Logistic Regression Modeling for Predicting Task-Related ICT Use in Teaching
The main goal of this study is to estimate the extent to which perceived innovation characteristics are associated with the probability of task related ICT use among secondary school teachers. The tasks were categorized as teaching preparation, teaching delivery, and management. Four hundred and six...
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Veröffentlicht in: | Educational technology & society 2006-01, Vol.9 (2), p.141-151 |
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description | The main goal of this study is to estimate the extent to which perceived innovation characteristics are associated with the probability of task related ICT use among secondary school teachers. The tasks were categorized as teaching preparation, teaching delivery, and management. Four hundred and sixteen teachers from secondary schools in Turkey, completed a questionnaire, which was designed to determine the taskrelated usage and the perceptions of the teachers in regard to ICT. Logistic stepwise regression analysis showed that complexity or ease of use was found to be a common perceived innovation characteristic for teaching delivery, preparation and managerial tasks in schools. Another result of this survey lead one to conclude that observability is a perceived attribute in teaching delivery in some specific tasks performed during the class period whereas relative advantage and compatibility are for teaching preparation tasks. |
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subjects | Adoption (Ideas) Art teachers Computer Attitudes Computers in education Distance learning Educational innovation Educational technology Foreign Countries Full Length Articles Information Technology Innovation adoption Innovation diffusion Innovations Instructional Innovation Logistic regression Logistics Observability (systems) Predictor Variables Questionnaires Regression (Statistics) Regression analysis Secondary School Teachers Statistical analysis Stepwise Regression Teacher Attitudes Teachers Technological innovation Technology Education Technology Uses in Education Turkey (Ankara) Use Studies |
title | Logistic Regression Modeling for Predicting Task-Related ICT Use in Teaching |
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