Name
Title | ||
|---|---|---|
Graph-based Massive Open Online Course (MOOC) Dropout Prediction using Clickstream Data in Virtual Learning Environment |
Abstract | ||
|---|---|---|
Although the field of massive open online course (MOOC) is expanding, it faces the challenge of high dropout rate. To ensure continued learning by students, it is important to conduct an analysis based on a dropout prediction model that utilizes student behavior history data. In this paper, we propose a dropout prediction model using graph-based machine learning involving graph-structured relation... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICCSE51940.2021.9569582 | 2021 16th International Conference on Computer Science & Education (ICCSE) |
Keywords | DocType | ISBN |
Computer aided instruction,Analytical models,Electronic learning,Tensors,Machine learning algorithms,Machine learning,Predictive models | Conference | 978-1-6654-1468-5 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Izumi Nitta | 1 | 0 | 0.34 |
| Ryo Ishizaki | 2 | 0 | 0.34 |
| Masafumi Shingu | 3 | 0 | 0.34 |
| Satoshi Nakashima | 4 | 0 | 0.34 |
| Koji Maruhashi | 5 | 0 | 1.35 |
| Arseny Tolmachev | 6 | 0 | 1.35 |
| Masaru Todoriki | 7 | 0 | 1.01 |