Computerized Adaptive Testing for Classifying Examinees Into Three Categories  

Oleh:

Straetmans, G.J.J.M. ; Eggen, T. J. H. M.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Educational and Psychological Measurement vol. 60 no. 5 (2000), page 713-734.
Topik: COMPUTERIZED; psychology; psychological tests; computers; algorithms; classification
Fulltext: 713.pdf (155.1KB)

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: EE30.6 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

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 differnt 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 are 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 tesing 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.

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