Name
Title | ||
|---|---|---|
Automating open educational resources assessments: a machine learning generalization study |
Abstract | ||
|---|---|---|
Assessing the quality of online educational resources in a cost effective manner is a critical issue for educational digital libraries. This study reports on the approach for extending the Open Educational Resource Assessments (OPERA) algorithm from assessing vetted to peer-produced content. This article reports details of changes to the algorithm, comparisons between human raters and the algorithm, and the extent the algorithm can automate the review process. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/1998076.1998129 | JCDL |
Keywords | DocType | Citations |
cost effective manner,study report,open educational resources assessment,open educational resource assessments,peer-produced content,online educational resource,critical issue,human raters,educational digital library,article reports detail,generalization study,review process,cost effectiveness,digital library,online education,machine learning | Conference | 0 |
PageRank | References | Authors |
0.34 | 5 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Heather Leary | 1 | 9 | 1.65 |
| Mimi Recker | 2 | 108 | 54.75 |
| Andrew Walker | 3 | 45 | 14.93 |
| Philipp G. Wetzler | 4 | 7 | 1.90 |
| Tamara Sumner | 5 | 614 | 100.91 |
| James Martin | 6 | 153 | 10.17 |