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

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Figure 44: Higher education institutions by score on importance of different sources of income 107 N=51 importance of local and regional sources importance of international sources importance of national sources 0% 20% 40% 60% 80% 100% insignificant significant critical has become less insignificant has become significant has become critical MAPPING DIVERSITY
108 Discussion In this chapter we discuss the results of the survey and the consequences these may have for the selection and clustering of dimensions and indicators. First we explore the dimensions with ‘poor’ indicators. The survey showed that a number of indicators scored signifi cantly lower on criteria such as validity and feasibility than others. Are these poor indicators evenly dispersed over the dimensions or can we identify particularly ‘challenging’’ dimensions (dimensions with predominantly poor indicators)? And what consequences may that have for the selection of dimensions and indicators? The focus then turns to a way to cluster the dimensions, using the scores on the questions on relevance. ‘Challenging’ dimensions One of the reasons for organising the survey was to fi nd out which dimensions and indicators would work and which would not. To fi nd an answer to this question we combined the information on the validity, feasibility and reliability of the indicators selected for each dimension. We do not use the scores on the perceived relevance of the dimensions since a high proportion of responding higher education institutions strongly disagreeing with the relevance of a dimension is not an indication of the quality of the dimension. We see such a lack of consensus as an indication of the diversity of the missions and profi les of the higher education institutions. Only if the vast majority of the responding higher education institutions disagreed with the relevance would we reconsider the choice of this dimension. This was not the case with any of the fourteen dimensions. To identify potential challenging dimensions we selected those dimensions for which at least one indicator scores more than 5% strongly disagree on the validity and reliability items and is in the bottom fi ve of the overall feasibility ranking. Using these criteria, there are two ‘challenging’ dimensions: dimension 4, ‘Involvement in live long learning’ and dimension 6 ‘innovation intensiveness’. If we use the validity and feasibility criteria only one more dimension emerges as being ‘challenging’: ‘regional engagement’. If we use the validity and reliability criteria there are four ‘challenging’ dimensions: ‘program orientation’, ‘involvement in life long learning’, ‘research intensiveness’, and ‘innovation intensiveness’. MAPPING DIVERSITY If we use the feasibility and reliability criteria again only the dimensions ‘Involvement in life long learning’ and ‘innovation intensiveness’ emerge. Clustering dimensions The scores on the relevance questions can also be used to cluster the dimensions. First we look at the scores on the question where the three most and the three least important dimensions were identifi ed. If the scores on two dimensions correlate positively it is likely (Teeuwen 2004) that whenever a respondent thinks one of the indicators is most important he thinks the other indicator is most important as well. If a pair of dimensions are negatively correlated, it is likely that whenever a respondent thinks one of the indicators as most important he thinks the other indicators is least important. There are fi ve pairs of dimensions that appear to correlate positively and seven that correlate negatively.
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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
Page 58 and 59: 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
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Page 104 and 105: Figure 37: Higher education institu
Page 106 and 107: Indicator 13b: Exhibitions 105 The
Page 110 and 111: The clustering is based on the corr
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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