Machine Learning Algorithms for Early Predicting Dropout Student Online Learning-Reference-Cited by-同舟云学术

Machine Learning Algorithms for Early Predicting Dropout Student Online Learning

Published:2023-11-07 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 9th International Conference on Computing, Engineering and Design (ICCED)
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Author:

Dewi Meta Amalya¹,Kurniadi Felix Indra²,Murad Dina Fitria¹,Rabiha Sucianna Ghadati¹,Romli Awanis³

Affiliation:

1. Bina Nusantara University,BINUS Online Learning,Information Systems Department,Jakarta,Indonesia,11480

2. Bina Nusantara University,School of Computer Science,Computer Science Department,Jakarta,Indonesia,11480

3. Universiti Malaysia Pahang,Faculty of Computing,Pahang,Malaysia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10424960/10424702/10425359.pdf?arnumber=10425359

Reference20 articles.

1. Making Waves: Coronavirus detection, presence and persistence in the water environment: State of the art and knowledge needs for public health

2. Early Identification of At-Risk Students Using Iterative Logistic Regression

3. Predicting students’ academic performance by using educational big data and learning analytics: evaluation of classification methods and learning logs

4. Using machine learning algorithms to predict students’ performance and improve learning outcome: A literature-based review;Of ori;Journal of Information and Technology,2020

5. Student Engagement Predictions in an e-Learning System and Their Impact on Student Course Assessment Scores

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