Validation of the data model of the Foundation for talent identification of students with potential for teaching jobs

Document Type : Original Article

Authors

1 PhD Student Department of Educational Administration, Marand Branch, Islamic Azad University, Marand, Iran

2 Associate professor of Educational Administration, Azarbaijan Shahid Madani University, tabriz, iran.

Abstract

The present study was conducted with the aim of validating the data model of the talent identification foundation of students with potential for teaching jobs. This study was conducted using a combined method (qualitative and quantitative). In the qualitative part, the foundation data method was used, and in the quantitative part, the structural equation modeling (SEM) method was used. The population studied in the qualitative part of this research included all the education experts of Iran who were selected by the purposeful judgment sampling method and the data collected from them reached the theoretical saturation in the 19th person through the interview method. The statistical population of the research in the quantitative part included 2600 people from the executive and teaching staff of the schools along with the professors of Farhangian University, which according to the Morgan table, the sample size was estimated to be 335 people. Sampling was done by multi-stage cluster random method. The research tool in the quantitative part was a researcher-made questionnaire. The questions and items of the questionnaire were compiled using research literature and the results of a qualitative study. In order to confirm the validity and reliability of the questionnaire and also to confirm the validity of the model, the PLS algorithm has been followed. PLS modeling takes place in two stages. In the first step, the measurement model (external model) is examined through validity and reliability analyzes (Cronbach's alpha coefficient and composite reliability) and confirmatory factor analysis. In the second step, the structural model of the research (internal model) was examined. The data was analyzed by SmartPLS software. The results indicated that the causal conditions, background conditions, intervening factors and consequences in the talent identification model of gifted students are valid and approved.

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