Automated Student Model Improvement. - Kenneth R. Koedinger; Elizabeth A. McLaughlin; John C. Stamper (EDM, 2012)

Using Data-Driven Discovery of Better Student Models to Improve Student Learning. - Kenneth R. Koedinger; John C. Stamper; Elizabeth A. McLaughlin; Tristan Nixon (AIED, 2013)

A Comparison of Model Selection Metrics in DataShop. - John C. Stamper; Kenneth R. Koedinger; Elizabeth A. McLaughlin (EDM, 2013)

New Potentials for Data-Driven Intelligent Tutoring System Development and Optimization. - Kenneth R. Koedinger; Emma Brunskill; Ryan Shaun Joazeiro de Baker; Elizabeth A. McLaughlin; John C. Stamper (AI Mag., 2013)

Interpreting model discovery and testing generalization to a new dataset. - Ran Liu 008; Elizabeth A. McLaughlin; Kenneth R. Koedinger (EDM, 2014)

Data-driven Learner Modeling to Understand and Improve Online Learning: MOOCs and technology to advance learning and learning research (Ubiquity symposium). - Kenneth R. Koedinger; Elizabeth A. McLaughlin; John C. Stamper (Ubiquity, 2014)

Methods for Evaluating Simulated Learners: Examples from SimStudent. - Kenneth R. Koedinger; Noboru Matsuda; Christopher J. MacLellan; Elizabeth A. McLaughlin (AIED Workshops, 2015)

Learning is Not a Spectator Sport: Doing is Better than Watching for Learning from a MOOC. - Kenneth R. Koedinger; Jihee Kim; Julianna Zhuxin Jia; Elizabeth A. McLaughlin; Norman L. Bier (L@S, 2015)

Closing the Loop with Quantitative Cognitive Task Analysis. - Kenneth R. Koedinger; Elizabeth A. McLaughlin (EDM, 2016)

Is the doer effect a causal relationship?: how can we tell and why it's important. - Kenneth R. Koedinger; Elizabeth A. McLaughlin; Julianna Zhuxin Jia; Norman L. Bier (LAK, 2016)

Is there an explicit learning bias? Students beliefs, behaviors and learning outcomes. - Paulo F. Carvalho; Elizabeth A. McLaughlin; Ken Koedinger (CogSci, 2017)

Explanatory learner models: Why machine learning (alone) is not the answer. - Carolyn P. Rosé; Elizabeth A. McLaughlin; Ran Liu 008; Kenneth R. Koedinger (Br. J. Educ. Technol., 2019)

A General Multi-method Approach to Design-Loop Adaptivity in Intelligent Tutoring Systems. - Yun Huang 002; Vincent Aleven; Elizabeth A. McLaughlin; Kenneth R. Koedinger (AIED (2), 2020)

Computer-Supported Human Mentoring for Personalized and Equitable Math Learning. - Peter Schaldenbrand; Nikki G. Lobczowski; J. Elizabeth Richey; Shivang Gupta; Elizabeth A. McLaughlin; Adetunji Adeniran; Kenneth R. Koedinger (AIED (2), 2021)

A General Multi-method Approach to Data-Driven Redesign of Tutoring Systems. - Yun Huang 002; Nikki G. Lobczowski; J. Elizabeth Richey; Elizabeth A. McLaughlin; Michael W. Asher; Judith M. Harackiewicz; Vincent Aleven; Kenneth R. Koedinger (LAK, 2021)

Item Response Theory-Based Gaming Detection. - Yun Huang 002; Steven Dang; J. Elizabeth Richey; Michael W. Asher; Nikki G. Lobczowski; Danielle R. Chine; Elizabeth A. McLaughlin; Judith M. Harackiewicz; Vincent Aleven; Kenneth R. Koedinger (EDM, 2022)

When the Tutor Becomes the Student: Design and Evaluation of Efficient Scenario-based Lessons for Tutors. - Danielle Thomas; Xinyu Yang; Shivang Gupta; Adetunji Adeniran; Elizabeth A. McLaughlin; Kenneth R. Koedinger (LAK, 2023)

Using latent variable models to make gaming-the-system detection robust to context variations. - Yun Huang 002; Steven Dang; J. Elizabeth Richey; Pallavi Chhabra; Danielle R. Thomas; Michael W. Asher; Nikki G. Lobczowski; Elizabeth A. McLaughlin; Judith M. Harackiewicz; Vincent Aleven; Kenneth R. Koedinger (User Model. User Adapt. Interact., 2023)

Beyond Repetition: The Role of Varied Questioning and Feedback in Knowledge Generalization. - Gautam Yadav; Paulo F. Carvalho; Elizabeth A. McLaughlin; Kenneth R. Koedinger (L@S, 2024)