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Finally, Kolb is concerned about the growing specialisation in US higher education and does not want students to be equipped only with the learning styles appropriate for particular careers. Instead, he argues for ‘integrative development’, where students become highly competent in all four learning modes: active, reflective, abstract and concrete (see Kolb et al. 1986 on integrative learning for managers). So Kolb’s aim is to produce balanced learners with a full range of learning capacities, rather than simply matching instruction to existing learning styles. Empirical evidence for pedagogical impact The literature on learning styles contains many discussions of the significance and relevance of Kolb’s theory and practical concerns for pedagogy (eg Claxton and Murrell 1987; Sharp 1997). Unfortunately, that section of the literature which consists of experimental studies of the fit between learning styles and teaching methods is rather small, the size of the samples is not large, and the findings are contradictory and inconclusive. Some studies – some negative and others more supportive – will now be described to give a flavour of the range. Sugarman, for example, views Kolb’s theory of experiential learning ‘as a model of effective teaching’ (1985, 264). She also raises the interesting question as to whether all courses should begin with concrete experience as this is the first stage in Kolb’s learning cycle and he claims that the most effective learning emanates from personal experiences. Such a proposal may run up against the expectations of students, but unfortunately there is no testing of the idea by Sugarman. Empirical investigations of the relationship between learning styles and teaching methods have, however, produced some surprising findings. McNeal and Dwyer (1999), for instance, used Kolb’s LSI to ascertain the learning styles of 154 US nursing students who were then assigned either to a group where the teaching agreed with their learning style, or where it did not, or to a control group. The hypothesis was that teaching which was consistent with the learning style of the learners would enhance their learning, but no significant differences were found in the achievement of the three groups. Similarly, Buch and Bartley (2002, 7) administered both Kolb’s LSI and a new instrument devised by the authors – the Preferred Delivery Mode Self-Assessment – to 165 employees in a large US financial institution. The workers had to choose between five different teaching methods – computer, TV, print, audio or classroom. Buch and Bartley’s review of research into the relationship between learning style and training delivery mode led them to hypothesise that accommodators and convergers would prefer computers, divergers would prefer classrooms and assimilators would choose print. The results, however, showed that ‘all learners, regardless of learning style, prefer the traditional approach to learning, face-to-face classroom delivery’ (2002, 9). Was this because the workers felt more comfortable with a teaching method which they had known since early childhood? Or did they prefer the classroom to modern technology for social reasons, or because they did not want to be challenged by new methods? No definitive answers are provided by the study. Another study explored the interesting question: would knowledge of learning styles and the provision of ‘prescriptive study strategies’ improve the academic achievement of adult graduate students? Ehrhard (2000) explored this hypothesis with 148 students: they were divided into an experimental group, who were sent a personalised learning profile and study strategies that were appropriate for their learning type, and a control group who received nothing. The scores for the two groups were similar. So knowledge of learning style backed up by some supportive advice did not appear, in this case, to be sufficient to improve learning. On the other hand, students who were given Kolb’s theory and LSI as a framework to discuss their learning, often reported an ‘increased sense of self-esteem and self-understanding’ (Mark and Menson, quoted by Claxton and Murrell 1987, 31). More positively still, Katz (1990) in a quasi-experimental study of 44 occupational therapy students in the US and 50 in Israel, hypothesised that students whose learning styles matched the teaching method would perform better (ie more effectively) and would need less time to study outside class (ie more efficiently). The findings in both countries supported the premise that ‘the better the match is between students’ individual characteristics and instructional components, the more effective or efficient the learning program is’ (Katz 1990, 233). But even this conclusion needed to be qualified as it applied only to higher-order cognitive outcomes and not to basic knowledge.
LSRC reference Section 6 page 68/69 Further support is provided by Sein and Robey (1991) who administered Kolb’s LSI to 80 undergraduate computer students in the US and then assigned them randomly to one of two different training methods. The results appear to indicate that ‘performance can be enhanced by tailoring instructional methods to accommodate individual preferences in learning style’ (1991, 246). However, no control group was used and no indication was given of the size of the effect. How is one to make sense of such conflicting evidence, based as it is on rather small samples? Fortunately, there are two reviews of the literature which provide a little help. Cavanagh and Coffin evaluated the literature on ‘matching’ and found ‘relatively little empirical work to indicate the exact nature and magnitude of the change that can be expected in a student’s learning’ (1994, 109). The age of the learner appears to be crucial, as there was evidence that matching improved academic performance in primary education in the US; but the evidence in higher education generally, and in nursing more particularly, was inconclusive. Crucially, they concluded that little is known about the interaction of learning styles with organisational and resource issues. Their advice (1994, 109) is that ‘just varying delivery style may not be enough and … the unit of analysis must be the individual rather than the group’. The second, more recent, review by Smith, Sekar and Townsend found that: ‘For each research study supporting the principle of matching instructional style and learning style, there is a study rejecting the matching hypothesis’ (2002, 411). Indeed, they found eight studies supporting and eight studies rejecting the ‘matching’ hypothesis, which is based on the assumption that learning styles, if not a fixed characteristic of the person, are at least relatively stable over time. Kolb’s views at least are clear: rather than confining learners to their preferred style, he advocates stretching their learning capabilities in other learning modes. Grasha (1984) reviewed the literature on matching and concluded that no single dimension of learners should dictate teaching methods. Conclusion In a recent article, Mainemelis, Boyatzis and Kolb (2002) summarise the evidence for and against the LSI by reference to two unpublished doctoral dissertations in the US. The first, by Hickox, analysed 81 studies and concluded that ‘overall 61.7 per cent of the studies supported the Experiential Learning Theory (ELT), 16.1 per cent showed mixed support and 22.2 per cent did not support ELT’ (cited by Mainemelis, Boyatzis and Kolb 2002, 12). The second meta-analysis by Iliff of 101 quantitative studies found that ‘49 studies showed strong support for the LSI, 40 showed mixed support and 12 studies showed no support’ (cited by Mainemelis, Boyatzis and Kolb 2002, 12). Iliff also concluded that the balance of the evidence suggested that the statistical standards set for predictive validity had not been met by the LSI, while recognising that the LSI was developed as a self-assessment exercise and not as a predictive test. It seems difficult, if not impossible, to move beyond this continuing debate, with some researchers advocating the use of the LSI, and others denouncing it, while still others (eg Loo 1999) recognise the weaknesses of the instrument, and at the same time, argue for its usefulness as a pedagogical tool. In response to earlier criticism, Kolb (2000) claims that the latest version of the LSI has further improved the test–retest reliability, but as yet there is no independent body of evidence to confirm or deny that statement. In the meantime, Kolb and his associates have developed two new instruments: the Adaptive Style Inventory (ASI) which aims to measure flexibility in learning – ‘the degree to which individuals change their learning style to respond to different learning situations in their life’ (Mainemelis, Boyatzis and Kolb 2002, 11); and the Learning Skills Profile (LSP) – to assess levels of skill development in interpersonal, information, analytical and behavioural skills. This latest instrument (LSP) means that learning styles must now be distinguished from learning skills. According to Kolb (2000, 50), the former are the ways we prefer to absorb and incorporate new information, while the latter are more situational and subject to intentional development: ‘A skill is a combination of ability, knowledge and experience that enables a person to do something well’. Despite this recent surge of creativity, it is still difficult to resist the conclusion that the statistical sophistication used to analyse the data is not matched by the theoretical sophistication used to improve the concept of learning styles.
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LSRC reference Contents 1 9 13 37 4
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LSRC reference Figures and tables L
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LSRC reference Acknowledgements The
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Section 1 A systematic review of le
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Figure 3 Vermunt’s model of learn
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We devised this classificatory syst
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The popular appeal of the notion th
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Page 29 and 30: Table 1 Gregorc’s Mind Styles Mod
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Page 33 and 34: The measures Over 25 years, Dunn an
Page 35 and 36: Table 4 Percentages of respondents
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Page 69 and 70: Section 6 Flexibly stable learning
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Section 8 Implications for pedagogy
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Our recommendation in favour of inc
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As for the research evidence in fav
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Learning styles in practice: labell
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Table 44 13 learning-styles models
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It may be argued that it is importa
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The comparative neglect of knowledg
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Appendix 3 Glossary of terms LSRC r
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