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ANALYSIS OF A DECADE OF STUDENT GRADES IN THE ELECTRICAL ENGINEERING DEPARTMENT AT SHARIF UNIVERSITY OF TECHNOLOGY USING GRAPH SIGNAL PROCESSING
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ANALYSIS OF A DECADE OF STUDENT GRADES IN THE ELECTRICAL ENGINEERING DEPARTMENT AT SHARIF UNIVERSITY OF TECHNOLOGY USING GRAPH SIGNAL PROCESSING
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ANALYSIS OF A DECADE OF STUDENT GRADES IN THE ELECTRICAL ENGINEERING DEPARTMENT AT SHARIF UNIVERSITY OF TECHNOLOGY USING GRAPH SIGNAL PROCESSING
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Journal Article
ANALYSIS OF A DECADE OF STUDENT GRADES IN THE ELECTRICAL ENGINEERING DEPARTMENT AT SHARIF UNIVERSITY OF TECHNOLOGY USING GRAPH SIGNAL PROCESSING
2025
Overview
In this research, we examine the academic performance of students and identify patterns influencing their success or decline using graph signal processing tools. The study focuses on undergraduate students from the Department of Electrical Engineering at Sharif University of Technology during 2011-2021. The research data includes students’ grades in various courses, their specializations (majors), and the timing of course enrollment. Importantly, all data was utilized, and no sampling was applied. Each student is represented as a node in a graph, and the nodes are connected through weighted edges based on the similarity of academic performance. Using the graph connections, we evaluate how well the grades of specific courses align with the overall performance of the students. The results indicate a lack of alignment between the grades of certain courses and the overall performance of the students, which may be attributed to varying grading policies and teaching styles. This feedback can help improve grading practices. Additionally, the analysis shows that students’ major choices align with their abilities in only 44% of cases. Another analysis observed that during the COVID-19 pandemic, 5% of students experienced a significant increase in their grades, possibly indicating systematic cheating in online exams.
Publisher
Iran Academy of Science
