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Williamson, Ben – Journal of Education Policy, 2016
Educational institutions and governing practices are increasingly augmented with digital database technologies that function as new kinds of policy instruments. This article surveys and maps the landscape of digital policy instrumentation in education and provides two detailed case studies of new digital data systems. The Learning Curve is a…
Descriptors: Visualization, Synchronous Communication, Governance, Data Collection
Predicting Higher Education Outcomes and Implications for a Postsecondary Institution Ratings System
Walker, Eddie G., II – Journal of Higher Education Policy and Management, 2016
The accountability of colleges and universities is a high priority for those making policy decisions. The purpose of this study was to determine institutional characteristics predicting retention rates, graduation rates and transfer-out rates using publicly available data from the US Department of Education. Using regression analysis, it was…
Descriptors: Higher Education, Predictive Measurement, Predictive Validity, Prediction
Barrett, Jamie D.; Vessey, William B.; Griffith, Jennifer A.; Mracek, Derek; Mumford, Michael D. – Creativity Research Journal, 2014
There is little doubt that career experiences contribute to scientific achievement; however this relationship has yet to be thoroughly investigated in terms the effects on scientific creativity. In this study, a historiometric approach was used to examine 3 areas of adult career experiences common to scientific achievement. In doing so, prior…
Descriptors: Science Achievement, Prediction, Predictor Variables, Correlation
Kim, Iljoo – ProQuest LLC, 2011
The size and dynamism of the Web poses challenges for all its stakeholders, which include producers/consumers of content, and advertisers who want to place advertisements next to relevant content. A critical piece of information for the stakeholders is the demographics of the consumers who are likely to visit a given web site. However, predicting…
Descriptors: Stakeholders, Prediction, Internet, Audiences
Cox, G. W.; Hughes, W. E., Jr.; Etzkorn, L. H.; Weisskopf, M. E. – IEEE Transactions on Education, 2009
This paper presents the results of an analysis of indicators that can be used to predict whether a student will succeed in a Computer Science Ph.D. program. The analysis was conducted by studying the records of 75 students who have been in the Computer Science Ph.D. program of the University of Alabama in Huntsville. Seventy-seven variables were…
Descriptors: Case Studies, Prediction, Computer Science Education, Doctoral Degrees
Clarke, Johnnie Ruth – 1968
This study attempted to provide a way to identify disadvantaged students at the junior college and to determine what data could be used as a basis for developing a curriculum to help them. Two measures of cognition, School and College Ability Test (SCAT) and Florida 12th Grade Battery, and three measures of the affective domain, Social Reaction…
Descriptors: Measurement, Prediction, Predictive Measurement, Statistical Analysis
Western, Drew; Weinberger, Joel – American Psychologist, 2004
This article reconsiders the issue of clinical versus statistical prediction. The term clinical is widely used to denote 1 pole of 2 independent axes: the observer whose data are being aggregated (clinician/expert vs. lay) and the method of aggregating those data (impressionistic vs. statistical). Fifty years of research suggests that when…
Descriptors: Psychometrics, Prediction, Inferences, Predictive Measurement
Peer reviewedJohnson, Kurt L.; And Others – Rehabilitation Counseling Bulletin, 1987
Applied statistical methods to predict case expenditures for low back pain rehabilitation cases in proprietary rehabilitation. Extracted predictor variables from case records of 175 workers compensation claimants with some degree of permanent disability due to back injury. Performed several multiple regression analyses resulting in a formula that…
Descriptors: Disabilities, Expenditures, Prediction, Predictive Measurement
Peer reviewedBruno, James E. – Socio-Economic Planning Sciences, 1975
Compares the accuracy of various student test score projection techniques, including idiographic analysis, standard score method, regression analysis, and a differential equation growth model. Concludes with an overview of the problems of projecting student test scores and suggests a stochastic procedure based on Bayesian analysis for educational…
Descriptors: Educational Assessment, Elementary Secondary Education, Models, Prediction
Peer reviewedLevy, Kenneth J. – Educational and Psychological Measurement, 1978
Kaminsky and Nelson's method for estimating the times of future "success" from the times of earlier "successes" in the same sample is discussed in terms of its potential applications to long term psychological treatment, research, or training programs. (Author/JKS)
Descriptors: Educational Programs, Guidance Programs, Prediction, Predictive Measurement
Jorgenson, Dale O. – J Educ Meas, 1970
Results in this study suggest that it is possible to use performance on a moderator or predictability scale to select a subgroup for whom correspondence between two predictors and the criterion is much greater than that of a subgroup whose scores on the moderator indicate a lesser degree of correspondence. (Author/ES)
Descriptors: Individual Differences, Prediction, Predictive Measurement, Predictive Validity
Toms, John G.; Brewer, James K. – Rehabilitation Literature, 1971
Presented and applied to a sample of 239 vocational rehabilitation clients is a discrete multivariate classification procedure for predicting vocational rehabilitation outcomes using several background characteristic combinations. Several cost-of-misclassification functions are proposed. (Author/KW)
Descriptors: Disabilities, Discriminant Analysis, Prediction, Predictive Measurement
Peer reviewedGilman, 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
Halinski, Ronald S.; Feldt, Leonard S. – J Educ Meas, 1970
Four commonly employed procedures were repeatedly applied to computer-simulated samples to provide comparative data pertaining to two questions: (a) which procedure can be expected to produce and equation that yields the most accurate predictions for the population, and (b) which procedure is most likely to identify the optimal set of independent…
Descriptors: Correlation, Multiple Regression Analysis, Prediction, Predictive Measurement
Peer reviewedHolderness, Aubrey; Handorf, James – Business Education Forum, 1976
The method used to arrive at four measures (three aptitude test scores and a high school grade point average) for predicting probable success is described. These measures were developed into three separate equations to predict success in: learning shorthand theory, reading shorthand notes, and dictation/transcription ability. (Author/MS)
Descriptors: Academic Ability, Office Occupations Education, Prediction, Predictive Measurement

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