Running head: PERSONALITY AND ACADEMIC PERFORMANCE META-ANALYSIS

This article reports a meta-analysis of personality-academic performance relationships, based on the Five-Factor Model (FFM), with cumulative sample sizes ranging to over 70,000. Most analyzed studies came from the tertiary level of education, but there were similar aggregate samples from secondary and tertiary education. There was a comparatively smaller sample derived from studies at primary level. Academic performance was found to significantly correlate with Agreeableness, Conscientiousness and Openness to Experience. Where tested, correlations between Conscientiousness and academic performance were largely independent of intelligence. When secondary academic performance was controlled for, Conscientiousness added as much to the prediction of tertiary academic performance as did intelligence. Strong evidence was found for moderators of correlations. Academic level (primary, secondary or tertiary), average age of participant, and the interaction between academic level and age significantly moderated correlations with academic performance. Possible explanations for these moderator effects are discussed and recommendations for future research are provided. Key-words: Personality; Intelligence; Academic Performance; Meta-Analysis; Moderation A Meta-Analysis of . 3 A Meta-Analysis of the Five-Factor Model of Personality and Academic Performance Research on personality and its relationships to important personal, social and economic constructs is as vibrant and influential as ever (Funder, 2001) and has been credited with prompting many of the major advances in fields such as organizational behavior (Hough, 2001). Much of this contribution can be linked directly to theoretical and statistical reviews of the role of personality, such as the pivotal meta-analyses of correlations between personality and work performance (Barrick & Mount, 1991; Hough, Eaton, Dunnette, Kamp, & McCloy, 1990). Such integrations of research have allowed researchers to assess the major features of these relationships, providing guidance for future studies. It is therefore surprising that, to date, there has been no comparable review of the relationship between personality and academic performance. This article reports on an attempt to provide just such an exhaustive statistical review. A brief history of research on personality and academic performance One of the earliest applications of trait-based personality assessment was the prediction of academic performance. Webb (1915) proposed the existence of a construct he labelled w, representing a will factor, which Spearman (1927) later argued sat alongside the general intelligence factor g as a contributor to academic ability. Consistent with this, research by Webb and others (e.g., Flemming, 1932) found that personality measures were correlated with academic performance. Unfortunately, early research was beset by inconsistent research findings and methodological problems. In one of the earliest reviews of the field, Harris (1940) expressed the view that personality contributed to academic performance, but acknowledged that this was unsupported by evidence because research up to that point was marred by inconsistent and flawed methodologies. Later, Stein (1963) emphasized the difficulty of making sense of research A Meta-Analysis of . 4 based on diverse theories and measures, while Margrain (1978) noted much creativity in methodology, but findings that showed no clear trends. The next major review of the field (De Raad, & Schouwenburg, 1996) still highlighted the scattered nature of this research and its lack of an overarching framework or paradigm, while Farsides and Woodfield (2003) concluded that findings had been “erratic” (p. 1229). In brief, reviews of research on the relationship between personality and academic performance have generally presented equivocal conclusions, largely due to the use of variable research methodologies and theoretical bases. Just as with academic performance, early research on links between personality and work performance found variable results, leading to the conclusion that general dimensions of personality were largely unrelated to work performance (Guion & Gottier, 1965). Two methodological advances helped reverse that conclusion: the advent of meta-analytical techniques for effectively combining results from previous research (e.g., Hunter, Schmidt, & Jackson, 1982) and the growing acceptance of broad factorial models of personality, which provided a framework for comparing personality studies. In particular, the Five-Factor Model (FFM) of personality, which is made up of the dimensions of Agreeableness (reflecting likeability and friendliness), Conscientiousness (dependability and will-to-achieve), Emotional Stability (adjustment versus anxiety), Extraversion (activity and sociability), and Openness (imaginativeness, broad-mindedness and artistic sensibility), has been important in this regard. The value of the FFM is that it encompasses most of the variance in personality description in a simple set of dimensions, thus bringing order to the previous “chaotic plethora” of personality measures (Funder, 2001, p. 200). Barrick and Mount (1991) used the FFM to organize their meta-analysis, thus providing one of the first broad-ranging estimates of the relationship between personality and work performance. Since then, a series of meta-analyses, culminating in Barrick, A Meta-Analysis of . 5 Mount and Judge’s (2001) second-order meta-analysis, have provided a largely consistent picture — personality measures, especially Conscientiousness, are associated with a range of workplace performance criteria. Given the long-standing interest in the relationship between personality and academic performance, it is surprising that no similarly authoritative meta-analyses have been reported. A thorough meta-analysis using the FFM framework would effectively address many of the concerns raised by earlier reviewers regarding inconsistent personality theories and scales. To date, there have been several meta-analyses of the relationship between personality and academic performance; however each of these is limited in range or suffer from methodological problems. Beginning with measurement issues, the meta-analysis reported by Hough (1992) was based on a broad set of personality measures that had within-category correlations ranging from . 33 to . 46 (average of .39), casting doubt on the homogeneity and hence the interpretability of these categories. Similar criticisms can be made of the meta-analysis reported by Trapmann, Hell, Hirn and Schuler (2007), which used a variety of measures of personality that had not been designed to assess the FFM (e.g., early versions of the 16PF and the California Psychological Inventory). Hough also included both grades and college attendance as measures of academic performance, but these measures are far from synonymous. For example, Farsides and Woodfield (2003) reported a correlation of -. 36 between absenteeism and final-year percentage. In contrast, the meta-analyses reported by Poropat (2005) and O’Connor and Paunonen (2007) addressed these measurement problems by using only FFM-based measures and restricting themselves to measures of grade and grade point average (GPA). However, O’Connor and Paunonen (2007), like Poropat (2005) and Trapmann et al. (2007) restricted their meta-analyses to post-secondary A Meta-Analysis of . 6 academic performance. Hough (1992) did include correlations with secondary school performance but aggregated these with correlations with post-secondary academic performance. One of the main strengths of meta-analysis is that it allows researchers to test for the presence of moderators, rather than accepting a single, over-arching estimate. However, neither Hough (1992) nor the meta-analyses by Poropat (2005) and O’Connor and Paunonen (2007) reported estimates of homogeneity for their samples, which is the first step in looking for moderators. Trapmann et al. (2007) did look for moderators and found heterogeneity in their sample of correlations, but their search for moderators was limited by application of a restrictive significance level (p < .00455) and the use of the unreliable method of hierarchical sub-group analysis (Steel & Kammeyer-Mueller, 2002: moderator analysis is discussed in more detail in the Results section). A further problem is that, apart from Hough (1992), each of these metaanalyses restricted its surveys to published studies, with O’Connor and Paunonen (2007) using what they referred to as “the major papers available on the topic” (p.974). This form of sampling can lead to biased estimates due to selective publication (Rosenthal & DiMatteo, 2001). Finally, none of these meta-analyses assessed whether correlations between personality and academic performance were confounded with underlying relationships with intelligence. As one reviewer noted, there is a long-standing speculation that all positively evaluated traits, such as personality and intelligence, are associated (Thorndike, 1940) so any links between personality and academic performance may be due to this. These various flaws have limited the interpretability of earlier meta-analyses, so the current research was undertaken to provide reliable estimates based on a literature search that was relatively exhaustive, while investigating the impact of various moderators and controlling for the influence of intelligence. A Meta-Analysis of . 7 Academic performance Apart from its theoretical value, there is considerable practical value in being able to statistically predict academic performance. Among the member countries of the Organisation for Economic Cooperation and Development (OECD), an average of 6.2% of gross domestic product is spent on educational activities, while the average young person in these countries will stay in education until the age of 22 (OECD, 2007). Clearly, the academic performance of students is highly valu