Simultaneous optimization of decisions using a linear utility function

Hendrik J. Vos

Research output: Book/ReportReportOther research output

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Abstract

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.
Original languageUndefined
Place of PublicationEnschede, the Netherlands
PublisherUniversity of Twente, Faculty Educational Science and Technology
Number of pages56
Publication statusPublished - 1988

Publication series

NameOMD research report
PublisherUniversity of Twente, Faculty of Educational Science and Technology
No.88-15

Keywords

  • Linear Programing
  • Higher Education
  • Selection
  • Science Tests
  • Decision Making
  • College Freshmen
  • IR-104180
  • Expert Systems
  • Mastery Tests
  • Bayesian Statistics
  • Computer Assisted Instruction
  • Medical Students

Cite this

Vos, H. J. (1988). Simultaneous optimization of decisions using a linear utility function. (OMD research report; No. 88-15). Enschede, the Netherlands: University of Twente, Faculty Educational Science and Technology.
Vos, Hendrik J. / Simultaneous optimization of decisions using a linear utility function. Enschede, the Netherlands : University of Twente, Faculty Educational Science and Technology, 1988. 56 p. (OMD research report; 88-15).
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number = "88-15",

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Vos, HJ 1988, Simultaneous optimization of decisions using a linear utility function. OMD research report, no. 88-15, University of Twente, Faculty Educational Science and Technology, Enschede, the Netherlands.

Simultaneous optimization of decisions using a linear utility function. / Vos, Hendrik J.

Enschede, the Netherlands : University of Twente, Faculty Educational Science and Technology, 1988. 56 p. (OMD research report; No. 88-15).

Research output: Book/ReportReportOther research output

TY - BOOK

T1 - Simultaneous optimization of decisions using a linear utility function

AU - Vos, Hendrik J.

N1 - Portions of this paper were presented at the European Meeting of the Psychometric Society (Enschede, Netherlands, 1987)

PY - 1988

Y1 - 1988

N2 - 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.

AB - 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.

KW - Linear Programing

KW - Higher Education

KW - Selection

KW - Science Tests

KW - Decision Making

KW - College Freshmen

KW - IR-104180

KW - Expert Systems

KW - Mastery Tests

KW - Bayesian Statistics

KW - Computer Assisted Instruction

KW - Medical Students

M3 - Report

T3 - OMD research report

BT - Simultaneous optimization of decisions using a linear utility function

PB - University of Twente, Faculty Educational Science and Technology

CY - Enschede, the Netherlands

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Vos HJ. Simultaneous optimization of decisions using a linear utility function. Enschede, the Netherlands: University of Twente, Faculty Educational Science and Technology, 1988. 56 p. (OMD research report; 88-15).