Relationship Between Personality, Intelligence and Academia

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20th Mar 2019 Psychology Reference this

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The Relationship between Conscientiousness, Intellectual Ability, and Academic Performance in an Undergraduate Psychology Cohort

Abstract

This report examines the relationship between intellectual ability, conscientiousness and academic achievement. Psychology Students studying at the University of Adelaide (N=50) completed online versions of the OCEANIC (Schulze & Roberts, 2006) and Advanced Progressive Matrices (APM; Bors & Stokes, 1998). Results showed that there was a slight positive association between intellectual ability and academic performance, a slight positive association between conscientiousness and academic achievement and effectively no relationship between conscientiousness and intellectual ability. The study shows that personality traits can be promising predictors of academic achievement and thus may be useful in student development and admission systems.

Introduction

The relationships between personality traits, intellectual ability and academic performance have long been explored. These relationships were first used, in ancient times, for selecting civil servants in the Middle East, India and China to its current role as the driver of advanced economics (Poropat, 2011). Much of the research done in the past has been linked to theoretical and statistical reviews of the role of personality. One of the earliest applications of personality trait assessment was the prediction of academic performance (Poropat, 2009). This report attempts to further examine the relationship between personality traits, intellectual ability and academic performance in particular, conscientiousness and intellectual ability and their relationship with academic performance.

Intelligence is one of the most effective empirical predictors of academic performance (Poropat, 2009). Nothing has changed since the thirties when it was suggested that one of the most important factors in academic achievement is intelligence. Intelligence is the most documented variable as a predictor of cognitive performance and in past research has shown a positive association with academic success (Busato & Prins & Elshout, & Hamaker, 2000). In 2000 Busato conducted a study in which intellectual ability was compared to academic performance over three years. Intellectual ability was positively associated with academic achievement after one year and after three year, which is consistent with earlier studies. However, intelligence is not the only predictor of academic performance. In later research, Kappe and Flier (2012) suggested that conscientiousness, a personality trait that describes impulse control and self-regulation of behaviour (Ivcevic & Brackett, 2014), is the best predictor of academic achievement explaining five times as much variance in GPA (used to measure academic performance) as does intelligence. Earlier studies by Conard (2006) also showed positive bivariate correlations between conscientiousness and academic achievement. Whilst both intellectual ability and consciousness can predict academic performance, Poropat (2009) suggested that conscientiousness is largely independent of general intelligence. Chamorro-Remuzic, Furnham and Moutafi conducted a study in 2004 as a precursor to Poropat’s research in which they found a significant negative association between conscientiousness and two intelligence tests. They suggested that this was consistent with the idea that conscientiousness might partly develop as a compensation for low intellectual level and that high intelligent individuals may not need to engage in systematic, organised and dutiful study or work habits (Chamorro-Remuzic, & Furnham, & Moutafi, 2004).

The goals presented above guided this study, thus this report will further examine the relationships between intellectual ability, personality traits and academic achievement as explored above, focussing on three hypotheses: Hypothesis 1, there will be a significant positive relationship between intellectual ability and academic performance; Hypothesis 2, there will be a significant positive relationship between the personality trait conscientiousness and academic performance and; Hypothesis 3, there will be a significant negative relationship between conscientiousness and intellectual ability.

Method

Participants

The participants were 50 first-year Psychology students studying at the University of Adelaide. The participants took part in the study as part of an assessment task.

Materials

The OCEANIC (Schulze & Roberts, 2006) was employed to measure the Big Five personality traits. Intellectual ability was measured as performance on the short form of the Raven’s Advanced Progressive Matrices (APM; Bors & Stokes, 1998). Academic performance was operationalized as the participants’ final grade for the previous semester’s Psychology course.

Procedure

The participants were instructed to complete online versions of the OCEANIC and Advanced Progressive Matrices. They were free to perform the tasks wherever they chose, but were advised to try to complete the tasks in a quiet, distraction-free environment. The participants were instructed not to collaborate with anyone else on the tasks. There was no time limit placed upon the tasks, but it was stipulated that they had to be completed within a single test session.

Results

In Table 1, the means and standard deviations for the Big Five Personality traits (Openness, Conscientiousness. Extraversion, Agreeableness and Neuroticism), Intellectual ability (Raven’s APM), and Academic Performance are displayed.

In Table 2, the Correlation Coefficients for the variables associated with the three hypotheses are shown (Raven’s APM and Final Grade, Conscientiousness and Final Grade, Conscientiousness and Raven’s APM).

In Table 3, the r2-values for the variables associated with the three hypotheses are shown (Raven’s APM and Final Grade, Conscientiousness and Final Grade, Conscientiousness and Raven’s APM).

Table 1. Means and standard deviations for the Big Five personality traits, Intellectual Ability (Raven’s APM), and Academic Performance

  Mean Standard Deviation
Openness 31.88 7.00
Conscientiousness 36.58 6.98
Extraversion 33.06 7.57
Agreeableness 43.14 6.36
Neuroticism 26.74 7.83
Intellectual Ability (Ravens’ APM) 7.8 2.96
Academic Performance (Final Grade) 69.66 14.05
Notes: The maximum score for the Big Five personality traits is 54. The maximum for the APM is 12. Academic Performance is expressed as a percentage.

Table 2. Correlation Coefficients for Raven’s APM, Conscientiousness and Final Grade.

Final Grade

r-value

Raven’s APM

r-value

Raven’s APM 0.32*
Conscientiousness 0.39* -0.02 ***
Notes: *P<0.05; **P=0.05; ***P>0.05

Table 3. r2 values for Raven’s APM, Conscientiousness and Final Grade.

Final Grade

r-value

Raven’s APM

r-value

Raven’s APM 0.10
Conscientiousness 0.15 0.00

Hypothesis 1: There will be a significant positive relationship between intellectual ability and academic performance.

Figure 1. The relationship between Raven’s APM and Final grade.

According to Hypothesis 1, a significant positive relationship was expected between intellectual ability and academic performance. As shown in Figure 1, a quantitative analysis (Pearson’s correlation coefficient) indicated that there was a weak-moderate, positive relationship between Raven’s APM and final grade (r = 0.32), and that this relationship was statistically significant (p=0.02). Those who scored high in the Raven’s APM (M=7.8, SD=2.96), which operationalised intellectual ability, tended to score high in their final grade (M=69.66, SD=14.05), which operationalised academic performance. This provided qualitative support for the hypothesis.

Hypothesis 2: there will be a significant positive relationship between the personality trait conscientiousness and academic performance.

Figure 2. The relationship between conscientiousness and final grade.

According to Hypothesis 2, a significant positive relationship was expected between the personality trait conscientiousness (M=36.58, SD=6.98) and academic performance (M=69.66, SD=14.05). As shown in Figure 2, a quantitative analysis (Pearson’s correlation coefficient) there was a weak-moderate, positive relationship between conscientiousness and final grade (r=0.39), and that this relationship was statistically significant (p=0.01). Those with high conscientiousness (M=36.58, SD=6.98) tended to score high in their final grade (M=69.66, SD=14.05), which operationalised academic performance. This provided qualitative support for the hypothesis.

Hypothesis 3: there will be a significant negative relationship between conscientiousness and intellectual ability.

Figure 3. The relationship between conscientiousness and Raven’s APM.

According to Hypothesis 3, a significant negative relationship was expected between conscientiousness and intellectual ability. As shown in Figure 3, a quantitative analysis (Pearson’s correlation coefficient) indicated that there was an extremely weak, but effectively no negative relationship between conscientiousness and Raven’s RPM (r=-0.02), and that this relationship was not statistically significant (p>0.89). Those with high conscientiousness (M=36.58, SD= 6.98) did not consistently score high or low in Raven’s APM (M=7.8, SD=2.96), which operationalised intellectual ability. This did not provide support for the hypothesis.

Discussion

The purpose of this study was to examine the relationship between personality traits, intellectual ability and academic performance. Adding information, specifically relating to the relationships between intellectual ability and academic performance; Conscientiousness and academic achievement and; Conscientiousness and intellectual ability. According to the correlational analysis, intellectual ability was positively associated with academic performance. This is in accordance with the literature cited in the introduction (Poropat 2009, Busato et al. 2000). However this correlation was smaller than the correlation between personality trait conscientiousness and academic ability, reiterating research by Conard (2006) in the introduction. The r2 values for both these relationships, academic achievement and intellectual ability (r2 =0.10) and conscientiousness and academic ability (r2 =0.15), suggest that only 1% of the variability in academic achievement can be explained by intellectual ability and only 1.5% of the variation in academic achievement can be explained by conscientiousness. This suggests that there are other factors that play an important role in the variation of academic achievement. The association between conscientiousness and academic performance was also positive, suggesting that conscientiousness might have a bigger impact on academic performance than intellectual ability, which is consistent with the cited researchers Kappe and Flier (2012). The correlational research presented a very slightly negative, but effectively no association between conscientiousness and intellectual ability this does not support the relationship suggested by Chamorro-Remuzic, Furnham and Moutafi (2004) whose research highlighted a significant negative relationship between conscientiousness and intellectual ability. The r2 value for this relationship (r2 =0) suggests that 0% of the variance in intellectual ability can be explained by conscientiousness.

A lesson that may be taken from this study is that whilst intellectual ability is a positive predictor of academic performance, students are also able to perform well academically if they are willing to work hard and conscientiously. Another practical perspective of the research is that intelligence is probably the most used selection criteria for entrance to tertiary education. However the findings within this study suggesting that Conscientiousness is just as good or potentially a better predictor of academic performance suggests another practical selection tool, provided it can be accurately and validly assessed. (Poropat, 2009) However, conscientiousness creates a greater chance of faking over an intelligence test.

There are a number of limitations to this study. Firstly, there is a restriction of range, given it was only first year psychology students surveyed. A bivariate normal relationship may exist for the entire population whereas this relationship may not be evident for all sub-populations (i.e. Psychology students). Or otherwise, what appears to be a linear relationship for a sub-population could actually be a curvilinear relationship for the entire population (Haslam & McGarty, 2014). This means the relationships found by doing the quantitative analysis may not be a representation of the wider population. It would be beneficial to conduct a meta-analysis on students of different disciplines and potentially international students to find out how generalisable the results are. The sample size of 50 participants is also small. It is unlikely to reflect the population adequately. Whilst surveys are easy to develop, cost-effective and relatively easy to administer, there are a number of limitations associated with survey-based research. Researcher’s personal bias and idiosyncrasies are more influential in qualitative research; the knowledge of the study might also influence the participants’ responses. That is, respondents may feel encouraged to provide inaccurate and dishonest answers. Participants may interpret the survey questions and answer options differently and data errors caused by non-responses (i.e the number of participants who chose to respond to the survey as opposed to those that chose not to) may also affect the results.

References

Bors, D. A. & Stokes, T. L. (1998). Raven’s advanced progressive matrices: Norms for first-year university students and the development of a short form. Education and Psychological Measurement, 58, 382-398

Schulze, R. & Roberts, R. D. (2006). Assessing the Big Five: Development and validation of the Openness Conscientiousness Extraversion Agreeableness Neuroticism Index Condensed (OCEANIC). Zeitschrift fur Psychologie, 214, 133-14

Chamorro-Remuzic, T. & Furnham, A. & Moutafi, J. (2004). The relationship between estimated and psychometric personality and intelligence scores. Journal of Research in Personality, 38, 505-513.

Conard, M. A. (2006). Aptitude is not enough: How personality and behaviour predict academic performance. Journal of Research in Personality, 40, 339-346.

Ivcevic, Z. & Brackett, M. (2014). Predicting school success: Comparing Conscientiousness, Grit, and Emotion Regulation Ability. Journal of Research in Personality, 52, 29-36.

Kappe, R. & Flier, H. (2012). Predicting academic success in higher education: what’s more important than being smart? European Journal of Psychology of Education, 27, 605-619.

Busato, V. V. & Prins, F. J. & Elshout, J. J. & Hamaker, C. (2000). Intellectual ability, learning style, personality, achievement motivation and academic success of psychology students in higher education. Personality and Individual Differences, 29, 1057-1068.

Poropat, A. E. (2009). A Meta-Analysis of the Five-Factor Model of Personality and Academic Performance. Psychological Bulletin, 135, 322-338.

Poropat, A. E. (2011). The Eysenckian personality factors and their correlations with academic performance. British Journal of Educational Psychology, 81, 41-58.

Haslam, S. A. & McGarty, C. (2014). Research Methods and Statistics in Psychology. Great Britain: SAGE Productions Inc.

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