
An Application of Item Response Theory to Language Testing
Inn-Chull Choi(Author)
Peter Lang Verlag
1st Edition
Will be published approx. on 1. August 1992
Book
Paperback/Softback
XII, 196 pages
978-0-8204-1573-4 (ISBN)
Description
This book explores the appropriateness of Item Response Theory (IRT) in language testing. It investigates the dimensionality of the reading tests of the Cambridge First Certificate of English Test (FCE) and the Test of English as a Foreign Language (TOEFL), and the relative fit of 1, 2, 3 parameter IRT models in which the Rasch model is closely examined. Finding that the Rasch model fails to provide an adequate fit for the data, the study recommends that its predominant use in language testing be re-evaluated. Moreover, the 2 and 3 parameter models fit the data much better than the Rasch model. Finally, it shows that moderate departures from unidimensionality do not necessarily lead to an unacceptable model fit, nor does the use of IRT in test development guarantee that the unidimensionality assumption will be satisfied.
More details
Series
Edition
1. Auflage
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Edition type
New edition
Dimensions
Height: 230 mm
Width: 155 mm
Thickness: 12 mm
Weight
323 gr
ISBN-13
978-0-8204-1573-4 (9780820415734)
Schweitzer Classification
Person
The Author: Inn-Chull Choi earned a Bachelor of Engineering in industrial engineering at Korea University, Seoul, Korea. He earned a Master of Arts in TESL at the Division of English as a Second Language of the University of Illinois at Urbana-Champaign. He majored in language testing during his doctoral study in SLATE (Second Language Acquisition & Teacher Education) in the Department of Educational Psychology at the same institution. He is currently a lecturer at Korea University and an editor of the College English Teachers Association of Korea, and a member of Teachers of English to Speakers of Other Languages and of the National Council on Measurement in Education. His areas of research interest include language testing and computer assisted language learning.
Content
Contents: The model-data fit studies investigate the relative model fit of 1, 2, and 3 parameter models in language testing, and the effects of departures from unidimensionality on the application of IRT in language testing.