Assessing the Relationship Between Nontraditional Factors and Academic Entitlement

Abstract

The current study explores the intersection of two trends of interest in higher education: reported increases in academic entitlement (AE) and increases in the proportion of students considered nontraditional. AE has shown to have negative effects in the classroom and for students. Based on reports from educators, levels of AE may be lower for nontraditional students. The current study sought to understand the level of AE in nontraditional students, compare AE levels with traditional students, and investigate if specific nontraditional factors have larger impacts on AE. Four hundred and twenty-nine participants were assessed for nontraditional factors and their current level of AE. Nontraditional students were found to have lower levels of AE than traditional students, having more nontraditional factors predicted lower AE, and AE was found to vary within nontraditional grouping levels. Additionally, age and hours worked were found to be individual factors that best predicted AE levels.

Keywords

academic entitlement nontraditional students

Introduction

Academic entitlement (AE) is thought of as a student’s expectation that they deserve preferred grades despite actual performance or effort (Boswell, 2012; Chowning & Campbell, 2009; Greenberger et al., 2008). AE attitudes have become perennial complaints between professors and have reportedly increased in recent decades (Ciani et al., 2008; Lippmann et al., 2009). Jiang et al. (2017) report the most common AE behavior was asking for accommodations such as higher grades, exceptions to rules, and extra help. Blaming the professor was the second most common behavior. If these attitudes were merely nuisances for faculty, the current discussion could be handled in lounges across the academy. Instead, more research is linking AE to negative outcomes such as increased cheating tolerance (Shapiro, 2012), academic incivility (Jiang et al., 2017), academic dishonesty (Greenberger et al., 2008), and decreased course self-efficacy (Boswell, 2012). The current article seeks to explore how AE attitudes are related to one of the most important sectors of higher education—nontraditional students.

Nontraditional Students

Nontraditional students, often thought of as adult learners, are students whose educational pathway deviates from the seemingly normative model depicted in today’s society. Discussions of nontraditional students often occur under the umbrella of lifelong learning (LLL; Schuetze, 2014; Schuetze & Slowey, 2000). Within this model, two axes are of particular import (Slowey & Schuetze, 2012). The first focuses on learning taking place across one’s lifetime, not just in youth. The second highlights that learning can and does happen outside of formal education for most people. Exploring patterns of LLL globally, Slowey and Schuetze (2012) showcase how discussions revolving around LLL often involve particular subgroups that can be defined by aspects such as how they enter the educational system, their admission qualifications, and their primary motivations.

Nontraditional students make up a significant proportion of the undergraduate student population. The majority of college students hold at least one nontraditional factor, and the portion of the undergraduate population that is at least minimally nontraditional has been fairly stable for the past 20 years. Between 1995 and 2012, 70% to 75% of undergraduates displayed at least one factor of being nontraditional (U.S. Department of Education, National Center for Education Statistics, 2015). The National Center for Education Statistics has identified seven factors of nontraditional undergraduate students: a delay in beginning college, attending part-time, working 35 or more hours per week, being financially independent, having children or dependents, being single parents, and having a GED (Horn, 1996). Age is an additional factor often included.

Implications of Being a Nontraditional Student

Persistence is a common concern with nontraditional students with regard to degree completion. Additional stresses associated with being nontraditional, such as finances, family obligations, and work commitments, can negatively affect degree completion (Forbus et al., 2011; Taniguchi & Kaufman, 2005). Part-time enrollment can extend the time it takes for nontraditional students to obtain their degree, and part-time nontraditional enrollees are more likely to leave college without degree completion (Taniguchi & Kaufman, 2005). Within 3 years of beginning a Bachelor’s degree, 50% of highly nontraditional students were still enrolled while 88% of traditional students remained enrolled (U.S. Department of Education, National Center for Education Statistics 2002a).

Family status has both positive and negative effects on nontraditional students’ attendance. Suggested benefits of being married and/or having children include a positive support system and the motivation to be a role model for one’s own children (Forbus et al., 2011; Taniguchi & Kaufman, 2005). Taylor and House (2010) suggest that nontraditional students may be motivated by more intrinsic reasons than traditional students. However, the responsibilities of caring for one’s family can cause school enrollment to be an added stressful commitment if not taken on with caution and appropriate time-management skills (Forbus et al., 2011; Taniguchi & Kaufman, 2005).

Understanding the nonacademic barriers nontraditional students face is critical in supporting their success. Many nontraditional students report feeling isolated and unsupported when seeking academic assistance (Goncalves & Trunk, 2014; Meuleman et al., 2015). Part-time enrollment may allow for fewer interactions with professors and fellow students who can aid them in challenging educational times (Taniguchi & Kaufman, 2005). Nontraditional students report placing higher value on faculty interactions than traditional students (Lundberg, 2003), and learning is more enjoyable for nontraditional students when in collaboration with professors (Bye et al., 2007). Instructors echo these feelings by reporting positive perceptions of nontraditional students, reporting that nontraditional students were better at time management, more motivated, and could work independently to a higher degree (Brinthaupt & Eady, 2014). It may be that some of the positivity associated with nontraditional students is an acknowledgement of decreased AE.

Academic Entitlement

Sessoms et al. (2016) state that students with AE attitudes have three main negative attributes: an external locus of control, a belief they should exert control over policies in the classroom, and a belief that they are customers and should be treated as such. A consequence of this is they do not see themselves as an active participant in learning. Lippmann et al. (2009) see AE as a “self-centered disposition” (p. 198) where students disregard traditional faculty–student relationship norms in higher education. Kopp et al. (2011) point out that AE definitions are varied and some aspects may contradict each other. Others remind us that AE is likely best thought of as multidimensional (Jackson et al., 2011).

AE can have direct effects in the classroom. Jiang et al. (2017) found AE was positively correlated with reported incivility. Increases in incivility were connected to increases in work strain for professors. Some speculate that students with high AE can actually hinder a professor’s ability to teach effectively (Barrett & Scott, 2014), and others have discussed the formation of disengagement pacts where a professor and student have a tacit agreement to not ask too much of the other (Kuh, 2003). Overall, professors report increased stress from AE encounters (Jiang et al., 2017).

The current focus on AE attitudes is not just because it can have negative effects on faculty. Research continues to show that students themselves are likely the ones most harmed. AE has been directly linked to poor judgment making with regard to academic issues. Students with higher entitlement scores showed no difference in judging inappropriate behaviors and appropriate behaviors as acceptable, and entitled students reported being less likely to engage in academically appropriate behaviors (Chowning & Campbell, 2009). Elias (2017) found a negative relationship between AE and perceiving cheating as unethical. Students with higher levels of AE were more accepting of cheating behaviors. The negative associations linked to AE have bled out of the academic arena. AE has been negatively correlated with constructs such as self-esteem and social commitment (Greenberger et al., 2008).

Systemic Causes of Academic Entitlement

Increasing tuition costs have been implicated in increasing AE and creating feelings that students are customers purchasing a service (Lippmann et al., 2009). As state funding decreases, many universities must rely on tuition as revenue, which can influence the consumer model of higher education. This customer relations model may allow students to think they have inappropriate power and authority in academic situations (Cain et al., 2012). Schaefer et al. (2013) highlight that students enter college with unrealistic ideas of how effort and participation are the minimum criteria for success, while also having a mismatched set of expectations with regard to the consumer model applied in the typical college classroom. Shapiro (2012) echoes these findings as attitudes assessed before the first day of college indicated that AE was present in students prior to attendance.

Morrow (1994) was an early voice in understanding the shift toward increased entitlement. He described the shift from an educational focus on learning to one focused on achievement. College was once emphasized as a place of growth and development, but many now see it as a transaction like any other in the marketplace, where ability to pay is the only requirement for completion (Lippmann et al., 2009; Sohr-Preston & Boswell, 2015). Jackson et al. (2011) do highlight that there may be a mismatch regarding goals related to academic achievement between faculty and students. Faculty may see achievement in terms of mastery. Students may see achievement in terms of completion and graduation. In exploring reasons behind AE, six different themes were found; the unifying concept between these themes was control (Jackson et al., 2011; Singleton-Jackson et al., 2010). AE may be developed as a coping mechanism for poor performance (Greenberger et al., 2008). Elias (2017) found that students with higher GPAs (grade point average) were less likely to have higher AE, and self-esteem and AE have been found to be negatively correlated (Sohr-Preston & Boswell, 2015). AE attitudes may serve as a way to protect a threatened sense of self.

Individual Differences and Entitlement

Individual difference variables and demographics have been increasingly studied to help understand AE formation. Men tend to exhibit higher levels of AE than women (Boswell, 2012; Chowning & Campbell, 2009; Ciani et al., 2008; Elias, 2017; Greenberger et al., 2008; Sohr-Preston & Boswell, 2015), though some researchers find no gender differences (Lemke et al., 2017). Boswell (2012) discusses how men are socialized to place greater value on success and accomplishment, which may lead to valuing extrinsic rewards such as grades over learning and self-development. More focus on an external locus of control has been linked to AE attitudes (Chowning & Campbell, 2009). Men in our society may be more at risk to develop AE attitudes because of this.

While gender appears to have a consistent connection to AE, other variables are more unreliable. Some studies show small effects of ethnicity (Greenberger et al., 2008), while others report no effects (Sohr-Preston & Boswell, 2015). Stiles et al. (2017) compared attitudes about cheating and AE for an American and Chinese sample. While the Chinese sample showed higher AE, it was not predictive of cheating attitudes. For the American sample, AE attitudes were predictive of cheating attitudes. This finding is a reminder that the negative effects of AE may vary depending on cultural norms.

Time-related variables also show mixed results. Some research indicates age is not related to AE (Greenberger et al., 2008), while other studies find a connection (Schaefer et al., 2013). Exploring how being a first-generation student affected AE, Boswell (2012) found no difference in AE for first-generation versus continuing-generation students; however, different factors predicted AE in these students. For continuing-generation students, college course self-efficacy, sex, and social network usage were predictors of AE. In first-generation students, only college course self-efficacy predicted AE.

Ciani et al. (2008) suggest that AE may increase slightly the longer students are in college, as they found seniors to have more entitled beliefs than freshmen. However, Greenberger et al. (2008) found no evidence of association with year in school and AE, and Chowning and Campbell (2009) saw no difference in reported AE levels between first year and upper-class students. Other studies have found small increases in AE over the first 1.5 years of college (Sessoms et al., 2016). Hagedorn et al. (2001) found being younger was linked with increased retention.

The Current Study

Many of the individual difference factors reported above that have been thought to be linked to AE align with factors that are used to label students as nontraditional; however, limited research has explored the AE attitudes of these nontraditional students. Anecdotally, faculty report nontraditional students as being less entitled and having more nontraditional factors may reduce AE attitudes. The current study seeks to further understand the levels of AE found in nontraditional students and how different nontraditional factors can affect AE scores. Importantly, the current study will not just compare nontraditional students with traditional students. Understanding the AE attitudes of nontraditional students can be vital in understanding the future of higher education and planning appropriate retention and persistence interventions that often treat all nontraditional students identically. Most research to date explores nontraditional students as a single body. Having several nontraditional factors may greatly affect the way a student perceives their academic experience. Finally, the current study seeks to explore if individual nontraditional factors will predict AE attitudes.

Hypothesis 1: Nontraditional students will report lower levels of AE than traditional students.

Hypothesis 2: Participants with the most nontraditional factors will report lower levels of AE than traditional students.

Hypothesis 3: The number of nontraditional factors a participant reports will predict AE scores. In particular, having more nontraditional factors will predict decreased AE.

Hypothesis 4: The seven nontraditional factors model will predict AE attitudes. As this is an exploratory hypothesis, we do not make specific predictions concerning individual predictors.

Method

Participants

Participants (N = 429) were recruited from undergraduate psychology classes at a large, nonresidential, urban university in the south-central region of the United States. The sample included 311 women (72.5%), 114 men (26.6%), and 4 individuals (1%) who chose not to identify in binary gender terms. Age ranged from 18 to 65 years (M = 24.78 years, SD = 7.66). Participants were ethnically diverse; 191 (44.5%) identified as Latinx, 115 (26.8%) identified as Black, 57 (13.3%) identified as White, 45 identified as Asian (10.5%), 15 identified as Other (3.5%), and 6 individuals (1.4%) chose not to assign themselves an ethnicity. The sample is indicative of the student population of the university as reported by the most recent university fact book. Participants also identified themselves as either freshmen (112, 26.1%), sophomores (79, 18.4%), juniors (105, 24.5%), seniors (123, 28.7%), or college graduates/graduate students (10, 2.3%).

Measures

Nontraditional Factors

Participants were asked to provide personal information on criteria that commonly define nontraditional students: age, high school graduation status, enrollment delay, having dependents, single parent, hours worked, and enrollment status (U.S. Department of Education, National Center for Education Statistics 2002b). Participants were coded as nontraditional for the age factor if they reported being 25 years or older. Participants were coded as nontraditional for high school graduation status if they reported receiving their GED. Participants were coded as nontraditional for enrollment delay if they reported any delay in attending higher education. Participants were coded as nontraditional for dependent status if they reported having dependents. Participants were coded as nontraditional for single parent if they reported being single parents. Participants were coded as nontraditional for hours worked if they reported working 35 hours or more a week while enrolled. Participants were coded nontraditional for the enrollment status if they reported being anything but full-time students.

Based on Horn’s (1996) classification system, the number of nontraditional factors each participant identified was used to create four groups. Participants reporting no nontraditional factors formed the traditional group (35%), participants reporting one nontraditional factor formed the minimally nontraditional group (20.3%), participants reporting two or three nontraditional factors formed the moderately nontraditional group (31.2%), and participants reporting four to seven nontraditional factors formed the highly nontraditional group (13.5%), see Table 1 for a breakdown of nontraditional factors.

Table 1.

Nontraditional Factors by Nontraditional Grouping.

Nontraditional grouping	Traditional, n = 150 (35.0%)	Minimally nontraditional, n = 87 (20.3%)	Moderately nontraditional, n = 134 (31.2%)	Highly nontraditional, n = 58 (13.5%)	Total, N = 429
Nontraditional factor, n (%)
Age	0 (0.0)	16 (18.4)	81 (60.4)	56 (96.6)	153 (35.7)
High school graduation status	0 (0.0)	0 (0.0)	10 (7.5)	6 (10.3)	16 (3.7)
Delay in attendance	0 (0.0)	14 (16.1)	63 (47.0)	47 (81.0)	124 (28.9)
Has dependent	0 (0.0)	16 (18.4)	47 (35.1)	48 (82.8)	111 (25.9)
Single parent	0 (0.0)	0 (0.0)	13 (9.7)	28 (48.3)	41 (9.6)
Work 35+ hours	0 (0.0)	20 (23.0)	67 (50.0)	49 (84.5)	136 (31.7)
Enrollment status	0 (0.0)	21 (24.1)	53 (39.6)	35 (60.3)	109 (25.4)

Academic Entitlement Measures

Multiple scales of entitlement were used in the current study. Each scale is thought to tap into a different aspect of entitlement. The 15-item Academic Entitlement Scale (AES; Chowning & Campbell, 2009) contains two factors. The first factor is derived from 10 items that measure students’ academic externalized responsibility (AER) for their academic success (α = .835). The second factor consists of five items that measure students’ academic entitled expectations (AEE) concerning professors and course policies (α = .785). Participants rated each item on a 7-point scale from 1 (strongly disagree) to 7 (strongly agree). A sample AER item was “It is unnecessary for me to participate in class when the professor is paid for teaching, not for asking questions.” A sample AEE item is “My professors are obligated to help me prepare for exams.”

Greenberger et al.’s (2008) 15-item AES measures students’ sense of deserving more and being entitled to more than other students (α = .899). This scale captures a more general form of entitlement not captured by the Chowning and Campbell (2009) measure. Participants rated each of the items on a 7-point scale from 1 (strongly disagree) to 7 (strongly agree). A sample item is “If I have explained to my professor that I am trying hard, I think he/she should give me some consideration with respect to my course grade.”

Procedure

Students signed up for the survey using the Sona Systems online experiment management system. Participants were directed to a link to complete the survey using SurveyMonkey. This study was approved by the internal review board, participation was voluntary, and once students gave consent for the study they were compensated with either credit toward a research requirement or extra credit in their psychology course. After providing consent, participants were asked about their nontraditional factors. Next, they completed the Chowning and Campbell (2009) and Greenberger et al. (2008) AE scales. Participants then completed the remainder of the survey, which did not pertain to the current study. Participants were then debriefed and thanked for their time. The current study was part of a larger data collection project. The measures in the current study were the first encountered by the participants, thus concerns regarding response fatigue and selective attrition are less warranted.

Results

Impact of Nontraditional Factor

Examining whether the presence of any nontraditional factors impacted participants’ levels of AE, participants were separated into two groups. The first group consisted of participants that reported no nontraditional factors. The second group consisted of participants that reported at least one nontraditional factor. A one-way multivariate analysis of variance with nontraditional status as the factor was conducted on the AER factor, the AEE factor, and AES.

The analysis revealed effects for both the AEE factor and the AES. With regard to the AEE factor, participants with at least one nontraditional factor (M = 3.86) reported less entitlement expectation than participants with no nontraditional factors (M = 4.31), F(1, 380) = 11.00, p = .001, partial η² = .028. As seen in Table 2, the analysis of the AES revealed a similar pattern with participants reporting at least one nontraditional factor (M = 2.91) indicated having less AE than participants with no nontraditional factors (M = 3.23), F(1, 380) = 12.94, p < .001, partial η² = .033.

Table 2.

Levels of Academic Entitlement for Traditional and Nontraditional Students.

	AEE		AER		AES
Nontraditional status	M	SD	M	SD	M	SD
Traditional (n = 138)	4.31	1.28	1.96	0.74	3.29	0.97
Nontraditional (n = 244)	3.86	1.26	1.83	0.80	2.91	1.02

Note. AEE = academic entitled expectations; AER = academic externalized responsibility; AES = Academic Entitlement Scale. Each scale had a ranged of 1 (strongly disagree) to 7 (strongly agree). Only participants that completed the scale were included in the current analyses.

Nontraditional Factor Analyses

To test whether participants with different levels of nontraditional factors would report different levels of AE, participants were separated into four status groups as described in Horn (1996)—traditional (0 nontraditional characteristics), minimally nontraditional (1 characteristic), moderately nontraditional (2-3 characteristics), and highly nontraditional (4-7 characteristics).

A 4 × 3 × 2 multivariate analysis of variance with nontraditional status grouping, ethnicity (White, Black, and Latinx) and gender as the factors was conducted on the AER factor, the AEE factor, and the AES. Analysis revealed no main effects for ethnicity. Analysis revealed main effects on each of the entitlement measures for gender, ps < .05. In each instance, men reported significantly more entitlement than women, see Table 3.

Table 3.

Levels of Academic Entitlement by Gender and Ethnicity.

	AEE		AER		AES
Participant variable	M	SD	M	SD	M	SD
Gender
Female (239)	3.74_a	0.11	1.67_a	0.06	2.83_a	0.08
Male (79)	4.15_b	0.17	2.09_b	0.10	3.13_b	0.13
Ethnicity
Latinx (167)	3.91_a	0.15	2.02_a	0.09	3.10_a	0.12
Black (99)	4.00_a	0.17	1.80_a	0.10	2.96_a	0.13
White (52)	4.00_a	0.19	1.85_a	0.11	2.89_a	0.14

Note. AEE = academic entitled expectations; AER = academic externalized responsibility; AES = Academic Entitlement Scale. Each scale had a ranged of 1 (strongly disagree) to 7 (strongly agree). _a,bItems with different subscripts differ at p < .05.

Main effects were seen for nontraditional status on the AEE factor, F(3, 294) = 2.76, p = .042, partial η² = .027 and the AES, F(3, 294) = 3.87, p = .010, partial η² = .038, see Table 4. To explore these findings, planned pairwise comparisons were conducted between the different groups. A similar pattern of results was seen for both variables. In each instance, the highly nontraditional group reported less AE than both the traditional and minimally nontraditional groups (ps < .03), which did not differ from each other (ps > .10).

Table 4.

Levels of Academic Entitlement for Nontraditional Groupings.

	AEE		AER		AES
Nontraditional group	M	SD	M	SD	M	SD
Traditional (112)	4.23_a	1.27	1.88_a	0.66	3.23_a	0.92
Minimally nontraditional (61)	4.00_a	1.23	1.83_a	0.90	3.00_a	1.13
Moderately nontraditional (99)	3.80_ab	1.22	1.69_a	0.63	2.80_b	0.92
Highly nontraditional (46)	3.28_b	1.14	1.71_a	0.79	2.61_b	0.83

Note. AEE = academic entitled expectations; AER = academic externalized responsibility; AES = Academic Entitlement Scale. Each scale had a ranged of 1 (strongly disagree) to 7 (strongly agree). Only participants identifying as Latinx, Black, or White were included in the current analysis. _a,bItems with different subscripts differ at p < .05.

A single significant interaction was seen between nontraditional status grouping and gender on the AES, F(3, 294) = 3.45, p = .017, partial η² = .034. A marginally significant interaction effect was seen on the AER factor, F(3, 294) = 2.59, p = .053, partial η² = .026. Follow-up analysis revealed that the interaction was driven primarily by men in the minimally nontraditional group reporting the highest levels of entitlement and men in the highly nontraditional group reporting the lowest levels of entitlement overall. Interpretation of this interaction should be limited. As nontraditional status was a quasi-independent variable, the number of men and women in each cell was not controllable. The cells driving the effect seen here are much smaller than the other cells. The interaction should not be disregarded, but future research should endeavor to conduct an analysis with more balanced cells to replicate this finding.

Regression Analyses

To examine if the number of nontraditional factors participants reported predicted AE, separate linear regressions were used to test if the number of nontraditional factors students reported predicted scores on the AER factor, the AEE factor, and the AES. In each analysis only the number of nontraditional factors reported was entered into the model. The number of nontraditional factors reported by participants was a significant predictor for all three entitlement scales. Nontraditional factors showed a negative relationship with the AER factor, β = −.107, with a significant portion of the variance explained, R² =.011, F(1, 405) = 4.7, p = .031. For the AEE factor, nontraditional factors negatively predicted entitlement expectations, β = −.272, with a significant portion of the variance explained, R² = .074, F(1, 401) = 32.79, p < .001. Showing the same pattern of results, nontraditional factors displayed a negative relationship with AES, β = −.257, with a significant portion of the variance explained, R² = .066, F(1, 390) = 27.49, p < .001, see Table 5.

Table 5.

Number of Nontraditional Factors as a Predictor of Academic Entitlement.

Scale	Β	SE	β	R ²	p
Externalized responsibility (406)	−.051	0.024	−.107	.011	.031
Entitled expectations (412)	−.217	0.038	−.272	.074	.001
Academic Entitlement Scale (391)	−.164	0.031	−.257	.066	.001

Note. Only participants that completed the scale were included in the current analyses.

Regression With Individual Factors as Predictors

Finally, a series of linear regressions were conducted on the three AESs using the seven nontraditional factors as individual predictors. The seven factors were loaded into the model in a single step. For the AER factor, a significant portion of the variance was explained R² = .041, F(7, 399) = 2.46, p = .018. Age was the only individual factor that significantly predicted scores, β = −.255, p = .009. For the AEE factor, a significant portion of the variance was explained R² = .093, F(7, 405) = 5.96, p < .001. Hours worked was the only individual factor that significantly predicted scores, β = −.443, p = .003. For the AES, a significant portion of the variance was explained R² = .10, F(7, 384) = 6.07, p < .001. Both age, β = −.460, p < .001, and hours worked, β = −.331, p = .006, significantly predicted entitlement scores. See Table 6 for a full list of outcomes.

Table 6.

Regressions Analysis with Presence of Nontraditional Factors as Predictors.

Scale	Β	SE	β	t	p
AER (406)
Age	−.255	0.097	−.157	−2.62	.009
High school graduation status	−.385	0.210	−.093	−1.84	.067
Attendance delay	.042	0.096	.025	0.438	.662
Having dependents	−.040	0.100	−.023	−0.401	.688
Single parent	.095	0.149	.035	0.638	.524
Work 35+ hours	−.069	0.091	−.041	−0.754	.451
Enrollment status	.118	0.093	.066	1.27	.203
AEE (412)
Age	−.259	0.156	−.096	−1.66	.098
High school graduation status	−.402	0.338	−.058	−1.19	.234
Attendance delay	.163	0.155	.057	1.06	.292
Having dependents	−.303	0.161	−.103	−1.89	.060
Single parent	−.176	0.238	−.040	−0.739	.460
Work 35+ hours	−.443	0.147	−.159	−3.02	.003
Enrollment status	−.232	0.148	−.078	−1.57	.118
AES (391)
Age	−.460	0.127	−.214	−3.63	.001
High school graduation status	−.368	0.268	−.069	−1.37	.172
Attendance delay	.078	0.126	.034	0.619	.537
Having dependents	−.117	0.134	−.049	−0.873	.383
Single parent	−.095	0.199	−.027	−0.477	.634
Work 35+ hours	−.331	0.121	−.149	−2.75	.006
Enrollment Status	.150	0.126	.062	1.20	.233

Note. AER = academic externalized responsibility; AEE = academic entitled expectation; AES = Academic Entitlement Scale. Each model’s significance was <.05.

Discussion

The current study sought to bridge two trends thought to be increasing in higher education: the proportion of the student population that is nontraditional and the rising levels of AE. Faculty report positive experiences with nontraditional students, and it was hypothesized nontraditional students would report less AE than traditional students. It was also hypothesized the number of nontraditional factors would predict levels of AE. The current analysis revealed nontraditional students reported less AE than traditional students, having more nontraditional factors predicted lower AE, and some individual nontraditional factors were better predictors of AE.

Hypothesis 1 predicted that nontraditional students would report lower levels of AE than traditional students. Full support was found for Hypothesis 1. Analysis revealed participants with any nontraditional factors reported significantly less AE than their traditional counterparts. In the current study, 65% of participants reported at least one nontraditional factor. Importantly, no single factor accounted for most of these individuals being nontraditional. Age was the single most common nontraditional factor. Working more than 35 hours was the second most common factor. High school completion was the least common factor. Retention interventions and integration efforts will need to be varied to benefit this diverse group of students. The academic needs associated with having dependents or working full-time while going to school are likely different from the academic needs of those with a delayed college start or not graduating from high school. One group may need more attention in the college readiness area, while the other needs assistance in time management skills.

Hypothesis 2 predicted participants with the most nontraditional factors would report lower levels of AE than traditional students. Support for Hypothesis 2 was found in the current analysis. Participants in the highly nontraditional group reported significantly less AE than traditional students. Highlighting the potential error of lumping all nontraditional students together, the current study also found differences in AE among the nontraditional groups. The highly nontraditional group reported significantly lower levels of AE than the minimally nontraditional group. There was no difference in the AE levels of the minimally nontraditional and traditional students. For fear that a single nontraditional factor was at play in this group, a breakdown of the single nontraditional factor revealed a variety of factors as seen in Table 1. It seems that the reduction in AE is linked to having more nontraditional factors and not solely due to a single factor being overrepresented.

Hypothesis 3 stated that having more nontraditional factors would predict decreased AE. Hypothesis 3 was fully supported. Regression analyses of all three scales revealed that having more nontraditional factors predicted lower AE scores. To our knowledge, this is the first study to show the compounding effect of nontraditional factors in this manner. One theory of the cause of AE has been the increased reliance of customer relation models by university officials. Cain et al. (2012) propose that these types of models may cause students to think they have inappropriate power and authority in academic situations. Individuals with higher AE have been shown to have trouble differentiating between appropriate and inappropriate academic behaviors (Chowning & Campbell, 2009). It may be that nontraditional students have more experiences that properly prepare them for the accepted norms and expectations in academic situations. They may have a better grasp on appropriate behaviors in the classroom and how to interact with professors. Nontraditional factors such as working full-time, having dependents, and age may be life experiences that are excellent teachers in the ways of how to appropriately engage with university life and other hierarchical social structures. It could also be that nontraditional factors may be more aligned with themes associated with academic maturation. Echoing the ideas of LLL (Schuetze & Slowey, 2000) and self-directed learning (Knowles, 1975), Filipović and Jovanović (2016) highlight that academic maturity can help foster an academic environment that transcends the classroom by creating a network of reciprocal learning that can foster continued education through life. Conversely, it could be that nontraditional students are too overburdened and busy to have time to build up a sense of AE. Many may be trying to simply stay afloat. Nontraditional students may be showing academic apathy as opposed to academic maturity. The work by Brinthaupt and Eady (2014) goes against this idea, but future research should further seek to understand the possible relationship between nontraditional factors and academic maturity.

Hypothesis 4 stated the nontraditional factor models would predict AE attitudes. Support was found for Hypothesis 4. For each of the scales, the presence of the seven nontraditional factors in the current study significantly predicted AE scores. Once again, the presence of these factors negatively predicted AE scores. For AER, age was the only individual factor that predicted scores. For AEE, hours worked was the only individual factor that predicted scores. Showing convergence of the factors, the AES had both age and hours worked as significant individual predictors. The current study adds to the literature showing the multifaceted nature of AE. The study also contributes by showing the validity of both the generalized AES and the AER and AEE factors. The two predictors that emerged may be particularly important. Age and working full-time are both important ways that individuals learn acceptable thoughts and behaviors. In particular, having a full-time job can help individuals learn acceptable norms and behaviors in asymmetric power relationships. The professor–student relationship should not be adversarial in nature, but there is not equal power in certain aspects of the relationship. The current trend to add consumer model expectations attempts to level out this imbalance; however, the traditional power differential in the classroom may be for the student’s benefit. The student is not a subject matter expert yet. Lemke et al. (2017) theorize that AE may be more about recognizing a student’s “academic sweat” than entitlement. Students may be seeking ways to confirm they comprehend the material. Age and understanding proper norms in a hierarchical power structure may be good ways to learn how to assess understanding without increased entitled attitudes. Once again, the nontraditional factors of age and hours worked echo the axes of LLL (Schuetze, 2014; Schuetze & Slowey, 2000). Here, learning takes place throughout life and outside of the typical academic environment.

AE has been thought of as a coping mechanism against poor performance (Greenberger et al., 2008) and linked conceptually to having a more pronounced external locus of control (Chowning & Campbell, 2009). Morris et al. (2003) theorize that nontraditional and traditional students may use different coping methods. They found that nontraditional students used more active, target-appropriate strategies while traditional students used more passive and external strategies. Nontraditional students may be motivated by more intrinsic reasons (Taylor & House, 2010). The current study contributes by highlighting how students with more nontraditional factors seem to be taking more ownership of their behaviors and their effects. In particular, the nontraditional students do not seem to be pushing off their poor performance on professors. One limitation of the current study is that a measure of locus of control was not used. Future research should replicate these findings and ascertain if there if having more nontraditional factors is a reliable predictor of decreased external locus of control.

The current study is consistent with previous literature showing that men had higher levels of AE than women. This was the case for both factors and the generalized scale. The current study also adds to the literature that shows no meaningful effect of ethnicity on AE attitudes. This finding seems particularly significant in the current study as the sample was quite diverse and reflected the makeup of the university at large. Ethnicity effects that have been seen are often between Caucasian and Asian participants (Greenberger et al., 2008; Stiles et al., 2017). The number of participants identifying as Asian was not large enough to include in the full analysis. A larger sample is needed to test for these effects in the current study.

Limitations

While the current study adds to the literature understanding AE and nontraditional students, it is not without limitations. Full manipulation of the relevant variables is not possible. Because of this, causal relationships are not possible to identify in some situations. Even when grouping and comparisons can be made, the direction of the effect may not be clear. One of the largest limitations of the study is the lack of longitudinal data. Age is a major predictor of AE in the current study. The current study does not allow an examination of if AE actually decreases with age. It may be that the differences seen in the current study are more due to a cohort effect than a change over time in the individual. In recent years, the media is full of accounts of helicopter parenting that could affect the way a student sees their level of responsibility on a college campus. Additionally, a recent report out of the Pew Research Center highlighted that summer employment for teens is down since 2000 (Desilver, 2019). As discussed previously, less exposure to the workforce could inflate AE attitudes. Examining the breakdown of nontraditional factors in the current sample, we do not think this is simply a cohort effect as age was a factor present in all the nontraditional factor groupings. Future research should continue to measure AE over time to look for changes based on maturation or accrued life experience.

The diversity of the sample is a major strength of the current study. Some may consider this diversity a limitation though. Because a large portion of the existing literature is based on samples lacking the current level of diversity, making comparisons between studies might be more difficult. It is also important to note that the current sample is composed of 100% commuter students. It may be that the current findings are qualified by this fact. Being a commuter student may shift how one thinks about their investment of time and energy in higher education pursuits. As the current sample highlights, the residential college experience is not normative for a large segment of the collegiate population today. While research has largely been conducted on residential students, examining the experience of commuter students is an area that needs further expansion. Future research should directly assess and compare the AE attitudes of commuter and residential nontraditional students.

As mentioned previously, the makeup of the current sample did not allow for the full analysis of ethnicity effects. As well, the quasi-independent nature of gender did not allow for controlling cell sizes. The presence or absence of interaction effects should be treated with caution because of this. Future research should strive to have an even larger, more diverse sample so that there is sufficient power to detect findings and have more confidence in their meaningfulness.

Conclusion

The current study expands the understanding of AE in nontraditional students. Nontraditional students were found to have lower levels of AE than their traditional counterparts. Highly nontraditional students were found to have the lowest levels of AE and significantly less AE than traditional or minimally nontraditional students. There seems to be a compounding effect of nontraditional factors. Age and hours worked were found to be individual nontraditional factors that best predicted decreased AE. These factors seem to have a protective quality in the current study. Much has been written elsewhere about how and why the needs of nontraditional students matter. It is important moving forward to be mindful that being nontraditional is not by definition a negative quality. The most nontraditional may have the most to give. The diversity of life experience brought by nontraditional students could greatly enhance classroom experiences and give traditional students good models to use in future courses. Through modeling good behaviors that lack AE, nontraditional students may provide a solution to the growing problem of AE in the traditional college population.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Travis S. Crone

Author Biographies

Travis S. Crone is an associate professor at the University of Houston-Downtown. His areas of research include religious priming, nonconscious goals, and the effectiveness of pedagogical techniques.

Stephanie Babb earned her PhD in Psychology, Neuroscience and Behavior, from the University of Georgia in 2006. Her primary areas of study include nontraditional undergraduate students, gender and race bias, online learning and teaching, and episodic memory.

Francisca Torres is a graduate student at the University of Houston’s Special Populations program. Her current primary areas of study are in special education and behaviorism.

References

Barrett

Scott

(2014). Pedagogical and professional compromises by medical teachers in hospitals. The Clinical Teacher, 11(5), 340–344. https://doi.org/10.1111/tct.12190

Boswell

S. S.

(2012). “I deserve success”: Academic entitlement attitudes and their relationships with course self-efficacy, social networking, and demographic variables. Social Psychology of Education, 15(3), 353–365. https://doi.org/10.1007/s11218-012-9184-4

Brinthaupt

T. M.

Eady

(2014). Faculty member’s attitudes, perceptions, and behaviors toward their nontraditional students. Journal of Continuing Higher Education, 62(3), 131–140. https://doi.org/10.1080/07377363.2014.956027

Bye

Pushkar

Conway

(2007). Motivation, interest, and positive affect in traditional and nontraditional undergraduate students. Adult Education Quarterly, 57(2), 141–158. https://doi.org/10.1177/0741713606294235

Cain

Romanelli

Smith

K. M.

(2012). Academic entitlement in pharmacy education. American Journal of Pharmaceutical Education, 76(10), Article 189. https://doi.org/10.5688/ajpe7610189

Chowning

Campbell

N. J.

(2009). Development and validation of a measure of academic entitlement: Individual differences in students’ externalized responsibility and entitled expectations. Journal of Educational Psychology, 101(4), 982–997. https://doi.org/10.1037/a0016351

Ciani

K. D.

Summers

J. J.

Easter

M. A.

(2008). Gender differences in academic entitlement among college students. Journal of Genetic Psychology, 169(4), 332–334. https://doi.org/10.3200/GNTP.169.4.332-344

Desilver

(2019). In the U.S., teen summer jobs aren’t what they used to be. https://www.pewresearch.org/fact-tank/2019/06/27/teen-summer-jobs-in-us/

Elias

R. Z.

(2017). Academic entitlement and its relationship with perception of cheating ethics. Journal of Education for Business, 92(4), 194–199. https://doi.org/10.1080/08832323.2017.1328383

10.

Filipović

Jovanović

(2016). Academic maturation and metacognitive strategies in academic research and production. Universal Journal of Educational Research, 4(6), 1442–1451. https://doi.org/10.13189/ujer.2016.040623

11.

Forbus

Newbold

J. J.

Mehta

S. S.

(2011). A study of non-traditional and traditional students in terms of their time management behaviors, stress factors, and coping strategies. Proceedings of the Academy of Leadership, 15(2), 67–71.

12.

Goncalves

S. A.

Trunk

(2014). Obstacles to success for the nontraditional student in higher education. Psi Chi Journal of Psychological Research, 19(4), 164–172. https://doi.org/10.24839/2164-8204.jn19.4.164

13.

Greenberger

Lessard

Chen

Farruggia

S. P.

(2008). Self-entitled college students: Contributions of personality, parenting, and motivational factors. Journal of Youth and Adolescence, 37(10), 1193–1204. https://doi.org/10.1007/s10964-008-9284-9

14.

Hagedorn

L. S.

Maxwell

Hampton

(2001). Correlates of retention for African-American males in community colleges. Journal of College Student Retention: Research, Theory & Practice, 3(3), 243–263. https://doi.org/10.2190/mj6a-tfac-mrpg-xdkl

15.

Horn

(1996). Nontraditional undergraduates, trends in enrollment from 1986 to 1992 and persistence and attainment among 1989–90 beginning postsecondary students (NCES 97–578). U.S. Department of Education, National Center for Education Statistics.

16.

Jackson

D. L.

Singleton-Jackson

J. A.

Frey

M. P.

(2011). Report of a measure of academic entitlement. American International Journal of Contemporary Research, 1(3), 53–65.

17.

Jiang

Tripp

T. M.

Hong

P. Y.

(2017). College instruction is not so stress free after all: A qualitative and quantitative study of academic entitlement, uncivil behaviors, and instructor strain and burnout. Stress & Health, 33(5), 578–589. https://doi.org/10.1002/smi.2742

18.

Knowles

M. S.

(1975). Self-directed learning: A guide for learners and teachers (Vol. 2). Association Press.

19.

Kopp

J. P.

Zinn

T. E.

Finney

S. J.

Jurich

D. P.

(2011). The development and evaluation of the academic entitlement questionnaire. Measurement and Evaluation in Counseling and Development, 44(2), 105–129. https://doi.org/10.1177/0748175611400292

20.

Kuh

G. D.

(2003). What we’re learning about student engagement from NSSE: Benchmarks for effective educational practices. Change: The Magazine of Higher Learning, 35(2), 24–32. https://doi.org/10.1080/00091380309604090

21.

Lemke

Marx

Dundes

(2017). Challenging notions of academic entitlement and its rise among liberal arts college students. Behavioral Sciences, 7(4), Article 81. https://doi.org/10.3390/bs7040081

22.

Lippmann

Bulanda

R. E.

Wagenaar

T. C.

(2009). Student entitlement. College Teaching, 57(4), 197–204. https://doi.org/10.3200/ctch.57.4.197-204

23.

Lundberg

C. A.

(2003). The influence of time-limitations, faculty, and peer relationships on adult student learning: A causal model. Journal of Higher Education, 74(6), 665–688. https://doi.org/10.1353/jhe.2003.0045

24.

Meuleman

Garrett

Wrench

King

(2015). “Some people might say I’m thriving but . . .”: Non-traditional students’ experiences of university. International Journal of Inclusive Education, 19(5), 503–517. https://doi.org/10.1080/13603116.2014.945973

25.

Morris

E. A.

Brooks

P. R.

May

J. L.

(2003). The relationship between achievement goal orientation and coping style: Traditional vs. nontraditional college students. College Student Journal, 37(1), 3–8.

26.

Morrow

(1994). Entitlement and achievement in education. Studies in Philosophy and Education, 13(1), 33–47. https://doi.org/10.1007/BF01074084

27.

Schaefer

Barta

Whitley

Stogsdill

(2013). The “you owe me!” mentality: A student entitlement perception paradox. Journal of Learning in Higher Education, 9(1), 79–91.

28.

Schuetze

H. G.

(2014). From adults to non-traditional students to lifelong learners in higher education: Changing contexts and perspectives. Journal of Adult and Continuing Education, 20(2), 37–55. https://doi.org/10.7227/JACE.20.2.4

29.

Schuetze

H. G.

Slowey

(Eds.). (2000). Higher education and lifelong learners: International perspectives on change. Routledge/Falmer.

30.

Sessoms

Finney

S. J.

Kopp

J. P.

(2016). Does the measurement or magnitude of academic entitlement change over time? Measurement and Evaluation in Counseling and Development, 49(3), 243–257. https://doi.org/10.1177/0748175615625755

31.

Shapiro

P. D.

(2012). Entitled to cheat: An examination of incoming freshmen at a small regional university. Journal of Public and Professional Sociology, 4(1), 1–15.

32.

Singleton-Jackson

J. A.

Jackson

D. L.

Reinhardt

(2010). Students as consumers of knowledge: Are they buying what we’re selling? Innovative Higher Education, 35(5), 343–358. https://doi.org/10.1007/s10755-010-9151-y

33.

Slowey

Schuetze

H. G.

(Eds.). (2012). Global perspectives on higher education and lifelong learners. Routledge.

34.

Sohr-Preston

Boswell

S. S.

(2015). Predicting academic entitlement in undergraduates. International Journal of Teaching and Learning in Higher Education, 27(2), 183–193.

35.

Stiles

B. L

Pan

LaBeff

E. E.

Wong

(2017). The role of academic entitlement in college cheating: A comparison between China and the United States. Research in Higher Education Journal, 33, 1–15.

36.

Taniguchi

Kaufman

(2005). Degree completion among nontraditional college students. Social Science Quarterly, 86(4), 912–927. https://doi.org/10.1111/j.0038-4941.2005.00363.x

37.

Taylor

House

(2010). An exploration of identity, motivations, and concerns of nontraditional students at different stages of higher education. Psychology Teaching Review, 16(1), 46–57.

38.

U.S. Department of Education, National Center for Education Statistics. (2002a). The condition of education 2002 (NCES 2002–025). https://nces.ed.gov/pubs2002/2002025.pdf

39.

U.S. Department of Education, National Center for Education Statistics. (2002b). Nontraditional undergraduates (NCES 2002–012). https://nces.ed.gov/pubs2002/2002012.pdf

40.

U.S. Department of Education, National Center for Education Statistics. (2015). Demographic and enrollment characteristics of nontraditional undergraduates: 2011-12. https://nces.ed.gov/pubs2015/2015025.pdf