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The mathematical abilities and personality of undergraduate psychology students relative to other student groups Roy Bhakta, Clare Wood & Duncan Lawson This study examined differences in personality and mathematical ability between students studying Business, Psychology, Sports and Nursing. There were 286 participants who each completed a mathematics diagnostics test and a Revised Eysenck Personality Questionnaire (EPQ-R) during the first term of their first year of study. There was a significant effect of subject studied on the students’ performance on the maths diagnostic questionnaire and their scores on the ‘psychoticism’ subscale of the EPQ. Furthermore significant correlations were observed between psychoticism scores and mathematical ability within both the Business Management and Psychology groups, although the direction of those associations were different for each group (the association was positive for the business students, but negative for the psychology students). Based on these results it is suggested that there are significant differences in both psychoticism and mathematical ability between students from different courses. Furthermore, students may benefit from differing methods of teaching mathematical concepts, especially in the cases where students are averse to working in groups and collaboratively. Keywords: mathematics; numeracy; personality; psychoticism; extraversion; collaborative study; EPQ; EPQ-R; GCSE. HIS STUDY is concerned with the been relaxed by many institutions. The mathematical abilities of psychology result of this has been increased recruitment students relative to other undergrad- of students into higher education, combined T uate students and the extent to which indi- with greater diversity in the educational and vidual differences in the students’ social backgrounds of those students. personality profiles are associated with math- A by-product of widening participation in ematical competence. As Smith (2004) has higher education is a greater variation in highlighted, there is a constant need for a current and potential attainment of the numerate workforce and this is not limited students (Hawkes & Savage, 2000). In partic- to just those who study mathematics at ular, the number of students who are degree level: entering universities ill-prepared for the ‘Advanced economies need an increasing mathematical demands of their chosen number of people with more than minimum university course has risen substantially qualifications in mathematics to stay ahead in (Williamson et al., 2003) and such students international competitiveness and, in are more prone to failing or dropping out particular, to effectively exploit advances in due to mathematical or numeracy issues technology. An adequate supply of young (Bourn, 2002, 2007). people with mastery of appropriate A major difference between England and mathematical skills at all levels is vital to the other parts of the world is the non-compul- future prosperity of the UK.’ sory nature of mathematics study once the Smith (2004, p.12) compulsory phase of education has been Over the past two decades the types of quali- completed (Wolf, 1997). This feature sets fications that have been accepted as valid for the English education system apart from the entry onto higher education courses has majority of other developed countries where 96 Psychology Teaching Review Vol. 16 No. 2 © The British Psychological Society 2010 The mathematical abilities and personality of undergraduate psychology students… mathematics is to some extent compulsory ligence (intelligence test, historical knowl- and seen as an essential deciding factor for edge, writing ability, foreign language) and acceptance onto university courses. As a personality (NEO-PI, measuring Neuroti- result, English university students may have cism, Extraversion, Openness to experience, avoided mathematics prior to entry onto the Conscientiousness and Agreeableness) university course, but that could lead to a among Estonian speaking students (N=381) mismatch between students’ own abilities during the application process to a univer- and the demands and expectations arising sity. This study found weak but statistically from staff at universities. This problem is significant correlations between the person- widespread and observable in many different ality scales and general ability as measured disciplines (Smith, 2004). by the intelligence test. In particular, the Even though mathematical study is not intelligence test scores were found to be compulsory after GCSEs, students still have negatively correlated with conscientiousness the option of studying mathematics. (r=–0.19, p<0.001) and agreeableness However, Ruggeri et al.’s (2008) study of 196 (r=–0.18, p<0.001). Extraversion was not psychology students (first year=158 and found to be correlated with any of the meas- second year=38) found that only 46.7 per ures of intelligence. Allik and Realo cent reported knowing about the compul- concluded that although personality and sory statistics components of their course achievement were not directly related, prior to entry. This could help explain why students with lower intelligence scores may many students intending to take psychology behave differently (thrill seeking and with do not undertake post compulsory mathe- the urge to explore their fantasies) than matics study and as a result find the statistical individuals who scored highly on the intelli- components of the psychology degree chal- gence tests (who tended to be controlling, lenging. self-regulatory and control of their Research has shown that psychology emotions). Furthermore Komarraju et al. undergraduate students have mathematical (2009) looked at how personality could be skills that are not always sufficient for their related to both motivation and achievement studies at university (Mulhern & Wylie, (among 308 undergraduate students at an 2005). Furthermore, the mathematical skills American university. Of particular note is of psychology students since 2002 is signifi- their finding that conscientiousness, open- cantly lower than a similar cohort of students ness, neuroticism and agreeableness as meas- in 1992 (Mulhern & Wylie, 2004). Further- ured using the NEO-FFI instrument more, a report by Kounine et al. (2008) accounted for 14 per cent in the variance of suggests that the overall standard of mathe- Grade Point Average (GPA) scores whilst matics has been declining since the mid only five per cent could be accounted for by 1970s, to the extent that students can intrinsic motivation. This suggests that achieve a good pass at GCSE with little personality may have a greater influence on conceptual understanding. Similarly, Ofsted attainment than the degree of personal (2009, pp.51–52) highlight that students’ motivation. Komarraju et al.’s (2009) mathematical competencies are focused research also showed that amongst their more on the performance of mathematical sample, there was a significant positive corre- procedures and less on the underlying lation between GPA scores and: conscien- concepts involved. tious (r=0.29, p<0.01), agreeableness (r=0.22, It has been suggested that there may be p<0.01) and openness (r=0.13, p<0.05). some relationship between personality traits The influence of conscientiousness on and academic achievement. A study attainment is further highlighted by the use conducted by Allik and Realo (1997) looked of the Hogan Personality Inventory (HPI) by at the correlation between measures of intel- Martin et al. (2006) who conducted a four- Psychology Teaching Review Vol. 16 No. 2 97 Roy Bhakta, Clare Wood & Duncan Lawson being more accurate compared to extroverts year longitudinal study which looked at the effectiveness of personality measures and who were quicker and made more errors. pre-entry academic assessments as predictors Social Constructivism (Vygotsky, 1978) for undergraduate performance in the form suggests that learning is more productive of GPA scores for undergraduates (N=587) at when performed as a collaborative process; an American university. Their study showed individuals work with others rather than in that there was a correlation between GPA isolation., The notion of collaborative and both Prudence (positive correlation) learning has also been highlighted by Lave and Sociability (negative correlation), where and Wenger’s (Lave & Wenger, 1991; Wenger, Prudence was used as a measure of consci- 1998) work on communities of practice. entiousness and Sociability when combined However, it is important to note that the with ambition was considered a measure of collaboration and learning as a group idea is Extraversion (NEO and EPQ). However, it dependent on the individuals and how they was also shown that over the four years the interact with each other. Personality traits strength of the correlations decreased, such as extroversion and psychoticism which suggests that tuition can attenuate the (Eysenck & Eysenck, 1991) suggest how indi- extent of any relationships between person- viduals may interact with their peers: intro- ality and attainment. Fruyt and Mervielde verts are more likely to prefer working alone (1998) also found conscientiousness as whilst extroverts are more likely to engage measured by the NEO-PI-R (Dutch Flemish with group based activities. Similarly, those version) to be a predictor of the achieve- scoring higher on psychoticism measures may ment of 934 final year undergraduate be more inclined to work alone rather than students (various disciplines). collaborate with peers. What is not clear from The literature, therefore, suggests that the literature is if this is true in all areas of there is an inconsistent relationship between learning or just isolated to certain areas, for extraversion and academic achievement, example, numeracy, literacy or foreign although the aspect of personality measured languages. Furthermore, it is unclear whether variously as ‘conscientiousness’ and ‘psycho- there are significant differences in the person- ticism’ would appear to have a consistent ality and mathematical competencies of relationship with academic achievement. students from different courses. In particular, However, it is important to note that not all differences in personality may influence how the studies use the same scales for measuring individuals prefer to study, for example, indi- personality; for example, the psychoticism vidually or within groups (e.g. Vygotsky, 1978; scale on the EPQ instrument can be thought Lave & Wenger, 1991; Wenger, 1998). of as an amalgamation of conscientiousness By exploring the differences in person- and agreeableness scales on the NEO instru- ality between groups of students and the ment. A meta analysis by Wolf and Ackerman correlations with mathematics ability, it may (2005) suggests that past research has identi- be possible to inform discussions of how best fied statistically significant correlations to facilitate students’ learning of mathe- between intelligence (including numerical matics related content, for example, within ability) and the extraversion personality quantitative research methods and statistics. trait. Wolf and Ackerman also suggest that This study, therefore, examined the relation- the magnitude of the positive correlation has ships between personality and mathematical decreased over time and that more recent competency in students from university studies imply a negative correlation. The courses where A-level mathematics is not a Extraversion trait also suggests that pre-requisite for entry, but where the course extraverts’ and introverts’ behaviours when requires some element of mathematical taking test taking tests were different ability. This study, therefore, aimed to assess (Eysenck, 1994); introverts being slower but if there were differences in personality traits 98 Psychology Teaching Review Vol. 16 No. 2 The mathematical abilities and personality of undergraduate psychology students… and Sports). Only subjects that did not and mathematical competencies between students from different courses. The study require a mathematics qualification greater also aimed to explore whether any relation- than a grade C at GCSE level (or equivalent) ships existed between personality variables were selected. In total 288 undergraduate and the mathematics competencies of students at Coventry University volunteered undergraduate students. to participate in the study (see Table 1). Methodology Materials Design Students who volunteered to participate were This study explored the relationship asked complete a questionnaire that gath- between mathematics diagnostics scores and ered data on mathematical ability, personality personality measures amongst undergrad- and demographic data. Within the question- uate students at Coventry University. naire the instruments appeared in the A mixed design was used such that the following order: Demographics, Mathemat- personality and mathematics diagnostics ical ability questionnaire, Eysenck Personality variables were within participant variables Questionnaire – Revised (EPQ-R). and the course being studied was a between Mathematical ability. All students who participants variable. The outcome variable participated in the study were required to was the mathematics diagnostic test scores have a GCSE or equivalent qualification as (scored between 0 and 10) while the an entry criterion for their courses. It should predictor variables were the course of study be noted that the use of past mathematics (five possible courses) and personality meas- qualifications (e.g. GCSE) as accurate meas- ures (psychoticism 0 to 32, extraversion 0 to ures of mathematical ability on entry has 23, neuroticism 0 to 24, lie 0 to 21, addiction, been questioned. A number of universities 0 to 32, criminality 0 to 34). have found that the increasing diversity of entrance qualifications combined with the Participants varying times between achieving the qualifi- Participants were recruited from five courses cation and enrolment on the course has that were offered at Coventry University meant that past qualifications are poor meas- (Business Foundation Year, Business ures of mathematical ability on entry (LTSN Management, Adult Nursing, Psychology, MathsTeam Project, 2003). The document Table 1: Age, gender and university course of those involved in the study. Course Male Female Mean Median Age Age Business Foundation year 41 34 19.96 19 (SD) (3.87) Business Management 20 41 20.77 19 (SD) (4.32) Adult Nursing 4 46 25.10 23 (SD) (6.50) Psychology 4 49 21.13 19 (SD) (5.55) Sports 20 27 19.38 19 (SD) (2.34) Psychology Teaching Review Vol. 16 No. 2 99
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