EDUCATIONAL MEASUREMENT IN ITALIAN UNIVERSITIES and THE UNIVERSITY RATING EVOLUTION

1
EDUCATIONAL MEASUREMENT IN ITALIAN UNIVERSITIES
and THE UNIVERSITY RATING EVOLUTION

• by
• Raimondo Manca

2
SOME HISTORY

• In the second half of the 19 century Italy was
  unified
• There was a high rate of illitteralicy
• Big differences between the north and south
• Two big intuitions at the end of the century
• Montessoris method
• The teacher should adequate to the scholars
• Creation of universities devoted to the
  preparation of teachers for primary school
• Italian primary school was very good and the
  Montessori method was adopted in many countries

3
CRISIS OF ITALIAN SCHOOL

• Strong increase of university students in
  seventies
• Many people became University professors without
  the quality
• The school teachers were paid less
• Teaching was considered a second best
• More and more students that are not well prepared
  arrive at university
• A vicious circle was created

4
ACTUAL SITUATION

• The Faculties that prepared primary school
  teachers were cancelled and were transformed in
  something more general (Educational Sciences)
• There are 36 faculties of Educational Sciences
• 16 statistics or psicometry professors (associate
  or full)
• 9 assistant professors
• Educational measurement is not yet well
  established in Italy

5
COUNTRIES OF FIRST 100 UNIVERSITIES
Criteria Indicator Code Weight
Quality of Education Alumni of an institution winning Nobel Prizes and Fields Medals Alumni 10
Quality of Faculty Staff of an institution winning Nobel Prizes and Fields Medals Award 20
Quality of Faculty Highly cited researchers in 21 broad subject categories HiCi 20
Research Output Papers published in Nature and Science NS 20
Research Output Papers indexed in Science Citation Index-expanded and Social Science Citation Index PUB 20
Per Capita Performance Per capita academic performance of an institution PCP 10
Total 100
6
FIRST 20 WORLD UNIVERSITY
World Rank Institution Region Regional Rank National Rank
1 Harvard University Americas 1 1
2 University of California, Berkeley Americas 2 2
3 Stanford University Americas 3 3
4 Massachusetts Institute of Technology (MIT) Americas 4 4
5 University of Cambridge Europe 1 1
6 California Institute of Technology Americas 5 5
7 Princeton University Americas 6 6
8 Columbia University Americas 7 7
9 University of Chicago Americas 8 8
10 University of Oxford Europe 2 2
11 Yale University Americas 9 9
12 Cornell University Americas 10 10
13 University of California, Los Angeles Americas 11 11
14 University of California, San Diego Americas 12 12
15 University of Pennsylvania Americas 13 13
16 University of Washington Americas 14 14
17 University of Wisconsin - Madison Americas 15 15
18 The Johns Hopkins University Americas 16 16
18 University of California, San Francisco Americas 16 17
20 The University of Tokyo Asia/Pacific 1 1
7
UNIVERSITY RATING TIME EVOLUTION I

• Hypotheses
• Homogeneity
• Semi-Markov process
• Discrete time (DTHSMP)
• Steps
• State subdivision
• Embedded Markov Chain
• Waiting time distribution function
• Model application
• Results

8
STATE SUBDIVISION

• State set
• State 1 1-20
• State 2 21-40
• State 3 41-70
• State 4 71-100
• State 5 101-150
• State 6 151-200
• State 7 201-300
• State 8 301-400
• State 9 401-500
• State 10 No Rating

9
INPUT CONSTRUCTION

• Embedded Markov Chain construction
• Number of transitions from the state i to
  the state j
• Number of transition from the state i
• Probability to go from state i
  to state j
• Waiting time distribution function
• number of transition from i to j
  within a time t
• probability to have a
  transition in a time t

10
HSMP 1
11
HSMP 2
12
CONCLUSIONS

• Universities
• Private universities
• Countries
• Data collection for the first 6000 world
  universities
• Construction of input data