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Keynote Speakers -

Prof. Xiangen HU

Prof. Xiangen HU

Professor in Experimental (Cognitive) Psychology @

Department of Psychology

The University of Memphis

USA

Professor of Psychology, Institute for Intelligent Systems, The University of Memphis

Professor of Electrical and Computer Engineering, Professor of Computer Science, The University of Memphis

​Dean & Professor, School of Psychology, Central China Normal University

Topic of Presentation:

AutoTutor: an example of Conversation Based Intelligent Tutoring System

Speaker Bio: 

Dr. Xiangen Hu is a professor in the Department of Psychology, Department of Electrical and Computer Engineering and Computer Science Department at The University of Memphis (UofM) and senior researcher at the Institute for Intelligent Systems (IIS) at the UofM and is professor and Dean of the School of Psychology at Central China Normal University (CCNU). Dr. Hu received his MS in applied mathematics from Huazhong University of Science and Technology, MA in social sciences and Ph.D. in Cognitive Sciences from the University of California, Irvine. Dr. Hu is the Director of Advanced Distributed Learning (ADL) Partnership Laboratory at the UofM, and is a senior researcher in the Chinese Ministry of Education’s Key Laboratory of Adolescent Cyberpsychology and Behavior.

Abstract: 

AutoTutor, an implementation of Conversation-Based Intelligent Tutoring Systems (ITS)
Abstract: AutoTutor started as a flagship application at the Institute of Intelligent Systems (IIS) of the University of Memphis 20 years ago. It started as an application that taught computer literacy in college. Now it is a well-studied, understood, and implementable framework for advanced learning environment. In the past 20 years, there have been major research funding on AutoTutor Research and Development (Over $35 Million US Federal Funding). In this talk, I will talk about three aspects of AutoTutor: 1) selected cognitive theories of learning that served as theoretical foundations of AutoTutor, 2) Enabling technologies that make AutoTutor work, 3) Example applications of AutoTutor in different domains.
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