Year: 2012
Type: article
Abstract: The present study investigates how a conversational agent can facilitate explanation activity.An experiment was conducted where pairs of participants, who were enrolled in a psychology course, engaged in a task of explaining to their partners the meanings of concepts of technical terms taught in the course.During the task, they interacted with a conversational agent, which was programmed to provide back-channel feedbacks and metacognitive suggestions to encourage and facilitate conversational interaction between the participants.Results of an experiment suggested that affective positive feedbacks from conversational agent facilitate explanation and learning performance.It is discussed that a conversational agent can play a role for pedagogical tutoring and triggers a deeper understanding of a concept during an explanation.
Authors: Yugo Hayashi, Mariko Matsumoto, Hitoshi Ogawa
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
Funder: Ritsumeikan University
OpenAlex ID: W2401662245