Building a European Classification of Higher Education Institutions

1. Workshop ‘New challenges in higher education research and policy in Europe and in CR’, Prague 27-28 November 2008 Building a European Classification of Higher Education Institutions Frans Kaiser

2. European Classification of HEIs • Rationale • The project so far • CEIHE I; breaking the ground • CEIHE II; the survey • The next steps; U-Map

3. Functions of European Classification • Profiles European higher education at a global scale • Provides basis for effective policies and investment strategies • Allows institutional development strategies • Facilities benchmarking, networking and partnerships • Is a prerequisite for rankings

4. The Classification Project • stakeholders approach: exploration and discussions • first phase: basic design principles & first set of dimensions and indicators • second phase: adapted set of dimensions and indicators • third phase: reduced set of dimensions; first version of on-line tool

5. Design principles • inclusive for all European HEIs 1st phase • a posteriori information • multi-dimensional • non-hierarchical • focus on ‘objective’ data

6. Design principles (2) • non-prescriptive 1st phase • flexible • parsimonious regarding extra data-needs • related to European Register of Quality Assurance Agencies

7. First Version of a European Classification 2nd phase Methods used: • interaction with stakeholders • analysis of existing data sources • in-depth case studies • survey, to access relevance, validity, reliability and feasibility of dimensions and indicators

8. Dimensions and indicators 2nd phase Education Research and innovation Cultural and regional engagement International orientation Size and setting

9. Dimensions and indicators • Highest degree offered (degree level) • degrees/diplomas granted per level • Subject mix • Orientation of programmes • number of programmes offered for licensed professions • Involvement in LLL • number of mature (> 30 years) students as % of total enrollment 2nd phase Education

10. Dimensions and indicators • Research intensiveness • peer reviewed publications per academic staff • scientometric ‘crown’ indicator • Innovation intensiveness • Financial volume privately funded research as % of total financial volume • Number of start-ups • Number of filed patents • Income from licensing 2nd phase Research and innovation

11. Dimensions and indicators • Teaching and staff • international degree seeking students as % of total number of students • incoming international/European exchange students as % of total number of students • outgoing international/European exchange students as % of total number of students • joint international programmes as % of total number of programmes offered • programmes offered abroad • fte international academic staff as % of total academic staff 2nd phase International orientation

12. Dimensions and indicators 2nd phase • Research • Financial turnover in EU research programmes as % of total financial research volume International orientation

13. Dimensions and indicators • Size • Total number of students (per degree level) • Total number of fte’s academic staff • Total financial turn over per year • Mode of delivery • distance learning programmes as % • Part-time programmes as % • Part-time students as % • Public/private character • Income from government sources as % of total income • Legal status size and settings

14. Dimensions and indicators 2nd phase Cultural and regional engagement • Cultural engagement • Number of concerts • Number of exhibitions • Regional engagement • Graduates in the region • Turnover in EU structural funds • Extra-curricula courses for region • Importance of regional income

15. Phase II: the survey 2nd phase

16. Setup of the Survey 2nd phase • The questionnaires • The sample • Sampling methods • Stratification criteria • The strata in the response

17. The Questionnaires 2nd phase • Based on CEIHE I • Two separate questionnaires • on-line

18. The Questionnaire 2nd phase

19. The Sample 2nd phase • Sampling methods • Sample size and criteria • Age, size, region • Sample and response

20. The Sample 2nd phase • Age of institution

21. The Sample 2nd phase • Size (enrolment)

22. The Sample 2nd phase • Region (UN definitions)

23. Assessment of the dimensions 2nd phase ‘This dimension is essential for the profile of our institution’

24. ‘This dimension is essential for the profile of our institution’ 2nd phase

25. Assessment of the Indicators 2nd phase • Validity • Reliability • Feasibility

26. Validity; not problematic 2nd phase

27. Validity; some doubts 2nd phase

28. Validity; potentially challenging 2nd phase

29. Reliability; not problematic 2nd phase

30. Reliability; some doubts 2nd phase

31. Feasibility 2nd phase • Time on collecting information • ‘Easy to collect’ • Existing sources • Number of valid cases • Overall score

32. Feasibility 2nd phase

33. What are the data used for? 2nd phase • Calculate indicators • Assess feasibility • Identify and stress conceptual and definition issues • Rethinking the role of indicators in institutional strategies

34. Next steps • reduce number of dimensions/classes 3rd phase

35. Next steps 3rd phase Classification is about grouping entities as a way to reduce complexity • A limited number of dimensions • A limited number of classes per dimension and per indicator

36. Next steps 3rd phase Reduce the number of dimensions • Using conceptual considerations • Using empirical considerations

37. Next steps 3rd phase Reduce the number of dimensions Reduce the number of classes per dimension

38. % international academic staff 3rd phase

39. % tuition fee income 3rd phase

40. Size; enrolment 3rd phase

41. Licensing income (as % of total income) 3rd phase

42. Size; academic staff 3rd phase

43. Next steps • reduce number of dimensions/classes 3rd phase • develop on-line tool

44. Future use of the Classification 3rd phase • providing information to stakeholders and clients about characteristics of a higher education institution Examples

45. Future use of the Classification 3rd phase Examples

46. Future use of the Classification 3rd phase • Providing assistance to institutional strategies and inter-institutional partnerships, benchmarking, and networking Examples

47. Future use of the Classification 3rd phase Examples

48. Next steps • reduce number of dimensions/classes 3rd phase • develop on-line tool • rethink indicators • communication process with stakeholders and preview • ‘communities’ for special dimensions; www.u-map.eu • institutionalisation and ownership

49. A European Classification of Higher Education Institutions www.u-map.eu Thank you for your attention! This project has been funded with support from the European Commission. This presentation content reflects the views only of the author. The Commission cannot be held responsible for any use which may be made of the information contained therein.