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About
Prof. Alyssa Wise
Director, NYU Learning Analytics Research Network (NYU-LEARN)
Professor of Learning Sciences & Educational Technology
New York University
Dr Alyssa Wise is Associate Professor of Learning Sciences and Educational Technology at New York University and the Director of LEARN, NYU’s pioneering university-wide Learning Analytics Research Network. She holds a Ph.D. in Learning Sciences and an M.S. in Instructional Systems Technology from Indiana University as well as a B.S. in Chemistry from Yale University. Dr Wise’s research is situated at the intersection of learning and educational data sciences, focusing on the design of innovative analytics systems that are theoretically grounded, computationally robust, and pedagogically useful for informing teaching and learning. Drawing on almost twenty years of experience designing educational tools and developing methods and metrics to evaluate learning, she examines how we can best use the data generated through online activity to enhance students’ learning experiences. Dr Wise serves as Co-Editor-in-Chief of the Journal of Learning Analytics, is a Co-Editor of the Handbook of Learning Analytics and has produced numerous high-impact publications on the identification and application of useful traces of learning to inform educational decision-making.
Keynote Topic
Applying Advances in Data Technologies to Rehabilitation Education
Brief
Recent advances in data about learning and the technologies available to analyze them are enabling production of timely new insights that can support teaching. Commonly referred to as Learning Analytics, systems are being built to collect, process and feed-back information about teaching and learning to educators and students while their activities are still in progress. But what kinds of things can (and can’t) easily available data tell us? What insights can investment in more sophisticated data collection and analysis produce? Equally importantly, how can instructors, students, advisors, administrators practically use this kind of information to make better decisions? And what considerations need to be taken into account at an institutional level in order for such efforts to be successful? Drawing on the rich ecosystem of learning analytics we have built over the last five years at NYU as well as more broadly from work in the field, I will address this collection of questions as a starting point for considering rehabilitation education’s changing relationships with data and digital technologies.