Review On Educational Academic Performance Analysis and Dropout Visualization by Analyzing Grades of Student
DOI:
https://doi.org/10.47392/IRJAEM.2024.0194Keywords:
Grades, Educational data mining, Data analysis, Dropout visualization, Academic performanceAbstract
Education is a crucial aspect of a nation's development, and ensuring the success and retention of students is of paramount importance. The current studies show the need for an effective and efficient education prediction system. Education is a pivotal aspect of a country's development. It acts as a powerful tool to change the world. Education is the key to a literate society. In India, it is necessary to have an integrated web platform to analyze the academic performance and dropout rates across school, higher, and technical education. Student dropout is a significant problem for any nation. Discontinuing schooling due to financial, practical, and social reasons, as well as disappointment in examination results, is what is commonly referred to as student dropout. Educational Data Mining (EDM) techniques can help discover insights from data in educational environments, allowing tutors and researchers to predict future trends and student behavior. The use of machine learning and data mining techniques provides valuable tools for understanding the student learning environment. This literature review aims to synthesize the existing research findings on this topic and identify knowledge gaps for future research.
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Copyright (c) 2024 International Research Journal on Advanced Engineering and Management (IRJAEM)
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