 2013); however, approximately half of the students in the institution sampled for the current study leave without a degree (Office of Institutional Research, 2015). This higher than average drop-out rate indicates that the sample studied is in particular need of understanding what contributes to their academic success.

It is possible that the hours worked moderation was not significant due to individual differences in participants’ definitions of academic success. Therefore, future research should explore the variance in students’ perspectives of academic success. Additionally, the inventory used to measure self-reported academic success, the ASICS, is a relatively new measure with little existing research. Future studies should consider exploring the usefulness and psychometric stability of this instrument. For instance, future research on the current study’s surprising finding of a positive relationship between scores on the ASICS and scores on the CTI may reveal nuances in the structure of the ASICS that could be altered to further strengthen the instrument. Additionally, cognitive influences (i.e. positive thinking and negative career thoughts) explained much of the variance in the relationships between congruence, academic success, and academic satisfaction. These variables were included in the analyses as covariates because of evidence in the literature that these variables might affect the aforementioned relationships (e.g. Snyder et al., 2002). However, the high amount of variance accounted for by these variables indicate that they might be better used as independent variables in future research.

Finally, it is possible that the participants in the current study were engaging in types of work that were like their major or shared transferable skills with their anticipated career. Students who engage in work during college that is related to their field of study and/or career goals reap benefits such as increased experience with the world of work and more transferable skills (Carnevale, Smith, Melton, & Price, 2015). In the current study, the congruence between participants’ jobs and majors was not assessed. The effects of working in field related to one’s major while in college could have affected the results of the current study in that the possible negative effect of increased working hours could be buffered if students felt satisfied because they felt their work while in college is furthering their career development.

Because of the aforementioned benefits, this is likely a worthwhile avenue of exploration while examining the relationship between congruence between interest and major and its relationship to academic success and satisfaction.