Date of Award

2010

Document Type

Dissertation

Degree Name

Doctor of Philosophy (Ph.D.)

Cedarville University School or Department

Science and Mathematics

First Advisor

Arthur L. White, PhD

Keywords

Education, science, preservice teachers, teacher education programs, VNOS-C, logic process model

Abstract

This study examined the understanding of nature of science among participants in their final year of a 4-year undergraduate teacher education program at a Midwest liberal arts university. The Logic Model Process was used as an integrative framework to focus the collection, organization, analysis, and interpretation of the data for the purpose of (1) describing participant understanding of NOS and (2) to identify participant characteristics and teacher education program features related to those understandings. The Views of Nature of Science Questionnaire form C (VNOS-C) was used to survey participant understanding of 7 target aspects of Nature of Science (NOS). A rubric was developed from a review of the literature to categorize and score participant understanding of the target aspects of NOS. Participants' high school and college transcripts, planning guides for their respective teacher education program majors, and science content and science teaching methods course syllabi were examined to identify and categorize participant characteristics and teacher education program features. The R software (R Project for Statistical Computing, 2010) was used to conduct an exploratory analysis to determine correlations of the antecedent and transaction predictor variables with participants' scores on the 7 target aspects of NOS. Fourteen participant characteristics and teacher education program features were moderately and significantly ( p < .01) correlated with participant scores on the target aspects of NOS. The 6 antecedent predictor variables were entered into multiple regression analyses to determine the best-fit model of antecedent predictor variables for each target NOS aspect. The transaction predictor variables were entered into separate multiple regression analyses to determine the best-fit model of transaction predictor variables for each target NOS aspect. Variables from the best-fit antecedent and best-fit transaction models for each target aspect of NOS were then combined. A regression analysis for each of the combined models was conducted to determine the relative effect of these variables on the target aspects of NOS. Findings from the multiple regression analyses revealed that each of the fourteen predictor variables was present in the best-fit model for at least 1 of the 7 target aspects of NOS. However, not all of the predictor variables were statistically significant ( p < .007) in the models and their effect (β) varied. Participants in the teacher education program who had higher ACT Math scores, completed more high school science credits, and were enrolled either in the Middle Childhood with a science concentration program major or in the Adolescent/Young Adult Science Education program major were more likely to have an informed understanding on each of the 7 target aspects of NOS. Analyses of the planning guides and the course syllabi in each teacher education program major revealed differences between the program majors that may account for the results.

Comments

© 2010 William I. Jones. All rights reserved.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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