131 citations · 189 across the 3 of their papers we have counts for
3 papers
Likely to stop? Predicting Stopout in Massive Open Online Courses
Colin Taylor, Kalyan Veeramachaneni, Una-May O'Reilly
Understanding why students stopout will help in understanding how students learn in MOOCs. In this report, part of a 3 unit compendium, we describe how we build accurate predictive…
Towards Feature Engineering at Scale for Data from Massive Open Online Courses
Kalyan Veeramachaneni, Una-May O'Reilly, Colin Taylor
We examine the process of engineering features for developing models that improve our understanding of learners' online behavior in MOOCs. Because feature engineering relies so hea…
MOOCdb: Developing Standards and Systems to Support MOOC Data Science
Kalyan Veeramachaneni, Sherif Halawa, Franck Dernoncourt +3
We present a shared data model for enabling data science in Massive Open Online Courses (MOOCs). The model captures students interactions with the online platform. The data model i…