The Role of Machine Learning in Identifying Students At-Risk and Minimizing Failure-Reference-Cited by-同舟云学术

The Role of Machine Learning in Identifying Students At-Risk and Minimizing Failure

Published:2023 Issue: Volume:11 Page:1224-1243
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Pek Reyhan Zeynep¹^ORCID,Ozyer Sibel Tariyan²,Elhage Tarek³,Ozyer Tansel²,Alhajj Reda¹^ORCID

Affiliation:

1. Department of Computer Engineering, Istanbul Medipol University, Istanbul, Turkey

2. Department of Computer Engineering, Ankara Medipol University, Ankara, Turkey

3. ABC Private School, Abu Dhabi, United Arab Emirates

Funder

Scientific and Technological Research Institution of Turkey

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10002336.pdf?arnumber=10002336

Reference53 articles.

1. Hybrid model for Twitter data sentiment analysis based on ensemble of dictionary based classifier and stacked machine learning classifiers-SVM, KNN and C5.0;rani;J Theor Appl Inf Technol,2020

2. Preventing Student Dropout in Distance Learning Using Machine Learning Techniques

3. Predicting at-Risk Students at Different Percentages of Course Length for Early Intervention Using Machine Learning Models

4. Predicting Students’ Performance With School and Family Tutoring Using Generative Adversarial Network-Based Deep Support Vector Machine

5. Ensemble Methods

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