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- short-paperJuly 2024
Beyond Repetition: The Role of Varied Questioning and Feedback in Knowledge Generalization
L@S '24: Proceedings of the Eleventh ACM Conference on Learning @ ScaleJuly 2024, Pages 451–455https://doi.org/10.1145/3657604.3664688This study examines the effects of question type and feedback on learning outcomes in a hybrid graduate-level course. By analyzing data from 32 students over 30,198 interactions, we assess the efficacy of unique versus repeated questions and the impact ...
- research-articleMay 2023
Using latent variable models to make gaming-the-system detection robust to context variations
- Yun Huang,
- 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 Modeling and User-Adapted Interaction (KLU-USER), Volume 33, Issue 5Nov 2023, Pages 1211–1257https://doi.org/10.1007/s11257-023-09362-1AbstractGaming the system, a behavior in which learners exploit a system’s properties to make progress while avoiding learning, has frequently been shown to be associated with lower learning. However, when we applied a previously validated gaming detector ...
- research-articleMarch 2023
When the Tutor Becomes the Student: Design and Evaluation of Efficient Scenario-based Lessons for Tutors
LAK2023: LAK23: 13th International Learning Analytics and Knowledge ConferenceMarch 2023, Pages 250–261https://doi.org/10.1145/3576050.3576089Tutoring is among the most impactful educational influences on student achievement, with perhaps the greatest promise of combating student learning loss. Due to its high impact, organizations are rapidly developing tutoring programs and discovering a ...
- ArticleJune 2021
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
Artificial Intelligence in EducationJun 2021, Pages 308–313https://doi.org/10.1007/978-3-030-78270-2_55 - research-articleApril 2021
A General Multi-method Approach to Data-Driven Redesign of Tutoring Systems
- Yun Huang,
- Nikki G. Lobczowski,
- J. Elizabeth Richey,
- Elizabeth A. McLaughlin,
- Michael W. Asher,
- Judith M. Harackiewicz,
- Vincent Aleven,
- Kenneth R. Koedinger
LAK21: LAK21: 11th International Learning Analytics and Knowledge ConferenceApril 2021, Pages 161–172https://doi.org/10.1145/3448139.3448155Analytics of student learning data are increasingly important for continuous redesign and improvement of tutoring systems and courses. There is still a lack of general guidance on converting analytics into better system design, and on combining ...
- ArticleJuly 2020
A General Multi-method Approach to Design-Loop Adaptivity in Intelligent Tutoring Systems
Artificial Intelligence in EducationJul 2020, Pages 124–129https://doi.org/10.1007/978-3-030-52240-7_23AbstractDesign-loop adaptivity, which involves data-driven redesign of an instructional system based on student learning data, has shown promise in improving student learning. We present a general, systematic approach that combines new and existing data ...
- research-articleApril 2016
Is the doer effect a causal relationship?: how can we tell and why it's important
LAK '16: Proceedings of the Sixth International Conference on Learning Analytics & KnowledgeApril 2016, Pages 388–397https://doi.org/10.1145/2883851.2883957The "doer effect" is an association between the number of online interactive practice activities students' do and their learning outcomes that is not only statistically reliable but has much higher positive effects than other learning resources, such as ...
- research-articleMarch 2015
Learning is Not a Spectator Sport: Doing is Better than Watching for Learning from a MOOC
L@S '15: Proceedings of the Second (2015) ACM Conference on Learning @ ScaleMarch 2015, Pages 111–120https://doi.org/10.1145/2724660.2724681The printing press long ago and the computer today have made widespread access to information possible. Learning theorists have suggested, however, that mere information is a poor way to learn. Instead, more effective learning comes through doing. While ...
- forumMay 2014
Data-driven Learner Modeling to Understand and Improve Online Learning: MOOCs and technology to advance learning and learning research (Ubiquity symposium)
Ubiquity (UBIQUITY), Volume 2014, Issue MayMay 2014, Article No.: 3, Pages 1–13https://doi.org/10.1145/2591682Advanced educational technologies are developing rapidly and online MOOC courses are becoming more prevalent, creating an enthusiasm for the seemingly limitless data-driven possibilities to affect advances in learning and enhance the learning ...
- research-articleSeptember 2013
New Potentials for Data‐Driven Intelligent Tutoring System Development and Optimization
AI Magazine (AIMA), Volume 34, Issue 3Fall 2013, Pages 27–41https://doi.org/10.1609/aimag.v34i3.2484Increasing widespread use of educational technologies is producing vast amounts of data. Such data can be used to help advance our understanding of student learning and enable more intelligent, interactive, engaging, and effective education. In this ...