Mapping Diversity: Developing a European Classification of ... - U-Map

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The clustering is based on the correlation matrix of the scores on the questions (Kendall’s tau). The signifi cant correlations were mapped to fi nd out whether clear clusters emerge 10 . Using Kendall’s tau, ten combinations emerge as statistically signifi cant. 109 Table 12: Correlations between dimensions dimension dimension Kendall’s tau 11 12 0.82** 2 9 0.49* 4 10 0.48* 8 14 0.80* 11 13 0.46* 6 9 -0.71** 2 14 -0.69** 5 10 -0.54** 2 11 -0.53* 5 11 -0.54* 7 11 -0.53* 9 13 -0.41* ** signifi cant at 0.01 level * signifi cant at 0.05 level If the dimension public character (11) is mentioned it is very likely that the dimension legal status (12) is mentioned also in a similar way (most or least important). The same goes (to a lesser extent) for the combinations ‘range of subjects’ – ‘size’; ‘life long learning’ – ‘mode of delivery’; ‘international research orientation’ – ‘regional engagement’ and ‘public character’ – ‘cultural engagement’. For the other pairs listed it is likely that if one is mentioned important (innovation intensiveness) the other is considered to be least important (size). The other way to probe for possible clusters of dimensions used the answers to the relevance questions, posed for each dimension. Again we calculated the bivariate correlations between the scores. A high correlation between two dimensions means that if the respondent scores one dimension as highly relevant it is likely that he scores the other dimension this way as well. 10 Factor analysis is not an option, due to the measurement level (which is ordinal). MAPPING DIVERSITY
We mapped the dimensions and their statistically signifi cant correlations 110 11 . Visual inspection of the map suggests that there are at least three clusters of dimensions, with one or two sub-clusters. Figure 45: Mapping of the dimensions and the correlations between the scores on relevance 6 .34** .29** .31** 5 .29** 2 .46** .40** 1 .30** .36** 3 14 8 .37** .38** 7 .28** 4 .27** 11 .28** 13 .35** 9 .32** 12 .28** 10 MAPPING DIVERSITY 1: types of degrees offered 2: range of subjects 3: orientation of degrees 4: involvement in life long learning 5: research intensiveness 6: innovation intensiveness 7: international orientation (students and staff) 8: international orientation; research 9: size 10: mode of delivery 11: public private 12 legal status 13 cultural engagement 14 regional engagement The fi rst cluster comprises fi ve dimensions where dimension 8 (international research orientation) is the central dimension. The other dimensions in this cluster are 5 (research intensiveness), 1 (types of degrees offered), 2 (range of subjects), 6 (innovation intensiveness), and 7 (international orientation (teaching and staff)). This cluster has two faces: one R&D oriented side and one international orientation side. The second cluster includes dimensions 3 (orientation of degrees) and 14 (regional engagement) 11 Using two-tailed Kendall’s Tau
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Mapping Diversity Developing a Euro
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Mapping Diversity Contents Developi
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The research project team consisted
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2. Building a European Classificati
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with university rankings, rankings
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Classifi cations use the principles
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Table 1: Draft and classifi cation
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• Fontys Hogescholen, the Netherl
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3.1.2 Response to the survey 67 Res
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The question ‘this dimension is e
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4. Conclusions 21 In this chapter w
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of information on non-degree offeri
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4.3 Reduction of the number of dime
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Dimension Indicator new and suggest
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5. Operational implementation Part
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etter world’ from 19 th to 20 th
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Government model In this model gove
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also underline the need for coopera
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Bailey, K. D. (1994) Typologies and
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Annex I: Exploratory analysis of ex
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EU The Rebaspinoff projects (part o
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World of Learning. If a further bre
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Annex II: The case studies 45 Case
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Indicator 1.3.1.: number of program
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Indicator 3.1.2a.: number of Europe
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Case Study: University of Strathcly
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Indicator 1.3.2.: number of program
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Indicator 4.2.2.: number of part ti
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The dimension ‘cultural engagemen
Page 60 and 61: Figure 4: Institutional profi les b
Page 62 and 63: and life long learning. Feasibility
Page 64 and 65: Conclusions The pilot survey showed
Page 66 and 67: Indicator 10b: The percentage of pr
Page 68 and 69: Figure 32: Higher education institu
Page 70 and 71: Introduction 69 Rationale for the s
Page 72 and 73: Table 2: Age strata IAU based strat
Page 74 and 75: What is more problematic (or more d
Page 76 and 77: Table 5: Overview of indicators and
Page 78 and 79: Figure 3: Opinions regarding the st
Page 80 and 81: Figure 4: Opinions on the statement
Page 82 and 83: enrolment and 12a: legal status) or
Page 84 and 85: Data from existing sources The ques
Page 86 and 87: Valid cases The fourth indication o
Page 88 and 89: ate (3r d doctor cycle) or (1st bac
Page 90 and 91: If 40% is used as a cutoff point, t
Page 92 and 93: doct er mast Figure 16: Higher educ
Page 94 and 95: As a result of the discussion on th
Page 96 and 97: Indicator 6d: Financial volume of p
Page 98 and 99: doctorate er mast or bachel or +mas
Page 100 and 101: Indicator 9a: Enrolment The number
Page 102 and 103: er mast or bachel er mast or bachel
Page 106 and 107: Indicator 13b: Exhibitions 105 The
Page 112 and 113: as well as dimension 4 (involvement
Page 114 and 115: Appendix 1: Comments 113 Dimension
Page 116 and 117: 7e number of program offered abroad
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