Designing an Optimal Hybrid Educational Management Model in Secondary Education

Hybrid school means that in addition to mathematics and experimental sciences, all courses and activities have serious importance and goal setting. The present study was conducted with the aim of developing an optimal model of hybrid educational management in the educational system.

This research was applied-developmental in terms of its purpose and is a mixed exploratory research with a qualitative (review of research literature and content analysis) and quantitative (structural equation modeling) approach in terms of data collection method. In the first stage, using these findings, 15 experts (teachers, school administrators, education experts) were selected through semi-structured interviews and the interviews continued until data saturation. Theoretical sampling was used to select the experts, and to ensure validity, confirmability and member review techniques were used, and the content analysis method was used to analyze the data. In the quantitative part, the statistical population consisted of 4635 secondary school teachers in Urmia, of which 381 were selected using stratified random sampling. The data collection tool was a researcher-made questionnaire that was developed based on qualitative steps. Content validity (reviewed by five experts) was used to validate the tool, and Cronbach's alpha coefficient (0.78) was used to determine reliability. Finally, structural equation modeling was used to analyze quantitative data with LISREL software version 8.8..

The results of data analysis showed that the factors affecting hybrid educational management in secondary schools were categorized into three main themes and six sub-themes. The main themes of human resource management, technology management, and educational management were identified, and an optimal model was obtained (p<0.05).

Based on the research results, it can be said that the model fit indices are appropriate and the research model generally has a good fit with the data and provides the necessary criteria for optimal fit.