Factors affecting college grades: a review of the literature, 1930-1937.

Harris, D. E.

doi:10.1037/h0055365

Cited by 129 publications

(71 citation statements)

References 150 publications

(123 reference statements)

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“…The findings in this study support the writings of Harris (1940), Cattell (1965), and O'Conner and Paunonen (2007 that personality is an important predictor of academic achievement in post-secondary education. Intelligence, when entered as the first variable in the regression equation, accounts for only 5% of the variance in GPA in the current study, which coincides with the 4% reported by Farsides and Woodfield (2003) and 3% reported by Furnham and Chamorro-Premuzic (2004).…”

Section: Discussionsupporting

confidence: 78%

“…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.…”

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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: Discussionsupporting

confidence: 78%

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confidence: 99%

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

2012

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“…Intelligence tests (e.g., Harris, 1940; Neisser et al, 1996) reflect cognitive capacities, including the ability to represent and manipulate abstract relations (Carpenter, Just & Shell, 1990). Such measures assess what an individual can do.…”

Section: Psychological Correlates Of Gpa: a Brief Overviewmentioning

confidence: 99%

Psychological correlates of university students' academic performance: A systematic review and meta-analysis.

Richardson

Abraham

Bond

2012

Psychological Bulletin

2,630

204

2,167

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A review of 13 years of research into antecedents of university students' grade point average scores (GPA) generated: (i) a comprehensive, conceptual map of known correlates of tertiary GPA, (ii) assessment of the magnitude of average, weighted correlations with GPA and (iii) tests of multivariate models of GPA correlates within and across research domains. A systematic search of psycINFO and web of knowledge databases between 1997 and 2010 identified 7167 English language articles yielding 242 datasets reporting 50 conceptuallydistinct correlates of GPA including 3 demographic factors and 5 traditional measures of cognitive capacity or prior academic performance. In addition, 42 non-intellective constructs were identified from 5 conceptually-overlapping but distinct research domains: (1) personality traits, (2) motivational factors, (3) self-regulatory learning strategies, (4) students' approaches to learning, and (5) psychosocial contextual influences. 1105 independent correlations were retrieved and data were analyzed using hypothesis-driven, random effects meta analyses. Significant average, weighted correlations were found for 41 of 50 measures.Univariate analyses revealed that demographic, and psychosocial contextual factors generated, at best, small correlations with GPA. Medium-sized correlations were observed for high school GPA, SAT, ACT, and 'A' level scores. Four non-intellective constructs also showed medium-sized correlations with GPA, namely, need for cognition, academic selfefficacy, grade goal, and effort regulation. A large correlation was observed for performance self-efficacy which was the strongest correlate (of 50 measures) followed by high school GPA, ACT, and grade goal. Implications for future research, student assessment and intervention design are discussed.Key terms: student, grade point average, self-efficacy, goal, meta analysis. NON INTELLECTIVE CORRELATES OF ACADEMIC PERFORMANCE 2The psychology of individual differences originated in attempts to predict scholastic performance. Binet and Simon's (1916) work showed that children's individual cognitive capacities explained variability in educational performance and, in doing so, laid the foundations for extensive research into intelligence and intelligence testing (Neisser et al., 1996). Theoretical debate focused on the psychological nature of intelligence and applied research explored how differences in intelligence(s) can be most usefully assessed (e.g., Capenter, Just & Shell, 1990; Gardner, 1983;Spearman, 1927). Subsequent research has identified a variety of individual differences that predict scholastic performance and prompted construction of a wide range of assessment instruments. This diverse literature has not clarified how, and to what extent, separate measures of academic potential are related.Greater conceptual and methodological integration would help focus future research questions and facilitate optimal assessment of students' academic potential. In order to achieve this we reviewed 13 years of research...

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“…This concept of ''student centred learning'' is characterised by active rather than passive learning, deep learning and understanding (rather than surface learning) and an increased responsibility by the student (Biggs and Tang 2007;Lea, Stephenson, and Troy 2003). The process of learning is complex and influenced by students' attributes and experiences as well as by conditions of learning presented by the course (Busato 2000;Harris 1940). There are two factors, however, that are widely seen as hugely important to learning: student engagement and good quality feedback (Gibbs 2010;Trowler and Trowler 2010).…”

Section: Introductionmentioning

confidence: 99%

Combining the formative with the summative: the development of a twostage online test to encourage engagement and provide personal feedback in large classes

Voelkel

2013

Research in Learning Technology

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The aim of this action research project was to improve student learning by encouraging more ''time on task'' and to improve self-assessment and feedback through the introduction of weekly online tests in a Year 2 lecture module in biological sciences. Initially voluntary online tests were offered to students and those who participated achieved higher exam marks than those who did not, but completion rate was low. Making the tests compulsory led to high completion rates, but class performance decreased, indicating that using the same assessment for formative and for summative purposes is not always beneficial for learning. Finally, these problems were resolved by introducing a two-stage approach: the first stage of each test was formative and provided prompt feedback. However, students had to achieve 80% to progress to the second summative stage of the test. The two-stage online tests led to significantly improved class performance. This novel test design ensures that students go through at least two attempts and therefore fully benefit from the learning opportunities presented by the formative stage. Two-stage online tests present the opportunity to provide regular feedback in large classes and to improve performance not only of good but also of ''weak'' students.

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Factors affecting college grades: a review of the literature, 1930-1937.

Cited by 129 publications

References 150 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?

Psychological correlates of university students' academic performance: A systematic review and meta-analysis.

Combining the formative with the summative: the development of a twostage online test to encourage engagement and provide personal feedback in large classes

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