I Like My Relational Machine Teacher: An AI Instructor’s Communication Styles and Social Presence in Online Education

积极倾听 课程 感知 心理学 数学教育 人工智能 风格(视觉艺术) 计算机科学 教育学 沟通 历史 考古 神经科学
作者
Jihyun Kim,Kelly Merrill,Kun Xu,Deanna D. Sellnow
出处
期刊:International Journal of Human-computer Interaction [Taylor & Francis]
卷期号:37 (18): 1760-1770 被引量:50
标识
DOI:10.1080/10447318.2021.1908671
摘要

New advancements in technology have made machines teachers, or technology-powered robots or AI that assist in the overall learning experience, a possibility. Though adoption rates are currently low, colleges and universities will likely incorporate some aspects of machine teachers (e.g., AI, robots) in their curriculums in the foreseeable future. However, little is known about how to create an effective machine teacher-based education. As an initial step, the present study examines whether an AI instructor's communication style would have an impact on students' perceptions about an AI instructor-based education. To test this inquiry, the study conducted an online experiment using a 2 (communication styles: functional vs. relational) x 2 (course topic: natural science vs. social science) between-subjects design. Primary results indicate that students develop more favorable perceptions about an AI instructor-based education when the AI instructor is relational rather than functional. This tendency is particularly strong when listening to a social science lecture. Further, social presence of an AI instructor functions as a mediator, which explains the reason why a relational AI instructor leads to more favorable perceptions about an AI instructor-based education is because of one's social presence of an AI instructor. Collectively, the study's findings indicate the importance of communication styles and social presence of an AI instructor.
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