Relation between public secondary teachers' self-efficiency perceptions regarding distance education and their technostress levels
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Abstract (EN)
The aim of this study is to examine the relationship between secondary school teachers' self-efficiency perceptions regarding distance education and technostress levels. For this purpose, the research was carried out with the relational scanning model, one of the general scanning methods. The universe of the research is secondary school teachers who worked actively during distant education period in Anatolian High Schools in the four central districts (Yenişehir, Sur, Bağlar and Kayapınar) in Diyarbakır in the 2022-2023 academic year. The data was obtained by reaching 345 teachers selected through simple random sampling from 1715 teachers in these four central districts and applied face to face. Statistical techniques such as skewness and kurtosis values, Levene homogeneity test, arithmetic mean and standard deviation values, t-test for independent samples, one-way ANOVA, LSD, correlation analysis and simple linear regression analysis were used in the analysis of the data. The reliability coefficient of the research for the Self-Efficacy Scale for Distance Education was calculated as 0.978, and for the Scale for Determining Teachers' Technostress Levels as 0.945. To the findings of the research, while there are no significant differences in the perception of teacher self-efficacy regarding distance education according to the variables of gender, faculty of graduation and education level; there are significant differences in the variables of branch, seniority and in-service training. The results of the research show that as teachers' self-efficacy increases, their technostress levels decrease and that self-efficacy is a predictor of technostress.
Author
Nurşin Narin
Institution

Dicle University
Eğitim Programları ve Öğretim Bilim Dalı
How to Cite
Nurşin Narin (Master Thesis). Relation between public secondary teachers' self-efficiency perceptions regarding distance education and their technostress levels, 2024, Dicle University.
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