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Peer reviewedMills, David S. – Physics Teacher, 1981
Describes a variation of the familiar laboratory investigation on the spring and mass oscillator. (SK)
Descriptors: College Science, Higher Education, Mathematical Applications, Mathematical Models
Peer reviewedWilcox, Rand R. – Educational and Psychological Measurement, 1981
The paper considers the problem of selecting the t best of k normal populations and simultaneously determining whether the selected populations have a mean larger than a known standard. Illustrations are given for selecting the t best of k examinees when the binomial error model applies. (Author)
Descriptors: Competitive Selection, Criterion Referenced Tests, Decision Making, Mathematical Models
Peer reviewedMaxwell, Scott E.; Howard, George S. – Educational and Psychological Measurement, 1981
This paper delineates conditions under which the use of change scores will not produce misleading results, and may perhaps be preferable to other methods of analysis. The validity of change scores in randomized pretest-posttest designs is discussed along with situations where analysis of change scores should be used. (Author/GK)
Descriptors: Analysis of Covariance, Analysis of Variance, Mathematical Models, Pretests Posttests
Peer reviewedVan Der Meer, A. – International Journal of Mathematical Education in Science and Technology, 1980
Some ways to link calculus instruction with the mathematical models used in physics courses are presented. The activity of modelling is presented as a major tool in synchronizing physics and mathematics instruction in undergraduate engineering programs. (MP)
Descriptors: Calculus, College Mathematics, Engineering Education, Higher Education
Peer reviewedYeshurun, Shraga – International Journal of Mathematical Education in Science and Technology, 1980
The cognitive method, an algorithmic method for transforming verbal word problems into equations, equation systems, inequalities, etc., is presented and discussed. The psychological and mathematical aspects of the cognitive method are also reviewed. (MP)
Descriptors: Algorithms, Cognitive Processes, Educational Psychology, Learning Theories
Peer reviewedDavis, Philip J. – Two-Year College Mathematics Journal, 1980
Aspects of the source of power of mathematics and the ways in which mathematics works are discussed. The author discusses various philosophies about mathematics, presents several unusual "real world" problems, and reviews the social consequences of the "imposition of mathematics" on humanity. (MP)
Descriptors: Computers, Educational Philosophy, Mathematical Concepts, Mathematical Enrichment
Peer reviewedChartrand, Gary; Wall, Curtiss E. – School Science and Mathematics, 1980
Graph theory is presented as a tool to instruct high school mathematics students. A variety of real world problems can be modeled which help students recognize the importance and difficulty of applying mathematics. (MP)
Descriptors: Graphs, Mathematical Applications, Mathematical Models, Mathematics Education
Peer reviewedMcGaw, Barry; Glass, Gene V. – American Educational Research Journal, 1980
There are difficulties in expressing effect sizes on a common metric when some studies use transformed scales to express group differences, or use factorial designs or covariance adjustments to obtain a reduced error term. A common metric on which effect sizes may be standardized is described. (Author/RL)
Descriptors: Control Groups, Error of Measurement, Mathematical Models, Research Problems
Hambleton, Ronald K. – New Directions for Testing and Measurement, 1980
Latent trait models provide a new scale for reporting educational and psychological measurements. Characteristics, interpretations, and uses of these scales are considered. (Author/RL)
Descriptors: Goodness of Fit, Latent Trait Theory, Mathematical Models, Measurement Techniques
Peer reviewedMansfield, Jerry W. – Journal of Academic Librarianship, 1981
Classical queuing theories and their accompanying service facilities totally disregard the human factors in the name of efficiency. As library managers we need to be more responsive to human needs in the design of service points and make every effort to minimize queuing and queue frustration. Five references are listed. (Author/RAA)
Descriptors: Evaluation Methods, Human Factors Engineering, Humanization, Library Administration
Peer reviewedSvenson, Ola; Hedenborg, Maj-Lene – Scandinavian Journal of Educational Research, 1980
Children, 9-11 years old, solved subtraction problems in the form of M-N=..., then gave a verbal report on the thought processes used, analysis of which utilized a model based on analyses of reaction times, and resulted in a more detailed process model. (AN)
Descriptors: Children, Cognitive Measurement, Mathematical Logic, Mathematical Models
Peer reviewedKumar, Ramesh C.; And Others – Socio-Economic Planning Sciences, 1980
Describes a simulation model that examines the relationship of dropout behavior and re-entry flows in a local school system to changes in local socioeconomic factors, school-related conditions, and aspects of labor market participation. Assesses the policy implications for affecting these flows at the local board level. (Author/IRT)
Descriptors: Dropouts, Educational Environment, Enrollment Projections, Foreign Countries
Peer reviewedSchulman, Robert S. – Psychometrika, 1979
An alternative to the uniform probability distribution model for ordinal data is considered. Implications for statistics and for test theory are discussed. (JKS)
Descriptors: Career Development, Correlation, Mathematical Models, Nonparametric Statistics
Peer reviewedBradford, John W. – Arithmetic Teacher, 1980
Money models that can be used in a group-instruction mode and a shorthand notation that allows students to demonstrate their ability to count out change by a written procedure are described and discussed. (MK)
Descriptors: Educational Media, Elementary Education, Elementary School Mathematics, Mathematical Models
Peer reviewedLohnes, Paul R. – American Educational Research Journal, 1979
Factorial modeling is justified as a method for analyzing correlations in support of causal inference. The method is illustrated and compared to path analysis, LISREL-type analysis, canonical correlation, and commonality analysis. Predictions of impacts of policy manipulations are demonstrated. (Author/CP)
Descriptors: Algorithms, Correlation, Educational Research, Factor Structure


