Prediction Model for a Good Learning Environment Using an Ensemble Approach

Author:

Subha S.,Baghavathi Priya S.

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

General Computer Science,Theoretical Computer Science,Control and Systems Engineering

Reference17 articles.

1. E-Learning and students motivation: A research study on the effect of e-learning on higher education;Abou El-Seoud;International Journal of Emerging Technologies in Learning,2014

2. Using learning analytics to predict (and improve) student success: A faculty perspective;Uhler;Journal of Interactive Online Learning,2013

3. Prediction of students’ performance in e-learning environment using random forest;Abubakar;International Journal of Innovative Computing,2017

4. Student engagement predictions in an e-learning system and their impact on student course assessment scores;Hussain;Computational Intelligence and Neuroscience,2018

5. Study on student performance estimation, student progress analysis, and student potential prediction based on data mining;Yang;Computers & Education,2018

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1. Predicting Student Performance to Boost Educational Outcomes: The Efficacy of a Random Forest Approach;2024 13th International Conference on Educational and Information Technology (ICEIT);2024-03-22

2. Personalization-based deep hybrid E-learning model for online course recommendation system;PeerJ Computer Science;2023-11-27

3. An Ensemble Learning-Enhanced Smart Prediction Model for Financial Credit Risks;Journal of Circuits, Systems and Computers;2023-11-23

4. XAutn: Blockchain-based cross domain authentication for digital certificates in the education sector;Journal of Intelligent & Fuzzy Systems;2023-11-01

5. Ensemble Model for Spindle Thermal Displacement Prediction of Machine Tools;Computer Modeling in Engineering & Sciences;2023

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