Personality and approaches to learning predict preference for different teaching methods

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1 Learning and Individual Differences 17 (2007) Personality and approaches to learning predict preference for different teaching methods Tomas Chamorro-Premuzic a,, Adrian Furnham b, Martin Lewis b a Department of Psychology, Goldsmiths College, University of London, New Cross, London SE146NW, UK b Department of Psychology, University College London, UK Received 29 May 2006; received in revised form 27 November 2006; accepted 5 December 2006 Abstract A total of 221 (111 female and 110 male) British Medical students completed the NEO-FFI personality inventory [Costa, P. T., Jr., and McCrae, R. R. (1992). Revised NEO Personality Inventory (NEO-PI-R) and NEO Five-Factor Inventory (NEO-FFI) professional manual. Odessa, FL: Psychological Assessment Resources.], an abbreviated version of Biggs' [Biggs, J. B (1987). Study process questionnaire manual. Hawthorn, Vic: Australian Council for Educational Research.] approaches to learning scale, and a purpose-designed questionnaire to assess their preference for different teaching methods (e.g., lab classes, standard lectures, and discussion groups). Correlations between several personality traits and approaches to learning factors suggested that personality and learning approaches are distinct, but related, constructs. The deep approach to learning was associated with Emotional Stability, Openness, and Agreeableness. These personality traits were also negatively related to the surface approach to learning, whilst Conscientiousness was associated with deep and achieving learning approaches. Hierarchical regression analyses showed that preference for interactive teaching was associated with a combination of Emotional Stability, Agreeableness, and deep learning approach. Implications are discussed with regard to individual differences in educational contexts Elsevier Inc. All rights reserved. Keywords: Big Five; Approaches to learning; Biggs; Academic performance Universities offer a variety of teaching modalities, from traditional lectures to small, more interactive, discussion groups and individual tutorials. Methods vary as a function of the topic being taught, the different assessment criteria, and the preferences of the lecturers, who may emphasize theoretical, practical or mixed approaches. Yet, little work has been done on students' preferences for different teaching modalities, let alone on what determined these preferences. Generally, it has been assumed that if there is a fit between the student preferred teaching style and method and those chosen by the lecturer/teacher/professor 1, the result would be both happier and more academically successful students, though research often fails to support this hypothesis (Furnham, 1995). In fact, most research has concentrated on students' personality traits or their preferred learning styles, rather than their preferred teaching methods. Corresponding author. Tel.: address: pss02tc@gold.ac.uk (T. Chamorro-Premuzic). 1 For the purpose of the present report these terms may be used interchangeably /$ - see front matter 2006 Elsevier Inc. All rights reserved. doi: /j.lindif

2 242 T. Chamorro-Premuzic et al. / Learning and Individual Differences 17 (2007) The Big Five in academic settings The development of the Five Factor of Big Five personality framework (Costa & McCrae, 1992; Goldberg, 1990), which posits that individual differences in normal or non-clinical behavior can be conceptualized in terms of five basic orthogonal dimensions, namely Extraversion (e.g., sociable, cheerful and active), Neuroticism (e.g., emotionally unstable, anxious, and pessimistic), Openness to Experience (e.g., imaginative, artistically sensitive, and intellectually curious), Agreeableness (e.g., compassionate, trustworthy and empathic), and Conscientiousness (responsible, organized and hard-working), has provided researchers with a reliable psychometric instrument to assess the predictive validity of personality traits in many settings, including school and university. Although recent studies have looked at the relationship between students' Big Five personality traits and their preferences for different types of academic assessment (Chamorro-Premuzic, Furnham, Dissou, & Heaven, 2005; Furnham & Chamorro-Premuzic, 2005), as well as their academic performance (Chamorro-Premuzic & Furnham, 2003a,b, 2004, 2005), personality correlates of preferences for different teaching modalities remain unexplored. Professional accreditations in careers such as business, law, and medicine, offer a wide range of teaching methods, from traditional content-based lectures, to more interactive discussion groups, lab classes, and practical tutorials. Clearly, each of these teaching methods may suit different personalities, as well as different learning styles. 2. Learning approaches Recent research has emphasized the importance of students' learning approaches as determinants of academic performance and knowledge acquisition (Duff, 2003; Duff, Boyle, & Dunleavy, 2004). Biggs (1987, 1992) conceptualized three major learning approaches to classify students, namely deep, surface and achieving. A deep approach to learning is characterized by intrinsic motivation, engagement with the subject matter, and the desire to know everything about a given topic. Conversely, students who opt for a surface approach to learning are not interested in the task per se, but aim at learning the minimum amount of material required to pass. Finally, achieving approaches to learning are characterized by students' goal-oriented study strategies; consequently, achieving oriented students are pragmatic and inspired by results (i.e., high grades). Biggs (1987) further divided each of these three approaches into motive and strategy, as the same approach may or not be used to describe students' goals (reasons to learn or motives) as well as their methods and processes (strategies) to achieve them. An interesting, but largely neglected, question is whether learning approaches can be simply understood as a function of established personality traits, or whether, on the contrary, they may contribute independently to specific academic choices. So far, evidence has been inconsistent, with some studies (Zhang, 2003) concluding that learning approaches and personality traits are related, but distinct, constructs (about 25% overlap), and others (e.g., Duff et al., 2004) reporting a substantial overlap (about 45%) between these measures. Specific associations between learning approaches and personality traits have yet to be replicated. For instance, Zhang (2003) and Duff et al. (2004) reported similar associations between the a) deep learning approach and Openness, b) achieving approach and Conscientiousness, and c) Neuroticism and surface approach. However, Zhang (but not Duff et al.) found d) negative associations between Agreeableness and achieving approach, and e) negative associations between Extraversion and surface approach, whilst Duff et al. (but not Zhang) found f) positive associations between Agreeableness and surface approach, and positive association between Extraversion and achieving approach to learning. 3. Personality and learning approaches as predictors of teaching preferences The relationship between personality traits and learning approaches will provide information on the extent to which students' strategies and motivations can be predicted at an early age (as personality traits show longitudinal consistency across the life-span). On the other hand, it is important to know whether personality and learning approaches in particular if these are distinct psychological constructs can account for students' teaching preferences, as teaching methods may affect students' learning and, in turn, their academic performance. Thus the present study was designed to assess the degree to which students' personality traits and learning approaches can explain their preferences for specific teaching methods. For this purpose, a sample of UK medical students will be employed. In the UK, medical students are exposed to a variety of teaching methods, from small to large, and interactive to theoretical/taught, courses. Thus they represent an adequate sample to test the hypotheses of

3 T. Chamorro-Premuzic et al. / Learning and Individual Differences 17 (2007) this study (students with no experience on more than one or two teaching modalities would only be able to guess their preferred options). The following sets of hypotheses will be tested: H1. There will be significant links between personality traits and learning approaches, such that (H1a) Extraversion will be significantly and positively correlated with the achieving learning approach, (H1b) Neuroticism (low Emotional Stability) will be significantly and negatively correlated with deep, but positively and significantly correlated with surface, learning approaches, (H1c) Openness to Experience will be positively and significantly correlated with deep, but negatively and significantly correlated with surface, learning approaches, (H1d) Conscientiousness will be significantly and positively correlated with achievement, but negatively and significantly correlated with surface, learning approaches, and (H1e) Agreeableness will be significantly and negatively correlated with achieving strategy. These correlations were predicted on the basis of Duff's and Zhang's findings. H2. There will be significant links between personality traits and preferences for teaching methods, such that (H2a) Extraversion will be significantly and negatively correlated with preference for independent study (studying alone), (H2b) Neuroticism will be negatively and significantly correlated with preferences for most teaching methods, (H2c) Openness will be positively and significantly correlated with preferences for novel teaching methods, (H2d) Conscientiousness will be positively and significantly correlated with preference for most teaching methods, and (H2e) Agreeableness will be positively and significantly correlated with preferences for most teaching methods. H3. There will be significant links between approaches to learning and preferences for teaching methods, such that (H3a) deep learning approach will be significantly and positively correlated with most teaching methods, and (H3b) surface learning will be significantly and negatively correlated with most teaching methods. 4. Method 4.1. Sample Two hundred and twenty one undergraduate medical students from two UK universities participated in this study. Students were on the first year of clinical training and attended either University College London (57 male and 45 female) or Queens University Belfast (53 male and 66 female). This gave nearly equal numbers of males (n=110=49.8%) and females (n=111=50.2%). Questionnaires were distributed, completed and collected at the beginning of a lecture. Age ranged from 20 to 28 with a mean of (SD =1.18) years Measures Students completed three self-report inventories that assessed five personality traits, six learning approach scales, and preferences for a total of seven different teaching modalities. Each of these measures is described below: Personality Personality was assessed using the NEO-FFI (Costa & McCrae, 1992). This inventory is a short version of the NEO- PI-R and assesses the personality dimensions of Neuroticism (low Emotional Stability), Extraversion, Openness to Experience, Agreeableness and Conscientiousness. Hundreds of studies have used this inventory as it demonstrates both good internal and external validity (Costa & McCrae, 1992; Matthews, Deary, & Whiteman, 2003). It has been shown to be a satisfactory tool in assessing relationships between personality and a number of academic variables such as intellectual competence, self-esteem and teaching effectiveness. Items involve questions about typical behaviors or reactions and are answered on a five-point Likert-type scale, ranging from strongly disagree to strongly agree. Individuals are asked to describe themselves over a range of 60 items with 12 questions for each factor Approaches to learning Approaches to learning were assessed through an abbreviated version of the Study Process Questionnaire (SPQ) (Biggs, 1987; Fox, McManus, & Winder, 2001). This inventory is used to assess three major approaches to learning, namely surface, deep and achieving. Each of these approaches can be further broken down into two components,

4 244 T. Chamorro-Premuzic et al. / Learning and Individual Differences 17 (2007) Table 1 Descriptive statistics and Cronbach's α's for all measures Measure Cronbach's α Range of scores Observed range M SD Extraversion Neuroticism Openness Conscientiousness Agreeableness Deep motive Deep strategy Achieving motive Achieving strategy Surface motive Surface strategy Lab class Small groups Lectures Independent study Clinical Group discussion Research Note. n=221. namely learning motive (which refers to why students learn), and learning strategy (which refers to how they learn). There are thus six factors: a) deep motive, b) deep strategy, c) achieving motive, d) achieving strategy, e) surface motive, and f) surface strategy. In its original form, the SPQ comprises a total of 42 items (7 items per factor). The abbreviated version of the SPQ used in the present study consisted of 18 items (3 for each of the six factors described above) and also assessed three second order shared indicator factors (surface, deep, achieving), as well as one higher order deep-achieving factor similar to that proposed by Biggs (1987). Participants' responses were recorded on a 5- point Likert-type scale. Psychometric information on the reliability and validity of the SPQ has been reported elsewhere (Biggs, 1987, 1992; Fox et al., 2001; Zhang, 2000, 2004). In the present data set, all Cronbach's α's for the SPQ factors were higher than.67 indicating acceptable internal consistency (see Table 1) Preference for teaching modality A purpose designed self-report scale was used to assess participants' preference for different teaching modalities. A total of seven teaching modalities were included in the present questionnaire, namely a) post-mortems/laboratory classes, b) small-group tutorials, c) standard lectures, d) independent study, e) clinical/ward teaching, f) group discussion/seminars and g) research projects. Ratings of preference were provided on a 10-point Likert-type scale ranging from 1 (least preferred) to 10 (most preferred). Participants rated their preferred teaching method for each of the subjects that they were studying, namely geriatrics, surgery, obstetrics, psychiatry/neuroscience, general practitioner, pediatrics, anatomy, pathology and physiology. 5. Results This study was aimed at testing the relationship between personality traits (Big Five), approaches to learning, and preferences for teaching methods. Correlational data was derived from three different questionnaires. All relationships are reported below and the ultimate goal of this research was to test the extent to which personality traits and approaches to learning are associated with preferences for different teaching modalities Descriptive statistics Table 1 lists the mean scores (M), standard deviations (SD), possible and observed ranges, and internal reliability coefficients (Cronbach's α for all measures) for all measures. All α's were higher than.67 and consistent with those reported for the same measures in previous studies (even though the present study employed an abbreviated measure of

5 Table 2 Inter-correlations among sex, age, personality traits (Big Five), approaches to learning (Six Factors), and preference for teaching methods Measure Sex Age Extraversion Neuroticism Openness Conscientiousness Agreeableness Deep Motive Deep Strategy Achieve Motive Achieve Strategy Surface Motive Surface Strategy Lab class Small groups Lectures Independent Clinical Discussion group Research Note. n=221. pb.05, pb.01. T. Chamorro-Premuzic et al. / Learning and Individual Differences 17 (2007)

6 246 T. Chamorro-Premuzic et al. / Learning and Individual Differences 17 (2007) Table 3 Factor loadings for preferences for teaching methods Factor 1: Interactive teaching 2: Non-interactive teaching Group discussion.90 Small groups Lab class.74 Clinical teaching Independent study.85 Lectures.83 Eigenvalue=2.69 Eigenvalue=1.51 % Variance=44.95 % Variance=25.20 Overall % variance=70.16, correlation between factors 1 and 2: r=.24 Note. For each measure, the highest factor loading above.30 is indicated in bold. Loadingsb.30 have been omitted. Extraction method: principal component analysis. Rotation method: oblimin with Kaiser normalization. pb.01. SPQ). The most preferred teaching method was small groups (M=62.40), and the least preferred teaching method was research project (M = 39.33), which also showed the smallest SD Correlational analysis Table 2 reports the correlation matrix with the Pearson product moment coefficients for all possible parings (with exception of age and gender, which correlated significantly at r =.17, p b.05, indicating that males tended to be older than females). Twenty out of thirty possible correlations between personality traits and SPQ factors were significant; most of these correlations were in the predicted direction yielding support to our hypothesis. Extraversion was positively and significantly correlated with both achieving motive and deep strategy (partly supporting H1a). Neuroticism was negatively and significantly correlated with both deep strategy and motive and positively and significantly correlated with both surface strategy and motive (supporting H1b). Openness to Experience correlated positively and significantly with both deep motive and strategy, and negatively and significantly with both surface motive and strategy (supporting H1c). Conscientiousness was significantly and positively correlated with both deep motive and strategy, as well as both achieving motive and strategy (supporting H1d). Agreeableness was positively and significantly correlated with both deep motive and strategy, as well as achieving strategy. Agreeableness was also negatively and significantly correlated with both surface strategy and motive, as well as achieving motive (thus support for H1e remained ambiguous). In addition, structural equation model with AMOS 5.0 (Arbuckle, 2003) was used to estimate the correlation between the two latent (higher order) components underlying the Big Five and approaches to learning. This correlation was r=.19, pb.01, showing a modest but significant link between these two sets of constructs. Principal component analysis, on the other hand, identified two different higher order components, namely one (27.29% of variance) where deep motive (.70), surface strategy (.68), Neuroticism (.68), deep strategy (.68), surface motive (.59), Openness to Experience (.53), and Agreeableness (.52) loaded, and another (14.51% of variance) where achieving strategy (.65), Achieving motive (.56), Conscientiousness (.52), and Extraversion (.48) loaded. Given that this study was concerned with the degree to which both personality and learning approaches predict preferences for specific teaching modalities, the traditional Big Five and learning approaches factors, rather than common latent factors, were retained for further analyses. Correlations between preferences for different teaching methods showed several significant associations and were thus simplified through data reduction (see Factor analysis section below, as well as Tables 3 and 4). Correlations between personality traits and preferences for specific teaching methods showed a number of significant associations. Extraversion was negatively and significantly related to preferences for independent study (i.e., the more extraverted students were, the less they preferred to study independently) (partly supporting H2a). Neuroticism was negatively and significantly correlated with preferences for lab classes, small groups, clinical teaching, and group discussion (i.e., the more emotionally stable the students, the more they preferred these teaching modalities) (partly supporting H2b). These four teaching methods were also significantly correlated with Openness, though positively (i.e., the more open the students, the more they preferred these teaching methods) (partly supporting

7 T. Chamorro-Premuzic et al. / Learning and Individual Differences 17 (2007) Table 4 Regression Analyses of Predictors of Preference for Interactive Teaching Methods Step Variables entered ΔR 2 R 2 df ΔF Std. β (step 1) Std. β (step 2) t 1 Personality traits (Big Five) Extraversion Neuroticism Openness Conscientiousness Agreeableness Learning approaches Extraversion Neuroticism Openness Conscientiousness Agreeableness Deep motive Deep strategy Achieving motive Achieving strategy Surface motive Surface strategy Note. pb.05. pb.01. H2c). Conscientiousness was positively and significantly related to preference for clinical teaching (i.e., the more conscientious the students, the more they preferred clinical teaching) (partly H2d). Finally, Agreeableness like Openness was positively and significantly correlated with preference for lab classes, small groups, clinical teaching, and group discussion (i.e., the more agreeable the students, the more they preferred these four teaching methods) (partly supporting H2e). Correlations between SPQ factors and preference for specific teaching methods also showed a number of significant associations. Deep motive and strategy were positively and significantly correlated with preference for lab classes, small groups, clinical teaching, and discussion groups (partly supporting H3a). These teaching methods were also significantly correlated with surface motive and strategy, though negatively (partly supporting H3b) Factor analysis An exploratory factor analysis using maximum likelihood extraction and direct oblimin rotation with Kaiser normalization was performed on the data to identify any underlying component/s in students' preferences for teaching methods. Results are reported in Table 4. Based on the Eigenvalues and a Scree Test, two factors were extracted which accounted for 70.16% of the variance. The first factor was labeled interactive teaching and explained 44.95% of the total variance. The second factor was labeled non-interactive teaching and accounted for 25.50% of the total variance. Four type of teaching modalities loaded most strongly on the interactive teaching factor, namely lab classes, clinical teaching, small groups and discussion groups. Preferences for traditional lectures and independent study loaded most strongly on the non-interactive teaching. Preferences for research classes did not load strongly enough on any of the two factors. Both factors showed acceptable internal consistency (Cronbach's α's =.71 for non-interactive teaching, and.78 for interactive teaching) and scores were computed through simple addition Hierarchical linear regression analysis Finally, two linear hierarchical regressions were performed on the data to test the extent to which Big Five personality traits and approaches to learning can predict interactive and non-interactive teaching methods. Furthermore, these regressions attempted to test whether approaches to learning have any incremental validity in the prediction of preference for teaching methods, over and above established personality traits. The first hierarchical regression was conducted to predict students' level of preference for non-interactive teaching by personality traits (block 1) and approaches to learning (block 2). Neither personality traits nor approaches to

8 248 T. Chamorro-Premuzic et al. / Learning and Individual Differences 17 (2007) learning were found to be significant predictors of preference for non-interactive teaching, and the combined predictors only accounted for 3% of the variance (F (11, 209)=.51, p=not sig.). The second hierarchical regression (reported in Table 4) showed that personality traits and approaches to learning were significant predictors of students' levels of preferences for interactively taught courses. In model 1, Big Five traits significantly accounted for 26% of the variance, and Neuroticism (negatively), Agreeableness and Openness were significant predictors in the model. In block 2, SPQ factors were entered as predictors and accounted for an additional 6% of the variance. Again, Neuroticism (negative) and Agreeableness, but not Openness, were significant personality predictors in the model, whilst the only significant predictor amongst SPQ factors was deep motive. 6. Discussion This study set out to explore the degree to which personality and learning approaches could explain preferences for specific teaching modalities. To this end, it examined whether students' Big Five personality traits (Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness) and learning approaches (deep, surface, and achieving motives and strategies) were related to their preferences for different teaching methods. Given previous findings on the relationship between personality and learning approaches, it was also important to determine the independent contribution of both sets of constructs in the prediction of teaching preferences. Thus a secondary aim of this study was to investigate the correlation between the Big Five and the SPQ. Correlational analysis showed that all of the Big Five personality traits were significantly associated with different approaches to learning. These correlations were in line with initial predictions (H1a to H1e) as well as previous studies. Deep approach to learning was associated with Emotional Stability (low Neuroticism), Openness, Agreeableness, and Conscientiousness. Achieving approach to learning was associated with Conscientiousness and Agreeableness. Surface learning was associated with Neuroticism (low Emotional Stability), low Conscientiousness, and low Agreeableness. Extraversion was only significantly related to deep strategy and achieving motive. This pattern of results shows considerable overlap with Zhang's (2003) findings. In particular the finding that open, conscientious, and emotionally stable individuals all tend to prefer deep approaches and dislike surface approaches to learning. However, whereas Zhang (2003) found that achieving approaches were associated with low Agreeableness, the present results indicated just the opposite pattern: agreeable, rather than disagreeable, students prefer achieving approaches. The replicated findings regarding the relationship between personality traits and approaches to learning are also consistent with a growing number of investigations looking at the personality correlates of academic performance. Neurotic students, who are more likely to worry about the outcomes of exams and have lower confidence in their abilities to grasp a subject matter or to perform well in exams, opt for a surface rather than deep approach, as the latter may be hindered by worries and de-focused attention. It is quite possible that neurotic students prefer surface strategies because being fast helps them to regulate stress. Another interpretation, however, may be that students higher in Neuroticism would be less resilient in face of their sensitivity to failure, thus choosing compensational strategies such as merely studying for the test. Likewise, conscientious students may opt for learning approaches that reflect an interaction between past efforts and various exam scores. Indeed, correlations between Conscientiousness and both deep and achieving approaches to learning partly are consistent with the success of conscientious students in university settings (Chamorro-Premuzic & Furnham, 2002, 2003a,b; Furnham, Chamorro-Premuzic & McDougall, 2003): not only are these students more organized, motivated, and hard-working, but they also approach learning with deep and achieving motives and strategies, rather than surface strategies. Conscientious students are achievement oriented and ambitious and no doubt discover that deep as well as achievement strategies work best in securing good grades. With regard to Openness to Experience, it is no surprise that open students tended to use deep learning motives and strategies, and avoid surface ones: open individuals are characterized by higher intellectual curiosity, creativity and imagination and it therefore makes sense that they approach learning in a deep, rather than superficial, way. The fact (reflected by previous studies) that Openness is a weaker predictor of academic exam performance than Conscientiousness may be partly explained by the fact that Conscientiousness is associated with achieving learning, whilst Openness is not. However future research is needed to explore this hypothesis directly. As academic performance data was not available for the present sample, our data cannot answer the question of whether achieving approaches are the distinctive feature in the performance between open and conscientious students.

9 T. Chamorro-Premuzic et al. / Learning and Individual Differences 17 (2007) Finally the most surprising finding regarding the correlation between personality traits and learning approaches was that Agreeableness was significantly correlated with all learning approaches, and more so than any other trait. This is surprising for two reasons: a) Agreeableness had rarely been identified as a significant predictor of academic outcomes, and b) correlations between Agreeableness and achieving learning approaches were positive, rather than negative. It may be that agreeable people are content and try all different methods but the explanation for this finding remains unclear. Another central finding of the present study refers to the extent to which personality traits and approaches to learning overlap. Previous studies had yielded conflicting evidence. Some argued that learning approaches are essentially a subset of major personality dimensions (such that differences in learning approaches could be largely explained by individual differences in personality), but other studies concluding that personality and learning approaches represent different, albeit related, construct. In the present study, correlations between personality traits and learning approaches were certainly lower than they would have been if overlapping constructs had been measured. The highest correlation, between Neuroticism and deep strategy, was r=.44, which indicates that there is less than 20% of shared variance between these measures. Furthermore, the average correlation between all personality traits and learning approaches was r =.20, which indicates that, on average, personality traits and learning approaches share 4% of the variance. We thus provide further empirical support to Zhang's (2003) finding that the Big Five personality traits and learning approaches are distinct, rather than overlapping, constructs. The most important, and unique, aspect of this study was no doubt to examine the relationship of personality and learning approaches with preferences for different methods (H2a to H2e). To our knowledge, no previous study had examined the extent to which Big Five traits and learning approaches would predict students' attitudes towards a wide range of ways of delivering medical training. The first finding was that the six relatively common methods factored into two distinct types: interactive methods involving group work and practical teaching modalities on one hand, and more traditional, theoretical, less interactive, methods on the other. Linear multiple regression analysis showed that Big Five traits and the six learning approaches combined accounted for a total of 32% of variance in preferences for interactive methods, but only 3% of the variance in preferences for theoretical oriented, traditional, teaching. Emotionally stable, open, and agreeable students tended to prefer lab classes, small group tutorials, and clinical training, whilst conscientious students tended to prefer clinical training and discussion groups (which were also highly rated by open students). Introverts were more likely to prefer independent study than were their extravert counterparts. There was a consistent pattern of associations between learning approaches and preferences for different teaching modalities (H3b). Lab classes, small groups, clinical, and discussion groups were all significantly related to deep and surface approaches, positively and negatively, respectively. Thus students with a deep approach to learning, as those least likely to adopt a surface approach, enjoyed lab classes, small tutorial groups, clinical training and discussion groups. A factor analysis of students' preferences for teaching methods identified two clear components, namely noninteractive and interactive teaching. Of these two components, only the latter was significantly associated with personality or learning approaches variables (note that the non-interactive teaching factor included the items of independent study and standard lectures, which were virtually unrelated to personality and learning approaches with the exception of Extraversion in the case of independent study). Looking at the means and standard deviations of students' preferences, it can be seen that only research ratings were different (less preferred, more homogenous) to the ratings for other modalities, and that similar distributions were found for independent study, standard lectures, and the other measures. One would therefore expect personality traits and learning outcomes to correlate with indicators of preference for traditional, non-interactive, methods; yet such pattern of results was not found. This maybe because most teaching at school and university is of this type and scholars and students have learned to adapt to and accept these methods (without actually experiencing newer methods). On the other hand the hierarchical regression to predict preferences for interactive teaching showed that learning approaches exhibit little incremental validity over personality traits, and suggested that such preferences are mostly influenced by the personality traits of Emotional Stability and Agreeableness, and a deep approach to learning. In higher education, particularly at postgraduate levels, a wider variety of teaching methods are used than the traditional lecture. Furthermore students can and do choose courses that specifically and explicitly offer different methods of teaching and assessment. Indeed students appear to have a strong preference both for and against certain teaching methods which suit their temperament, ability and experience. This study demonstrated that just two selfreport measures could explain a third of variance in preferences for more interactive, practical, less structured and less

10 250 T. Chamorro-Premuzic et al. / Learning and Individual Differences 17 (2007) traditional teaching methods like class discussion. Whilst it may not always be possible for lecturers and teachers to use the teaching methods preferred by students it is certainly interesting to get some idea of the preferences. More importantly, it would be interesting to get them to try to explain why they have the preferences they do. This study did not include measures of cognitive ability or actual exam marks. These factors, as well as teaching and exam history, would no doubt explain additional variance in teaching method preferences. It should however be noted that participants were sampled from top universities where intelligence scores can be expected to be at least one, and probably mostly two, SD above average, and restricted in range. This study was also limited to medical students, though there is no reason to assume the results would not generalize to other students in other applied disciplines. Thus future research should examine whether and to what extent ability may mediate or moderate the relationship among personality traits, approaches to learning, and preferences for different teaching modalities, as a combination of ability, dispositions, and preferences is likely to increase both our prediction and knowledge of educational and learning outcomes. References Arbuckle, J. L. (2003). Amos 5.0 update to the Amos user's guide. Chicago, IL: SPSS. Biggs, J. B. (1987). Study process questionnaire manual. Hawthorn, Vic: Australian Council for Educational Research. Biggs, J. B. (1992). Why and How do Hong Kong Students learn? Using the Learning and Study Process Questionnaires. Education Paper No 14. Faculty of Education, The University of Hong-Kong. Chamorro-Premuzic, T., & Furnham, A. (2002). Neuroticism and special treatment in examinations. Social Behaviour and Personality, 30, Chamorro-Premuzic, T., & Furnham, A. (2003). Personality predicts academic performance: Evidence from two longitudinal studies on British University students. Journal of Research in Personality, 37, Chamorro-Premuzic, T., & Furnham, A. (2003). Personality traits and academic exam performance. European Journal of Personality, 17, Chamorro-Premuzic, T., & Furnham, A. (2004). A possible model to understand the personality intelligence interface. British Journal of Psychology, 95, Chamorro-Premuzic, T., & Furnham, A. (2005). Personality and intellectual competence. Mahwah: Lawrence Erlbaum Associates. Chamorro-Premuzic, T., Furnham, A., Dissou, G., & Heaven, P. (2005). Personality and preference for academic assessment: A study with Australian University students. Learning and Individual Differences, 15, Costa, P. T., Jr., & McCrae, R. R. (1992). Revised NEO Personality Inventory (NEO-PI-R) and NEO Five-Factor Inventory (NEO-FFI) professional manual. Odessa, FL: Psychological Assessment Resources. Duff, A. (2003). Quality of learning on an MBA programme: The impact of approaches to learning on academic performance. Educational Psychology, 23, Duff, A., Boyle, E., & Dunleavy, J. F. (2004). The relationship between personality, approach to learning and academic performance. Personality and Individual Differences, 36, Fox, R. A., McManus, I. C., & Winder, B. C. (2001). The shortened Study Process Questionnaire: An investigation of its structure and longitudinal stability using confirmatory factor analysis. British Journal of Educational Psychology, 71, Furnham, A. (1995). The relationship of personality and intelligence to cognitive learning style and achievement. In D. Saklofske & M. Zeidner (Eds.), International handbook of personality and intelligence (pp ). New York: Plenum Press. Furnham, A., & Chamorro-Premuzic, T. (2005). Individual differences and beliefs concerning preferences for university assessment methods. Journal of Applied Social Psychology, 35, Furnham, A., Chamorro-Premuzic, T., & McDougall, F. (2003). Personality, cognitive ability, and beliefs about intelligence as predictors of academic performance. Learning and Individual Differences, 14, Goldberg, L. R. (1990). An alternative description of personality: The Big Five factor structure. Journal of Personality and Social Psychology, 59, Matthews, G., Deary, I. J., & Whiteman, M. C. (2003). Personality traits, (2nd edition). Cambridge: Cambridge University Press. Zhang, L. (2000). University students' learning approaches in three cultures: An investigation of Bigg's 3P model. Journal of Psychology, 134, Zhang, L. (2003). Does the Big Five predict learning approaches? Personality and Individual Differences, 34, Zhang, L. (2004). Learning approaches and career personality types: Biggs and Holland united. Personality and Individual Differences, 37,