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Measuring the Quality of PostSecondary Education: Concepts, Current Practices, and a Strategic Plan

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Title: Measuring the Quality of PostSecondary Education: Concepts, Current Practices, and a Strategic Plan


1
Measuring the Quality of Post-Secondary
Education Concepts, CurrentPractices, and a
Strategic Plan
  • Ross Finnie
  • Queens University
  • Alex Usher
  • EPI

2
I. Introduction
  • What is quality?
  • Accountability agendas
  • Goals (and outline) of the paper
  • examine current practices in Canada and elsewhere
  • propose a framework and measurement principles
  • short-run strategies
  • longer-run strategies

3
II. Global Tour
  • Four general approaches to quality
    measurement/assurance
  • Minimum Standards Approach
  • Rankings/Indicators Approach
  • Learning Outcomes Approach
  • Continuous Improvement Approach

4
1. Minimum Standards
  • Largely qualitative in nature
  • Begins with self-audit
  • External confirmation
  • Good management tool, very collegial
  • Poor transparency/little use to others

5
2. Rankings/Indicators
  • Mostly Quantitative (e.g., MacLeans)
  • Rankings tend to focus on inputs
  • Indicators focus on outputs
  • Easy to understand
  • Otherwise useful, but incomplete
  • Also less useful as management tool

6
3. Learning Outcomes
  • Try to measure quality of the learning
    environment
  • Usually at the institution level
  • Inside-the-box
  • Based on what we think matters

7
4. Continuous Improvement
  • Quality as process, not specific outcomes
  • ISO 9000 analogy
  • Quality monitoring/improvement processes
  • Government can oversee, help, monitor
  • Permits institutional sensitivity
  • No resulting measures for others

8
III. Conceptual Framework
  • Simple Model
  • Beginning Characteristics
  • Inputs
  • Learning Outcomes
  • Final Outcomes

9
The Model
Learning Outcomes (Zi)
Final Outcomes (Yi)
Inputs (Xi)
Beginning Chars. (Bi)
?i
?i
? i
?i
Other Factors (Fi)
10
1. Beginning Characteristics
  • Controls for ability, skills, etc.
  • Intelligence (High school marks and other
    measures)
  • Motivation and other personal characteristics
  • Anything else that affects learning or later
    outcomes
  • Proxies and related demographic characteristics
  • Age
  • Gender
  • Family income
  • Ethnicity
  • Etc.

11
2. Inputs
  • Financial and material Inputs such as
  • /student
  • Prof-student ratio
  • Library books, IT resources
  • Etc. (MacLeans-type stuff and more)
  • Organization/Use of inputs (pedagogies) such
    as
  • Student/staff contact
  • Frequency of small group discussions
  • Types of exams
  • Other aspects of the student experience

12
3. Learning Outcomes
  • Skills
  • Generic work skills
  • Specific work skills
  • Character development (motivation, etc.)
  • Anything else that education affects, that
    matters
  • (Possibly) Efficiency measures
  • Graduation rate
  • Time-to-completion
  • Etc.

13
4. Final Outcomes
  • Employment, Income, job satisfaction, etc.
  • Civic engagement
  • Self-actualisation
  • Happiness
  • Anything else we think is important

14
Applying the Framework
  • Estimate the model
  • Identify inputs that matter
  • Good learning/final outcomes
  • Effective inputs imply quality
  • Can monitor or score institutions, sytems
  • Use in other ways

15
The Role of Institutions in the Estimation
  • Large samples per institution not required
  • Institutions are just specific bundles of
    inputs
  • In a well-specified model, with all inputs
    perfectly identified and measured, pure
    institutional effects should be zero

16
Alternative Approach FocusingDirectly on
Institutions
  • Similar model/estimation framework
  • But focus on institutions
  • Identify institutional effects directly
  • Although they remain a black box
  • But can be correlated with inputs

17
IV. Short- and Long-Run Options
  • Short-run
  • Continuous Improvement
  • Measurement with available data
  • Long-run
  • Measurement with new data

18
Short-Term Measures (1) Self-Monitoring
  • Move to Quality Self-Monitoring
  • Institutions self-measure their quality
  • Periodically publish findings
  • Develop procedures to improve quality
  • Governments role light touch

19
Short-Term Measures (2) The Model
  • Use existing data
  • Develop more data where easy/feasible
  • Do modelling using mix of datasets
  • Build results into a full story

20
Long-Term Measures
  • Develop better data
  • Build on existing resources
  • Link, adapt, coordinate
  • YITS, NGS, ESIS, NSSE, etc.
  • Combine interests, resources
  • Statscan for expertise, existing databases
  • Other partners including institutions
  • Combine resources, interests, etc.

21
V. Conclusion
  • Who knows what quality is?
  • But here is a framework to get started
  • Short- and long-run options
  • Start now so we get there
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