Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 0 |
| Since 2016 (last 10 years) | 1 |
| Since 2006 (last 20 years) | 1 |
Descriptor
| Computer Science Education | 1 |
| Educational Technology | 1 |
| Humanities Instruction | 1 |
| Large Group Instruction | 1 |
| Markov Processes | 1 |
| Models | 1 |
| Online Courses | 1 |
| Probability | 1 |
| Student Behavior | 1 |
| Technology Uses in Education | 1 |
Source
| Journal of Educational Data… | 1 |
Author
| Geigle, Chase | 1 |
| Zhai, ChengXiang | 1 |
Publication Type
| Journal Articles | 1 |
| Reports - Descriptive | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full textGeigle, Chase; Zhai, ChengXiang – Journal of Educational Data Mining, 2017
Massive open online courses (MOOCs) provide educators with an abundance of data describing how students interact with the platform, but this data is highly underutilized today. This is in part due to the lack of sophisticated tools to provide interpretable and actionable summaries of huge amounts of MOOC activity present in log data. To address…
Descriptors: Large Group Instruction, Online Courses, Educational Technology, Technology Uses in Education
