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

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Case Study: University of Strathclyde 51 Introduction The purpose of the case study was: • to assess the potential use of a European classifi cation; • to fi nd out to what extent the dimensions and indicators are seen to be relevant and feasible; • to fi nd out to what extent the necessary data would be available or could be produced. General issues The University is an old Scottish university, having its roots in the technological fi elds. During the last half century, the scope of the university was expanded into a university with fi ve faculties (Education; Engineering; Law, arts & social science; Science; and a Business school). The university has a focus on entrepreneurship and on ‘useful learning’. The potential role of a European Classifi cation of Institutions of Higher Education was discussed in the context of the use and abuse of international league tables. These league tables, especially the Shanghai one are very much focused on the American model of a research university. In many Asian higher education systems (the systems where potentially most international students come from) this model is seen as the dominant and best model. A European classifi cation of higher education institutions, if it is robust and trustworthy, may serve to challenge the dominance of the American model and to put the European model on the international stage. The main use of a classifi cation would be to contribute to the identifi cation of robust benchmarks. Nowadays, the benchmarks are identifi ed based on potentially outdated views and perceptions. Specialised higher education institutions, like the University of Strathclyde, have a problem identifying those. The use of league tables is not very helpful in this respect. The main impact the league tables have is on the recruitment of international (undergraduate) students and on international MBA students. A robust classifi cation would help to overcome the problems of the league tables But the issue is not only an international one: it also has a national/ UK dimension. The bulk of the competitors/ potential benchmark institutions are located within the UK. The international student market is becoming more and more important, but it is also essential for the internal market to have a robust instrument to identify the benchmark institutions. The university is developing a new strategy in which the performance of the departments and academic services are under scrutiny. The perception that the University’s position was deteriorating was partly fed by the information from the national rankings. The use of a classifi cation as a benchmark fi nding tool would improve the institutions capacity to better position itself and act on that information. Another area where a trustworthy classifi cation would be very welcome is the international recruitment of students. The university’s experience is that applications from international students, and more specifi cally Asian students are very much infl uenced by (changes in) the position of the university in international rankings (like the Shanghai and Times Higher rankings). The use of a classifi cation may play a role in fundraising but here, the impact of a classifi cation is expected to be limited. The bulk of fundraising activities is related to specifi c projects and has a predominantly regional or local focus. MAPPING DIVERSITY
Dimensions and Indicators 52 During six different sessions the dimensions and indicators were discussed regarding: • education; • research; • international orientation; • institutional aspects. General practical aspects The university has to comply with very detailed data-reporting requirements from both HESA and the Scottish HE funding council. Most of the data-elements of the classifi cation questionnaire are covered in those data-reporting activities. However, the exact defi nitions and breakdowns requested in the draft-classifi cation questionnaire are not always fully compatible with the defi nitions and breakdowns used in the national data-reporting activities. The administrative burden for the university would be reduced and the response rate might be raised if the questionnaire would follow the national data reporting as closely as possible. In addition, this may lead to a better reliability of data since the national data-reporting is extensively validated. Reworking the data increases the risk of errors and different interpretations. . The suggestions developed here were to check for national data repositories and to add a question in the questionnaire on whether the data requested are already reported to a national data agency (and if so to what agency). In the following texts the various remarks and conclusions are presented per indicator per dimension. Dimension 1: types of degrees offered Indicator 1.1.1.: highest degree offered • a good and important indicator; • data are easy to provide. Indicator 1.1.2.: number of qualifi cations granted • data are easy to provide. Dimension 2: range of subjects offered MAPPING DIVERSITY Indicator 1.2.1.: number of subjects offered • It was suggested to use national conversion tables for the indicator on subjects. University staff do not use the ISCED categories. The data reporting to the international organizations is done by national agencies (Ministry or central statistical offi ce). These agencies use national conversion tables to convert the national subject categories into the ISCED categories. If such conversion tables could be presented (in an extra info-fi eld) institutions may be able to complete the question. Dimension 3: orientation of degrees Indicator 1.3.1.: number of programmes offered for licensed professions • data may be diffi cult to compare.
Page 1 and 2: Mapping Diversity Developing a Euro
Page 4 and 5: Mapping Diversity Contents Developi
Page 6 and 7: The research project team consisted
Page 8 and 9: 2. Building a European Classificati
Page 10 and 11: with university rankings, rankings
Page 12 and 13: Classifi cations use the principles
Page 14 and 15: Table 1: Draft and classifi cation
Page 16 and 17: • Fontys Hogescholen, the Netherl
Page 18 and 19: 3.1.2 Response to the survey 67 Res
Page 20 and 21: The question ‘this dimension is e
Page 22 and 23: 4. Conclusions 21 In this chapter w
Page 24 and 25: of information on non-degree offeri
Page 26 and 27: 4.3 Reduction of the number of dime
Page 28 and 29: Dimension Indicator new and suggest
Page 30 and 31: 5. Operational implementation Part
Page 32 and 33: 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 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 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 104 and 105:
Figure 37: Higher education institu
Page 106 and 107:
Indicator 13b: Exhibitions 105 The
Page 108 and 109:
Figure 44: Higher education institu
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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