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LSRC reference Section 4 page 40/41 Peer matching and mismatching research on 64 dyads by Frank and Davis (1982) implies that FI individuals can lift the performance of an FD partner, while Saracho and Dayton (1980) infer from their results that the impact of an FI teacher on both FI and FD students can be significantly greater than the impact of an FD teacher. However, this study was conducted with younger children and should be placed in the context that individuals tend to be more FD as children and to become more FI as they get older. Moreover, Saracho (1998a) found that FI teachers had a more positive view of their matched FI students than did FD teachers of FD students, thus giving rise to a possible confusion between positive effects due to FDI matching, and positive effects due to positive affect. However, Garlinger and Frank (1986), in a meta-analysis of ‘matching’ studies relating to field dependence/ independence, find that matching FD students with FD teachers does not increase attainment, although matching FI students with FI teachers does, but effect sizes for the post-16 samples are very small (0.21 for 386 community college students; 0.12 for 192 14–17 year olds). Conclusions It is a common criticism of the learning styles field that ‘style research is peppered with unstable and inconsistent findings, while style theory seems either vague in glossing over inconsistencies or confused in stressing differential features selectively’ (Messick 1984, 59). Kagan and Kogan (1970, 1273) draw a favourable distinction between the battery of tests used by Cattell in the 1890s, measuring temporal awareness, sensory acuity and motor skills, and those used by their own contemporaries: ‘The contemporary battery evaluates richness of language, reasoning, classification and perceptual synthesis and decision process.’ But while they attribute the tests used by Victorians to ‘the intellectual prejudices of the nineteenth century’, they do not explicitly recognise that late 20th century definitions of cognition are equally influenced by social and economic mores. They are keen to link their conceptions of cognitive functioning, at least analogously, with the language of genetics – citing environment-specific behaviour as similar to pleiotropy (one gene, many effects) and multi-determined behaviours/polygeny (many genes, single development). In doing this, they want (1970, 1275) to link thematically with the ‘hard sciences’: The laws of biology, chemistry and physics consist, in the starkest sense, of collections of functional statements about entities. In biology the cell and the gene are basic units. In chemistry the molecule and the atom … In physics, particles and planets are units … Psychology’s units may turn out to be cognitive structures, and laws about cognitive process will describe how these units function. Many members of this group express a desire for a meta-taxonomy. Messick (1984, 66) argues that a comprehensive view of cognitive style: would include broad versus narrow categorising; complexity versus simplicity and the closely related constructs of conceptual level and integrative complexity; field independence versus field dependence (or field sensitivity); levelling versus sharpening; scanning versus focussing; converging versus diverging; automatization versus restructuring; reflection versus impulsivity and possibly risk taking versus cautiousness. However, some theorists have moved on from cognitive styles and structures into new theories of intelligence, albeit shaped by ideas of style; for example, Guilford’s Structure of Intellect model (1967, 1977) and Gardner’s Multiple Intelligences theory (1983, 1993). Kogan’s complaint (1973, 177) that ‘The real-world referents of cognitive styles outside the context of formal schooling have simply not been spelled out in any systematic fashion’ has not been addressed by empirical work stemming directly from this family of learning styles. Researchers have drawn on the work of the cognitive structure family before moving away to focus more specifically on approaches and strategies for learning. Given the increasing focus on the strategies which are peculiar to FI and FD students and which may, therefore, underpin good or poor performance (Tinajero and Paramo 1998b), it may be logical to suggest that the intellectual heirs of the cognitive structure family may be Entwistle (see Section 7.1) and Vermunt (see Section 7.2). 4.1 Riding’s model of cognitive style and his Cognitive Styles Analysis (CSA) Richard Riding is director of the Assessment Research Unit at the University of Birmingham’s School of Education. He has extensively researched cognitive style, learning design and personality and is joint editor of the journal Educational Psychology. He markets the Cognitive Styles Analysis (CSA) privately through Learning and Training Technology. Definitions, description and scope Riding and Rayner (1998, 7–8) define cognitive style as ‘the way the individual person thinks’ and as ‘an individual’s preferred and habitual approach to organising and representing information’. They define learning strategy as ‘those processes which are used by the learner to respond to the demands of a learning activity’. To distinguish between cognitive style and learning strategy, Riding and Cheema (1991, 195–196) claim that: ‘Strategies may vary from time to time, and may be learned and developed. Styles, by contrast are static and are relatively in-built features of the individual.’
Riding and Rayner (1998) do not define learning style, but group models of learning style in terms of their emphasis on: experiential learning orientation to study instructional preference the development of cognitive skills and learning strategies. They state that their own model is directed primarily at how cognitive skills develop, and claim that it has implications for orientation to study, instructional preference and experiential learning, as well as for social behaviour and managerial performance. The structure of Riding’s model and of his computerised assessment tool, the CSA, is two-dimensional. The model has two independent (uncorrelated) dimensions, one relating to cognitive organisation (holist-analytic) and one relating to mental representation (verbal-imagery) (see Figure 6, based on Riding and Rayner 1998). It is important to note that the verbaliser-imager dimension is intended to measure a natural tendency to process information quickly in verbal or in visual form, not to indicate the relative strength of verbal and visual cognitive abilities as measured by intelligence tests. With both dimensions, the concern is with speed of reaction and processing rather than with accuracy. Riding and Cheema (1991) claim that previous models of cognitive/learning style can be accommodated within their two-dimensional framework and that the differences between models are largely matters of labelling. For example, they claim that their holist-analytic dimension is essentially the same as Entwistle’s surface-deep dimension and Hudson’s diverger-converger dimension. These claims rest almost completely on conceptual ‘analysis’, but have some empirical support in the form of a factor analysis carried out by Riding and Dyer (1983) on data collected from 150 12 year olds. Figure 6 The two dimensions of the CSA Verbaliser Holist Analytic Imager Origins The theoretical basis for Riding’s work is diverse, as he seeks to encompass many other models. Riding and Buckle (1990) state that the holist-analytic dimension derives from the work of Witkin (1962) on field dependence and field independence. The verbal-imagery dimension is related to Paivio’s dual coding theory (1971) and aligned by Glass and Riding (1999) with the neuropsychological evidence that language is predominantly a left-brain function, while visual thinking tends to be accompanied by more right-brain activity. On the basis of two early studies, Riding thought that the verbal-imagery dimension was also related to introversion-extraversion, with introverts tending to be imagers and extraverts to be verbalisers, but he later found no relationship between these qualities in a large sample of FE students (Riding and Wigley 1997). The Cognitive Styles Analysis (CSA) Description of the measure Riding (1991a, 1991b, 1998a, 1998b) has developed a computerised assessment method called the Cognitive Styles Analysis (CSA). This is not a self-report measure, but presents cognitive tasks in such a way that it is not evident to the participant exactly what is being measured. The test items in the CSA for the holist-analytic dimension are all visual, and the scoring is based on a comparison of speed of response (not accuracy) on a matching task (holist preference) and on an embedded figures task (analytic preference). The items for the verbal-imagery dimension are all verbal and are based on relative speed of response to categorising items as being similar by virtue of their conceptual similarity (verbal preference) or colour (visual preference). The literacy demand of the verbal test is not high, as only single words are involved, but this has not been formally assessed. The instrument is suitable for use by adults and has been used in research studies with pupils as young as 9 years. Reliability and validity No information about the reliability of the CSA has been published by Riding. Using a sample of 50 undergraduates, Peterson, Deary and Austin (2003a) report that the short-term test–retest reliability of the CSA verbal-imager dimension is very low and statistically not significant (r=0.27), while that of the holist-analytic dimension is also unsatisfactory in psychometric terms (r=0.53, p
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Page 5 and 6: LSRC reference Contents 1 9 13 37 4
Page 7 and 8: LSRC reference Figures and tables L
Page 9 and 10: LSRC reference Acknowledgements The
Page 11 and 12: Section 1 A systematic review of le
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Page 19 and 20: Figure 3 Vermunt’s model of learn
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Page 23 and 24: The popular appeal of the notion th
Page 25 and 26: Figure 5 Gregorc’s four-channel l
Page 27 and 28: From the evidence available, we con
Page 29 and 30: Table 1 Gregorc’s Mind Styles Mod
Page 31 and 32: Table 2 Variables and factors in th
Page 33 and 34: The measures Over 25 years, Dunn an
Page 35 and 36: Table 4 Percentages of respondents
Page 37 and 38: The BES instrument has elements for
Page 39 and 40: Shwery (1994) also questioned aspec
Page 41 and 42: However, the notion of ‘gifted’
Page 43 and 44: Second, the model encourages teache
Page 45 and 46: Table 6 Dunn and Dunn’s model and
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Page 49: Table 9 Studies of the interaction
Page 53 and 54: Implications for pedagogy Riding (2
Page 55 and 56: Section 5 Stable personality type L
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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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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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