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2010 – 2019
- 2019
[j8]Giora Alexandron
, Lisa Y. Yoo, José A. Ruipérez Valiente, Sunbok Lee, David E. Pritchard:
Are MOOC Learning Analytics Results Trustworthy? With Fake Learners, They Might Not Be! Int. J. Artif. Intell. Educ. 29(4): 484-506 (2019)- [j7]José A. Ruipérez Valiente, Pedro J. Muñoz Merino, Giora Alexandron, David E. Pritchard:
Using Machine Learning to Detect 'Multiple-Account' Cheating and Analyze the Influence of Student and Problem Features. IEEE Trans. Learn. Technol. 12(1): 112-122 (2019) - [c20]Giora Alexandron, José A. Ruipérez Valiente, David E. Pritchard:
Towards a General Purpose Anomaly Detection Method to Identify Cheaters in Massive Open Online Courses. EDM 2019 - [c19]Ángel Pérez-Lemonche, John Stewart, Byron Drury, Rachel Henderson, Alex Shvonski, David E. Pritchard:
Mining Students Pre-instruction Beliefs for Improved Learning. L@S 2019: 15:1-15:10 - 2018
- [c18]Giora Alexandron, José A. Ruipérez Valiente, Sunbok Lee, David E. Pritchard:
Evaluating the Robustness of Learning Analytics Results Against Fake Learners. EC-TEL 2018: 74-87 - [c17]Ángel Pérez-Lemonche, Byron Drury, David E. Pritchard:
Mining Student Misconceptions from Pre- and Post-Testing Data. EDM 2018 - 2017
- [j6]Giora Alexandron, José A. Ruipérez Valiente, Zhongzhou Chen, Pedro J. Muñoz Merino, David E. Pritchard:
Copying@Scale: Using Harvesting Accounts for Collecting Correct Answers in a MOOC. Comput. Educ. 108: 96-114 (2017) - [c16]Sunbok Lee, Zhongzhou Chen, David E. Pritchard, Alex Kimn, Andrew Paul:
Factor Analysis Reveals Student Thinking using the Mechanics Reasoning Inventory. L@S 2017: 197-200 - 2016
- [j5]Saif Rayyan, Colin Fredericks, Kimberly F. Colvin, Alwina Liu, Raluca Teodorescu, Analia Barrantes, Andrew Pawl, Daniel T. Seaton, David E. Pritchard:
A MOOC based on blended pedagogy. J. Comput. Assist. Learn. 32(3): 190-201 (2016) - [j4]Zhongzhou Chen, Christopher Chudzicki, Daniel Palumbo, Giora Alexandron, Youn-Jeng Choi, Qian Zhou, David E. Pritchard:
Researching for better instructional methods using AB experiments in MOOCs: results and challenges. Res. Pract. Technol. Enhanc. Learn. 11(1): 9 (2016) - [c15]Zhongzhou Chen, Neset Demirci, David E. Pritchard:
Examining the necessity of problem diagrams using MOOC AB experiments. EDM 2016: 579-580 - [c14]José A. Ruipérez Valiente, Giora Alexandron, Zhongzhou Chen, David E. Pritchard:
Using Multiple Accounts for Harvesting Solutions in MOOCs. L@S 2016: 63-70 - [c13]Giora Alexandron, Sunbok Lee, Zhongzhou Chen, David E. Pritchard:
Detecting Cheaters in MOOCs Using Item Response Theory and Learning Analytics. UMAP (Extended Proceedings) 2016 - 2015
- [c12]Yoav Bergner, Deirdre Kerr, David E. Pritchard:
Methodological Challenges in the Analysis of MOOC Data for Exploring the Relationship between Discussion Forum Views and Learning Outcomes. EDM 2015: 234-241 - [c11]Giora Alexandron, Qian Zhou, David E. Pritchard:
Discovering the Pedagogical Resources that Assist Students to Answer Questions Correctly - A Machine Learning Approach. EDM 2015: 520-523 - [c10]Yoav Bergner, Kimberly F. Colvin, David E. Pritchard:
Estimation of ability from homework items when there are missing and/or multiple attempts. LAK 2015: 118-125 - [c9]Christopher Chudzicki, David E. Pritchard, Zhongzhou Chen:
Learning Experiments Using AB Testing at Scale. L@S 2015: 405-408 - 2014
- [j3]Daniel T. Seaton, Yoav Bergner, Isaac L. Chuang, Piotr Mitros, David E. Pritchard:
Who does what in a massive open online course? Commun. ACM 57(4): 58-65 (2014) - [j2]Gerd Kortemeyer, Stefan Dröschler, David E. Pritchard:
Harvesting latent and usage-based metadata in a course management system to enrich the underlying educational digital library - A case study. Int. J. Digit. Libr. 14(1-2): 1-15 (2014) - [c8]Kimberly F. Colvin, John Champaign, Alwina Liu, Colin Fredericks, David E. Pritchard:
Comparing Learning in a MOOC and a Blended, On-Campus Course. EDM 2014: 343-344 - [c7]John Champaign, Kimberly F. Colvin, Alwina Liu, Colin Fredericks, Daniel T. Seaton, David E. Pritchard:
Correlating skill and improvement in 2 MOOCs with a student's time on tasks. L@S 2014: 11-20 - 2013
- [c6]Daniel T. Seaton, Albert J. Rodenius, Cody A. Coleman, David E. Pritchard, Isaac L. Chuang:
Analysis of Video Use in edX Courses. AIED Workshops 2013 - [c5]Zachary A. Pardos, Yoav Bergner, Daniel T. Seaton, David E. Pritchard:
Adapting Bayesian Knowledge Tracing to a Massive Open Online Course in edX. EDM 2013: 137-144 - [c4]Jennifer DeBoer, Glenda S. Stump, Daniel T. Seaton, Andrew D. Ho, David E. Pritchard, Lori Breslow:
Bringing student backgrounds online: MOOC user demographics, site usage, and online learning. EDM 2013: 312-313 - [c3]Daniel T. Seaton, Yoav Bergner, David E. Pritchard:
Exploring the relationship between course structure and etext usage in blended and open online courses. EDM 2013: 350-351 - [c2]Daniel T. Seaton, Yoav Bergner, Isaac L. Chuang, Piotr Mitros, David E. Pritchard:
Towards Real-Time Analytics in MOOCs. IWTA@LAK 2013 - 2012
- [c1]Yoav Bergner, Stefan Dröschler, Gerd Kortemeyer, Saif Rayyan, Daniel T. Seaton, David E. Pritchard:
Model-Based Collaborative Filtering Analysis of Student Response Data: Machine-Learning Item Response Theory. EDM 2012: 95-102
2000 – 2009
- 2003
- [j1]Simon Rainville, James K. Thompson, David E. Pritchard:
Two ions in one trap: ultra-high precision mass spectrometry? IEEE Trans. Instrum. Meas. 52(2): 292-296 (2003)
Coauthor Index
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