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Applying the Technology Acceptance Model to Predict and Explain Elementary and Secondary Preservice Teachers' Continuance Behavioral Intentions and Pedagogical Usage of Twitter to build Professional Capital: A Structural Equation Modeling Inquiry

The purpose of this research study was to predict and explain elementary and secondary preservice teachers' continuance behavioral intentions and pedagogical usage of Twitter, a web based social networking, microblogging platform, to build professional growth and capital. The objective of the research study was to examine preservice teachers' beliefs associated with the specified constructs that formed the latent variables of the hypothesized research model; these latent variables were then measured with their associated indicators or manifest variables, and the relationship between the manifest variables was examined through the Structural Equation Modeling (SEM) process. A non-experimental empirical research study was conducted using the survey methodology; purposive, criterion referenced, sampling of elementary and secondary preservice teachers, N=379, was employed using social media platforms and intern listserv at a large Southeastern university. The final sample of N= 250 participants was determined through the process of regression imputation of elementary and secondary preservice teachers' survey responses. The results demonstrated that constructs of the extended Technology Acceptance Model showed significant goodness-of-fit indices and coefficients of determination after analyzing the data from the survey. Implications of this research contribute significantly toward teacher education and training by providing insights into the factors that impact the pedagogical use of Twitter, a web-based social networking and microblogging platform, for building professional capital in preservice teachers.

Identiferoai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-6212
Date01 January 2016
CreatorsGurjar, Nandita
PublisherSTARS
Source SetsUniversity of Central Florida
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceElectronic Theses and Dissertations

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