Name
Abstract | ||
|---|---|---|
We systematically confirm that instructors are strongly influenced by the user interface presentation of Massive Online Open Course (MOOC) discussion forums. In a large scale dataset, we conclusively show that instructor interventions exhibit strong position bias, as measured by the position where the thread appeared on the user interface at the time of intervention. We measure and remove this bias, enabling unbiased statistical modelling and evaluation. We show that our de-biased classifier improves predicting interventions over the state-of-the-art on courses with sufficient number of interventions by 8.2% in F-1 and 24.4% in recall on average. |
Year | Venue | Field |
|---|---|---|
2018 | NATURAL LANGUAGE PROCESSING TECHNIQUES FOR EDUCATIONAL APPLICATIONS | Psychological intervention,Computer science,Mathematics education,Natural language processing,Artificial intelligence |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Muthu Kumar Chandrasekaran | 1 | 0 | 0.68 |
| Min-yen Kan | 2 | 2786 | 162.35 |