Publication Date
| In 2026 | 0 |
| Since 2025 | 1 |
| Since 2022 (last 5 years) | 3 |
| Since 2017 (last 10 years) | 3 |
| Since 2007 (last 20 years) | 3 |
Descriptor
| Academic Achievement | 3 |
| Algorithms | 3 |
| Learner Engagement | 3 |
| Models | 3 |
| Prediction | 3 |
| Electronic Learning | 2 |
| Learning Analytics | 2 |
| Accuracy | 1 |
| Artificial Intelligence | 1 |
| Cognitive Ability | 1 |
| College Students | 1 |
| More ▼ | |
Author
| Badal, Yudish Teshal | 1 |
| Haibin Zhu | 1 |
| Hua Ma | 1 |
| Keqin Li | 1 |
| Khaled Shaalan | 1 |
| Maha Salem | 1 |
| Peiji Huang | 1 |
| Sungkur, Roopesh Kevin | 1 |
| Wen Zhao | 1 |
| Wensheng Tang | 1 |
| Yuqi Tang | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 3 |
| Reports - Research | 2 |
| Information Analyses | 1 |
| Reports - Descriptive | 1 |
Education Level
| Higher Education | 1 |
| Postsecondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Maha Salem; Khaled Shaalan – Education and Information Technologies, 2025
The proliferation of digital learning platforms has revolutionized the generation, accessibility, and dissemination of educational resources, fostered collaborative learning environments and producing vast amounts of interaction data. Machine learning (ML) algorithms have emerged as powerful tools for analyzing these complex datasets, uncovering…
Descriptors: Electronic Learning, Prediction, Models, Educational Technology
Badal, Yudish Teshal; Sungkur, Roopesh Kevin – Education and Information Technologies, 2023
The outbreak of COVID-19 has caused significant disruption in all sectors and industries around the world. To tackle the spread of the novel coronavirus, the learning process and the modes of delivery had to be altered. Most courses are delivered traditionally with face-to-face or a blended approach through online learning platforms. In addition,…
Descriptors: Prediction, Models, Learning Analytics, Grades (Scholastic)
Hua Ma; Wen Zhao; Yuqi Tang; Peiji Huang; Haibin Zhu; Wensheng Tang; Keqin Li – IEEE Transactions on Learning Technologies, 2024
To prevent students from learning risks and improve teachers' teaching quality, it is of great significance to provide accurate early warning of learning performance to students by analyzing their interactions through an e-learning system. In existing research, the correlations between learning risks and students' changing cognitive abilities or…
Descriptors: College Students, Learning Analytics, Learning Management Systems, Academic Achievement

Peer reviewed
Direct link
