Document Type : Research Paper

Authors

• Sina Raeesi Vanani ¹
• Iman Raeesi Vanani ²
• Mohammad Taghi Taghavifard ³

¹ M.Sc., Management, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran. Iran

²  Faculty Member, Department of Industrial Management, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran. Iran(Corresponding Author: imanraeesi@atu.ac.ir)

³ Faculty Member, Department of Industrial Management, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran Iran

Abstract

Educational performance measurement through the identification and analysis of data extracted from learners’ activities can effectively result in the improvement of educational performance. In this Article, data of international learners was analyzed based on design science methodology and using data mining methods. In this regard, domestic and international research has been reviewed over the past decade and the academic and non-academic data of students were clustered into three categories: family, supportive, and academic behavior. After the validation of algorithms outputs and determining the number of optimal clusters in each category, clusters were labeled and analyzed. Analysis of labels presents the experience of success or failure of students and roots of effective performance in each cluster, and the labeling method proposed is a new and applicable method in most of the learning centers for segmenting and formulating the educational performance.

Keywords

• : Learning
• Educational Performance
• Data Mining
• Clustering