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UNIVERSITY INSTITUTIONAL EVALUATION

UNIVERSITY INSTITUTIONAL EVALUATION. EXTERNAL EVALUATION. PROF. SAMUEL FERNÁNDEZ. University of Oviedo. Process for Assesment for the Verification of University Official Qualifications Institutional Evaluation: Model for Assesment. INDICATORS:.

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UNIVERSITY INSTITUTIONAL EVALUATION

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  1. UNIVERSITY INSTITUTIONAL EVALUATION EXTERNAL EVALUATION PROF. SAMUEL FERNÁNDEZ University of Oviedo

  2. Process for Assesment for the Verification of University Official Qualifications • Institutional Evaluation: Model for Assesment INDICATORS: • University Offer • University Demand • Human Resources • Financial Resources • Physical Resources • Process Indicators • Results Indicators

  3. PROCESS FOR THE ASSESSMENT FOR THE VERIFICATION OF UNIVERSITY OFFICIAL QUALIFICATIONS

  4. EXTERNALEVALUATION: INDICATORS OF ACHIEVEMENT

  5. UNIVERSITY OFFER

  6. Internal distribution of the supply of qualifications. CODE: OFFER 1 DENOMINATION:

  7. EXAMPLE

  8. Percentage distribution of the supply of qualifications. CODE: OFFER 2 DENOMINATION:

  9. EXAMPLE

  10. Adequacy of the study in relation to the environment. CODE: OFFER 3 DENOMINATION:

  11. EXAMPLE

  12. UNIVERSITY DEMAND

  13. Pre-register at the first option on the total supply of seats. CODE: DEMAND 1 DENOMINATION:

  14. EXAMPLE

  15. New entry in the first option on all new recruits. CODE: DEMAND 2 DENOMINATION:

  16. Suppose that the number of people who decide to study biology as a first option is 40 and the total number of students enrolled in new recruits is 89. The relationship between the percentage of registered first choice and number of places offered is: EXAMPLE (40/89) x100 = 44.94%, 49.94% of the students in Biology enrolled in first option

  17. Average access of 20% higher. CODE: DEMAND 3.1 DENOMINATION:

  18. University “X” has 10 students whose access tidy notes are: 9, 9, 8.5, 8, 7, 7, 6.5, 6, 5, 5. 20% superiorde students for the first two and thus the average access of 20% would be: EXAMPLE (9 +9) / 2 = 9, which is the average access of 20% of students at the University "X".

  19. Average access. CODE: DEMAND 3.2 DENOMINATION:

  20. (For a university and one year:) EXAMPLE University X has 10 students whose access notes are: 9, 7.5, 8.5, 8, 6, 7, 6.5, 6, 9, 5, the average access is calculated as: (9 +7.5 +8.5 +8 +6 +7 +6.5 +6 +9 +5) / 10 = 6.25, the average access of students from University X.

  21. Mobility of students betweenAutonomies. CODE: DEMAND 4 DENOMINATION:

  22. EXAMPLE The branch Health Sciences of the Autonomous Community of Madrid offer 1000 places the number of students from other regions who come to study this year in Madrid is 70. Therefore, the percentage of students from other regions who come to study in Madrid is 7%.

  23. International mobility of students. CODE: DEMAND 5 DENOMINATION:

  24. EXAMPLE The technical education branch of the CAAC squares of Madrid 1000 bid, the number of foreign students coming to study this year in Madrid is 70. Therefore, the percentage of foreign students coming to study in Madrid is7%.

  25. HUMAN RESOURCES (Academic Staff and Administrative Staff)

  26. Full-time Academic Staff. CODE: HUM_RES 1 DENOMINATION:

  27. EXAMPLE Peter III University has 1000 faculty staff (Academic Staff), of which 200 university combine dedication with another professional (non-academic staff are full-time). The indicator for this example would be calculated as: (800/1000) x100 = 80% Therefore 80% of the staff of the University Peter III is a full-time academic staff.

  28. Academic Staff  Doctors CODE: HUM_RES 2 DENOMINATION:

  29. EXAMPLE Peter III University has 1000 teachers on its staff, of whom 500 are doctors. The indicator for this example would be calculated as: (500/1000) x100 = 50% Therefore a 50% PDI Peter III of the University are doctors.

  30. Academic Staff  Officials CODE: HUM_RES 3 DENOMINATION:

  31. EXAMPLE The old University Peter I have 2500 teachers, of whom 1500 are officials; its indicator is 60% is official. In contrast, the newly established University Peter V has only 30 officials from its total of 200 teachers; indicator is 15.

  32. Administrative Staff / Academic Staff. CODE: HUM_RES 4.1 DENOMINATION:

  33. EXAMPLE The Administrative Staff of University “X” is composed of 300 individuals and 600 Academic Staff. Consequently, this indicator takes the value 0.5, which shows that the number of Academic Staff is two times higher than that of Administrative Staff. This indicator becomes more meaningful when comparing different universities.

  34. Administrative Staff / Full-time Academic Staff. CODE: HUM_RES 4.2 DENOMINATION:

  35. EXAMPLE The Administrative Staff of University “X” is composed of 300 individuals and 300 Academic Staff. Consequently, this indicator takes the value 1.

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