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

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Data from existing sources The question whether the information was taken from existing sources and if so, from what source, serves a double purpose. First it is assumed that the use of existing sources has a positive infl uence on the feasibility of collecting and reporting data. 83 For eight indicators, more than 75% of the responding higher education institutions reported that they used existing sources. For 10 of the 31 7 indicators, less than 50% of the responding higher education institutions reported the use of existing sources. Table 9: Percentage of the responding higher education institutions using existing sources, by indicator More than 75% Less than 50% 1a 4a 1b 6c 2a 6d 7b 10a 9a 10c 9b 13a 11a 13b 11b 14a 14b 14c 14d Again there is a considerable overlap between this table and the previous two tables categorising the indicators as feasible and less feasible. 7 for indicator 5b, no questions were asked. MAPPING DIVERSITY
84 Figure 8: Number of responding higher education institutions using existing sources, by indicator 14d 14c 14b 14a 13b 13a 11b 11a 10c 10b 10a 9b 9a 8a 7d 7e 7b 7a 6d 6c 6b 6a 5 4a 3b 3a 2a 1b 1a 0 10 20 30 40 50 60 70 MAPPING DIVERSITY The second purpose of the question on the sources used refers to the potential use of national and international data sources. In an early stage of the project, national and international databases were analysed to fi nd out whether data from these existing sources could be used to fi ll the database underlying the classifi cation. The result of that analysis was rather negative: there are only reliable data on a few elements in international data sources, and the use of national sources will be very time consuming. The latter is caused by the many questions to be answered at the institutional level, legal constraints, methodological constraints and the differences in scope. The question of what existing source was used gives us the opportunity to fi nd out what existing sources the higher education institution uses and/or trusts. It is seen as a fi rst step in the quest for usable national sources, in order to reduce the survey load for higher education institutions. Only a few responding higher education institutions reported the use of a specifi c agency as a data source. For indicator 1b eight agencies were reported, for 1a and 9a six and for 2a, 7a and 11a fi ve. The most commonly mentioned agencies are ministries and statistical agencies. In some countries, higher education (funding) councils were mentioned.
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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
Page 34 and 35: Government model In this model gove
Page 36 and 37: also underline the need for coopera
Page 38 and 39: Bailey, K. D. (1994) Typologies and
Page 40 and 41: Annex I: Exploratory analysis of ex
Page 42 and 43: EU The Rebaspinoff projects (part o
Page 44 and 45: World of Learning. If a further bre
Page 46 and 47: Annex II: The case studies 45 Case
Page 48 and 49: Indicator 1.3.1.: number of program
Page 50 and 51: Indicator 3.1.2a.: number of Europe
Page 52 and 53: Case Study: University of Strathcly
Page 54 and 55: Indicator 1.3.2.: number of program
Page 56 and 57: 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 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 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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