Karafan Journal

Karafan Journal

Providing a governance model of skills training at the sub-national level with a data theory approach

Document Type : Original Article

Authors
1 PhD Student, Department of Educational Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
2 Professor, Department of Educational Management, Eslamshahr Branch, Islamic Azad University, Eslamshahr, Iran.
3 Assistant Professor, Department of Educational Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
Abstract
Governance of skills training and paying attention to sub-national actors is an irreplaceable paradigm in educational governance and by examining this this issue in a deep, comprehensive way in the swiftest and least harmful manner will advance the development of the country. The main purpose of this research was to design a governance model for skills training at the sub-national level. The research method was applied in terms of objectives, qualitative in terms of data and emerging foundation in terms of data type. Based on the method of informed sampling of targeted snowball type and based on theoretical saturation, 30 experts were selected for interviewing. The data collection tool used was exploratory interviews. After data collection, analysis was carried out in the form of open, axial and selective face coding. Based on the data analysis, an appropriate model for governing skills training at the sub-national level was presented. The results of the research indicate that this model consists of three dimensions: skills and entrepreneurship training, governance, quality and market-oriented skills training, and 27 components and 173 constructive indicators. In comparison with other models, this model was more valid and thus using and implementing this model can help improve the quality and entrepreneurship of skills training.
Keywords
Subjects

Reference
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Volume 17, Issue 3 - Serial Number 49
Management and Entrepreneurship
Autumn 2020
Pages 29-40

  • Receive Date 04 October 2020
  • Revise Date 16 November 2020
  • Accept Date 01 January 2021