Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Click here for FREE ACCESS to this landmark database

Click here for more information on Research and Evaluation in Education and Psychology, 3e

Sign In to gain access to subscriptions and/or personal tools.
Educational and Psychological Measurement
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Eggen, T.J.H.M.
Right arrow Articles by Straetmans, G.J.J.M.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

Computerized Adaptive Testing for Classifying Examinees into three Categories

T.J.H.M. Eggen

G.J.J.M. Straetmans

Cito, The Netherlands

The objective of this study was to explore the possibilities for using computerized adaptive testing in situations in which examinees are to be classified into one of three categories. Testing algorithms with two different statistical computation procedures are described and evaluated. The first computation procedure is based on statistical testing and the other on statistical estimation. Item selection methods based on maximum information (MI) considering content and exposure control are considered. The measurement quality of the proposed testing algorithms is reported. The results of the study are that a reduction of at least 22% in the mean number of items can be expected in a computerized adaptive test (CAT) compared to an existing paper-and-pencil placement test. Furthermore, statistical testing is a promising alternative to statistical estimation. Finally, it is concluded that imposing constraints on the MI selection strategy does not negatively affect the quality of the testing algorithms.

Educational and Psychological Measurement, Vol. 60, No. 5, 713-734 (2000)
DOI: 10.1177/00131640021970862
Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?


This article has been cited by other articles:


Home page
 Educational and Psychological MeasurementHome page
N. A. Thompson
Item Selection in Computerized Classification Testing
Educational and Psychological Measurement, October 1, 2009; 69(5): 778 - 793.
[Abstract] [PDF]

Home page
 Educational and Psychological MeasurementHome page
A. Weissman
Mutual Information Item Selection in Adaptive Classification Testing
Educational and Psychological Measurement, February 1, 2007; 67(1): 41 - 58.
[Abstract] [PDF]

Home page
 Applied Psychological MeasurementHome page
T. J. H. M. Eggen and A. J. Verschoor
Optimal Testing With Easy or Difficult Items in Computerized Adaptive Testing
Applied Psychological Measurement, September 1, 2006; 30(5): 379 - 393.
[Abstract] [PDF]

Home page
 ANN INTERN MEDHome page
C. A. McHorney
Ten Recommendations for Advancing Patient-Centered Outcomes Measurement for Older Persons
Ann Intern Med, September 2, 2003; 139(5_Part_2): 403 - 409.
[Abstract] [Full Text] [PDF]