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dc.contributor.authorBuchanan, Barbara Sanford, 1943-
dc.creatorBuchanan, Barbara Sanford, 1943-en_US
dc.date.accessioned2013-05-09T11:30:24Z
dc.date.available2013-05-09T11:30:24Z
dc.date.issued1987en_US
dc.identifier.urihttp://hdl.handle.net/10150/290572
dc.description.abstractThis study explored methods of identifying and describing diversity related to cultural data in educational settings using the individual profile of variables as a unit of study more appropriate than the variable when making decisions regarding instruction of small groups of individual students or when designing curriculum. Method. The construct of culture as the organization of diversity as opposed to culture as the replication of uniformity (Wallace, 1961a) was taken as an organizing principle for the study. Two research strategies (a data processing technique and a descriptive conceptualization) which matched the two definitions of diversity, variability in form and distinction in kind, were applied to pre-existing data sets, cognitive style, and goals and values, collected from a single set of 67 subjects in a major city in the American southwest. Results. Central Instance Analysis, the data processing technique that matched the variability in form definition of diversity produced a prototype and groups of increasing difference from the prototype. Unexpected variations in the form of the prototype occurred. Q-Factor Analysis is not recommended for further use as a data processing technique to match the distinction in kind definition of diversity because it places unrealistic restrictions on the very practical data sets educators might want to use. Although there are no specific hypotheses regarding outliers in the study, information about outliers was generated.
dc.language.isoen_USen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectEducational anthropology.en_US
dc.subjectCulture.en_US
dc.titleDESCRIBING CULTURAL DIVERSITY: A COMPARISON OF RESEARCH STRATEGIESen_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.identifier.oclc18175736en_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.identifier.proquest8803248en_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineEducational Foundations and Administrationen_US
thesis.degree.namePh.D.en_US
dc.description.noteThis item was digitized from a paper original and/or a microfilm copy. If you need higher-resolution images for any content in this item, please contact us at repository@u.library.arizona.edu.
dc.identifier.bibrecord.b16489056en_US
dc.description.admin-noteOriginal file replaced with corrected file July 2023.
refterms.dateFOA2018-04-12T11:57:33Z
html.description.abstractThis study explored methods of identifying and describing diversity related to cultural data in educational settings using the individual profile of variables as a unit of study more appropriate than the variable when making decisions regarding instruction of small groups of individual students or when designing curriculum. Method. The construct of culture as the organization of diversity as opposed to culture as the replication of uniformity (Wallace, 1961a) was taken as an organizing principle for the study. Two research strategies (a data processing technique and a descriptive conceptualization) which matched the two definitions of diversity, variability in form and distinction in kind, were applied to pre-existing data sets, cognitive style, and goals and values, collected from a single set of 67 subjects in a major city in the American southwest. Results. Central Instance Analysis, the data processing technique that matched the variability in form definition of diversity produced a prototype and groups of increasing difference from the prototype. Unexpected variations in the form of the prototype occurred. Q-Factor Analysis is not recommended for further use as a data processing technique to match the distinction in kind definition of diversity because it places unrealistic restrictions on the very practical data sets educators might want to use. Although there are no specific hypotheses regarding outliers in the study, information about outliers was generated.


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