Intelligent Management of Human Capital

Intelligent Management of Human Capital

Ranking Factors Influencing the Performance of Artificial Intelligence in Improving In-Service Teacher Training Using the Multi-Criteria Decision-Making SECA Method

Document Type : Original Article

Authors
Parvaneh Fath Ali Beigi 1
Masoumeh Al-Sadat Abtahi 2
Hamid Reza Maghami 3
Rahim Moradi 4
1 PhD Student in Curriculum Planning, Department of Educational Studies and Curriculum Planning, Science and Research Branch, Islamic Azad University, Tehran, Iran.
2 Assistant Professor, Department of Educational Studies and Curriculum Planning, Science and Research Branch, Islamic Azad University, Tehran, Iran.
3 Associate Prof, Department of Educational Technology, Faculty of Psychology and Educational Sciences, Allamah Tabatabai University, Tehran, Iran.
4 Assistant Prof., Department of Educational Technology, Faculty of Psychology and Educational Sciences, Arak University, Arak , Iran.
10.22034/imhr.2025.506738.1021
Abstract
Background and Objective: This study aimed to rank the factors influencing the performance of artificial intelligence in improving in-service teacher training by utilizing the SECA decision-making method in a qualitative and applied manner.
Methodology: The study is considered applied in terms of its objective and descriptive-survey in nature. The statistical population included all faculty members of Nasibeh Campus, Farhangian University in Tehran. The sampling method was purposive and adhered to the principle of theoretical saturation, encompassing 20 experts. Data collection was conducted through interviews with experts. After extracting expert-defined criteria influencing AI performance in in-service teacher training, a decision matrix was developed based on the criteria and alternatives. Finally, the SEC method was employed to determine the ranking of influencing factors, and the LINGO software was used to solve the nonlinear equations.
Findings: Educational data analysis, personalized training, and virtual interaction and collaboration were identified as the most significant factors influencing AI performance in improving in-service teacher training.
Conclusion: All the criteria identified by the experts were considered positive, indicating that an increase in any criterion would lead to an improvement in the performance of AI in enhancing in-service teacher training.
Keywords
Artificial Intelligence
In-Service Training
Teachers
Staff
Organizational Culture

Subjects

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Intelligent Management of Human Capital
Volume 1, Issue 2 - Serial Number 2
Autumn 2024
Pages 151-125