Cited by 170Online Learning and AnalyticsEvasion and Academic Success FactorsOnline and Blended Learning

Prediction of students’ early dropout based on their interaction logs in online learning environment

Mubarak, Ahmed A., Cao, Han, Zhang, Weizhen·2022·Interactive Learning Environments

Abstract

Online learning has become more popular in higher education since it adds convenience and flexibility to students’ schedule. But, it has faced difficulties in the retention of the continuity of students and ensure continual growth in course. Dropout is a concerning factor in online course continuity. Therefore, it has sparked great interest among educators and researchers to offer many models and strategies to reduce online course students’ dropout by analyzing students’ behavior and their individual and academic information. However, online education platforms still face challenges of high dropout rate and the difficulty of accurate prediction to reduce it. The key aim of the present study is to construct a predictive model to early predict students who are at-risk of dropout. This model is useful to the course instructors to make effective and timely interventions. We have noticed that dropout prediction is basically a sequence labeling or time series prediction problem. For these reasons, we proposed two models; the Logistic Regression by adding a regularization term and the Input-Output Hidden Markov Model (IOHMM). Results showed that the proposed models achieved an accuracy of 84% compared to the baseline of Machine Learning Models for prediction of the students at-risk of dropping out.

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Crossref · 10.1080/10494820.2020.1727529

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Authors
Mubarak, A. A., Cao, H., & Zhang, W.
Affiliations
  • Ibb University (YE)
  • Shaanxi Normal University (CN)
  • School of Computer and Science, Shaanxi Normal University, Xian, People’s Republic of China
Corresponding author
Cao, Han
Venue
Interactive Learning Environments
Published
2020-02-19
Volume
30
Issue
8
Pages
1414-1433
ISSN
  • 1049-4820 (ISSN-L)
  • 1744-5191
OpenAlex
W3007158916
Cited by
170
References
44
Citations by year
2026: 20 · 2025: 22 · 2024: 37 · 2023: 36 · 2022: 31 · 2021: 17 · 2020: 7
FWCI
20.90
Type
journal article
Language
en
Open access
closed
Locations
Interactive Learning Environments (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
  • Social Sciences › Demography › Evasion and Academic Success Factors
  • Social Sciences › Education › Online and Blended Learning
Keywords
student dropout prediction, early dropout, online learning, at-risk students, interaction logs, student retention, higher education, logistic regression, input-output hidden Markov model, sequence labeling, time series forecasting

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