Fairness, Justice, and Language Assessment : The Role of Measurement / Tim McNamara, Ute Knoch, and Jason Fan.
By: McNamara, Tim (Timothy Francis).
Contributor(s): Knoch, Ute | Fan, Jason.
Series: Oxford Applied Linguistics. Publisher: New York : Oxford University Press, 2019Description: 215 p. : ill. ; 24 cm.ISBN: 9780194017084 (pbk); 0194017087 (pbk).Subject(s): Educational tests and measurement | Knowledge assessment | Language -- TestingDDC classification: 418.0076 Online resources: Publisher's Website.Item type | Current location | Collection | Call number | Copy number | Status | Date due | Barcode |
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CR Julien-Couture RC (Teaching) New Materials Shelf | Non-fiction | TST MCN (Browse shelf) | 1 | Available | A029114 |
Includes bibliographical references and index.
"This book has two goals, each related to the validity of language assessment. The first goal is to explore the difference between fairness and justice in language assessment. The authors distinguish internal and external dimensions of the equitable and just treatment of individuals taking language tests which are used as gatekeeping devices to determine access to education and employment, immigrant status, citizenship, and other rights. The second goal is to show how the extent of test fairness can be demonstrated and improved using the tools of psychometrics, in particular the models collectively known as Rasch measurement." (Book Cover)
CONTENTS
1. Introduction
The quality of tests
The fairness and justice of tests: an example
Conclusion
2. Validity, justice, and fairness
Introduction
Validity: what is at stake in language tests?
The social role of language tests
Conclusion
3. The basic Rasch model
Introduction
The analysis of test data in classical test theory
Beyond raw scores: the basics of Rasch measurement
Conducting a simple Rasch analysis
A simple description of what happens during a Rasch analysis
Understanding the results of a simple Rasch analysis
Analysing multiple-choice data using the simple Rasch model
Summary
4. Beyond simple right or wrong answers: the Andrich rating scale model and the partial credit model
Introduction
Data types typically analysed
Differences between the simple Rasch model and the rating scale and partial credit models
Analysing polytomous data
Conducting an analysis using the partial credit model or the rating scale model using Winsteps
Understanding the results of a partial credit analysis
A closer look at the differences between the partial credit model and the rating scale model: when do we use which?
The rating scale model: using Rasch to analyse questionnaire data
Summary
5. Introducing raters and ratings: the many-facets Rasch model
Introduction
Understanding rater variability
Using many-facets Rasch to model rater effects
Interpreting the results of a many-facets Rasch analysis
Understanding basic many-facets Rasch analysis models
Summary
6. Investigating fairness using Rasch measurement
Introduction
Mapping the terrain
What kinds of fairness issues does Rasch-based research address?
Summary
7. Beyond the basics in Rasch measurement
Introduction
Setting up data
Identifying initial problems
Further investigations and issues
Reporting
Summary
8. Data, models, and dimensions
Introduction
The Rasch family of models
Debates over Rasch measurement
The Rasch model and other data analytic methods Summary
9. Conclusion: reconciling fairness and justice
Appendix
References
Index
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