Answer Quality Aware Aggregation for Extractive QA Crowdsourcing

Quality control is essential for creating extractive question answering (EQA) datasets via crowdsourcing. Aggregation across answers, i.e. word spans within passages annotated, by different crowd workers is one major focus for ensuring its quality. However, crowd workers cannot reach a consensus on a considerable portion of questions. We...

MOOC-Rec: Instructional Video Clip Recommendation for MOOC Forum Questions

In this work, we address the information overload issue that learners in Massive Open Online Courses (MOOCs) face when attempting to close their knowledge gaps via the use of MOOC discussion forums. To this end, we investigate the recommendation of one-minute-resolution video clips given the textual similarity between the clips’ transcripts...