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Choosing between what you want now and what you want most: Self-control explains academic achievement beyond cognitive ability☆. Matthias Stadler a,⁎ ...

Personality and Individual Differences 94 (2016) 168–172

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Choosing between what you want now and what you want most: Self-control explains academic achievement beyond cognitive ability☆ Matthias Stadler a,⁎, Miriam Aust a, Nicolas Becker b, Christoph Niepel a, Samuel Greiff a a b

University of Luxembourg, Luxembourg Saarland University, Germany

a r t i c l e

i n f o

Article history: Received 6 October 2015 Received in revised form 14 January 2016 Accepted 18 January 2016 Available online xxxx Keywords: Self-control Academic achievement Cognitive ability University students Subjective success

a b s t r a c t Achieving a university degree is a demanding long-term goal, and students often show varying levels of academic achievement despite similar intellectual abilities. In order to help students, researchers thereby need to understand the origins of these individual differences. However, it remains unclear whether self-control is important for students' academic achievement beyond their general cognitive ability. To answer this question, N = 150 German university students completed a measure of general cognitive ability as well as a German translation of the Brief Self-Control Scale. Grade point average (GPA) served as an objective indicator of academic achievement, complemented by personal ratings as a measure of subjective academic achievement (SAA). Both cognitive ability and self-control explained substantial amounts of variance in GPA; however, only self-control accounted for variance in SAA. The study's key finding was that self-control indeed contributed to explaining GPA and SAA, even when cognitive ability was controlled for. On the basis of these results, we argue that self-control holds important explanatory value for both objective and subjective academic achievement, and we discuss the results' practical relevance with regard to student success at university. © 2016 Elsevier Ltd. All rights reserved.

1. Introduction Since the earliest attempts to measure cognitive ability (e.g., Binet and Simon (1916)), cognitive ability has usually been considered to be the primary factor for determining academic achievement. However, more recent research has suggested that cognitive ability does not appear to be enough when individuals strive for a degree in higher education (e.g., Busato et al. (2000) and Richardson et al. (2012)). Despite possessing adequate levels of cognitive ability, many university students struggle to persist in working toward their degree (Day, Mensink, & O'Sullivan, 2000). Next to being cognitively able to cope with lectures, university students also need to learn study habits for a new academic environment that requires substantially more self-control1 than high school (Parker, Summerfeldt, Hogan, & Majeski, 2004). They must learn to function as independent adults who will make the right choices rather than give in to leisure-time activities that are more appealing than studying ☆ This research was funded by grants from the Fonds National de la Recherche Luxembourg (ATTRACT “ASKI21”; AFR “CoPUS”). ⁎ Corresponding author at: ECCS, University of Luxembourg, Maison des Sciences Humaines, 11 Porte des Sciences à Esch-Belval, L-4366, Luxembourg, Luxembourg. E-mail address: [email protected] (M. Stadler). 1 In the present paper, we consistently use the term self-control. However, it should be noted that other researchers use other terms that are close in meaning to self-control such as impulse control, or willpower. Current conceptualizations of emotional intelligence (Goleman, 1996; Mayer et al., 2001) also include competencies that are close to selfcontrol. Thus, many findings described here may be applicable to these terms as well. 0191-8869/© 2016 Elsevier Ltd. All rights reserved.

at any given moment (Steel, 2007)—a widespread problem among students (Day et al., 2000). To date, however, only a relatively small number of studies have investigated the role of self-control in university success (De Ridder et al., 2012). Moreover, no published studies have investigated the extent to which self-control is related to academic achievement at the university level when individual differences in cognitive abilities are controlled for. This is the question that we addressed in this study. More specifically, we aimed to examine whether self-control could incrementally explain academic achievement above and beyond cognitive ability in a heterogeneous sample of German university students. 2. Academic achievement at university Grade point average (GPA) is the most commonly used indicator of academic achievement (Richardson et al., 2012) as it reflects a multitude of course assessments throughout a student's academic journey, represents an objective and reliable measure (Bacon & Bean, 2006), and is economical in terms of data collection. GPA has been shown to be important for students' later professional careers (Neisser et al., 1996) and later occupational status (Strenze, 2007). However, several researchers (e.g., Trost (1985)) have questioned the psychometric quality of GPA because it is strongly related to demographic variables such as socioeconomic status, the field of study, and the referential frame for grading. Moreover, grade inflation—very good grades becoming more and more common—has been observed

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in tertiary education. Johnson (2003), and Didier et al. (2006) showed that grading varies substantially across institutions. An alternative to relying solely on GPA as an indicator of students' academic achievement lies in students' subjective evaluations of their academic achievement. Subjective success is already a well-established criterion for career success (for an overview, see Ng et al. (2005)), and even though it has been neglected in that domain so far, it might serve a similar function in the assessment of academic achievement (Stadler et al., 2015). Subjective success refers to how individuals judge their own achievements in comparison with their personal goals or their colleagues' achievements (Ng et al., 2005); therefore, it is closely related to objective measures but also includes a personal evaluation. This approach is valuable in the academic context because a student's personal frame of reference will determine how that student perceives a particular grade (Komarraju & Nadler, 2013). Thus, the same objective GPA may be regarded very differently by different students and will hence result in different consequences. The fact that about two thirds of students drop out of universities for subjective reasons despite being objectively capable of succeeding (Ulriksen et al., 2010) demonstrates the importance of considering subjective success as an additional measure of academic achievement. Correlations between students' subjective estimates of their academic success and their objective grades have correspondingly been found to be strong but far from perfect (Kornilova et al., 2009). Regardless of the definition of academic achievement, however, the question of why some students are more successful at university than others remains. In the following section, we will outline how both cognitive ability and self-control contribute to university students' academic achievement. 3. Cognitive ability and academic achievement Cognitive ability is one of the most well-researched and established predictors of academic achievement today (Jensen, 1998). However, although cognitive ability certainly does influence the academic achievement of university students (Richardson et al., 2012), there is quite a bit of deviation in effect sizes (e.g., Formazin, Schroeder, Köller, Wilhelm, and Westmayer (2015)). Meta-analyses on the psychological correlates of university students' academic achievement have consistently shown small to medium-sized correlations between cognitive ability and academic achievement. Richardson et al. (2012) reported a corrected average correlation of ρ = .21 (80% CI [.08, .34]). Thus, cognitive ability accounts for only 4% to 5% of the variance in university students' academic achievement. This value most likely underestimates the true relation between students' cognitive abilities and academic achievement due to a restriction in the variance of university students' levels of cognitive ability (Formazin et al., 2015). Correspondingly, tests of cognitive ability that are specifically designed for the selection of university students in terms of content and difficulty have shown considerably higher correlations with academic achievement (Hell, Trapmann, & Schuler, 2008). Still, a large part of the variance in students' academic achievement cannot be accounted for by differences in cognitive ability and thus calls for research on the relations between academic achievement and noncognitive constructs such as self-control.


functioning of the self (e.g., Carver et al. (2009) and Hofmann et al. (2009)). As the definitions of self-control in research are heterogeneous, self-control has been operationalized with a great variety of different measures, such as questionnaires, executive function tasks, and delay of gratification tasks (Duckworth & Kern, 2011). Despite the heterogeneous definitions and ways of operationalizing self-control in research, self-control was found to play an important role in an impressive range of positive, socially desirable behaviors and educational outcomes (De Ridder et al., 2012). Students need to concentrate on their work despite the presence of promising short-term temptations in order to persist in working toward their long-term goal of an academic degree. Correspondingly, measures of self-control in highschool students explain variance in school absences, hours spent doing homework, hours spent watching TV, as well as the time of day a student starts homework (Duckworth & Seligman, 2005). In a longitudinal study of 140 eighth graders (Duckworth & Seligman, 2005), self-control was measured with self-report questionnaires, ratings from parents and teachers, and a behavioral assessment and then related to later highschool GPA and other measures of academic achievement. Self-control was found to explain 30.2% to 44.9% of the variance in high-school GPA, a finding that was supported by a replication of the study with 164 eighth graders (Duckworth & Seligman, 2005). However, some of the strongest effects of self-control were found in the domain of higher education (De Ridder et al., 2012). This is no surprise as university students are required to budget their own time to a substantially larger degree than is required of high-school students (e.g., Parker et al. (2004)). University students scoring high on selfcontrol measures procrastinate less (Steel, 2007) and get tasks done on time as they manage their study time well (Misra & McKean, 2000). They do not let free-time activities or emotional distractions keep them from doing their work (Tangney et al., 2004). Regarding university success, self-control accounted for 10.2% to 15.2% of the variance in GPA in a sample of 351 university students (Tangney et al., 2004). A second study by Tangney et al. (2004) of 255 university students yielded slightly smaller effects (r = .19 to .23, p b .01). Wolfe and Johnson (1995) found that self-control explained 9% (p b .01) of the variance in university GPA beyond high school GPA (R2 = 19%, p b .01) in a sample of 201 psychology students. A meta-analysis conducted by De Ridder et al. (2012) illustrated that self-control was moderately related to university and work performance, accounting for approximately 13% of the variance. Thus, it seems that self-control indeed holds explanatory value in academic achievement, but so far, it is unclear how this finding is validity related to other constructs. In summary, self-control plays an important role in a wide range of human behaviors, one of the most important being academic performance (De Ridder et al., 2012). Whereas several studies have found that university students' academic achievement and self-control are moderately correlated (for a summary see De Ridder et al. (2012)), none of them controlled for individual differences in cognitive abilities when computing this effect. Therefore, in the current study, we investigated whether self-control would offer incremental validity over and above cognitive ability in predicting university students' academic achievement. 5. Hypotheses

4. Self-control Baumeister et al. (2007) define self-control as the capacity to voluntarily control one's automatic responses to act in ways that foster the accomplishment of long-term goals with regard to one's values and standards. Self-control is sometimes also referred to as “self-regulation, self-discipline, willpower, effortful control, ego strength, and inhibitory control” (Duckworth & Kern, 2011, p. 2). Thus, self-control is considered a dual system with “quick, involuntary, and often consummatory impulses [opposing] the control of these impulses by deliberate, volitional processes” (Duckworth & Kern, 2011, p. 5) that is central to the

On the basis of the theoretical findings and considerations presented above, we deduced several hypotheses. As cognitive ability is so wellestablished as a predictor of academic achievement (e.g., Formazin et al. (2015)), we hypothesized that cognitive ability would explain variance in university students' objective and subjective academic achievement in the present study as well. However, in recent research, there has been a tendency to move beyond the study of cognitive abilities as predictors of academic achievement and to investigate noncognitive capacities instead (e.g., ChamorroPremuzic and Furnham (2008); Lounsbury et al. (2003); and Poropat


M. Stadler et al. / Personality and Individual Differences 94 (2016) 168–172

(2009)). On the basis of the findings presented above, we expected that self-control would also account for variance in objective and subjective academic achievement in the present study. Finally, Duckworth and Seligman (2005) were able to show that selfcontrol is still a predictor of high-school GPA even when other predictors are controlled for such as previous grades, achievement tests, and cognitive ability. Yet up to this point, no study has addressed the question of whether self-control can explain variance in academic achievement beyond cognitive ability in a sample of university students. In this paper, we thus aimed to take a first step toward filling this gap, and therefore, we hypothesized that self-control would significantly predict variance in objective and subjective achievement even when cognitive ability was controlled for. 6. Method 6.1. Participants One hundred fifty students enrolled in their fourth semester at a medium-sized German university participated in the study. All participants were students of biology (30.7%), sports science (25.1%), or psychology (44.2%); 62.2% were female, and the students' mean age was 22.53 years (SD = 3.83; Range = 17–43). Data collection took place during students' lectures using mobile devices brought into the classrooms and lasted for 1 h. Participation was voluntary, and students did not receive any compensation for their participation but could receive feedback on their results. Following the ethical guidelines provided by the APA (6th edition), the Ethics Board and the Data Protection Commissioner of the university granted permission for this study to be conducted. All data were anonymized using the students' ID code.

6.2.4. Subjective academic achievement (SAA) The scale for measuring SAA was taken from Stadler et al. (2015) and consisted of five statements such as “I am successful in my studies.” Participants responded on a Likert scale ranging from 1 to 5 with 1 indicating little and 5 indicating great satisfaction with one's own academic achievement. In the present study, the internal consistency was good (α = .82), thus matching the Cronbach's alpha value already reported by Stadler et al. (2015), who also provided extensive information about the scale's validity. 6.3. Statistical analyses Due to the nature of our research goal (i.e., to assess the value of selfcontrol in predicting academic achievement), we decided to employ manifest regression analyses rather than latent structural equation models. The regression analyses were computed with MPlus 7.3 (Muthén & Muthén, 2007). Both objective and subjective academic achievements were regressed on intelligence and self-control, first separately and then together. Missing values were handled with fullinformation maximum likelihood estimation (FIML). 7. Results 7.1. Descriptive statistics and measurement models Table 1 displays the descriptive statistics and intercorrelations for the four variables cognitive ability, self-control, GPA, and SAA. Apart from the nonsignificant correlation between cognitive ability and SAA, all were significant and in the expected direction. 7.2. Regression models

6.2. Measures 6.2.1. General cognitive ability To assess general cognitive ability, we used the computer-based version of the “Intelligenz-Struktur-Test Screening” (IST-Screening; Liepmann et al., 2012). The overall score is based on three dimensions (i.e., verbal, numeric, and figural reasoning) that are represented by three groups of tasks with 20 items each. As reasoning is a good indicator of general cognitive ability (Guttman & Levy, 1991), we used the two terms interchangeably in the present paper. The reliability of the three subscales was estimated as falling between α = .72 and α = .90 (Liepmann et al., 2012), which was confirmed for our sample. The convergent and discriminant validity of the IST-Screening have been studied extensively (Liepmann et al., 2012). 6.2.2. Self-control The adapted version of the short self-control scale (Tangney et al., 2004) was chosen as the measure of self-control because of its psychometric quality and its good fit with the study's concept of self-control in an academic context (for validation studies, see e.g., Duckworth and Seligman (2005) and Tangney et al. (2004)). The items are presented as statements such as “I refuse things that are bad for me, even if they are fun.” Participants answered on a Likert scale ranging from 1 to 5 with 1 indicating low and 5 indicating high agreement with the statements. For the purpose of this study, the scale was translated into German, and its validity was then tested in an independent pilot sample yielding a good internal consistency (α = .77). 6.2.3. Grade point average (GPA) Students' current grade point average (GPA) at university was obtained through the university's secretary as an indicator of objective academic achievement. The German grading system uses a scale that ranges from 1.0 to 5.0 with 1.0 being the best grade; a 4.0 is needed to pass. This scale was inverted so that higher values corresponded with better performance.

Cognitive ability significantly predicted GPA (β = .28, p = .002), explaining 7.9% of its variance (Model 1a), but general cognitive ability did not account for any variance in SAA (Model 2a: β = .10; p = .299; R2 = .01). Self-control explained 4.1% of the variance in GPA (Model 1b: β = .20; p = .014). Self-control was also a significant predictor of SAA (Model 2b: β = .33, p b .000; R2 = .11). Together, general cognitive ability and self-control explained 12.2% of the variance in GPA (Model 1c: R2 = .12; p b .01). Including selfcontrol in the model explained significantly more variance than general cognitive ability on its own (ΔR2 = .04; p b .05). Furthermore, selfcontrol explained variance beyond general cognitive ability in SAA (Model 2c: R2 = .11; p b .01; ΔR2 = .10). The results of all regression models are summarized in Table 2. 8. Discussion In this study, we aimed to investigate the influence of self-control on academic achievement. In this regard, a central question was whether self-control would show incremental validity beyond cognitive ability as an established predictor. The results of the regression analyses

Table 1 Descriptive statistics and correlations for all variables.

Cognitive ability Self-control GPA SAA



Possible range

Cognitive ability

47.26 3.16 2.29 3.34

5.92 0.60 0.61 0.83

0–60 1–5 1–4 1–5

(.80) .03 .28⁎⁎ .10




(.77) .20⁎ .33⁎⁎⁎

– .55⁎⁎⁎


Note. GPA = grade point average, SAA = subjective academic achievement. Internal consistencies (α) are given on the diagonal. ⁎ p b .05. ⁎⁎ p b .01. ⁎⁎⁎ p b .001.

M. Stadler et al. / Personality and Individual Differences 94 (2016) 168–172 Table 2 Regression results for GPA (Model 1) and SAA (Model 2). Model









−.28 −.20 −.29 −.21 .10 .33 .10 .32

3.18 2.50 3.31 2.41 1.04 4.24 1.21 3.72

b.01 b.05 b.05 b.05 ns b.001 ns b.001

R2 1a 1b 1c 2a 2b 2c

Cognitive ability Self-control Cognitive ability Self-control Cognitive ability Self-control Cognitive ability Self-control

−.28 −.20

.08 .04

.07 .04

.35 −.10 −.33

.12 .01 .11

.11 .00 .10






Note. GPA = grade point average; SAA = subjective academic achievement.

supported self-control as a predictor of academic achievement that provided incremental validity over and above cognitive ability. This was demonstrated for objective and subjective measures of academic achievement. In line with our hypotheses and previous research, both cognitive ability and self-control were significant predictors of university students' GPA. Cognitive ability explained more variance in GPA than self-control (8% as opposed to 4%). However, in contrast to our hypothesis, cognitive ability failed to explain variance in SAA. On the other hand, self-control was found to be a significant predictor of SAA. Taken together, cognitive ability and self-control explained 12% of the variance in GPA and accounted for 11% of the variance in SAA. In both cases, self-control showed substantial incremental validity over and above cognitive ability, thus confirming our hypotheses. However, in order to properly interpret the results of this study, several strengths and limitations need to be taken into account. A noteworthy strength of this is study lies in the recruited sample, which was more heterogeneous than most in this area of study as research in psychology often relies solely on psychology students as participants (Henrich, Heine, & Norenzayan, 2010). On the other hand, the cross-sectional approach used in the present study limits any causal interpretation of the results as well as their generalizability. However, the results replicated findings described in previous studies that applied longitudinal designs (e.g., Duckworth and Seligman (2005) and Furnham and Chamorro-Premuzic (2003)). Furthermore, there was considerable restriction in the range of cognitive ability as was to be expected in a sample of university students enrolled in selective programs. In our sample of university students, we observed that nearly all students scored in the upper half of the cognitive ability measure. However, as this is the case in most German universities, the sample reflects the reality of German universities in which students are selected on the basis of their previous academic achievement, which is strongly related to cognitive ability (Roth et al., 2015). Furthermore, as university students tend to range from intelligent to very intelligent, noncognitive abilities become even more prominent and interesting as they explain why students vary in their academic achievement despite having similar levels of cognitive ability. Research on the factors that predict academic achievement is important because it provides universities with selection criteria (Richardson et al., 2012) and helps to reduce drop-out rates (DeBerard et al., 2004). The results of this study confirm previous findings on the important role of self-control as a relevant addition to cognitive ability in the understanding of why students succeed at university (e.g., Tangney et al. (2004)). They may be applicable to related constructs such as emotional intelligence, which requires self-control as an important competency (e.g., Goleman (1996)) and has also been linked to academic achievement at university (e.g., Parker et al. (2004)). The important role of self-control is most likely explained by the students' studying behavior in that students with high self-control procrastinate less (Steel, 2007) and get tasks done on time as they manage their study time well (Misra & McKean, 2000). These behaviors may even potentially compensate for existing individual differences in cognitive ability. Following


this line of thought, Conard (2006) suggested that self-control be addressed in the frame of student development. She argued that low scores on self-control might serve to identify students who are likely to need interventions to succeed, whereas more self-control might assist students to access their potential and make the best use of it. The incremental validity of self-control over and above general cognitive ability found in our study further supports this argument. Students' self-control seems to provide an important additional starting point for successful student development. Moreover, self-control might help students to compensate for or even circumvent their natural limitations in cognitive ability as has already been discussed in cognitive ability compensation theory (e.g., Wood and Englert (2009)). According to this theory, relatively less intelligent individuals might compensate for their relative lack of intelligence by becoming more methodical, organized, thorough, and persistent (i.e., self-controlled). 9. Conclusion Research has shown that cognitive ability and self-control are both important factors for being a successful university student (Richardson et al., 2012). Yet, previous research had not addressed whether both factors have individual explanatory value in academic achievement and whether self-control has incremental validity beyond cognitive ability. The present study took a first step toward filling that gap. Self-control is important for academic achievement, and this importance goes beyond the explanatory value of cognitive ability. The effect is even stronger for subjective academic achievement than GPA. On the basis of these results, the paper discussed the importance of noncognitive factors that influence university students' academic achievement. These individual differences in self-control might shed light on the important question of why some university students perform poorly even though they are cognitively able to excel. References Bacon, D.R., & Bean, B. (2006). GPA in research studies: An invaluable but neglected opportunity. Journal of Marketing Education, 28, 35–42. 0273475305284638. Baumeister, R.F., Vohs, K.D., & Tice, D.M. (2007). The strength model of self-control. Current Directions in Psychological Science, 16, 351–355. 1467-8721.2007.00534.x. Binet, A., & Simon, T. (1916). The development of cognitive ability in children: The Binet–Simon Scale (No. 11). Williams & Wilkins Company.–000. Busato, V.V., Prins, F.J., Elshout, J.J., & Hamaker, C. (2000). Intellectual ability, learning style, personality, achievement motivation and academic achievement of psychology students in higher education. Personality and Individual Differences, 29, 1057–1068. Carver, C.S., Johnson, S.L., & Joormann, J. (2009). Two-mode models of self-regulation as a tool for conceptualizing effects of the serotonin system in normal behavior and diverse disorders. Current Directions in Psychological Science, 18, 195–199. http://dx. Chamorro-Premuzic, T., & Furnham, A. (2008). Personality, cognitive ability and approaches to learning as predictors of academic achievement. Personality and Individual Differences, 44, 1596–1603. Conard, M.A. (2006). Aptitude is not enough: How personality and behavior predict academic achievement. Journal of Research in Personality, 40, 339–346. 10.1016/j.jrp.2004.10.003. Day, V., Mensink, D., & O'Sullivan, M. (2000). Patterns of academic procrastination. Journal of College Reading and Learning, 30, 120–134. 2000.10850090. De Ridder, D.T., Lensvelt-Mulders, G., Finkenauer, C., Stok, F.M., & Baumeister, R.F. (2012). Taking stock of self-control: A meta-analysis of how trait self-control relates to a wide range of behaviors. Personality and Social Psychology Review, 16, 76–99. http://dx.doi. org/10.1177/1088868311418749. DeBerard, M.S., Spielmans, G., & Julka, D. (2004). Predictors of academic achievement and retention among college freshmen: A longitudinal study. College Student Journal, 38, 66–80 (Retrieved from: 04/PREDICTORS-OF-ACADEMIC-ACHIEVEMENT-AND-RETENTION-AMONGCOLLEGE-FRESHMEN.pdf). Didier, T., Kreiter, C., Buri, R., & Solow, C. (2006). Investigating the utility of a GPA institutional adjustment index. Advances in Health Sciences Education, 11, 145–153. http:// Duckworth, A.L., & Kern, M.L. (2011). A meta-analysis of the convergent validity of selfcontrol measures. Journal of Research in Personality, 45, 259–268. 10.1016/j.jrp.2011.02.004.


M. Stadler et al. / Personality and Individual Differences 94 (2016) 168–172

Duckworth, A.L., & Seligman, M.E. (2005). Self-discipline outdoes IQ in predicting academic achievement of adolescents. Psychological Science, 16, 939–944. http://dx.doi. org/10.1111/j.1467-9280.2005.01641.x. Formazin, M., Schroeders, U., Köller, O., Wilhelm, O., & Westmeyer, H. (2015). Studierendenauswahl im Fach Psychologie. Psychologische Rundschau. http://dx.doi. org/10.1026/0033-3042/a000093. Furnham, A., & Chamorro-Premuzic, T. (2003). Personality predicts academic achievement: Evidence from two longitudinal university samples. Journal of Research in Personality, 37, 319–338. Goleman, D. (1996). Emotional intelligence. Why it can matter more than IQ. Learning, 24, 49–50. Guttman, L., & Levy, S. (1991). Two structural laws for cognitive ability tests. Cognitive Ability, 15, 79–103. Henrich, J., Heine, S.J., & Norenzayan, A. (2010). The weirdest people in the world? Behavioral and Brain Sciences, 33, 61–83. Hell, B., Trapmann, S., & Schuler, H. (2008). Synopse der Hohenheimer Metaanalysen zur Prognostizierbarkeit des Studienerfolgs und Implikationen für die Auswahl-und Beratungspraxis. Bibliothek der Universität Konstanz. Hofmann, W., Friese, M., & Strack, F. (2009). Impulse and self-control from a dual-systems perspective. Perspectives on Psychological Science, 4, 162–176. 1111/j.1745-6924.2009.01116.x. Jensen, A.R. (1998). The g factor: The science of mental ability. Praeger Publishers. Johnson, V.E. (2003). Grade inflation: A crisis in college education. New York, NY: SpringerVerlag. Komarraju, M., & Nadler, D. (2013). Self-efficacy and academic achievement: Why do implicit beliefs, goals, and effort regulation matter? Learning and Individual Differences, 25, 67–72. Kornilova, T.V., Kornilov, S.A., & Chumakova, M.A. (2009). Subjective evaluations of intelligence and academic self-concept predict academic achievement: Evidence from a selective student population. Learning and Individual Differences, 19, 596–608. Liepmann, D., Beauducel, A., Brocke, B., & Nettelnstroth, W. (2012). Intelligenz-strukturtest – screening – (IST-screening). Manual. Göttingen: Hogrefe. Lounsbury, J.W., Sundstrom, E., Loveland, J.M., & Gibson, L.W. (2003). Cognitive ability, "big five" personality traits, and work drive as predictors of course grade. Personality and Individual Differences, 35, 1231–1239. S0191-8869(02)00330-6. Mayer, J.D., Salovey, P., Caruso, D.L., & Sitarenios, G. (2001). Emotional intelligence as a standard intelligence. Emotion, 1, 232–242. 3.232. Misra, R., & McKean, M. (2000). College students' academic stress and its relation to their anxiety, time management, and leisure satisfaction. American Journal of Health Studies, 16, 41–51 (Retrieved from Muthén, B.O., & Muthén, L.K. (2007). MPlus. Los Angeles, CA: Muthén & Muthén.

Neisser, U., Boodoo, G., Bouchard, T.J., Jr., Boykin, A.W., Brody, N., Ceci, S.J., ... Urbina, S. (1996). Cognitive ability: Knowns and unknowns. American Psychologist, 51, 77. Ng, T.W., Eby, L.T., Sorensen, K.L., & Feldman, D.C. (2005). Predictors of objective and subjective career success: A meta-analysis. Personnel Psychology, 58, 367–408. http://dx. Parker, J.D., Summerfeldt, L.J., Hogan, M.J., & Majeski, S.A. (2004). Emotional cognitive ability and academic achievement: Examining the transition from high school to university. Personality and Individual Differences, 36, 163–172. S0191-8869(03)00076-X. Poropat, A.E. (2009). A meta-analysis of the five-factor model of personality and academic achievement. Psychological Bulletin, 135, 322. Richardson, M., Abraham, C., & Bond, R. (2012). Psychological correlates of university students' academic achievement: A systematic review and meta-analysis. Psychological Bulletin, 138, 353. Roth, B., Becker, N., Romeyke, S., Schäfer, S., Domnick, F., & Spinath, F.M. (2015). Intelligence and school grades: A meta-analysis. Intelligence, 53, 118–137. Stadler, M.J., Becker, N., Greiff, S., & Spinath, F.M. (2015). The complex route to success: Complex problem solving skills in the prediction of academic achievement. Higher Education Research and Development, 1–15. 2015.1087387. Steel, P. (2007). The nature of procrastination. Psychological Bulletin, 133, 65–94. http://dx. Strenze, T. (2007). Cognitive ability and socioeconomic success: A meta-analytic review of longitudinal research. Cognitive Ability, 35, 401–426. intell.2006.09.004. Tangney, J.P., Baumeister, R.F., & Boone, A.L. (2004). High self-control predicts good adjustment, less pathology, better grades, and interpersonal success. Journal of Personality, 72, 271–324. Trost, G. (1985). Pädagogische diagnostik beim Hochschulzugang, dargestellt am Beispiel der Zulassung zu den medizinischen Studiengängen [educational assessment at university entrance illustrated by the example of admission to dental medicine programs]. Tests und Trends, 4, 41–81. Ulriksen, L., Madsen, L.M., & Holmegaard, H.T. (2010). What do we know about explanations for drop out/opt out among young people from STM higher education programmes? Studies in Science Education, 46, 209–244. 03057267.2010.504549. Wolfe, R.N., & Johnson, S.D. (1995). Personality as a predictor of college performance. Educational and Psychological Measurement, 55, 177–185. 0013164495055002002. Wood, P., & Englert, P. (2009). Cognitive ability compensation theory: A critical examination of the negative relationship between conscientiousness and fluid and crystallised cognitive ability. The Australian and New Zealand Journal of Organisational Psychology, 2, 19–29.