Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 0 |
| Since 2007 (last 20 years) | 1 |
Descriptor
| Accuracy | 1 |
| Bayesian Statistics | 1 |
| Expectation | 1 |
| Markov Processes | 1 |
| Maximum Likelihood Statistics | 1 |
| Monte Carlo Methods | 1 |
| Online Courses | 1 |
| Student Behavior | 1 |
Source
| International Educational… | 1 |
Publication Type
| Reports - Research | 1 |
| Speeches/Meeting Papers | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full textFaucon, Louis; Kidzinski, Lukasz; Dillenbourg, Pierre – International Educational Data Mining Society, 2016
Large-scale experiments are often expensive and time consuming. Although Massive Online Open Courses (MOOCs) provide a solid and consistent framework for learning analytics, MOOC practitioners are still reluctant to risk resources in experiments. In this study, we suggest a methodology for simulating MOOC students, which allow estimation of…
Descriptors: Markov Processes, Monte Carlo Methods, Bayesian Statistics, Online Courses
