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AIM Analytics: Perpetually Improving Educational Technology

November 6 @ 12:00 pm - 1:30 pm

Perpetually Improving Educational Technology: MOOClets for Collaborative, Dynamic, Personalized Experimentation presented by Joseph Jay Williams.

Join us on Monday, November 6 from 12:00 p.m. to 1:30 p.m.  at North Quad Space 2435 (105 South State Street.) for AIM Analytics.

AIM Analytics was created to bridge the gaps in the support of UM learning analytics researchers with respect to the building of technical skills, sharing knowledge of educational datasets, and facilitating collaborative investigations.

Abstract:

How can we use data from real-world users to rapidly enhance and personalize real-world educational technologies? Joseph will show  how we can build self-improving systems through three applications of MOOClets, a conceptual framework implemented in technology that leverages randomized A/B experiments as tools for collaboration, dynamic enhancement, and adaptive personalization. Joseph will also discuss future directions in residential courses and MOOCs, such as investigating which reflection prompts help students learn, how to enhance motivation through social-psychological interventions, and how to personalize web-apps that help students set and achieve micro-goals.

Bio:

Joseph Jay WilliamsJoseph Jay Williams is an Assistant Professor at the National University of Singapore’s School of Computing, department of Information Systems & Analytics, and a core faculty at the Institute for the Application of Learning Sciences and Educational Technology. He was previously a Research Fellow at Harvard’s Office of the Vice Provost for Advances in Learning, and a member of the Intelligent Interactive Systems Group in Computer Science. He completed a postdoc at Stanford University in the Graduate School of Education in Summer 2014, working with the Office of the Vice Provost for Online Learning and the Open Learning Initiative. He received his PhD from UC Berkeley in Computational Cognitive Science, where he applied Bayesian statistics and machine learning to model how people learn and reason. He received his B.Sc. from University of Toronto in Cognitive Science, Artificial Intelligence and Mathematics, and is originally from Trinidad and Tobago. More information about his research and papers is at www.josephjaywilliams.com.

Lunch will be provided.

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Details

Date:
November 6
Time:
12:00 pm - 1:30 pm
Event Categories:
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Venue

2435 North Quad
105 S State St.
Ann Arbor, MI 48109 United States
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