Education research, measurement and evaluation predictors of technology use for elementary school teachers in Massachusetts: A multilevel SEM approach
Helena P. Miranda, Boston College, United States
Boston College . Awarded
This dissertation consists of secondary data analysis of the USEIT data aiming to inform school administrators and policymakers about the factors that affect instructional technology use in elementary classrooms. SEM predictive models were developed for teacher-directed student use of technology (TDS) at three levels of analysis: (1) teacher, (2) school, and (3) district. A multilevel SEM model was developed depicting relationships across levels of analysis. The best predictors of TDS at the teacher level are teachers' experience with technology, belief that technology is beneficial to meet instructional goals, and perceived pressure to use technology. The strongest predictor of TDS at the school level is principals' use of technology. The best predictors of TDS at the district level are technology standards, teacher and student accountability to standards, and principals' technology discretion. Multilevel SEM results suggest that some factors may be ineffective in changing instructional technology use at the classroom level but may be effective in changing organizational culture to adopt instructional technology.
Miranda, H.P. Education research, measurement and evaluation predictors of technology use for elementary school teachers in Massachusetts: A multilevel SEM approach. Ph.D. thesis, Boston College.
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