Using Educational Data Science to Improve Learning in the University

Event details
Date | 15.01.2018 |
Hour | 11:15 › 12:00 |
Speaker | Alyssa Friend Wise is Associate Professor of Learning Sciences and Educational Technology in the Steinhardt School of Culture, Education, and Human Development. She holds a Ph.D. in the Learning Sciences and M.S. in Instructional Systems Technology, both from Indiana University, and a B. S. in Chemistry from Yale University. Wise's research is situated at the intersection of the learning sciences and educational data science, focusing on the design of learning analytics systems that are theoretically grounded, computationally robust, and pedagogically useful for informing teaching and learning. She has published extensively on the identification of useful traces of learning in large data sets and the application of these to inform educational decision-making by designers, instructors and students. She has also conducted influential research on the design of computer-supported collaborative learning systems in both online and physical environments and is particularly known for her pioneering work conceptualizing and researching learners' online listening behaviors. Wise is a member of the Executive Committee of the Society for Learning Analytics Research and the Computer-Supported Collaborative Learning Committee within in the International Society of the Learning Sciences. She serves on numerous journal editorial boards and in 2017 will become one of the principal editors of the Journal of Learning Analytics. Previously Wise was an Associate Professor and Coordinator of the Educational Technology & Learning Design Programs at Simon Fraser University in Canada. Her work has been extensively funded by the Social Sciences and Humanities Research Council of Canada and widely recognized for its contributions to the learning sciences and learning analytics literature. |
Location | |
Category | Conferences - Seminars |
There are many exciting opportunities to use educational data science to understand and inform teaching and learning in a university. In this presentation I will introduce LEARN, NYU’s new Learning Analytics Research Network and describe three of our exciting initial projects to develop data-based practices. The MOOCeology Project offers insight into online collaboration and how to support it. The Calculus Lifeline Project supports early detection and support for students likely to struggle. The Instructor Dashboard Project studies how instructors are starting to use data to inform their teaching activities. Each project will be showcased in the context of institutional challenges and strategies involved in launching a university wide analytics research network.
Practical information
- Informed public
- Free
- This event is internal