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The purpose of this study was to: a) investigate student teachers’ and experienced classroom teachers’ computer usage beliefs, intentions, and self-reported computer usage in the classroom using a mixed methodology approach (i.e., quantitative and qualitative), and b) examine the efficacy of the technology acceptance model (TAM) and the decomposed theory of planned behavior (DTPB) for predicting computer usage intentions. This study consisted of a sample of 160 student teachers and 158 experienced teachers from classes within a large urban university. All participants completed a Computer Usage Intention Survey. This survey was developed using a theoretical framework of the technology acceptance model (TAM) (Davis, 1989, 1993; Davis, Bagozzi, & Warshaw, 1989). The survey determined participants’ beliefs, future intentions usage (for the coming 6 months) and self-reported usage (for the past three months) of integrating computer applications (e.g. Word Processing, Spreadsheets, Database, Multimedia, Internet, Games, Drill and Practice, Simulations, Tutorials, Problem Solving, and educational subject-specific software) into subjectspecific lessons. After completion of the Computer Usage Intentions Survey, a purposeful sample of the study’s participants was selected for semi-structured interviews. This sample consisted of a total of 19 participants, 10 student teachers and 9 experienced classroom teachers. The interview questionnaire was developed using a theoretical framework of the decomposed theory of planned behavior (Taylor & Todd, 1995). Although the TAM was a good predictor of intentions, the DTPB emerged as the most important model for predicting teachers’ intentions. Similarities as well as significant differences were found between student teachers’ and experienced teachers’ computer usage. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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