Intelligent Management of Human Capital

Intelligent Management of Human Capital

Optimization of the Student Admission Process in Universities Using Recommender Systems (A Case Study of Imam Hossein Comprehensive University)

Document Type : Original Article

Authors
1 PhD student in Information Technology Management, Imam Hossein (AS) University, Tehran, Iran
2 Assistant Professor and Faculty Member, Information Technology Management Department, Imam Hossein (AS) University, Tehran, Iran
3 Researcher and faculty member of the Information Technology Management Department, Imam Hossein (AS) University, Tehran, Iran
Abstract
Background and Objective: Student admission in universities is a complex process that significantly impacts educational quality and scientific development. Traditional student selection methods are often inefficient and require enhancement through modern technologies. This study aims to optimize the student admission process at Imam Hossein Comprehensive University by proposing a competency-based recommender model.
 
Methodology: This applied and descriptive-analytical research employs a combination of data mining techniques, natural language processing, and similarity measurement algorithms. First, student competency criteria were extracted, and then a recommender system was designed and evaluated using language models and natural language processing techniques.
 
Findings: The proposed recommender model analyzes applicants' individual characteristics and provides personalized suggestions, thereby increasing the accuracy and efficiency of the admission process and enhancing decision-making in selecting qualified students.
 
Conclusion: The proposed model can serve as an effective tool for university administrators to optimize the student admission process. In addition to improving the precision of candidate selection, this approach contributes to the academic and research development of the university.
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