Student Performance Prediction via Online Learning Analytics using Exam Metrics

Authors

  • N. Sowmiya Masters Student, Department of Computer Science and Engineering, KSR College of Engineering, Tiruchengode, India
  • E. Baby Anitha Assistant Professor, Department of Computer Science and Engineering, KSR College of Engineering, Tiruchengode, India
  • M. Somu Assistant Professor, Department of Computer Science and Engineering, KSR College of Engineering, Tiruchengode, India

Keywords:

AWS, API, Prediction analysis, Machine Learning, Microservices, MangoDB

Abstract

Prediction of Student Performance will help the more understanding of the peer view model of the education system. It provides the supportive environment to the lectures to understand the student activities and the learning curves on the curriculum and non-curriculum activities. A Research conducted between 2012 and 2021 was the base research over the fundamental of the student prediction used the student outcomes on their curriculums. Now-a-days we are gone through various papers in the online mode with the college domain, So the main objective of this prediction is to apply the college level system prediction of the student using Microservices Architectural View of the Data Mining.

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Published

07-11-2021

Issue

Section

Articles

How to Cite

[1]
N. Sowmiya, E. B. Anitha, and M. Somu, “Student Performance Prediction via Online Learning Analytics using Exam Metrics”, IJRESM, vol. 4, no. 11, pp. 5–7, Nov. 2021, Accessed: Oct. 11, 2024. [Online]. Available: https://journal.ijresm.com/index.php/ijresm/article/view/1483