First Advisor

George G. Lendaris

Date of Publication

1-1-1983

Document Type

Dissertation

Degree Name

Doctor of Philosophy (Ph.D.) in Systems Science

Department

Systems Science

Language

English

Subjects

System design, Educational equalization -- United States, Decision making -- Data processing

DOI

10.15760/etd.795

Physical Description

3, vi, 175 leaves

Abstract

This dissertation presented research by the author in the development of a computer Decision Support System (DSS) for assisting in providing equal educational opportunity in a public school district. The research process consisted of five major phases: (1) The support of a local school district was obtained, and, with the assistance of the superintendent, a task group of concerned administrators was assembled to assist in defining the needs and goals for the DSS. (2) A list of key variables was developed for inclusion in the support system. Data were gathered and stored for a preliminary version of the DSS. (3) A thorough literature review was undertaken in order to reach an understanding of the concepts involved in Equality of Educational Opportunity (EEO) sufficient to provide a model to be included in the DSS. The literature review led to the development of four conceptual (subjective) EEO models. (4) Analytical techniques were undertaken to determine which model, if any, best represented reality (as defined by the data gathered in Phase 2.) The analytical techniques used were: correlation analysis, subgroup analysis, graphic analysis, and phenomena explanation. The results showed that one model, identified as the EEO Achievement Aspects Subjective Model, best fit the data examined. (5) The model was incorporated into a DSS in such a way that a single value, termed an EEO Accountability Index, was calculated for a given set of data. The potential uses of such an index and of such a DSS were then explained. The expected use of the DSS is in providing analyses based on a statistically-derived model of reality. The process of building the statistically-derived model is expected to add new insights into the concepts of EEO. Accordingly, this research is anticipated to be of particular use to (1) information specialists, (2) school district board members, superintendents, and decisionmakers, and (3) other academicians interested in developing a better understanding of the concepts of EEO and the implications those concepts have for educational decisionmaking.

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Comments

Portland State University. Systems Science Ph. D. Program.

Persistent Identifier

http://archives.pdx.edu/ds/psu/4660

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