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dc.contributor.advisorEvans, Selby H.
dc.contributor.authorMueller, Marvin Raymonden_US
dc.date.accessioned2019-10-11T15:11:26Z
dc.date.available2019-10-11T15:11:26Z
dc.date.created1967en_US
dc.date.issued1967en_US
dc.identifieraleph-255021en_US
dc.identifier.urihttps://repository.tcu.edu/handle/116099117/34633
dc.description.abstractA number of investigators (Bartlett, 1932; Woodworth, 1938; Hebb, 1949; Attneave, 1956) have used the term "schema" to designate a hypothetical construct which represents certain types of concepts. Generally, a schema is thought of as an abstraction of the redundant aspects of a variable population of objects or events. The theoretical attractiveness of the schema construct has been widely recognized; however, research has been somewhat limited due to inadequate methodology. In the present study, schema learning was studied with patterns which were randomly sampled from statistically defined populations. A computer program was used to generate samples of 15 column patterns at four levels of redundancy (R_c) in which the schema was clearly defined. The patterns resempled histograms and the schema was defined in terms of a most probable height for each column. The effects of R_c on performance were studied in a recognition task, a transfer task and a reproduction task. In addition, a new measure of schema conformity, the pattern variance(PV), was developed and evaluated. The results led to the following conclusions: 1. R_c is detrimental to performance in a recognition task. 2. Although detrimental to performance, high R_c in a recognition task facilitates schema learning as evidenced by transfer to the first trial of a reproduction task. 3. R_c facilitates both schema learning and performance in a reproduction task. 4. PV is superior to R_c as a measure of schema conformity because1 a. A significant correlation was demonstrated between PV and performance within one level of R_c indicating that PV is a more precise predictor of performance. b. The correlation between PV and performance provides an additional measure of schema learnings it is a function both of trials and of level of R_c. c. The use of the PV does not preclude the use of R_c. since one population value can be derived from the other. d. The EY allows a choice between direct and statistical control of individual pattern variability. Additionally, an interpretation of perceptual learning was presented which is consistent with the present results and partially reconciles the theoretical disagreement of Gibson and Gibson (1955) and Postman (1955) regarding the process and product of perceptual learning.
dc.format.extentvi, 69 leaves, bound : illustrationsen_US
dc.format.mediumFormat: Printen_US
dc.language.isoengen_US
dc.relation.ispartofTexas Christian University dissertationen_US
dc.relation.ispartofAS38.M84en_US
dc.subject.lcshPerceptionen_US
dc.titlePerceptual learning of statistically defined schemata as a function of constraint redundancy and kind of tasken_US
dc.typeTexten_US
etd.degree.departmentDepartment of Psychology
etd.degree.levelDoctoral
local.collegeCollege of Science and Engineering
local.departmentPsychology
local.academicunitDepartment of Psychology
dc.type.genreDissertation
local.subjectareaPsychology
dc.identifier.callnumberMain Stacks: AS38 .M84 (Regular Loan)
dc.identifier.callnumberSpecial Collections: AS38 .M84 (Non-Circulating)
etd.degree.nameDoctor of Philosophy
etd.degree.grantorTexas Christian University


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