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, NY : 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 |
---|---|---|---|---|---|---|---|
Books | CR Julien-Couture RC (Teaching) New Materials Shelf | Non-fiction | TST MCN (Browse shelf) | 1 | Available | A029114 |
Includes bibliographical references and index.
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
"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)
There are no comments for this item.