Presentation
Brains and Bots: EEG Insights into Moral Learning with Social Robots and Text-Based Methods
DescriptionHow do we more effectively teach moral virtues such as responsibility and fairness? This research identifies novel means of involving students in moral education, a basis for empathy and ethical decision-making. Standard text-based teaching, although efficient, has the danger of being overly theoretical and hard to relate to. To overcome these problems, we implemented two different ways of teaching moral principles: an interactive lesson with a speech-capable robot and a simple reading task, and a control group with no teaching. Seventy-five students aged 18–30 were randomly divided into one of the three groups. We tested their knowledge, monitored their interest in questionnaires, and measured their brain activity on EEG headbands to see how they processed the information better. Outcomes indicated that both the interactive and reading groups scored significantly higher than the control group on tests of comprehension of moral concepts. EEG outcomes also detected heightened mental effort in tasks engaged in learning, although a difference between the two active treatments was not found. These results indicate that active, participatory learning approaches—traditional or technology-enhanced—can optimize moral education performance. From a human factors point of view, providing multiple modes for learning can facilitate the needs and preferences of today's learners.
Event Type
Lecture
TimeThursday, October 16th12:10pm - 12:30pm CDT
LocationGrand Hall K
Human AI Robot Teaming (AI)
Similar Presentations