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LSRC reference Section 3 page 24/25 Emotional factors: motivation, responsibility, persistence and need for structure Rita Dunn (2001a) claims that emotional factors are relatively unstable, or perhaps the most responsive to experience. Nevertheless, matching these kinds of preference to instruction is said to result in learning gains with a mean effect size 5 of d=0.54 according to the meta-analysis by Dunn et al. (1995) of doctoral studies supporting the LSI. Physical factors: modality preference, intake, time of day and mobility A person’s preference as to whether tasks or activities are presented to appeal to auditory, visual, tactile or kinaesthetic senses (modality preference) is an important dimension in the model. Carbo (1983), on the Dunns’ behalf, questioned earlier research into modality preference, suggesting that ‘although only 2 of the 19 studies … achieved significant interactions between reading method and modality strengths’, methodological weaknesses in the majority of studies have obscured the connection between reading instruction and modality preference. This led Carbo to assert that there is, after all, a connection. Many other researchers on modality preference (not using the Dunns’ model) have reported a lack of evidence for modality preference as a guide to teaching strategy. For example, in a review of 22 studies, Kampwirth and Bates (1980, 603) reported that 20 ‘failed to indicate a significant interaction’, while Tarver and Dawson (1978) found that only two out of 14 studies showed an interaction between modality preference and teaching method. Similarly, Deverensky (1978) argued that research had not shown a causal relationship between modality and reading performance, but he suggested that this might be because of the difficulty of finding sensitive measures of preference. Recent research into modalities suggests that different modality effects are associated with reading performance, in particular with the problems that poor readers have with echoic (sound-based) memory (Penney and Godsell 1999). This implies that auditory instruction may benefit good readers more than poor readers. Westman and Stuve (2001) suggest that modality preferences exist and that self-report questions based around enjoyment are one way to elicit them. Yet, as the introduction to this section shows, there is disagreement as to whether modality preferences are important. There is also evidence to suggest that learning styles are more likely to be influenced by students’ understanding of the demands of a particular task than by modality preference (Westman, Alliston and Thierault 1997). In other research on modality preference, Kavale and Forness (1987) confronted the widespread belief among teachers working with learners with learning difficulties and/or disabilities that targeting modality preferences is an effective instructional strategy, arguing that the ‘question of the efficacy of the modality model remains controversial’ (1987, 229). After performing a meta-analysis of 39 empirical studies of the effects of matching modality strengths to special instruction in reading, they concluded that the diagnosis of modality preference was, in itself, problematic. In terms of the effects of modality-based instruction, they reported that the effect size of 0.14 ‘translates into only a 6 percentile rank improvement’ (1987, 233). They argued that ‘Although the presumption of matching instructional strategies to individual modality preferences to enhance learning efficiency has great intuitive appeal, little empirical support … was found … Neither modality testing nor modality teaching were shown to be efficacious.’ (1987, 237). Kavale and Forness excluded many studies in support of the LSI because these did not fit their meta-analysis criteria – namely, that studies should assess modality preference formally, design instructional materials and techniques to capitalise specifically on the assessed preference, and assess results of that instruction with a standardised outcome measure. This external research into one of the most important underlying claims of the Dunn and Dunn model provoked a response from Rita Dunn (1990a) and a riposte from Kavale and Forness (1990). These have been referred to as a ‘blistering exchange’ over ‘allegations and counter-charges of shoddy scholarship and vested interests [that] have clouded the issue and made it all the more difficult for practitioners to decide what’s worth pursuing’ (O’Neil 1990). Rita Dunn rejected the findings of Kavale and Forness because they excluded studies produced in support of the LSI and asserted that high achievers ‘may strongly prefer one modality more than another, but often they have two or more preferences and can learn easily through one or the other. In contrast, underachievers may have either no preference or only one – usually tactual or kinesthetic’ (Dunn 1990a, 354). In response, Kavale and Forness re-asserted the criteria for including studies in their meta-analysis and added (1990, 358): ‘When even a cursory examination revealed a study to be so inadequate that its data were essentially meaningless, it was eliminated from consideration. This is the reason that only two of Dunn’s studies were included in our analysis.’ 5 Throughout this section, we have converted effect sizes into d values, using the formula provided by Cohen (1988, 23).
Table 4 Percentages of respondents preferring a specific time of day for study (students with no preference not recorded) Study Measure Cohort Morning Early morning Late morning Afternoon Evening Callan 1999 LSI Grade 9 (n=245) 9% 10% 18% 21% Biggers 1980 LSI Grades 7–12 (n=641) 22.8% 42.4% 34.8% Carey, Stanley and Biggers 1988 Peak alert 4-item survey College freshmen (n=242) 16% 27% 57% Instead of modality-based teaching, Kavale and Forness recommended that specific instructional strategies could benefit all students. This idea is supported by the Dunn’s own research (Miller et al. 2000/01), which found that a teaching strategy based on a ‘programmed learning sequence’ and designed to favour visually- and tactilely-oriented students increased attainment for all students in the experimental group. Jaspers (1994) rejected the utility of identifying dominant modality preferences as a basis for designing targeted instructional materials, arguing that there is both a lack of theoretical support and doubts about the practical efficiency of such an approach. Targeted instructional materials were not supported by Moreno and Mayer (1999, 366) who found that mixed modality presentations (visual/auditory) produce better results, ‘consistent with Paivio’s theory that when learners can concurrently hold words in auditory working memory and pictures in visual working memory, they are better able to devote attentional resources to building connections between them.’ Time-of-day preference is another important dimension in the Dunn and Dunn model; it is divided into early morning, late morning, afternoon and evening. A number of studies dealing with variations in reported time-of-day preference are shown above in Table 4. A meta-analysis of studies by Dunn et al. (1995) indicates that the group termed ‘physiological’ by the authors has the largest effect size. However, it is important to note that many of the studies cited by Dunn et al. (1995) are concerned with test performance, rather than with learning in different conditions. Another methodological drawback is that the studies are also affected by the human need to present consistently in self-report instruments and either prior or subsequent performance. In addition, some of the studies (eg Biggers 1980; Carey, Stanley and Biggers 1988) have only three categories (morning, afternoon and evening) and use different measures to assess preference. There does not appear to be a clear distribution of populations across the preferences that predict the percentage of students who may have strong preferences for a particular time of day. Further caution about the importance of time-of-day preference emerges from research into the ‘clock gene’, discussed in the introduction to this section, which suggests that inferring an uncomplicated relationship between preference, peak alert and performance is highly questionable. Even if a relationship does exist, it is important not to confuse correlation with causation. Sociological influences: learning groups, authority figures, working alone and motivation from adults The absence of the element ‘motivation’ from the PEPS is perhaps surprising in the light of evidence that the desire to please parents persists well into adulthood (eg Luster and McAdoo 1996). Moreover, although adult learners continue to be influenced by authority figures, the PEPS does not deal with the impact of more experienced adults on learning cultures in the workplace – for example, in formal and informal mentoring relationships (see eg Allinson, Armstrong and Hayes 2001). A study of learning style preferences among males and females in different countries (Hlawaty and Honigsfeld 2002) claims statistically significant differences, with girls showing stronger preferences in motivation, responsibility and working with others than boys, and boys showing stronger preferences for kinaesthetic learning.
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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
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Page 29 and 30: Table 1 Gregorc’s Mind Styles Mod
Page 31 and 32: Table 2 Variables and factors in th
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Page 45 and 46: Table 6 Dunn and Dunn’s model and
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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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Appendix 3 Glossary of terms LSRC r
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