OULAD MOOC Dropout and Result Prediction using Ensemble, Deep Learning and Regression Techniques-Reference-Cited by-同舟云学术

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OULAD MOOC Dropout and Result Prediction using Ensemble, Deep Learning and Regression Techniques

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 11th International Conference on Computer Supported Education
language:
Short-container-title:

Author:

Jha Nikhil¹,Ghergulescu Ioana²,Moldovan Arghir-Nicolae¹

Affiliation:

1. School of Computing, National College of Ireland, Dublin and Ireland, --- Select a Country ---

2. Adaptemy, Dublin and Ireland, --- Select a Country ---

Publisher

SCITEPRESS - Science and Technology Publications

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Predicting student success in MOOCs: a comprehensive analysis using machine learning models;PeerJ Computer Science;2024-08-23

2. Improving Student Performance Prediction Through Feature Selection: Insights from ‘Offee’ Assessment Data during the Covid-19 Pandemic;Procedia Computer Science;2024

3. An Efficient Health Insurance Prediction System using Machine learning;2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES);2023-12-14

4. Comparison of Various Techniques Implemented for Educational Data Mining and Learning Analytics;2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON);2023-12-01

5. Performance prediction in online academic course: a deep learning approach with time series imaging;Multimedia Tools and Applications;2023-11-23

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