Document Details

Document Type : Thesis 
Document Title :
Identifying Key Factors Affecting Distance Learning Students Performance Using Data Mining Techniques
تحديد العوامل الرئيسية التي تؤثر على أداء طلاب التعليم عن بعد باستخدام طرق تنقيب البيانات
 
Subject : Faculty of Computing and Information Technology 
Document Language : Arabic 
Abstract : Educational data has grown over the years with the increased use of technology within educational environments. To meet this analytical need, Educational Data Mining (EDM) has emerged to assist educational institutions in identifying key benefits such as students at risk, the level of student engagement or predicting student performance. The aim of this research is to explore the various aspects of student interaction data using data mining techniques to identify relevant patterns of behaviors that have higher degrees of influence on distance learning students. The main findings identified several student profiles mapped to specific online learning strategies, based on the total activities, level of content access, and level of online interaction. The research proposed a prototype for processing interaction data based on R and Hadoop platforms to analyze student online profiles and behaviors affecting them. 
Supervisor : Dr. Muazzam Siddiqui 
Thesis Type : Master Thesis 
Publishing Year : 1441 AH
2020 AD 
Co-Supervisor : Dr. Naif Aljohani 
Added Date : Friday, May 29, 2020 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
أسامة سامر إسلامIslam, Osama SamerResearcherMaster 

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 46249.pdf pdf 

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