The Big Five personality traits, learning styles, and academic achievement

Komarraju, Meera; Karau, Steven J.; Schmeck, Ronald R.; Avdic, Alen

doi:10.1016/j.paid.2011.04.019

Cited by 533 publications

(419 citation statements)

References 25 publications

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“…This study examines whether students' absenteeism rate influences their academic performance. This approach is in line with the suggestion by Komarraju et al (2011) regarding future research on the predictors of academic achievement. In this study, the absenteeism rate will be computed as a percentage over the semester.…”

Section: Attendance and Academic Performancesupporting

confidence: 84%

“…Flemming (1932) showed that personality and emotions were correlated with academic performance. Subsequently, some of the determinants of academic performance studied by other researchers are Intelligence (Laidra, Pullman, & Allik, 2007;Chamorro-Premuzic & Furnham, 2008); Personality (Komarraju, Karau, Schmeck, & Avdic, 2011;Rosander, Backstrom, & Stenberg, 2011); Personality traits, self-esteem, and self-efficacy beliefs (Di Giunta, Alessandri, Gerbino, Luengo, Zuffiano, & Caprara, 2013); Educational persistence, motivational, and study skills indicators (Moreira, Dias, Vaz, & Vaz, 2013); Extracurricular activities (Ackerman, Chamorro-Premuzic, & Furnham, 2011); Gender (Furnham, Monsen, & Ahmetoglu, 2009); Self-efficacy beliefs in self-regulated learning (Zuffianò, Alessandri, Gerbino, Luengo, Di Giunta, Milioni, & Cappara, 2013); Learning styles (Entwistle, 2001;Cassidy, 2004;Vermunt & Vermetten, 2004;Ng, Pinto, & Williams, 2011); Socioeconomic status (SES) (Hauser, 1994;Sirin, 2005;Zuffianò et al, 2013); Gender differences (Carvalho, 2016); and Negative justice contact and school expulsion (Robison et al, 2017). In the current study, the dependant variable will be academic performance.…”

Section: Academic Performancementioning

confidence: 99%

“…The relationship between the Big Five personality traits-namely conscientiousness, openness, neuroticism, extraversion and agreeableness-and academic performance has been investigated by many researchers, namely, Busato, Prins, Elshout and Hamaker (2000), Komarraju et al (2011), Ackerman, Chamorro-Premuzic, and Furnham (2011), Chamorro-Premuzic and Furnham (2008, O'Connor and Paunonen (2007), Heaven and Ciarrochi (2012), Rosander and Bäckström (2014), Vedel (2014) and Morris and Fritz (2015). Although there are variations in their findings, these studies generally agree that neuroticism, in contrast with conscientiousness, correlates negatively with academic performance.…”

Section: Personality and Academic Performancementioning

confidence: 99%

“…Exit interview records show that a number of students withdrew from their studies due to a lack of financial means. In this study, SES is included as a variable together with the other predictors to determine whether it has an effect on academic performance, as suggested by Komarraju et al (2011), who recommended "examining environmental factors such as socioeconomic status as predictors of academic achievement". In his meta-analytic review of the literature, Sirin (2005) reported that the relationship between SES and academic achievement was inconsistent, ranging from a strong relationship to no correlation at all (Sirin, 2005).…”

Section: Socioeconomic Status (Ses) and Academic Performancementioning

confidence: 99%

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Early Detection of At-Risk Undergraduate Students through Academic Performance Predictors

Rowtho¹

2017

HES

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Undergraduate student dropout is gradually becoming a global problem and the 39 Small Islands Developing States (SIDS) are no exception to this trend. The purpose of this research was to develop a method that can be used for early detection of students who are at-risk of performing poorly in their undergraduate studies. A sample of 279 students participated in the study conducted in a Mauritian private tertiary academic institution. Results of regression analyses identified the variables having a significant influence on academic performance. These variables were used in a linear discriminant analysis where 74 percent of the students could be correctly classified into three categories: at-risk, pass or fail. In conclusion, this study has proposed a new technique that can be used by institutions to determine significant academic performance predictors and then identify at-risk students upon whom interventions can be implemented prior to exams to address the problem of dropouts.

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Section: Attendance and Academic Performancesupporting

confidence: 84%

Section: Academic Performancementioning

confidence: 99%

Section: Personality and Academic Performancementioning

confidence: 99%

Section: Socioeconomic Status (Ses) and Academic Performancementioning

confidence: 99%

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Early Detection of At-Risk Undergraduate Students through Academic Performance Predictors

Rowtho¹

2017

HES

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“…29 Furnham found that learning style, personality traits, and intelligence accounted for around 10% of the variance in college examination success. 30 Of the studies that looked at personality traits, the introversion/extroversion scale did not seem to be predictive or associated with learning performance but may have been potentially related to learning strategies (ie, deep vs surface vs strategic) 31 or instructional techniques (ie, lecture vs interactive).…”

mentioning

confidence: 99%

An Exploratory Analysis of Personality, Attitudes, and Study Skills on the Learning Curve within a Team-based Learning Environment

Persky

Henry

Campbell

2015

American Journal of Pharmaceutical Education

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Objective. To examine factors that determine the interindividual variability of learning within a teambased learning environment. Methods. Students in a pharmacokinetics course were given 4 interim, low-stakes cumulative assessments throughout the semester and a cumulative final examination. Students' Myers-Briggs personality type was assessed, as well as their study skills, motivations, and attitudes towards team-learning. A latent curve model (LCM) was applied and various covariates were assessed to improve the regression model. Results. A quadratic LCM was applied for the first 4 assessments to predict final examination performance. None of the covariates examined significantly impacted the regression model fit except metacognitive self-regulation, which explained some of the variability in the rate of learning. There were some correlations between personality type and attitudes towards team learning, with introverts having a lower opinion of team-learning than extroverts. Conclusion. The LCM could readily describe the learning curve. Extroverted and introverted personality types had the same learning performance even though preference for team-learning was lower in introverts. Other personality traits, study skills, or practice did not significantly contribute to the learning variability in this course.

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