Senioritis is characterized by tendencies such as arriving late or skipping class, decreased motivation, or behaving irresponsibly by investing little effort in schoolwork. Research on senioritis primarily focuses on high school seniors, so the present study explored the phenomenon at the college level by investigating perceptions of senioritis in college students. Results indicated that students believe senioritis exists at the college level and that supportive relationships with faculty members and advisors play a significant role in how senioritis is perceived. This study confirms the relevance of studying college-level senioritis and suggests future research to define and further explore the phenomenon.

While the final year of college should be a time of reflection, transition, and excitement, many college seniors approaching graduation exhibit signs of laziness, disinterest, and amotivation (Legault et al., 2006). This behavior has often been called senioritis. As early as the 1950s, this term was applied to high school seniors. It was later described by Hayes (1981) as a developmental identity crisis expected between adolescence and adulthood, often characterized by “lack of enthusiasm, fits of irresponsibility, and a generally depressed affect punctuated by occasional outbursts of irritability” (p. 369). Senioritis is a common colloquial term, but empirical understanding at the collegiate level is limited.

Senioritis in High School

Research on senioritis primarily focuses on high school students who, as graduation approaches, may experience an expansive decline of motivation unrecognized by teachers or students until grades begin plummeting (Puente, 2012). Manifested in numerous ways, senioritis in secondary-level students includes arriving late to class, exhibiting irritability in the classroom, and investing little effort in both classwork and homework (Hayes, 1981; Legault et al., 2006). Other aspects of high school senioritis include lower academic motivation, increased procrastination, lack of self-discipline, and an increased social preoccupation (Pickhardt, 2013). Additionally, countless high school seniors struggle with anxiety about what the future entails (Ballmann & Mueller, 2006; Hayes, 1981), which holds some students back from investing time in scholastic pursuits, perhaps as a way to delay inevitable confrontation with the future. Extensive research suggests reforms to maintain relevance of the curriculum and avoid the slump in engagement causing the high school senior year to be likened by some to an educational wasteland (Conley, 2003; McCarthy & Kuh, 2006; National Association of Secondary School Principals [NASSP], 2004; Sizer, 2002). While beyond the scope of this study, reforms suggested in these high school studies may be relevant for postsecondary advisors, faculty members, and administrators to consider in relation to academic success in college seniors.

Senioritis in College

High school graduation was once a common U.S. portal for passage to adulthood (Beit-Hallahmi, 1977), but that has changed in the past 50 years. The number of students attending college in 2016 was just under 17 million—an increase of nearly 143% since 1970, when about seven million undergraduate students were enrolled across all types of colleges and universities (National Center for Education Statistics [NCES], 2016). Pursuing postsecondary education may delay the developmental transition from adolescence because attaining the autonomy, independence, and financial self-sufficiency of adulthood requires gainful employment that is now delayed for many students until graduation from college or even from graduate and professional programs. Indeed, while educators may wish all students who attend college to be intrinsically motivated by a love of learning, the reality of earning gaps between individuals with and without a college degree is the largest in history; thus, if college is a necessary step to get a better paying or more secure job, this could provide clues to understanding issues with senior students' lack of sustained engagement with academic coursework (Kerckhoff, 2002; Rugaber, 2017).

While senioritis is less commonly researched in college students, the behaviors, outcomes, and strategies to mitigate high school senioritis may be just as applicable in college seniors. For example, while students with higher self-efficacy are often more successful, both in and out of the classroom (Young-Jones et al., 2013), even the best and the brightest can succumb to aspects of academic burnout (e.g., emotional exhaustion, feelings of low personal accomplishment; Maslach & Jackson, 1981), which has the appearance of senioritis (Winship, 2011). Senioritis occurs at the threshold between adolescence and adulthood, so when additional years of formal education delay this developmental transition, the final year at any level of formal education becomes a critical period for understanding senioritis and its relationship to academic motivation, specifically in medical residencies (Cook, 2018).

Self-Determination Theory Applied to Academic Motivation

Self-Determination Theory (SDT) posits that motivation ranges from amotivation to extrinsic motivation to intrinsic motivation. Intrinsically motivated people act with self-determination and engage in behaviors that make them feel competent (Deci & Ryan, 1985; Ryan & Deci, 2000a, 2000b). In fact, greater levels of intrinsic motivation are associated with resilience, lower levels of exhaustion, and higher self-efficacy (Paul et al., 2014; Pisarik, 2009). SDT has been utilized to study academic motivation in college students and the related roles faculty members and advisors play (Burt et al., 2014, 2016). In studies applying SDT to academic motivation, subscales of the Academic Motivation Scale (Vallerand et al., 1992) may be combined to calculate the Self-Determination Index (SDI) as a measure of self-determined motivation in the academic environment (e.g., Standage et al., 2006).

A broad application of SDT to academia suggests that students will remain intrinsically motivated and will engage in adequately structured academic environments where they are challenged with high expectations, where their autonomy is supported with opportunities to align their behaviors with their values and interests, and where they experience meaningful relationships with instructors. Conversely, student engagement and motivation will lessen in environments where these characteristics are absent (Conner, 2007; Faye & Sharpe, 2008). While students are motivated by a combination of both intrinsic (e.g., interest in materials, enjoyment of learning) and extrinsic (e.g., grades, post-graduation employment, financial success) factors (Ballmann & Mueller, 2006; Legault et al., 2006; Van Etten et al., 2008; Winship, 2011), high intrinsic motivation has been shown to positively impact classroom performance (Fortier et al., 1995), especially in male students (Cortright et al., 2013). Applying the SDT framework permits exploration of senioritis through a lens of self-determined motivation, and a comprehensive measure of self-determined motivation (i.e., the SDI) is important, as, even for intrinsically-motivated students, extrinsic factors during this transitional time may increasingly influence goal-setting and decision-making for the future.

Learning Environments

Young adults are more intrinsically motivated in environments that support their autonomy and competence (Gagné & Deci, 2005; Pisarik, 2009) whether at home, school, or during extracurricular involvement (e.g., sports, Greek life, clubs). An optimal learning environment facilitates creativity, fosters inclusion, equips students with skills necessary to complete a task, and gives students a say in the decisions made—all of which allow students to feel they play an integral role in their own success (Faye & Sharpe, 2008; Gagné & Deci, 2005). The classroom environment is a critical place for students to re-engage with and foster connections to their schoolwork and academic success (Heller, 2001), and conditions that support students as individuals help them feel in control of their own achievement and more likely to achieve academic success (Yoshida et al., 2008). With the college senior year being such a transitional time for college students, supporting academic motivation of seniors within the learning environment is especially warranted.

Cerino (2014) proposed that college students should place a strong focus on identifying ways to motivate themselves internally, as opposed to seeking outside rewards or incentives. How can instructors and academic advisors foster optimal conditions for this to occur as the final transition from a college student to an independent professional looms large? When students are assigned tasks that do not particularly pique their interest, challenge them, or affect their overall course performance or grade, they may begin to exhibit signs of amotivation and academic disengagement (Ballmann & Mueller, 2008; Legault et al., 2006; Winship, 2011). In fact, Ballmann and Mueller (2008) asserted that seniors may simply be uninterested in studying, reading assignments, or completing homework because they may instead be focused on entering the workforce or beginning research of their own. While completing simple tasks improves the motivation of students with lower academic motivation, students with higher academic motivation benefit most from scholastic opportunities to push themselves (Kindermann, 1993; Yoshida et al., 2008). Nevitt Sanford's (1968) theory of challenge and support aligned with Van Etten et al. (2008), suggesting that tasks categorized as moderately difficult are the most engaging. Clearly, a learning environment's relevance to students' goals is linked to sustained engagement of students with that environment. As students' goal orientations change from schooling in adolescence to adult careers and vocations, educational professionals are challenged to ensure learning environments remain relevant.

Faculty members are particularly well-positioned to support the satisfaction of students' needs for competence as course-related learning takes place in and out of the classroom (Burt et al., 2014). For example, a supportive and influential instructor who shows interest in the success students can positively impact academic motivation (Jang et al., 2010). However, many faculty members can attest to having students with potential who either struggle to perform or who have given up on themselves (Faye and Sharpe, 2008). To support students' academic motivation, it is in the best interests of both students and faculty members to reach common ground (Legault et al., 2006). Unfortunately, common ground is often found in mutually lowered expectations. Winship (2011) described a common unspoken agreement between faculty members and students, dubbed the “low-low contract,” in which students have low expectations of their faculty members with respect to teaching and faculty members have low expectations of their students with regards to performance. This is especially troubling considering findings that expectations and motivation are among the strongest predictors of academic performance (Tavani & Losh, 2003). Thus, college students' learning environments need to be considered when exploring their perceptions of senioritis.

Stress in College Seniors

The senior year, characterized by impending transition, weighty choices, shifting expectations, excitement for the future, and anxiety about the unknown, holds a unique array of stressors for college students (Kirst & Venezia, 2001; Sizer, 2002). While some researchers explore senioritis from a behavioral perspective (e.g., skipping class, not completing assignments), Sizer (2002) discussed senioritis as “an emotional state: a complex combination of vulnerability, nostalgia, restlessness, weariness, disappointment – and laziness and entitlement” (p. 136). Students may vacillate between feeling happy about an upcoming graduation, sad about moving on from an environment they know how to navigate, and anxious about all the unknowns ahead. In addition to the emotional challenges, the senior year requires many students to split their focus between current academic demands and interviewing for jobs or wading through graduate program admissions requirements.

Students' goals, time allocations, and emotional experiences shift along with priorities, and the accompanying unsteadiness or uncertainty can be stressful. This stress may be further compounded by pressure to solidify career goals or by rejection following application and screening processes in an increasingly competitive job market (Farnsworth, 2012; Hu et al., 2017; Yazedjian et al., 2010). Balancing academic and future career priorities is challenging, and the accompanying stress could lead to senioritis as students prioritize job searching or graduate school applications over academic assignments, withdraw into periods of inactivity, or leave college altogether because they feel overwhelmed and want to avoid making difficult decisions (Overton-Healy, 2010). Consider also that 64% of college students take out loans to pay for college, 70% of students who take out loans report stress about personal finances, and looming loan repayment obligations after graduation may be especially stressful for students who have not lined up gainful employment (Guo et al., 2011; McDaniel et al., 2015; Walsemann et al., 2015). Added to the academic demands of a college senior's course load, stress, anxiety, burnout, and depression can all contribute to the behaviors noted in descriptions of senioritis (Hunt et al., 2012).

For some seniors, periods of anxiety and sadness are less transient, becoming clinical mental health diagnoses, while new stressors can exacerbate existing mental health conditions. As students with certain mental health diagnoses may already have difficulty completing courses or maintaining their grade point averages (Eisenberg et al., 2009), the emergence of senior year stressors may increase these difficulties. Most colleges and universities provide career counseling and mental health counseling, but some groups (e.g., first-generation college students) are less likely to access those services (Overton-Healy, 2010). Clearly, stress is a relevant variable to consider when exploring senioritis within college students.

Relationships and Social Support

Perceived social support (through relationships in and beyond the classroom) is an integral aspect of academic motivation in students (Deci & Ryan, 1985; Burt et al., 2014). Interactions with peers and significant others, faculty members, and academic advisors have varying impacts on students' intrinsic motivation in the learning environment. Curiosity, an important aspect of engaged learning (Engel, 2011), develops from social exchanges, so students' meaningful interactions across relationships are vital to cultivate their curiosity and motivation to learn (Burt et al., 2014; Legault et al., 2006).

Personal Support

Peers, family members, and significant others are influential people in young adults' lives who can provide support during senior year transitions (Pistilli et al., 2003; Yazedjian et al., 2010). Not surprisingly, a strong correlation exists between one's friends and classroom performance (Altermatt & Pomerantz, 2003; Berndt & Keefe, 1995; Gallardo & Barrasa, 2016; Kindermann, 1993; Legault et al., 2006) as students tend to affiliate with peers who share similar motivation when it comes to academics (Altermatt & Pomerantz, 2003; Kindermann, 1993). Peer academic performance has also been found to predict performance both for better and for worse, with negative friendships leading to more disruptive behavior in the classroom and less involvement in class (Altermatt & Pomerantz, 2003; Berndt & Keefe, 1995).

On the other hand, positive family relationships can help to lower anxiety, increase students' confidence and self-worth, and contribute to psychological health in some students (Kenny & Sirin, 2006; Lane, 2016). However, for other students, close family relationships can result in disruptively high family pressure, posing dilemmas about communicating demands of the college environment, graduate school applications, or a professional job search, if those are areas where family members or significant others have little personal experience (Constantine & Flores, 2006). The complex dynamics of social support from personal relationships are important to consider in an exploration of senioritis in college students.

Academic Advisor Support

Supportive relationships with academic advisors satisfy college students' basic needs for autonomy and relatedness that predict intrinsic academic motivation; additionally, perceived support from advisors predicts college students' higher overall perceptions of social support, of their study skills, and of their levels of personal responsibility and self-efficacy (Burt et al., 2014; Young-Jones et al., 2013). Across an undergraduate experience, most students will meet with an advisor for guidance several times. Interactions commonly focus on academic matters (e.g., selecting classes, monitoring grades, developing academic plans, engagement with cocurricular activities) and assistance with longer-term goal setting related to careers and transitions that will follow graduation (Burt et al., 2014; Hayes, 1981; Pisarik, 2009; Young-Jones et al., 2013).

Across students' academic careers, an academic advisor plays three primary roles: mentor, teacher/educator, and motivator (Ferris et al., 2012). In the mentor role, advisors support students with personal, educational, and professional pursuits and can share relevant advice, stories, and encouragement because they have knowledge of unique interests in each life area. Through the teacher/educator role, advisors promote critical thinking and development of skills and knowledge that will help students make wise decisions throughout their lives. And finally, in the motivator role, advisors positively encourage and energize students to believe in themselves, validating students' talents and contributions.

The advisor-student relationship is a crucial contributor to students' academic, professional, and leadership success in college (Ferris et al., 2012). Academic motivation may be difficult to sustain for college students, but it is linked to meaningful interactions with academic advisors and instructors; in fact, academic advisors are particularly well-suited to meeting relational needs that predict academic motivation and even decision-making in the face of adolescent developmental challenges related to alcohol use (Burt et al., 2014; Burt et al., 2016). Regular meetings with advisors predict students' increased self-efficacy, study skills, and positive perceptions of advisor support to navigate the college environment (Young-Jones et al., 2013). The advisor's interwoven roles help students determine their own paths and make independent decisions, all while helping students feel supported. As such, this relationship is vital to consider when exploring senioritis.

Purpose of Study

The present study explored perceptions of senioritis within college students. We investigated relationships between senioritis perceptions and self-determined motivation, stress, social support, academic advisor support, demographic characteristics like academic class (e.g., freshman or senior), and hours of sleep per day. Our hypothesis was that significant differences would exist between collegiate freshman and senior perceptions of senioritis. To test that hypothesis, we explored senior students' perceptions of course-related causes of senioritis, perceived results (e.g., negative outcomes) of senioritis, and perceived social support for students experiencing senioritis. Additionally, we hypothesized that levels of self-determined motivation, stress, social support, advisor support, and demographic characteristics (e.g., academic class, sleep per day) would predict differing senior students' perceptions about senioritis.

Method

Participants and Procedure

Participants were recruited from an Introduction to Psychology course and three senior-level Psychology courses. Upon consent, 489 students initiated participation in this study and received research credit. Institutional Review Board approval and informed consent was obtained prior to data collection. Once consent was procured, participants logged into an online experiment management system using an existing username and password to complete the online survey.

Among students who initiated participation, 71% were female, 58.8% were classified as seniors, and 88.3% self-identified as White. In addition, the mean age of participants was 26.70 years, with a standard deviation of 6.4 years (see full demographic data in Table 1). Despite the mean age, participants were traditional college age students. The demographic form obtained age information by birth year and subtracted from date of analysis. Data were collected over two years, and age calculation was completed at the point of analysis almost two years later.

Table 1.

Demographic frequencies and descriptive statistics prior to data screening

Demographic frequencies and descriptive statistics prior to data screening
Demographic frequencies and descriptive statistics prior to data screening

Of the 489 students, 82 failed to complete the study, so partial data from these individuals were excluded from analyses. An additional eight individuals' data were removed because more than 10% of their total data was missing. An additional 13 cases were removed as univariate or multivariate outliers (see data screening details under Results). This left 386 cases for data analysis. Final numbers for specific analyses (i.e., MANCOVA, n = 289; canonical correlation analysis, n = 320) varied based on case deletion due to missing data.

Materials

Six instruments and a demographic questionnaire were used to collect data for the current study. The selected instruments explored college students' perceptions about senioritis (e.g., course-related causes of senioritis, results of senioritis, and social support in relation to senioritis) as dependent variables. Instruments measured self-determined motivation, objective and subjective stress, social support, academic advisor support, and demographic characteristics as possible predictors of senioritis perceptions. When applicable, Cronbach's α is reported for listed instruments.

Perceptions of Senioritis Inventory

The 17-item Perceptions of Senioritis Inventory (PSI) was designed by the researchers for the present study to measure students' perceptions about course-related causes of senioritis, results of senioritis, and social support for students with senioritis. Responses were made on a Likert scale ranging from 1 (very true) to 6 (very false), and subscale scores were created by averaging the responses from the relevant questions. The inventory evaluated perceptions of senioritis on the following three subscales, listed with Cronbach's α for each: course-related causes of senioritis, .89; results of senioritis, .87; and social support, .69.

Prior to hypothesis testing, the PSI was analyzed using exploratory factor analysis and demonstrated acceptable values of sampling adequacy (e.g., Kaiser-Meyer-Olkin value of .82), as well as sufficient correlation (p < .001) between the variables, as measured by Bartlett's test of sphericity. An initial principle components analysis revealed that a total of six factors had eigenvalues greater than 1.00, accounting for 61.0% of the total variance. Based on the proposed design of the measure, as well as correlations between the initial six factors, an unweighted least squares (ULS) procedure with a Promax rotation was used to extract three proposed factors of this inventory. The three-factor ULS Promax rotated structure produced a factor structure identical to the proposed structure, resulting in subscales considered appropriate for further analyses.

Academic Motivation Scale

Whereas the PSI was used to measure students' perceptions of course-related causes of senioritis, the Academic Motivation Scale (AMS; Vallerand et al., 1992) explored student motivation. The AMS assesses both intrinsic motivation (i.e., to know, to accomplish things, and to experience stimulation) and extrinsic motivation (i.e., identified regulation, introjected regulation, and external regulation) and it includes a subscale measuring amotivation, with each subscale consisting of four items. Responses are given in a Likert format ranging from 1 (does not correspond at all) to 7 (corresponds exactly). In the present study, Cronbach's α for each subscale was: to know, .90; to accomplish things, .89; to experience stimulation, .88; identified regulation, .81; introjected regulation, .83; external regulation, .83; and amotivation, .91. Scores on each of these subscales were combined similarly to previous research (e.g., Standage et al., 2006) to form an overall Self-Determination Index (SDI) to measure students' self-determined motivation; the Cronbach's α for the SDI measure was .89.

College Undergraduate Stress Scale

Renner and Mackin's (1998) College Undergraduate Stress Scale (CUSS) was used as an objective evaluation of stress in this study. The CUSS is an updated version of Holmes and Rahe's (1967) Social Readjustment Rating Scale (SRRS). The CUSS generates a score representative of the participant's stress level and, compared to the SRRS, it includes additional and more relevant issues of traditional-age college students, including both major and minor stressors. Fifty-one items are ranked on a scale of 20-100, with very stressful events (e.g., being raped, finding out that you are HIV-positive) given a rating of 100, and less stressful events (e.g., attending an athletic event) given a ranking of 20. A respondent having experienced any of the items within the last year would add the corresponding stress rating score to their overall total.

Perceived Stress Scale

Though the CUSS generates a valuable score representative of participant stress, it was also important to understand how participants perceived their own stress. Therefore, perceptions of stress within the previous month were assessed as a subjective measure of stress using the Perceived Stress Scale (PSS), developed by Cohen, Kamarck, and Mermelstein (1983). The PSS is a 10-item scale with responses ranging from 0 (never) to 4 (very often), with a total score on this scale ranging from 0 to 40. Cronbach's α for this scale was .88.

Multidimensional Scale of Perceived Social Support

Perceptions of social support were assessed using the Multidimensional Scale of Perceived Social Support (MSPSS; Zimet et al., 1990). This measure evaluates perceptions of social support on the three subscales, each including four items answered using a Likert scale from 1 (very strongly disagree) to 7 (very strongly agree). The three subscales, with Cronbach's α listed for each, include: family members, .94; friends, .96; and significant others, .96.

Perceived Advisor Support Scale

To evaluate students' perceptions of advisor support, the 27-item Perceived Advisor Support Scale (PASS) was designed by the researchers for the present study. Responses were made on a Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). The three PASS subscales measure dimensions of advisor support as listed below with Cronbach's α provided for each: autonomy, .98; engagement, .96; and relatedness, .95.

Prior to hypothesis testing, the PASS was analyzed using exploratory factor analysis, demonstrating acceptable sampling adequacy (Kaiser-Meyer-Olkin value of .97) as well as sufficient correlation (p < .001) between the variables as measured by Bartlett's test of sphericity. A principle components analysis of the PASS demonstrated three factors with eigenvalues exceeding 1.00, which accounted for a total of 82.4% of the total variance. Considering the proposed three-factor structure of this measure and the moderate correlations demonstrated between the components, a ULS procedure with Promax rotation was used to extract the three proposed factors. The three-factor ULS Promax rotated structure of the PASS replicated the proposed structure, leading to the use of the three subscales for hypothesis testing.

Demographic Questionnaire

Lastly, a demographic questionnaire requested participants to indicate their biological sex, year of birth, academic class (e.g., freshman, senior), ethnicity, number of hours spent at work per week, and number of hours spent sleeping per day.

Results

Data Analysis

All data were analyzed using IBM's Statistical Package for the Social Sciences (SPSS) software version 25. The means, standard deviations (SDs), and ranges for all independent and dependent variables are presented in Table 2. Data screening, descriptive analyses, a one-way between-subjects multivariate analysis of covariance (MANCOVA), and a canonical correlational analysis (CCA) were applied as described below.

Table 2.

Means, standard deviations, minimums, and maximums for all variables

Means, standard deviations, minimums, and maximums for all variables
Means, standard deviations, minimums, and maximums for all variables

Data Screening and Descriptive Analyses

Of 489 participants who initiated participation, 82 failed to complete the study, so partial data from these individuals were excluded from analyses. An additional eight individuals' data were removed because more than 10% was missing from their total data. Missing values were analyzed using Little's (1988) missing completely at random (MCAR) test and were found to be nonsignificant (χ2 = 253.18, p = .397), resulting in the use of listwise case exclusion for all subsequent analyses. Assessment of univariate outliers was performed using a 1.5 interquartile range threshold, resulting in the removal of eight cases, whereas the assessment of multivariate outliers was determined by computing the Mahalanobis distance for each case on the 13 continuous (predictor and dependent) variables shown in Table 2. A total of five cases were identified as outliers via this method and were removed prior to any additional analyses. The resulting number of available cases for data analysis was 386, with frequencies and descriptive statistics for demographic characteristics of these remaining participants presented in Table 3.

Table 3.

Demographic frequencies and descriptive statistics of participants in CCA

Demographic frequencies and descriptive statistics of participants in CCA
Demographic frequencies and descriptive statistics of participants in CCA

Descriptive statistics analyses revealed that responses to all three perceived social support subscales (e.g., MSPSS scores for friends, family members, and significant others), as well as responses to the number of hours slept per day, displayed levels of skewness and kurtosis beyond ±1. These variables were transformed following Howell's (2007) recommendations. Subsequent descriptive statistics analyses showed acceptable levels of univariate normality, and these transformed values were used in all further analyses. Multivariate normality was assessed using Small's (1980) test, which revealed significant deviations from normality (χ2 = 407.23, p < .001). Nevertheless, in the present study the number of cases (386) per variable of interest (13) was well above the 10-20 range suggested as sufficient to achieve stable multivariate analyses (Salkind, 2010). Furthermore, as indicated previously, each of the scales in the present study exhibited sufficient Cronbach's α reliabilities to proceed with our analyses.

MANCOVA of Freshmen and Senior Perceptions of Senioritis

A one-way between-subjects multivariate analysis of covariance (MANCOVA) design with listwise deletion for missing cases was used to examine the differences in senioritis perceptions between freshmen (n = 85) and seniors (n = 204), controlling for levels of self-determined motivation. The only significant difference in demographic variables between these two groups was related to the number of hours worked, with freshmen working fewer hours than predicted and seniors working more hours than predicted, χ2(1) = 22.9, p < .001 (for full demographic variables on these two groups, see Table 4). Suitability analyses demonstrated that data conformed to both the assumption of linearity and homogeneity of regression and that the multivariate class x SDI interaction was not significant, Wilks' λ = .983, F(3,283) = 1.68, p > .150. Bartlett's test of sphericity was statistically significant (approximate χ2= 131.38, df = 5, p < .001), suggesting sufficient correlations between the adjusted dependent variables to proceed with the analysis. Box's test was also not statistically significant [Box's M = 11.51, F(6,168919) = 1.89, p = .078], suggesting homogenous adjusted matrices.

Table 4.

Demographic frequencies and descriptive statistics of freshmen and seniors

Demographic frequencies and descriptive statistics of freshmen and seniors
Demographic frequencies and descriptive statistics of freshmen and seniors

The multivariate effect of the covariate SDI, Wilks' λ = .959, F(3,284) = 4.04, p = .008, and the independent variable of class, Wilks' λ = .890, F(3,284) = 11.75, p < .001, were statistically significant. Levene's tests of homogeneity of variance were nonsignificant for perceptions of negative outcomes resulting from senioritis and for perceptions about available social support for students experiencing senioritis (p > .080 in both cases), but Levene's test was significant for perceptions of senioritis as having course-related causes (p = .005). Therefore, the univariate effects for results (i.e., negative outcomes) of senioritis and social support for students with senioritis were evaluated at a Bonferroni corrected alpha level of .025 (.05/2), whereas the univariate effect for senioritis due to course-related causes was evaluated at a stricter corrected alpha level of .0125.

The SDI covariate was also statistically significant for senioritis perceptions about available social support, F(1,286) = 8.32, p = .004, but nonsignificant for senioritis having course-related causes, F(1,286) = 1.00, p = .317, and for negative results or outcomes being caused by senioritis, F(1,286) = .88, p = .349. In contrast, the independent variable of academic class demonstrated significant univariate effects for both course-related causes of senioritis, F(1,286) = 11.55, p = .001, and results (i.e., negative outcomes) of senioritis, F(1,286) = 21.62, p < .001, but nonsignificant univariate effects were found for perceptions about social support for students with senioritis, F(1,286) = 4.647, p = .032 (see Figure 1). These results indicated that seniors reported greater levels of belief that senioritis was due to course-related causes like irrelevancy or boredom (adjusted M = 2.88, SE = .09, 95% CI = 2.70, 3.06) and greater levels of belief that senioritis resulted in negative outcomes like lower motivation or concentration (adjusted M = 2.64, SE = .10, 95% CI = 2.46, 2.83) than did freshmen (senioritis due to course-related causes: adjusted M = 3.45, SE = .14, 95% CI = 3.17, 3.72; senioritis causing negative outcomes: adjusted M = 3.46, SE = .15, 95% CI = 3.17, 3.74).

Figure 1.

Perceptions of senioritis – comparing freshmen to seniors

Note. Estimated marginal means of perceptions of senioritis for freshmen and seniors. Lower values represent greater beliefs. Error bars represent standard errors of the mean.

Figure 1.

Perceptions of senioritis – comparing freshmen to seniors

Note. Estimated marginal means of perceptions of senioritis for freshmen and seniors. Lower values represent greater beliefs. Error bars represent standard errors of the mean.

Canonical Correlation Analysis of Variables Predicting Senioritis Perceptions

A canonical correlation analysis (CCA) is in the same family as a MANCOVA or multiple regression model (i.e., it takes the form of a General Linear Model), allowing researchers to evaluate the relationship between independent and co-related dependent variables (Meyers et al., 2017). With several dependent and predictor variables, a CCA generates multiple orthogonal Functions (the upper limit of which is the smallest number of each type of variable; Meyers et al., 2016), and each set of Functions is assessed for statistical validity in a sequential factor (e.g., in a dimension reduction analysis). The amount of shared variance between the predictors and the outcome variable for each of the Functions is provided by the squared canonical correlation (Rc2). This value is obtained through the calculation of an eigenvalue for each Factor, and this procedure is roughly analogous to the use of a t or F test in univariate terms (Meyers et al., 2016). The covariates and independent variables entered into the analysis provide structure coefficients akin to those found in multiple regression, thus allowing the relative impact of each variable to be identified on the Function in question.

Therefore, a canonical correlation analysis (CCA) was performed to explore the relationship between students' perceptions of senioritis and variables that have been shown to affect students' motivation. The dependent variables were three subscale measures from the Perceptions of Senioritis Inventory (PSI) exploring perceptions about course-related causes of senioritis, results (e.g., negative outcomes) of senioritis, and social support related to senioritis. The independent (predictor) variables included measures of self-determined motivation (e.g., the Self-Determination Index, SDI); objective stress (e.g., CUSS score); subjective stress (e.g., PSS score); hours of sleep per day; social support (e.g., MSPSS subscale scores for friends, family, and a significant other); and perceptions of academic advisor support (e.g., PASS subscale scores on advisor support for autonomy, engagement, and relatedness).

Due to listwise deletion of cases with missing data, the CCA included 320 cases (see demographic information in Table 3). Analyses revealed the relationship between all entered variables was statistically significant, Wilks's λ = 0.82, Approximate F(30,822.53) = 1.96, p = .002. The analysis revealed three functions, with sequential squared canonical correlations (Rc2) of 0.11, 0.07, and 0.01. Based on the Wilks's λ, the full model accounted for approximately 18.3% of the variance shared between the variable sets. The dimension reduction analysis revealed that, although Functions 1 to 3 were statistically significant, Functions 2 to 3, as well as Function 3, in isolation were not (both p's > 0.200). Thus, only Function 1, which accounted for approximately 59.6% of the explained variance, was examined further.

The Function 1 structure coefficients (similar to beta coefficients in a multiple regression model) for both the dependent and predictor variables are presented in Table 5. The predictor variable set consists of lower levels of self-determined motivation, higher levels of support from a significant other, and lower levels of perceived advisor support for autonomy. In contrast, the dependent variable set involves higher reported beliefs about senioritis being due to course-related causes (e.g., irrelevancy, boredom) along with lower reported beliefs about social support being available for students experiencing senioritis. In summation, these results indicate that facing motivational challenges and having decreased levels of advisor support for autonomy while having high levels of support from a significant other predicts higher perceptions of course-related causes for senioritis and lowered perceptions of social support being available to students experiencing senioritis.

Table 5.

Structure coefficients for dependent and predictor variables for function 1

Structure coefficients for dependent and predictor variables for function 1
Structure coefficients for dependent and predictor variables for function 1

Discussion

Our study explored students' perceptions of senioritis and the relationships between those perceptions and other variables known to influence academic motivation. MANCOVA was the statistical analysis initially chosen to examine the relationship between our study's predictor variables (e.g., self-determined motivation, stress, sleep, social support, advisor support) on outcome variables (e.g., senioritis perceptions). However, our analyses indicate the three outcome variables (e.g., perceived course-related causes of senioritis, perceived negative results/outcomes of senioritis, perceived social support for students with senioritis) are substantially interrelated, so we instead ran the canonical correlation analysis (CCA) to further explore relationships between predictor (independent) and outcome (dependent) variables.

Based on MANCOVA analyses comparing freshmen and senior students, we found that seniors report greater levels of belief that senioritis is due to course-related causes than do freshmen. Based on responses to the Perceptions of Senioritis Inventory, senior students' issues with courses include perceptions that the material will not help them in the future, will not be relevant to their intended career, will not be interesting or intellectually challenging, and will fail to engage them in class. We believe the difference between senior and freshman perceptions is partially because freshmen are beginning the college experience and may be excited about their futures on campus, new opportunities for learning, making new connections, and exploring new social environments. In contrast, seniors are nearing the end of their college experience and are beginning the transition to a career or graduate program, both of which may be stressful, uncertain, and require redirected focus and allocation of time and effort.

In our next analysis, the CCA, we found that if students with lower self-determined motivation feel they have social support but lack autonomy support from their advisor, they are more likely to perceive that senioritis has course-related causes. Additionally, these students have lower beliefs that social support is readily available (e.g., from faculty members, peers, or family members) for students with senioritis. It appears these students are placing blame on external factors (e.g., how a course is designed, course material), which they may view as unchangeable and outside of their control. Because of this, students may disengage from courses because they believe there is nothing they can do to improve the situation. If this is the case, regardless of efforts by the instructor, department, or university to “improve” a course, some students still may not benefit.

Results also show students may be unable to see the impact of social support (i.e., support that is not aimed at meeting academic goals) on their perceptions of senioritis. Students who maintain strong emotional support from a significant other (i.e., a special person who is available during times of need, who cares, offers comfort, and with whom joys and sorrows can be shared) but who also have lower self-determined motivation and low autonomy support from their advisor appear to disregard the impact of social factors on what they believe is true about senioritis. Students may seek approval and validation as part of social support, and students' own levels of motivation do influence the motivation levels of others. As such, academic motivation could be negatively impacted by peers who believe that issues with courses are inescapable reasons for senioritis that students cannot control. In addition, social support from people who have not taken college courses may be well-intentioned but lack empathy or specific encouragement that could bolster student motivation. However, even if students believe courses need improvement and are not fully aware of how social support influences their views, academic advising support for autonomy plays a key role in students' perceptions.

Implications for Advisors, Educators, and Administrators

Senior perceptions of course-related causes for senioritis provide applicable insights for administrators, faculty members, and academic advisors. Results highlight the importance of course content being relevant, interesting, and challenging, so our findings suggest faculty members do play an integral role in students' mindsets about senioritis. Creating classroom environments where students are challenged but also feel competent is an ongoing process. To keep curricular review and enhancement feasible for faculty members, Winship (2011) asserted that postsecondary institutions could offer incentives that motivate faculty members to spend as much time on preparing their curriculum as on other responsibilities. Senior perceptions indicate that they want to find course content relevant to their careers or helpful to their futures in some way. This is wise to consider when reviewing and updating the content of individual courses seniors take. Assignments requiring students to reflect on the link between course subject matter and career issues may also be wise to consider.

Although seniors tend to perceive course-related issues as impacting senioritis, senior perceptions also provide insight for how academic advisors can influence students' views of coursework in relation to senioritis. Conversations about students' goals are privileges and responsibilities of advising that remain relevant across the collegiate career since a students' goals shift over time. Seniors need to view coursework as relevant to their career and future, and advisors can support students' consideration of these connections. Conversations about the relevance of coursework to their future can and likely should take place before students reach their senior years, as academic advising may occur less frequently as students approach degree plan completion and graduation. If students have difficulty articulating the association between their goals and coursework, advisors can at least explicitly highlight the link between successful completion of projects and classes to attaining future goals related to faculty members' letters of reference, internship placements, careers, or graduate study. Advisor collaboration with campus career services is also important so advisors can keep up-to-date knowledge of careers and can clearly communicate to students how a visit for career counseling or a workshop might benefit them. College seniors also perceive that boredom or struggles to remain engaged with course content can cause senioritis. Applying insights from goal-related conversations will allow advisors to guide students toward opportunities to engage in high impact practices (e.g., service learning, community-based learning, undergraduate research, internships) that contribute to engagement and academic success (Kuh, 2008).

In addition to the aforementioned conversations that support students' autonomy, advisors also need to continually support the autonomy of students—but what does that really mean? According to the Perceived Advisor Support Scale employed in this study, seniors consider the following as important elements of advisor support for autonomy: listening to students' preferences, showing understanding and acceptance, inviting openness, answering questions and sharing resources, helping students understand goals of a degree program and how to equip themselves to successfully meet them, and suggesting options, alternatives, and choices of activities for students to consider. Within an autonomy-supportive relationship, advisors can help students focus on the present as it relates to obtaining future goals. Advisors are often able to see the big picture of students' academic struggles or challenges and support their autonomy and success; advisors can also make suggestions that will better equip students to face those challenges. For example, advisors may be able to suggest resources for study techniques, dealing with failure, overcoming procrastination, overextending oneself, or anxiety about the future.

As a resource person and trusted supporter who is familiar with specific students' struggles and goals, an advisor is perfectly positioned to support student autonomy by helping connect students with existing campus services. An updated list of services (e.g., counseling, tutoring, learning disability support) and contact people on campus is helpful both for advisors to make referrals and for students to reference when they decide to act. Advisors may also want to partner with counseling services on campus to provide workshops or even a written resource for students, explaining how social support can influence academic motivation for better or worse and pointing out the value of meeting with an advisor for ongoing support across a student's college career.

Limitations and Future Research

Most research on senioritis has been conducted with high school students, so the present study evaluating college students' perceptions of senioritis demonstrates the topic's importance to explore further with college students. One limitation of this study is the relatively homogenous sample of students in terms of demographic characteristics, so generalizability will be greater in future research with more participant diversity. Lack of instrument validity measures is an additional limitation. Also, this study asked students to report their birth year rather than age at the time of data collection. Data were collected over two years, and age calculation was completed at the point of analysis (up to four years after data collection). As such, the mean age for our senior students appears high because some students (particularly freshmen), were likely 18 at the time of data collection but were coded in the data as age 22 at the point of data analysis. Even knowing the birth year, if we knew exactly when each participant's responses were collected, we still would not know the month/day relative to the date of our analyses, so exact ages were unknown. While this is a recognized limitation to the study, the findings do make a novel contribution to academic advising research and provide a foundation for additional studies on senioritis in college students.

Factors beyond those included in the Perceptions of Senioritis Inventory likely influence students' views on senioritis (e.g., burnout, reasons for attending college, first-generation college status, faculty member and students' expectations, major selection, class size, current or past involvement with high impact educational practices), and studies including these variables would expand understanding of senioritis in college students. As the transition from college is more imminent for seniors than for freshmen, future longitudinal studies could explore when shifts begin to occur in senioritis perceptions to help institutions understand when targeted interventions could be most impactful for supporting students' autonomy, stress management, and understanding of the relationship between social support and academic performance. Also, while the term ‘senioritis' is common, an empirically-supported definition appears elusive. Qualitative research and focus groups created to explore perceptions of students, advisors, and faculty members could identify additional variables needing exploration in relation to senioritis. Analyses based on such exploratory research will move researchers toward a clear definition of senioritis to guide identification of students struggling with it and institutional efforts to support them.

References

Altermatt,
E. R.,
&
Pomerantz,
E. M.
(2003)
.
The development of competence-related and motivational beliefs: An investigation of similarity and influence among friends
.
Journal of Educational Psychology
,
95
(1)
,
111
123
.
Ballmann,
J. M.,
&
Mueller,
J. J.
(2006)
.
Using self-determination theory to describe the academic motivation of allied health professional-level college students
.
Journal of Allied Health
,
37
(2)
,
90
96
.
Beit-Hallahmi,
B.
(1977)
.
Identity integration, self-image crisis, and “superego victory” in postadolescent university students
.
Adolescence
,
12
(45)
,
57
64
.
Berndt,
T. J.,
&
Keefe,
K.
(1995)
.
Friends' influence on adolescents' adjustment to school
.
Child Development
,
66
,
1312
1329
.
Burt,
T. D.,
Yadon,
C. A.,
Young-Jones,
A. D.,
Henson,
K.,
&
Carr,
M. T.
(2016)
.
Satisfaction does not equal success: College alcohol use and basic psychological needs
.
College Student Affairs Journal
,
34
(1)
,
3
16
.
2016.0007
Burt,
T. D.,
Young-Jones,
A. D.,
Yadon,
C. A.,
&
Carr,
M. T.
(2014). The advisor and instructor as a dynamic duo: Academic motivation and basic psychological needs
.
NACADA Journal
,
33
(2)
,
44
54
.
Cerino,
E. S.
(2014)
.
Relationships between academic motivation, self-efficacy, and academic procrastination
.
Psi Chi Journal of Psychological Research
,
19
(4)
,
156
163
.
Cohen,
S.,
Kamarck,
T.,
&
Mermelstein,
R.
(1983)
.
A global measure of perceived stress
.
Journal of Health and Social Behavior
,
24
(4)
,
385
396
.
Conley,
D.
(2003)
.
Connecting the dots: Linking high schools and post-secondary education to increase student success
.
Peer Review
,
5
(2)
,
9
12
.
Conner,
J. O.
(2007)
.
Student engagement during the senior year: Experiences with the International Baccalaureate Diploma Program's extended essay (Publication No. AAT 3267592) [Doctoral dissertation, Stanford University]
.
ProQuest Digital Dissertations database.
Constantine,
M. G.,
&
Flores,
L. Y.
(2006)
.
Psychological distress, perceived family conflict, and career development issues in college students of color
.
Journal of Career Assessment
,
14
(3)
,
354
369
.
Cook,
T.
(2018)
.
After the match: Beware of senioritis
.
Emergency Medicine News, 40(5), 21.
Cortright,
R. N.,
Lujan,
H. L.,
Blumberg,
A. J.,
Cox,
J. H.,
&
DiCarlo,
S. E.
(2013)
.
Higher levels of intrinsic motivation are related to higher levels of class performance for male but not female students
.
Advances in Physiology Education
,
37
,
227
232
.
Deci,
E. L.,
&
Ryan,
R. M.
(1985)
.
Intrinsic motivation and self-determination in human behavior
.
Plenum
.
Eisenberg,
D.,
Golberstein,
E.,
&
Hunt,
J. B.
(2009)
.
Mental health and academic success in college
.
The BE Journal of Economic Analysis & Policy, 9(1).
Engel,
S.
(2011)
.
Children's need to know: Curiosity in schools
.
Harvard Educational Review
,
81
(4)
,
625
645
.
Farnsworth,
M.
(2012
,
April
8)
.
College seniors, weeks from graduation, face uncertain future
.
The Hechinger Report.
Faye,
C.,
&
Sharpe,
D.
(2008)
.
Academic motivation in university: The role of basic psychological needs and identity formation
.
Canadian Journal of Behavioral Science
,
40
(4)
,
189
199
.
Ferris,
S.,
Johnson,
C.,
Lovitz,
A.,
Stroud,
S.,
&
Rudisille,
J.
(2012)
.
Assuming the role: The successful advisor-student relationship
.
Association of College Unions International
.
Fortier,
M.,
Vallerand,
R., J.
&
Guay,
F.
(1995)
.
Academic motivation and school performance: Toward a structural model
.
Contemporary Educational Psychology
,
20
(3)
,
257
274
.
Gagné,
M.,
&
Deci,
E. L.
(2005)
.
Self-determination theory and work motivation
.
Journal of Organizational Behavior
,
26
,
331
362
.
Gallardo,
L. O.,
&
Barrasa,
A.,
&
Guevara-Viejo,
F.
(2016)
.
Positive peer relationships and academic achievement across early and midadolescence
.
Social Behavior and Personality
,
44
(10)
,
1637
1648
.
Guo,
Y. J.,
Wang,
S. C.,
Johnson,
V.,
&
Diaz,
M.
(2011)
.
College students' stress under current economic downturn
.
College Student Journal
,
45
(3)
,
536
543
.
Hayes,
R. L.
(1981)
.
High school graduation: The case for identity loss
.
The Personal Guidance Journal
,
59
(6)
,
369
371
.
Heller,
S. B.
(2001)
.
Speaking my mind: Dealing with “senioritis”
.
The English Journal
,
90
(5)
,
17
18
.
Holmes,
T. H.,
&
Rahe,
R. H.
(1967)
.
The social readjustment rating scale
.
Journal of Psychosomatic Research, 11(2), 21–-218.
Howell,
D. C.
(2007)
.
Statistical methods for psychology (6th ed.)
.
Thomson Wadsworth.
Hu,
S.,
Creed,
P. A.,
&
Hood,
M.
(2017)
.
Career goal revision in response to negative feedback: Testing a longitudinal cross-lagged model
.
Journal of Counseling Psychology, 64(3), 335.
Hunt,
P. F.,
Boyd,
V. S.,
Gast,
L. K.,
Mitchell,
A.,
&
Wilson,
W.
(2012)
.
Why some students leave college during their senior year
.
Journal of College Student Development
,
53
(5)
,
737
742
.
Jang,
H.,
Reeve,
J.,
&
Deci,
E. L.
(2010)
.
Engaging students in learning activities: It is not autonomy support or structure but autonomy support and structure
.
Journal of Educational Psychology
,
102
(3)
,
588
600
.
Kenny,
M. E.,
&
Sirin,
S. R.
(2006)
.
Parental attachment, self-worth, and depressive symptoms among emerging adults
.
Journal of Counseling & Development
,
84
(1)
,
61
71
.
Kerckhoff,
A. C.
(2002)
.
The transition from school to work
.
In
Mortimer
J. T.
&
Larson
R. W.
(Eds.),
The changing adolescent experience: Societal trends and the transition to adulthood
(pp.
52
87
).
Cambridge University Press
.
Kindermann,
T. A.
(1993)
.
Natural peer groups as contexts for individual development: The case of children's motivation in school
.
Developmental Psychology
,
29
(6)
,
970
977
.
Kirst,
M.,
&
Venezia,
A.
(2001)
.
Bridging the great divide between secondary school and postsecondary education
.
Phi Delta Kappan
,
83
(1)
,
92
97
.
Kuh,
G. D.
(2008)
.
High-impact educational practices: What they are, who has access to them, and why they matter
.
Association of American Colleges & Universities
.
Lane,
J. A.
(2016)
.
Attachment, well-being, and college senior concerns about the transition out of college
.
Journal of College Counseling
,
19
(3)
,
231
245
.
Legault,
L.,
Green-Demers,
I.,
&
Pelletier,
L.
(2006)
.
Why do high school students lack motivation in the classroom? Toward an understanding of academic amotivation and the role of social support
.
Journal of Educational Psychology
,
98
(3)
,
567
582
.
Little,
R. J.
(1988)
.
A test of missing completely at random for multivariate data with missing values
.
Journal of the American Statistical Association
,
83
(404)
,
1198
1202
.
Maslach,
C.
&
Jackson,
S. E.
(1981)
.
The measurement of experienced burnout
.
Journal of Organizational Behavior
,
2
(2)
,
99
113
.
McCarthy,
M.,
&
Kuh,
G. D.
(2006)
.
Are students ready for college? What student engagement data say
.
Phi Delta Kappan, 87(9), 664.
McDaniel,
A.,
Montalto,
C. P.,
Ashton,
B.,
Duckett,
K.,
&
Croft,
A.
(2015)
.
National student financial wellness study: Key findings report
.
The Ohio State University
.
Meyers,
L. S.,
Gamst,
G.,
&
Guarino,
A. J.
(2017)
Applied multivariate research design and interpretation (3rd ed.)
.
Sage
.
National Association of Secondary School Principals.
(2004)
.
Breaking ranks II: Strategies for leading high school reform
.
The Education Alliance
.
National Center for Education Statistics.
(2016)
.
Fast facts: Enrollment
.
Overton-Healy,
J.
(2010)
.
First-generation college seniors: A phenomenological exploration of the transitional experience of the final college year (Publication No. 3403198) [Doctoral dissertation, Indiana University of Pennsylvania]
.
ProQuest Dissertations Publishing
.
Paul,
H.,
Sriram,
S.
Subalukshmi,
S.
&
Mala,
V.
(2014)
.
Resilience, academic motivation and social support among college students
.
Indian Journal of Positive Psychology
,
5
(4)
,
430
434
.
Pickhardt,
C. E.
(2013
,
January
14)
.
Finishing high school and “senioritis” (academic letdown)
.
Psychology Today.
Pisarik,
C. T.
(2009)
.
Motivational orientation and burnout among undergraduate college students
.
College Student Journal
,
43
(4)
,
1238
1252
.
Pistilli,
M.,
Taub,
D.,
&
Bennett,
D.
(2003)
.
Development of the senior concerns survey: An exploratory factor analysis
.
Journal of the First-Year Experience & Students in Transition
,
15
(1)
,
39
52
.
Puente,
K.
(2012)
.
Finding a cure for senioritis: States and districts are adopting policies to make the final year of high school more rigorous
.
District Administration
,
48
(6)
,
42
49
.
Renner,
M. J.,
&
Mackin,
R. S.
(1998)
.
A life stress instrument for classroom use
.
Teaching Psychology
,
25
(1)
,
46
48
.
Rugaber,
C. S.
(2017
,
January
12)
.
Pay gap between college grads and everyone else at a record
.
USA Today.
Ryan,
R. M.,
&
Deci,
E. L.
(2000a)
.
Intrinsic and extrinsic motivations: Classic definitions and new directions
.
Contemporary Educational Psychology
,
25
,
54
67
.
Ryan,
R. M.,
&
Deci,
E. L.
(2000b)
.
Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being
.
American Psychologist
,
55
(1)
,
68
78
.
Salkind,
N. J.
(2010)
.
Encyclopedia of research design
.
SAGE Publications
.
Sanford,
N.
(1968)
.
Where colleges fail: A study of student as person
.
Jossey-Bass
.
Sizer,
N. F.
(2002)
.
Crossing the stage: Redesigning senior year
.
Heinemann
.
Small,
N. H. J.
(1980)
.
Marginal skewness and kurtosis in testing multivariate normality
.
Applied Statistics
,
29
,
85
87
.
Standage,
M.,
Duda,
J. L.,
&
Ntoumanis,
N.
(2006)
.
Students' motivational processes and their relationship to teacher ratings in school physical education: A self-determination theory approach
.
Research Quarterly for Exercise and Sport
,
77
(1)
,
100
110
.
Tavani,
C. M.,
&
Losh,
S. C.
(2003)
.
Motivation, self-confidence, and expectations as predictors of the academic performances among our high school students
.
Child Study Journal
,
33
(3)
,
141
151
.
Vallerand,
R. J.,
Pelletier,
L. G.,
Blais,
M. R.,
Briere,
N. M.,
Senecal,
C.,
&
Vallieres,
E. F.
(1992)
.
The academic motivation scale: A measure of intrinsic, extrinsic, and amotivation in academics
.
Educational and Psychological Measurement
,
52
(4)
,
1003
1017
.
Van Etten,
S.,
Pressley,
M.,
McInerney,
D. M.,
&
Liem,
A. D.
(2008)
.
College seniors' theory of their academic motivation
.
Journal of Educational Psychology
,
100
(4)
,
812
828
.
Walsemann,
K. M.,
Gee,
G. C.,
&
Gentile,
D.
(2015)
.
Sick of our loans: Student borrowing and the mental health of young adults in the United States
.
Social Science & Medicine
,
124
,
85
93
.
Winship,
C.
(2011)
.
The faculty-student low-low contract
.
Sociology
,
48
,
232
235
.
Yazedjian,
A.,
Kielaszek,
B.,
&
Toews,
M.
(2010)
.
Students' perceptions regarding their impending transition out of college
.
Journal of the First-Year Experience & Students in Transition
,
22
(2)
,
33
48
.
Yoshida,
M.,
Tanaka,
M.,
Mizuno,
K.,
Ishii,
A.,
Nozaki,
K.,
Cho,
K.,
&
Watanabe,
Y.
(2008)
.
Factors influencing the academic motivation of individual college students
.
International Journal of Neuroscience
,
118
,
1400
1411
.
Young-Jones,
A. D.,
Burt,
T. D.,
Dixon,
S.,
&
Hawthorne,
M. J.
(2013)
.
Academic advising: Does it really impact student success?
Quality Assurance in Education
,
21
(1)
,
7
19
.
Zimet,
G. D.,
Powell,
S. S.,
Farley,
G. K.,
Werkman,
S.,
&
Berkoff,
K. A.
(1990)
.
Psychometric characteristics of the multidimensional scale of perceived social support
.
Journal of Personality and Assessment
,
55
(3-4)
,
610
617
.

Author notes

Adena Young-Jones, PhD (Educational Psychology), is an associate professor of Psychology at Missouri State University.

Jason McCain, PhD (Educational Psychology), is an assistant professor of Psychology at Northwest Missouri State University.

Tracie Burt, EdD (Educational Leadership), is the director of TRiO ETS-Southwest for the University of Texas at San Antonio.

Megan Drew, BS, is a PhD candidate (Counseling Psychology) at the University of North Texas.

D. J. Heim, BS, is a Master's candidate (Experimental Psychology) at Missouri State University.