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ERIC Number: ED419008
Record Type: RIE
Publication Date: 1997
Pages: 36
Abstractor: N/A
Reference Count: N/A
Applications of Bayesian Decision Theory to Sequential Mastery Testing.
Vos, Hans J.
The purpose of this paper is to formulate optimal sequential rules for mastery tests. The framework for this approach is derived from empirical Bayesian decision theory. Both a threshold and linear loss structure are considered. The binomial probability distribution is adopted as the psychometric model involved. Conditions sufficient for sequentially setting optimal cutting scores are presented. Optimal sequential rules will be derived for the case of a beta distribution representing prior true level functioning. An empirical example of sequential mastery testing for concept-learning in medicine concludes the paper. (Contains 6 tables and 51 references.) (SLD)
Faculty of Educational Science and Technology, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands.
Publication Type: Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: Twente Univ., Enschede (Netherlands). Faculty of Educational Science and Technology.
Identifiers: Decision Theory; Sequential Testing