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Gilman, David A. – Planning and Changing, 1988
This article discusses the uses of production function models and describes the role of inferential statistics for making predictions in school finance. Specifically, the analysis evaluates types, suggests uses, explains the advantages and disadvantages, and lists the statistical complexities of production functions. (JAM)
Descriptors: Educational Finance, Elementary Secondary Education, Prediction, Predictive Measurement
Morrison, James L. – 1990
The focus of the session summarized in this paper was on how postsecondary educational institutions can better anticipate the future of higher education by using the "alternative futures approach to planning" model. The alternative futures model processes the best available information obtainable so that plausible alternative futures in…
Descriptors: Decision Making, Educational Planning, Educational Trends, Futures (of Society)
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Lam, Y. L. Jack – Journal of Educational Administration, 1984
Stepwise discriminant analysis coupled with logit regression analysis of freshmen data from Brandon University (Manitoba) indicated that six tested variables drawn from research on university dropouts were useful in predicting attrition: student status, residence, financial sources, distance from home town, goal fulfillment, and satisfaction with…
Descriptors: College Attendance, College Freshmen, Dropout Research, Higher Education
Lieshoff, Sylvia – 1993
This paper examines the use of environmental scanning for institutions of higher education to achieve the following objectives: (1) provide early warning of changes that will have an impact on education; (2) define potential threats and opportunities to the institution or department; (3) promote a future orientation in faculty; and (4) alert…
Descriptors: College Planning, Data Analysis, Data Collection, Environmental Scanning