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Simultaneous Optimization of Decisions Using a Linear Utility Function. Research Report 88-15 [microform] / Hans J. Vos
Bib ID 5507117
Format BookBook, MicroformMicroform, OnlineOnline
Author
Vos, Hans J
 
Online Versions
Description [Washington, D.C.] : Distributed by ERIC Clearinghouse, 1988 
56 p. 
Summary

The purpose of this paper is to simultaneously optimize decision rules for combinations of elementary decisions. As a result of this approach, rules are found that make more efficient use of the data than does optimizing those decisions separately. The framework for the approach is derived from empirical Bayesian theory. To illustrate the approach, two elementary decisions--selection and mastery decisions--are combined into a simple decision network. A linear utility structure is assumed. Decision rules are derived both for quota-free and quota-restricted selection-mastery decisions for several subpopulations. An empirical example of instructional decision making in an individual study system concludes the paper. The example involves 43 freshmen medical students (27 were disadvantaged and 16 were advantaged with respect to elementary medical knowledge). Both the selection and mastery tests consisted of 17 free-response items on elementary medical knowledge with test scores ranging from 0 to 100. The treatment consisted of a computer-aided instructional program. Three data tables and three figures are provided. (Author/TJH)

Notes

Availability: Bibliotheek, Department of Education, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands.

ERIC Note: Portions of this paper were presented at the European Meeting of the Psychometric Society (Enschede, Netherlands, 1987).

May also be available online. Address as at 14/8/18: https://eric.ed.gov/

Reproduction Microfiche. [Washington D.C.]: ERIC Clearinghouse microfiches : positive. 
Subjects Bayesian Statistics.  |  College Freshmen.  |  Computer Assisted Instruction.  |  Decision Making.  |  Expert Systems.  |  Higher Education.  |  Linear Programing.  |  Mastery Tests.  |  Medical Students.  |  Science Tests.  |  Selection.  |  Optimization Utility Function  |  Decision Rules Empirical Bayes Estimation Free Response Test Items Medical Knowledge Tests
Form/genre Reports, Evaluative.  |  Speeches/Meeting Papers.
Other authors/contributors Twente Univ., Enschede (Netherlands). Dept. of Education
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