Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1132
Title: Machine Learning-based Prediction Model for Academic Performance
Authors: Tharsha, S.
Dilogera, J.
Mohanashiyaam, B.
Kirushan, S.
Chathurika, K.B.A.B.
Swarnakantha, N.H.P.R.S.
Keywords: Artificial Intelligence
Machine Learning
Deep Learning
Smart Study Application
Student Management System
Data Mining Technique
Issue Date: 9-Dec-2021
Publisher: 2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT
Abstract: This paper represents the work of a new integrated and collaborative Smart application for managing students online through data mining techniques. Nowadays especially in this pandemic situation, there is a necessity for academic management to incorporate and change all study methods online. By considering all these conditions this research is focused to discuss the solution to manage and engage students smartly and easily. Thou technology advancements have a serious impact on the day-to-day life people face troubles when using complex applications, this implemented Smart application is simple to use and a great tool for Student Management systems. The survey feedback from students, academic staff, and the public illustrate that this project helps to improve the effectiveness and efficiency of learning capability among the targeted group. The main objective of this project is to build up a smart model using Machine Learning, Deep Learning, and Artificial Intelligence to overcome generic learning problems. Therefore, this paper aims to present the concept behind the development and implementation of the Smart Study Application for Student Management System.
URI: http://rda.sliit.lk/handle/123456789/1132
ISSN: 978-1-6654-0862-2/21
Appears in Collections:3rd International Conference on Advancements in Computing (ICAC) | 2021
Department of Computer systems Engineering-Scopes

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