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Entwistle also evaluated the predictive validity of the ASI by seeing how well it could discriminate between extreme groups, self-ranked as ‘high’ and ‘low achieving’. He found a prediction of 83.3% for the low-achieving group and 75% for the high-achieving group. In Ramsden and Entwistle (1981), similar results were obtained with moderate correlations between academic progress, organised study methods and a strategic approach. A deep approach did not appear to be the strongest predictor of high achievement in either study. Cluster analysis of ASSIST in Entwistle, Tait and McCune (2000) examined patterns of study between individuals responding to items in similar and different ways. Analysis suggested interesting signs of dissonance between students’ intentions to adopt particular approaches, their ability to apply them, and the effects of environmental factors on their ability to carry out their intentions. The importance of exploring similarities and dissonance between and across groups led the authors to argue that interpretation should combine factor and cluster analyses of responses to an inventory with analysis of findings from other studies. As research on the inventories has progressed, analysis of validity has combined the use of the inventory with qualitative data from interviews with students. More recent work has aimed to establish the ecological validity of the methodology as a whole by combining quantitative and qualitative methods (see McCune and Entwistle 2000). For example, the authors argue that the ASSIST measures the extent to which students adopt a particular approach at a given time and shows patterns within groups. It also ‘confirms and extends our understanding of patterns of study behaviours in relation to academic achievement and indicates the general influences of methods of teaching and assessment’ (CRLI 1997,12). Yet ASSIST does not show how individuals develop skills and approaches over time. In addition, although inventories are important, Entwistle and his colleagues argue that researchers using them need a close understanding of their evolution and of how conceptually related categories in inventories derive from different mental models of learning (Entwistle and McCune 2003). Combining quantitative and qualitative methodology and understanding their respective purposes are also important. Inventories need to be supplemented with methods that can explore the idiosyncratic nature of students’ learning and personal development, such as case studies of students’ activities and attitudes over time (McCune and Entwistle 2000). For example, deep learning approaches vary greatly between a student’s first- and final-year experiences, between different subjects and institutional cultures. Entwistle and his colleagues argue then, that combining psychometric measures with in-depth, longitudinal or shorter qualitative studies creates a robust methodology. In addition, the goal of ecological validity, achieved through detailed transcription and analysis of interviews, ‘allows staff and students to grasp the meaning of terms from their own experience, rather than facing technical terms that seem less relevant to their main concerns’ (Entwistle 1998, 85). In recent work, Entwistle and colleagues have used detailed case studies to explore how teachers’ sophisticated conceptions of teaching in higher education evolve over time (eg Entwistle and Walker 2000). External evaluation Reliability In a review of seven external studies and that of Ramsden and Entwistle (1981), Duff (2002, 998) claims that extensive testing of the ASI over 20 years, across samples and contexts, has produced scores that ‘demonstrate satisfactory internal consistency reliability and construct validity’. For example, using the Revised ASI with 365 first-year business studies students in a UK university, Duff (1997, 535) concluded that the RASI ‘has a satisfactory level of internal consistency reliability on the three defining approaches to learning’ proposed by Entwistle, with alpha coefficients of 0.80 for each approach. Richardson (1992) applied a shorter 18-item version of the 64-item ASI over two lectures held 2 weeks apart, to two successive cohorts of 41 and 58 first-year students on social science degree courses (n=99). He concluded that the broad distinction between a meaning orientation and a reproducing orientation is reliable, with alpha coefficients of 0.72 for meaning and 0.73 for reproducing. He presented test–retest reliability with coefficients of 0.83 on meaning, 0.79 on reproducing and 0.79 on achieving. Richardson argued that the ASI has good test–retest reliability, but that the internal consistency of its 16 sub-scales is variable (see below). Further support for the ASI as a reliable measure of broad orientations is offered by Kember and Gow (1990) who claim that, despite some small differences over factor structures relating to ‘surface orientation’, 1043 Hong Kong students revealed cultural differences in surface orientation where related constructs indicate a ‘narrow orientation’. This new orientation meant that students were dependent on tasks defined by the lecturer and wanted to follow tasks in a systematic, step-by-step approach. We have not found any external studies of reliability for the ASSIST.
LSRC reference Section 7 page 98/99 Validity In contrast to claims by Entwistle and his colleagues about the validity of the ASI, there is less agreement in external evaluations. For example, in a review of seven external studies and two by Entwistle and Ramsden, Richardson found problems with construct validity for many of the 16 sub-scales and individual items of the ASI generally. He argued that the ASI provided a convenient way of characterising students’ approaches to learning within different contexts, but an ongoing problem for researchers had been to retrieve the original constituent structure of the ASI. Although factor analyses in both internal and external studies of the ASI have retrieved the basic distinction between meaning and reproducing orientations, ‘dimensions concerning achieving orientation and styles and pathologies have been much less readily identifiable’ (Richardson 1992, 41). He concluded (1997) that meaning and reproducing orientations constitute a valid typology of approaches to studying and that there is evidence of gender and age differences in orientations. Problems with construct validity in the ASI are confirmed by Sadler-Smith (1999a), while other studies question the construct validity of some items for students of other cultures (see Meyer and Parsons 1989; Kember and Gow 1990). Kember and Gow argue that the test needs to be more culturally specific in terms of construct validity. There has also been disagreement about whether it offers predictive validity in correlating orientations and final assessment among 18–21-year-old undergraduates (Richardson 1992). However, Entwistle argues that the inventories were developed to describe different approaches to studying, not to predict achievement as such. In addition, the absence of standardised assessment criteria in higher education makes predictive validity difficult to demonstrate (Entwistle 2002). In response to problems with construct and predictive validity, Fogarty and Taylor (1997) tested the ASI with 503 mature, ‘non-traditional’ (ie without entry qualifications) entrants to Australian universities. Their study confirmed problems with internal consistency reliability for seven of the sub-scales, with alpha coefficients in the range 0.31 to 0.60. In a similar vein to other studies that advocate a focus on broad orientations, the authors argued (1997, 328) that it ‘may be better to concentrate on the meaning and reproducing orientations rather than on the various minor scales’. In terms of predictive validity, they found a negligible correlation between reproduction orientation and poor academic performance among their sample, but also a lack of correlation between a deep approach and good performance. This led them to argue that students unfamiliar with study may have appropriate orientations, but lack appropriate study skills to operationalise them. Another study (Kember and Gow 1990) explored relationships between, on the one hand, performance and persistence; and on the other, approaches and orientation as measured by the ASI. In a study of 779 students divided between internal and external courses, discriminant analysis evaluated which of the sub-scales could distinguish between those who persist and those who do not. For both internal and external students, the surface approach was the variable that discriminated between non-persisters and persisters [discriminant coefficients of 0.71 (internal students) and 0.94 (external students)]. The other variable was fear of failure. Persistence was therefore partly related to fear of failure, while a surface approach was more likely to lead to dropping out. In a study of 573 Norwegian undergraduates following an introductory course in the history of philosophy, logic and philosophy of science, Diseth (2001) evaluated the factor structure of the ASSIST. His study found evidence of the deep and surface approaches, but was less positive for items about course perception and assessment demands. In another test with 89 Norwegian psychology students, he found no links between general intelligence measures and approaches to learning. However, he noted (Diseth 2002) that straightforward correlations between achievement and the approaches that students adopt are not sufficient to predict success in assessment: instead, a surface approach had a statistically significant curvilinear link to examination grade: the highest level of achievement related to a low or moderate surface approach. The more that students used a surface approach, the more their achievement declined. A strategic approach is also associated with high achievement, suggesting a need to differentiate between deep and surface approaches to learning and a strategic approach to studying (Entwistle and McCune 2003). This also suggests the need for lecturers, and students themselves, to be realistic about the importance of strategic approaches in students’ responses to teaching and curriculum and assessment design. For example, the pressures of ‘credential inflation’ for achieving ever higher grades and levels of qualification are likely to encourage strategic approaches. There has recently been a large upsurge of interest in describing and measuring the study strategies of students in higher education. This interest arises from both political and pedagogical goals: for example, policy decisions such as the training and certification of teachers in universities demand empirical evidence about appropriate pedagogy (see Entwistle and McCune 2003). In addition, current proposals to use student evaluations of their courses as the basis for league tables of universities derive heavily from the Course Perceptions Questionnaire developed for quite different purposes in the 1980s.
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LSRC reference Learning styles and
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LSRC reference Learning styles and
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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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LSRC reference Section 1 page 2/3 E
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LSRC reference Section 1 page 6/7 T
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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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Figure 5 Gregorc’s four-channel l
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From the evidence available, we con
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Table 1 Gregorc’s Mind Styles Mod
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Table 2 Variables and factors in th
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The measures Over 25 years, Dunn an
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Table 4 Percentages of respondents
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The BES instrument has elements for
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Shwery (1994) also questioned aspec
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However, the notion of ‘gifted’
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Second, the model encourages teache
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Table 6 Dunn and Dunn’s model and
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The most influential member of the
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Table 9 Studies of the interaction
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Riding and Rayner (1998) do not def
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Implications for pedagogy Riding (2
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Page 69 and 70: Section 6 Flexibly stable learning
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Page 127 and 128: Section 8 Implications for pedagogy
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Appendix 3 Glossary of terms LSRC r
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