Intellectual ability, learning style, personality, achievement motivation and academic success of psychology students in higher education

Busato, Vittorio; Prins, Frans J.; Elshout, Jan J.; Hamaker, Christiaan

doi:10.1016/s0191-8869(99)00253-6

Cited by 559 publications

(384 citation statements)

References 44 publications

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“…O'Conner and Paunonen listed anxiety as a variable of interest and studies have shown it to correlate −0.29 with school grades (Hembree 1988), −0.28 with oral exams (Diaz et al 2001), and −0.29 with scholastic achievement (Chamorro-Premuzic and . As might be expected, anxiety is also correlated with other predictors of academic achievement such as intelligence, r0−0.33 (Ackerman and Heggestad 1997), and neuroticism, r00.53 (Busato et al 2000).…”

Section: Intelligence Student Intelligence Was Measured With the Shorsupporting

confidence: 70%

mentioning

confidence: 52%

“…This finding has been confirmed in two studies of higher education research in the Netherlands (Busato et al 2000;Resing and Drenth 2007). Resing and Drenth (2007) reported a modest relationship between academic achievement and intelligence in a general sample of university students, and Busato et al (2000) reported a minimal correlation of r00.13 in a sample of university psychology students. Based on studies performed in the USA and the UK, ChamorroPremuzic and noted that the correlation between intelligence scores and academic achievement decreased as students became older, declining from 0.60 to 0.50, to 0.40, and to 0.30, at the elementary, secondary, university undergraduate, and postgraduate levels, respectively.…”

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Predicting academic success in higher education: what’s more important than being smart?

2012

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This study investigated the combined predictive validity of intelligence and personality factors on multiple measures of academic achievement. Students in a college of higher education in the Netherlands (N0137) completed a survey that measured intelligence, the Big Five personality traits, motivation, and four specific personality traits. Student performance was measured with grade point average (GPA) and time to graduation, as well as with five specific performance measures: regular exams, skills training, team projects, internships, and a written thesis. Results show that 33% of the variance in GPA and 30% of the variance in time to graduation can be explained by combining intelligence, personality, and motivational predictors. Conscientiousness is the best predictor across a broad spectrum of academic achievement measures and explains five times as much variance in GPA as does intelligence. The practical implications are that institutes of higher education should collect personality data on students at the outset and then help students accordingly. Highly conscientious students who are organized and internally motivated might potentially be offered more challenging honours programs with corresponding special commendations on their diplomas, whereas students who score low on conscientious would receive more structure through student study groups, frequent deadlines, shorter assignments, group assignments, clearly defined learning goals, and less second chances for passing examinations.Keywords Academic success . Higher education . Intelligence . Motivation . Personality traits . Predictive validity Harris (1940) andCattell (1965) long ago noted the importance of personality factors for predicting academic achievement. Harris (1940) discussed the importance of persistence, in the guise of effort, and concluded that the essential factors for scholastic achievement were: Eur J Psychol Educ (2012) (a) ability, otherwise known as intelligence or scholastic aptitude, (b) effort, also known as drive or degree of motivation, and (c) personal, economic, social, and academic circumstances. Years later, Cattell (1965) suggested that, for university students who had already been selected on intelligence, personality and motivation would be just as important for predicting academic achievement. Recent research has shown that personality accounts for variance in academic achievement over and above intelligence (Bratko et al. 2006;Gilles and Bailleux 2001;Noftle and Robins 2007;Poropat 2009), and that personality may have even more predictive power than intelligence at the post-secondary levels of education (Conard 2006;Di Fabio and Busoni 2007;Furnham and Chamorro-Premuzic 2004;Furnham et al. 2003;Petrides et al. 2005).O 'Conner and Paunonen (2007) recently reviewed the studies concerning how well intelligence and personality factors predicted academic achievement at the post-secondary level and reiterated the earlier recommendations of Harris and Cattell. They offered a template for subsequent research and ca...

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Section: Intelligence Student Intelligence Was Measured With the Shorsupporting

confidence: 70%

mentioning

confidence: 52%

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confidence: 52%

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Predicting academic success in higher education: what’s more important than being smart?

2012

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“…They mostly confirm the general findings from the industrial-organizational literature, that conscientiousness is important (e.g., Busato, Prins, Elshout, & Hamaker, 2000;Hirschberg & Itkin, 1978;Van-Heyningen, 1997), and that the other personality variables can be important depending on the criterion (e.g., Chemers, Hu, & Garcia, 2001;Musgrave-Marquart, Bromley, & Dalley, 1997;Brown & Marshall, 2001). However, there have been no meta-analyses of this literature (and at this point there does not seem to be enough data on which to conduct a metaanalysis).…”

Section: Conscientiousnesssupporting

confidence: 82%

The Role of Noncognitive Constructs and Other Background Variables in Graduate Education

Kyllonen

Walters²,

Kaufman

2011

ETS Research Report Series

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This report reviews the literature on noncognitive and other background predictors (e.g., personality, attitudes, and interests) as it pertains to graduate education. The first section reviews measures typically used in studies of graduate school outcomes, such as attrition and time to degree. A review of qualities faculty members and administrators say they desire and cultivate in graduate programs is conducted. There appears to be a divergence between the qualities faculty members say are important and the measures researchers typically use in validity studies.The second section reviews three categories of noncognitive variables that might predict outcomes (general personality factors, quasi-cognitive factors, and attitudinal factors) and the definitions, measures, correlates, and the validity of those measures. The role of background factors, both environmental and group, is part of this review.Key words: noncognitive, personality, admissions, GRE ® , selection, assessment, new constructs ii Executive SummaryMany GRE ® studies conducted in the past several years have asked faculty members about the qualities that are important to success in graduate school. A consistent finding is that graduate faculty members believe that noncognitive factors, such as motivation, creativity, personality, interests, and attitude, ought to be considered in graduate admissions (e.g., Briel et al., 2000). Many faculty members believe that including such factors would increase both fairness and the validity of the current admissions process. At the same time there is a lack of knowledge about what the scientific literature says on what the noncognitive factors are, how important they are, how they could best be measured, and on whether it might be practical to use them in admissions decisions. The purpose of this review is to address these questions. This report reviews various noncognitive factors and definitions, measures, correlates, and the validity of those measures. Graduate School Outcomes and Their DeterminantsA notional path model illustrates the relationships between noncognitive predictor factors and graduate school outcome factors. Graduate school outcome factors are divided into traditional measures of convenience and performance factors. Traditional measures are attrition, time-to-degree, and grade point average. Performance factors are domain proficiency, general proficiency, communication, effort, discipline, teamwork, leadership, and management. The noncognitive predictor factors are divided into three main categories: personality (e.g., extroversion), quasi-cognitive (e.g., metacognition), and motivation factors (e.g., self-efficacy).In addition, there are two background categories assumed to affect the noncognitive factors:environmental (e.g., mentor support) and group factors (gender and ethnicity). The review is organized according to this model. Personality FactorsA consensus has emerged within the field that there are five major personality factors: extroversion, emotional stability, agreeableness, ...

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“…Yet whether or not learning style is a wholly integral part of personality theory remains unclear (Kirton, 1999, p. 120). Some studies concluded that learning style is a sub-set of personality based on consistent correlations between the two constructs (e.g., Furnham, 1992;Jackson & Lawty-Jones, 1996) whereas others have concluded learning style is distinctive and worthy of investigation separately from personality due to shared variance between the two constructs being low (e.g., Busato, Prins, Elshout & Hamaker, 2000;Chamorro-Premuzic, Furnham & Lewis, 2007;Riding & Wigley, 1997;von Wittich & Antonakis, 2011;Zhang, 2003Zhang, , 2006. Whilst sample, sample size, analytical methods adopted by different studies, and interpretations by researchers all contribute to different conclusions from previous studies, further investigations that can contribute to this scholarly debate is needed (ChamorroPremuzic & Furnham, 2009).…”

Section: Introductionmentioning

confidence: 99%

The relationship between Kolb's experiential learning styles and Big Five personality traits in international managers

Armstrong

2015

Personality and Individual Differences

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This study investigates the relationship between learning style and personality in international managers. Two-hundred-and-sixty-nine managers completed the NEO Five Factor Inventory (NEO-FFI) and Kolb's Learning Style Inventory (KLSI 3.1). Regression analyses revealed that extraverted managers: have a preference for grasping new experience by engaging in concrete experience rather than abstract conceptualization; prefer to transform experience via active experimentation rather than reflective observation; and tend to have an accommodative learning style. It was concluded that whilst Kolb's experiential learning style construct is associated with personality, it is also distinct from personality.

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Intellectual ability, learning style, personality, achievement motivation and academic success of psychology students in higher education

Cited by 559 publications

References 44 publications

Predicting academic success in higher education: what’s more important than being smart?

Predicting academic success in higher education: what’s more important than being smart?

The Role of Noncognitive Constructs and Other Background Variables in Graduate Education

The relationship between Kolb's experiential learning styles and Big Five personality traits in international managers

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