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organised by Assessment Research Centre of EdUHK
Invited Speakers -
Dr. Zhiqiang CAI
Dr. Zhiqiang CAI
Research Assistant Professor @
Institute for Intelligent Systems,
The University of Memphis
USA
Topic of Presentation:
AutoTutor: Creating Your Own Conversational Intelligent Tutoring Systems
Speaker Bio:
Zhiqiang Cai is presently a research assistant professor in the Institute of Intelligent Systems at the University of Memphis. Cai received his M.S. in mathematics from Huazhong University of Science and Technology and was an associate professor at Huazhong University of Science and Technology, a visiting associate professor at the University of Paris VI, a visiting associate professor at Sudan University for Science and Technology. His has 15 years teaching experiences in universities. Since 2001, he shifted his work from teaching to developing software that involves mathematical modeling in linguistics and cognition. He is the chief software designer and developer of QUAID, AutoTutor, Coh-Metrix, MetaTutor, Operation ARA, WPAL, ACE, ASAT, ASAT-V, CSAL-AutoTutor, ElectronixTutor, and more. He is an author/co-author of over 100 publications.
Abstract:
AutoTutor is a conversational intelligent tutoring system that has been developed for decades in the Institute for Intelligent Systems at the University of Memphis, USA. Delivering content with conversation is always attractive to content authors and students. Research has shown that delivering content through conversations is more effective than presenting a text. The AutoTutor team in the Institute for Intelligent systems (IIS) at the University of Memphis has been developing AutoTutor systems since 1990s. About a dozen of conversational ITSs have been successfully developed, including computer literacy tutor, conceptual physics tutor, critical thinking tutor (Operation ARA), adult literacy tutor (CSAL), electronics tutor (ElectornixTutor), and more. AutoTutor helps students learn by holding deep reasoning conversations. An AutoTutor conversation often starts with a main question about a certain topic. The goal of the conversation is to help students construct an acceptable answer to the main question. Instead of telling the students the answers, AutoTutor asks a sequence of questions (hints, prompts) that target specific concepts involved in the ideal answers to the main questions. AutoTutor systems respond to students' natural language input, as well as other interactions, such as making a choice, arranging some objects in the learning environment, etc. This workshop focuses on the authoring process of AutoTutor lessons. Participants of this workshop will have access to AutoTutor authoring tool and have the opportunity to learn how to create one’s own AutoTutor lesson.
Site to visit: http://alttai.x-in-y.com/course/view.php?id=23
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