Machine Learning in Higher Education: Students’ Performance Assessment Considering Online Activity Logs-Reference-Cited by-同舟云学术

Machine Learning in Higher Education: Students’ Performance Assessment Considering Online Activity Logs

Published:2023 Issue: Volume:11 Page:69586-69600
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Latif Ghazanfar¹^ORCID,Abdelhamid Sherif E.²^ORCID,Fawagreh Khaled S.¹,Brahim Ghassen Ben¹^ORCID,Alghazo Runna³

Affiliation:

1. Department of Computer Science, Prince Mohammad Bin Fahd University, Khobar, Saudi Arabia

2. Department of Computer and Information Sciences, Virginia Military Institute, Lexington, VA, USA

3. Department of Education, Health, and Behavioral Studies (EHBS), University of North Dakota, Grand Forks, ND, USA

Funder

Commonwealth Cyber Initiative, an investment in the advancement of cyber research and development, innovation, and workforce development

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/ielx7/6287639/10005208/10156839.pdf?arnumber=10156839

Reference46 articles.

1. Predicting student dropout in higher education;aulck;arXiv 1606 06364,2016

2. A systematic review of fundamental and technical analysis of stock market predictions

3. A Learning Performance Assessment Model Using Neural Network Classification Methods of e-Learning Activity Log Data

4. Predicting student grade based on free-style comments using Word2Vec and ANN by considering prediction results obtained in consecutive lessons;luo;International Educational Data Mining Society,2015

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