Persistent Link:
http://hdl.handle.net/10150/187594
Title:
FACTORS AFFECTING THE REDUCTION OF NARRATIVE DATA.
Author:
ENGLE, MOLLY ANN.
Issue Date:
1983
Publisher:
The University of Arizona.
Rights:
Copyright © 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.
Abstract:
Narrative data enable evaluators to understand other people's viewpoints without predetermining those viewpoints by using preselected questionnaire categories. Narrative data yield rich detail, insight, and information. However, reducing narrative data into meaningful conclusions is difficult and time consuming, and requires attention, commitment, and skill on the part of trained coders. The personal and situational characteristics of the coders (called value inertia and cognitive limitation biases) affect data reduction. The effects of coder exposure to expected project outcomes and the level of coder research methodology sophistication were investigated. Coders considered either sophisticated or naive in research methodology were exposed to positive, ambiguous, or negative project outcome expectations. The coders reduced, or categorized, 25 open-ended interview response sets into previously established positive, negative, and ambiguous statement-type, content-code categories. The effectiveness of coder training was also explored by computing generalizability (reliability) coefficients. High generalizability coefficients were found, regardless of level of exposure to project outcome expectations. This indicates that coders were able to code the same statements the same way and is an indication of the coders' ability to reproduce the results. Results of this study also indicate that evaluators should use sophisticated coders for the reduction of narrative data, given that option. Sophisticated coders appear more resistant to the effect of exposure to project outcome expectations, coding narrative data more positively with less variability than naive coders when exposed to positive outcome expectations.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Data reduction.; Statistics.; Psychometrics.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Educational Psychology; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Dinham, Sarah M.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleFACTORS AFFECTING THE REDUCTION OF NARRATIVE DATA.en_US
dc.creatorENGLE, MOLLY ANN.en_US
dc.contributor.authorENGLE, MOLLY ANN.en_US
dc.date.issued1983en_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.description.abstractNarrative data enable evaluators to understand other people's viewpoints without predetermining those viewpoints by using preselected questionnaire categories. Narrative data yield rich detail, insight, and information. However, reducing narrative data into meaningful conclusions is difficult and time consuming, and requires attention, commitment, and skill on the part of trained coders. The personal and situational characteristics of the coders (called value inertia and cognitive limitation biases) affect data reduction. The effects of coder exposure to expected project outcomes and the level of coder research methodology sophistication were investigated. Coders considered either sophisticated or naive in research methodology were exposed to positive, ambiguous, or negative project outcome expectations. The coders reduced, or categorized, 25 open-ended interview response sets into previously established positive, negative, and ambiguous statement-type, content-code categories. The effectiveness of coder training was also explored by computing generalizability (reliability) coefficients. High generalizability coefficients were found, regardless of level of exposure to project outcome expectations. This indicates that coders were able to code the same statements the same way and is an indication of the coders' ability to reproduce the results. Results of this study also indicate that evaluators should use sophisticated coders for the reduction of narrative data, given that option. Sophisticated coders appear more resistant to the effect of exposure to project outcome expectations, coding narrative data more positively with less variability than naive coders when exposed to positive outcome expectations.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectData reduction.en_US
dc.subjectStatistics.en_US
dc.subjectPsychometrics.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineEducational Psychologyen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorDinham, Sarah M.en_US
dc.identifier.proquest8404664en_US
dc.identifier.oclc690247437en_US
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