Predicting Students' Motivation Through Teachers Technological Literacy
The purpose of this study was to predict the motivation of students in the second elementary school of Hamadan through their teachers' technological literacy.
The research method was descriptive correlational. The statistical population of the study consisted of all teachers and students of the second elementary school in Hamadan with 598 and 15287 respectively. The sample of teachers was selected based on the Krejcie and Morgan table; using random cluster sampling methods 234 teacher and 702 students selected. For each teacher, three of their students were selected randomly. The data gathering tool was a researcher-made questionnaire of technological literacy and Hartre's Educational Motivation Questionnaire. Validity of the questionnaires was determined through content validity based on experts' viewpoints and reliability of the questionnaires based on Cronbach's alpha coefficient was α=0.89 and α=0.85 respectively. The collected data were analyzed using descriptive statistics indices such as percentage, mean, standard deviation and inferential statistics tests such as correlation tests and stepwise regression analysis.
Findings indicate that there is a positive and significant relationship between the teachers' technological literacy and the educational motivation of second elementary school students. There is also a positive and significant relationship between motivation of students in the second elementary school and the dimensions of teacher's technological literacy which includes understanding of the nature of technology, understanding connection between technology and society, understanding technology design, the technological capability, and the understanding of technology in the world around teachers. Therefore, it can be said that the teachers 'technological literacy has increased the student's motivation, and the combination of two dimensions of "technological capability" and "understanding of the relationship between technology and society" can predict students' academic motivation
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