ERIC Number: ED083317
Record Type: Non-Journal
Publication Date: 1973-Sep
Reference Count: N/A
Implementation of a Bayesian System for Decision Analysis in a Program of Individually Prescribed Instruction.
Ferguson, Richard L; Novich, Melvin R.
The decision process required for Individually Prescribed Instruction (IPI), an adaptive instructional program developed at the University of Pittsburgh, is described. In IPI, short tests are used to determine the level of proficiency of each student in precisely defined learning objectives. The output of these tests is used to guide instructional planning for individual students. The nature and effect of errors in proficiency decisions are described and a procedure for reducing the probability of such errors is proposed. The plan calls for a Bayesian procedure which would incorporate prior information on the instructional program, for example the distribution of the percentage of items answered correctly by students. Such a procedure would permit inferences about the true level of functioning of each student. The final section of the paper proposes two methods for implementing these procedures in an ongoing IPI program: one approach calls for the integration of the procedure as a part of a computer-based instructional management system, whereas the second approach describes how the procedure can be made tractable in a typical, non-automated IPI classroom. (Author)
Descriptors: Bayesian Statistics, Computer Assisted Instruction, Decision Making, Individualized Instruction, Mathematics Instruction
Publications Division, The American College Testing Program, P. O. Box 168, Iowa City, Iowa 52240 ($1.00)
Publication Type: N/A
Education Level: N/A
Sponsor: Office of Education (DHEW), Washington, DC.
Authoring Institution: American Coll. Testing Program, Iowa City, IA. Research and Development Div.