Zielke, Marjorie A.

Permanent URI for this collectionhttps://hdl.handle.net/10735.1/6706

Marjorie Zielke is an Assistant Professor of Arts and Technology and the Director of The Center for Modeling and Simulation/Virtual Humans and Synthetic Societies Lab. Her research has involved developing game-based simulations and virtual humans. Her recent work has focused on creating virtual teachers to "facilitate the most demanding portions of learning curricula for children with dyslexia."

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    Exploring Medical Cyberlearning for Work at the Human/Technology Frontier with the Mixed-Reality Emotive Virtual Human System Platform
    (Institute of Electrical and Electronics Engineers Inc.) Zielke, Marjorie A.; Zakhidov, Djakhangir; Hardee, Gary M.; Pradeep, Jithin; Evans, Leonard; Lodhi, Zahra; Zimmer, Kevin; Ward, Eric; Zielke, Marjorie A.; Zakhidov, Djakhangir; Hardee, Gary M.; Pradeep, Jithin; Evans, Leonard; Lodhi, Zahra; Zimmer, Kevin; Ward, Eric
    This paper describes the Mixed-Reality Emotive Virtual Human System Platform - a machine for cyberlearning at the human/technology frontier. Our initial use case is for medical school students practicing patient interviewing in preparation for Objective Structured Clinical Exams (OSCEs). The work is deliberately focused on a futures environment where students can seamlessly enter a virtual learning experience and return to the face-to-face. For the context of our work, we define mixed reality as the ability to traverse real and synthetic learning experiences utilizing a variety of technologies such as augmented reality and virtual reality in a dynamic, emergent environment. Much of the work is based on the Emotive Virtual-Reality Patient research sponsored by the Southwestern Medical Foundation and exploration of the US Ignite ultra-high speed network, sponsored by the National Science Foundation. We use the US Ignite network to facilitate the development of virtual humans and the overall platform. We also explore evolving learning theory that supports the development of this knowledge system which blends real and synthetic roles of professors, mentors, and standardized patients in an emergent artificial intelligence and machine learning driven environment. Future applications of the model are also discussed.

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