Azevedo, Lester Receive NSF Award for Intelligent Virtual Humans Research
Dr. James Lester, Distinguished Professor of Computer Science and Director of the Center for Educational Informatics (pictured at right), and Dr. Roger Azevedo, Professor of Psychology, have been awarded $1,365,603 by the National Science Foundation (NSF) to support their research proposal entitled “The Effectiveness of Intelligent Virtual Humans in Facilitating Self-Regulated Learning in STEM with MetaTutor.”
The award will run from September 1, 2014 to August 31, 2017.
Abstract – Intelligent virtual humans (IVHs) are able to connect with real people in powerful, meaningful, and complex ways. They can mimic the behavior of real people and therefore add a rich social dimension to computer interactions, providing not only a wealth of information but presenting information in more personals ways. This 3-year project will focus on testing the effectiveness of IVHs in facilitating college students’ self-regulated learning in STEM with MetaTutor. More specifically, we plan to test IVHs detection, monitoring, and modeling (both facially and verbally) the temporal dynamics of learners’ self-regulatory processes to enhance learners’ deployment of effective learning strategies, accurate metacognitive judgments, and appraisals of emotional states. This will be accomplished by aligning and conducting complex computational and statistical analyses of a multitude of trace data (e.g., log-files, eye-tracking), behavioral (e.g., human-virtual human dialogue moves), physiological measures (e.g., GSR, ECG, EEG), and learning outcome data collected in real-time.
The proposed research, in the context of using IVHs, is extremely challenging and will help us to better understand the nature and temporal dynamics of these processes, how they contribute to various types of learning, and provide the empirical basis for designing intelligent virtual human systems. The results from this grant will contribute significantly to models and theories of social, cognitive, and physiological bases of human-virtual human interactions; statistical and computational methods to make inferences from complex multi-channel data; theoretical and conceptual understanding of temporally-aligned data streams, and enhancing students understanding of complex science topics by making more sensitive and intelligent virtual humans.
For more information on Dr. Lester, click here.
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