Futures Studies in Planning Skill-Based Job Training Programs in Iran

Hosseni Ghasr, Zohreh Sadat; Alizadeh, Morteza; Omidvar, Ata Ollah

Futures Studies in Planning Skill-Based Job Training Programs in Iran

Document Type : Original Article

Authors

¹ . M.Sc. in Educational Research, Faculty of Psychology and Educational Sciences, Khwarazmi University, Tehran, Iran (corresponding author)

² M.Sc. in General Psychology, Faculty of Humanities, Islamic Azad University, Torbat Jam Branch, Torbat Jam, Iran

³ B.Sc. in Agricultural Engineering, Faculty of Agriculture, Islamic Azad University, Mashhad Branch, Mashhad, Iran

Abstract

The aim of this study is to identify approaches for planning skill-based job training programs in Iran using a normative model with a Futures Studies perspective. For this research, eleven years of data (2011-2021) from vocational training programs in Technical and Vocational Training Centers of Razavi Khorasan Province were utilized. The data were entered into Excel software in a quantitative and descriptive format and analyzed based on the 11-stage normative planning model. The results are based on the opinions of 35 experts from the Technical and Vocational Training Organization regarding four proposed scenarios in this field. According to expert opinions, Scenario 1 indicates that aligning skill-based training programs with market needs is expected to regulate supply and demand through labor market mechanisms and positively impact the trend of increasing job opportunities in Iran by 2025. Scenario 2 predicts that market-aligned skill training will accelerate the phasing out of jobs with low and declining rates of change in the labor market. Conversely, Scenario 4 suggests that providing skill-based training programs unrelated to market needs will slow progress toward meeting society's job requirements by 2025. Lastly, Scenario 3 presents the weakest forecast, suggesting that offering skill-based training programs unrelated to market needs will sustain outdated and obsolete jobs, leading to a regression in the region's skill training levels.

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