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Stansfield, David – This Magazine Is About Schools, 1971
Descriptors: Competitive Selection, Creativity, Individual Differences, Individualized Instruction
Peer reviewedKatz, F. M.; Fleming, J. – Australian Journal of Education, 1971
Descriptors: College Students, Individual Differences, Models, Rating Scales
Croll, William L. – J Exp Child Psychol, 1970
Descriptors: Classification, Discrimination Learning, Individual Differences, Stimulus Generalization
Brodbelt, Samuel – Peabody J Educ, 1970
A new device for measuring the thought processes of individual students has been developed at a major university and is expected to revolutionize the educational methods used in the schools. (CK)
Descriptors: Cognitive Processes, Cybernetics, Individual Differences, Technological Advancement
Miller, George E. – Bus Educ Forum, 1970
Aptitude was found to be a significant determinant of level of performance for computer keyboard instruction. (CH)
Descriptors: Aptitude, Business Education, Computers, Individual Differences
Hinton, Bernard L. – J Creative Behav, 1970
Descriptors: Creativity, Individual Differences, Measurement Instruments, Task Performance
Peer reviewedWilde, G. J. S.; DeWit, O. E. – British Journal of Psychology, 1970
Descriptors: Individual Differences, Personality Measures, Questionnaires, Test Validity
Casler, Lawrence – Contemp Psychol, 1970
Descriptors: Book Reviews, Child Development, Individual Differences, Personality
Rankin, Richard J. – Contemp Psychol, 1970
Descriptors: Book Reviews, Individual Differences, Measurement Techniques, Testing
Peer reviewedBoker, Steven M.; Nesselroade, John R. – Multivariate Behavioral Research, 2002
Examined two methods for fitting models of intrinsic dynamics to intraindividual variability data by testing these techniques' behavior in equations through simulation studies. Among the main results is the demonstration that a local linear approximation of derivatives can accurately recover the parameters of a simulated linear oscillator, with…
Descriptors: Data Analysis, Individual Differences, Measurement Techniques, Simulation
Peer reviewedBronson, Gordon W. – Journal of Experimental Child Psychology, 1990
Longitudinal findings concerning five male and five female infants suggest a number of age-related changes in the dominant mode of visual scanning. Changes involve attention to locations of stimulus contours and prominent features of the stimulus, accuracy of saccades, and reversion to scanning behaviors typical of younger ages under certain…
Descriptors: Age Differences, Individual Differences, Infants, Visual Stimuli
Peer reviewedColombo, John; And Others – Child Development, 1989
States of 40 newborn infants were observed during 2, 35- to 70-minute periods that were separated by 6-48 hours. Analyses identified 3 state profiles that differentiated infants on a behavioral assessment measure at 2 weeks of age. Scores showed significant agreement on individual differences in neurologically based measures. (RH)
Descriptors: Individual Differences, Neonates, Predictor Variables, Profiles
Peer reviewedThomas, Hoben – Journal of Experimental Child Psychology, 1989
Individual differences in children's performance on a classification task are modeled by a two component binomial mixture distribution. The model accounts for data well, with variance accounted for ranging from 87 to 95 percent. (RJC)
Descriptors: Children, Classification, Cognitive Development, Individual Differences
Peer reviewedMcLaughlin, Steven D.; And Others – Social Work, 1988
Surveyed adolescent mothers who placed their children for adoption (N=146) and adolescent mothers who parented their children (N=123). Found mothers who relinquished children were more likely to complete vocational training, delay marriage, be employed after births, and live in higher income households than mothers who did not; found few…
Descriptors: Adolescents, Adoption, Early Parenthood, Individual Differences
Peer reviewedLeenen, Iwin; Van Mechelen, Iven; De Boeck, Paul; Rosenberg, Seymour – Psychometrika, 1999
Presents a three-way, three-mode extension of the two-way, two-mode hierarchical classes model of P. De Boeck and S. Rosenberg (1998) for the analysis of individual differences in binary object x attribute arrays. Illustrates the model with data on psychiatric diagnosis and discusses the relation between the model and other extant models. (SLD)
Descriptors: Algorithms, Individual Differences, Models, Set Theory


