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Peer reviewedHockley, William E.; Murdock, Bennet B., Jr. – Psychological Review, 1987
The model of the decision system in Murdock's two-stage memory- and-decision model for item recognition is developed and tested. The decision model is shown to be able to fit the accuracy and mean response latency data from four major recognition paradigms (Sternberg, study-test, continuous, and prememorized list). (Author/LMO)
Descriptors: Cognitive Processes, Decision Making, Goodness of Fit, Mathematical Models
Peer reviewedFox, John; Moore, James C., Jr. – Social Psychology Quarterly, 1979
Fourteen experimental studies were reviewed using linear model of Berger et al. The model fits the data from these experiments remarkably well. These results demonstrate the utility and apparent validity of this theory of status-organizing processes. (Author/RD)
Descriptors: Cognitive Processes, Expectation, Goodness of Fit, Mathematical Models
Hattie, John; Fitzgerald, Don – 1979
Four alternative theoretical models of intellectual competence were assessed, using confirmatory factor analysis to account for the correlation patterns derived from Wechsler intelligence tests. It was argued that the difference between the chi-square goodness of fit statistics that are provided when using confirmatory factor analysis gives a…
Descriptors: Cognitive Ability, Cognitive Processes, Elementary Secondary Education, Factor Structure
Dowson, Martin; McInerney, Dennis M. – 1997
This paper outlines the development of a quantitative instrument designed to measure students' multiple achievement goals and key aspects of their cognitive engagement in Australian educational settings. The paper demonstrates the use of congeneric measurement models in assessing and improving the validity of the scales comprising the Goal…
Descriptors: Academic Achievement, Achievement Need, Cognitive Processes, Educational Objectives
Tatsuoka, Kikumi K.; Tatsuoka, Maurice M. – 1985
The study examines the rule space model, a probabilistic model capable of measuring cognitive skill acquisition and of diagnosing erroneous rules of operation in a procedural domain. The model involves two important components: (1) determination of a set of bug distributions (bug density functions representing clusters around the rules); and (2)…
Descriptors: Artificial Intelligence, Cognitive Processes, Computer Assisted Testing, Computer Software


