We will explore the intersection between learning and work to develop and apply innovative approaches to education and workforce training that empower people to fulfill active roles in society through participation, engagement and entrepreneurship. We aim to empower people for a future in which robots, automation and artificial intelligence will be more common.
The creative and ill-structured nature of graphic design tasks creates difficulty in terms of assessment validity and reliability. Further, best practices in teaching and assessment are hampered by issues around scalability and efficiency. Finally, increasingly validated indications that good design(s) may be a function of a group consensus rather than the opinions of a few extensively trained individuals, have all led to an increased emphasis on researching new approaches to improving graphic design education.
HapTutor-Lab: Promoting Complex Learning in STEM Domains through Intelligent Tutors and Haptic Feedback.
There has been a breakthrough in recent years concerning artificial talking head agents that can have a conversation with the human learning in natural language in the form of intelligent tutoring systems. Faculty members are leading a project to integrate two lines of research.
Drs. Bartholomew & McGraw and Mr. Charlesworth hypothesize that some of the struggles with data-driven decision-making instruction stem from the lack of context and real-world application for students (Merrill, Custer, Daugherty, Westrick, & Zeng, 2009). Further, they believe that placing students in positions requiring data-driven decision approaches may increase the effectiveness of these experiences and foster student interest in pursuing related education and careers.