ERIC Number: EJ1141020
Record Type: Journal
Publication Date: 2017-Jun
Abstractor: As Provided
The Impact of Student Teaching Experience on Pre-Service Teachers' Readiness for Technology Integration: A Mixed Methods Study with Growth Curve Modeling
Sun, Yan; Strobel, Johannes; Newby, Timothy J.
Educational Technology Research and Development, v65 n3 p597-629 Jun 2017
Adopting a two-phase explanatory sequential mixed methods research design, the current study examined the impact of student teaching experiences on pre-service teachers' readiness for technology integration. In phase-1 of quantitative investigation, 2-level growth curve models were fitted using online repeated measures survey data collected from 68 pre-service teachers doing their student teaching. The results revealed significant progress in readiness for technology integration during student teaching and significant variability in individual change trajectories of readiness for technology integration. Two dummy variables, "prior-teaching" (0 = "having no prior teaching experience"; 1 = "having prior teaching experience") and "grade-level" (0 = "elementary level"; 1 = "secondary level"), were identified as significant in predicting the shape of individual change trajectories of readiness for technology integration. In phase-2 of qualitative investigation, follow-up interview data were collected from 11 pre-service teachers among those who participated in the online surveys. The interview data was analyzed both deductively and inductively yielding clues and insights for interpreting and understanding the quantitative results from phase-1. Based on its quantitative and qualitative results, this study made recommendations for future technology integration research and for improving pre-service teachers' technology use experience during student teaching.
Descriptors: Student Teaching, Student Teacher Attitudes, Readiness, Technology Integration, Mixed Methods Research, Structural Equation Models, Data Collection, Teaching Experience, Instructional Program Divisions, Predictor Variables, Attitude Change, Interviews, Online Surveys, Data Interpretation
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
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