| 2019 | EDM | Towards a General Purpose Anomaly Detection Method to Identify Cheaters in Massive Open Online Courses. | Giora Alexandron, Jos A. Ruiprez-Valiente, David E. Pritchard |
| 2018 | EDM | Mining Student Misconceptions from Pre- and Post-Testing Data. | ngel Prez-Lemonche, Byron Drury, David E. Pritchard |
| 2016 | EDM | Examining the necessity of problem diagrams using MOOC AB experiments. | Zhongzhou Chen, Neset Demirci, David E. Pritchard |
| 2015 | EDM | Discovering the Pedagogical Resources that Assist Students to Answer Questions Correctly - A Machine Learning Approach. | Giora Alexandron, Qian Zhou, David E. Pritchard |
| 2015 | EDM | Methodological Challenges in the Analysis of MOOC Data for Exploring the Relationship between Discussion Forum Views and Learning Outcomes. | Yoav Bergner, Deirdre Kerr, David E. Pritchard |
| 2015 | LAK | Estimation of ability from homework items when there are missing and/or multiple attempts. | Yoav Bergner, Kimberly F. Colvin, David E. Pritchard |
| 2014 | EDM | Comparing Learning in a MOOC and a Blended, On-Campus Course. | Kimberly F. Colvin, John Champaign, Alwina Liu, Colin Fredericks, David E. Pritchard |
| 2013 | AIED | Analysis of Video Use in edX Courses. | Daniel T. Seaton, Albert J. Rodenius, Cody A. Coleman, David E. Pritchard, Isaac L. Chuang |
| 2013 | EDM | Bringing student backgrounds online: MOOC user demographics, site usage, and online learning. | Jennifer DeBoer, Glenda S. Stump, Daniel T. Seaton, Andrew D. Ho, David E. Pritchard, Lori Breslow |
| 2013 | EDM | Adapting Bayesian Knowledge Tracing to a Massive Open Online Course in edX. | Zachary A. Pardos, Yoav Bergner, Daniel T. Seaton, David E. Pritchard |
| 2013 | EDM | Exploring the relationship between course structure and etext usage in blended and open online courses. | Daniel T. Seaton, Yoav Bergner, David E. Pritchard |
| 2013 | LAK | Towards Real-Time Analytics in MOOCs. | Daniel T. Seaton, Yoav Bergner, Isaac L. Chuang, Piotr Mitros, David E. Pritchard |
| 2012 | EDM | Model-Based Collaborative Filtering Analysis of Student Response Data: Machine-Learning Item Response Theory. | Yoav Bergner, Stefan Drschler, Gerd Kortemeyer, Saif Rayyan, Daniel T. Seaton, David E. Pritchard |