Performance Prediction of Students in Higher Education Using Multi-Model Ensemble Approach-Reference-Cited by-同舟云学术

Performance Prediction of Students in Higher Education Using Multi-Model Ensemble Approach

Published:2023 Issue: Volume:11 Page:136091-136108
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Butt Naveed Anwer¹^ORCID,Mahmood Zafar¹,Shakeel Khawar¹,Alfarhood Sultan²^ORCID,Safran Mejdl²^ORCID,Ashraf Imran³^ORCID

Affiliation:

1. Department of Computer Science, University of Gujrat, Gujrat, Pakistan

2. Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

3. Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, Republic of Korea

Funder

Researchers Supporting Project Number

King Saud University, Riyadh, Saudi Arabia

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/ielx7/6287639/10005208/10328829.pdf?arnumber=10328829

Reference71 articles.

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4. Revealing online learning behaviors and activity patterns and making predictions with data mining techniques in online teaching;Hung;MERLOT J. Online Learn. Teach.,2008

5. Linking learning behavior analytics and learning science concepts: Designing a learning analytics dashboard for feedback to support learning regulation

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