A. Arora, Amit Arora, K. Sivakumar, John R. McIntyre
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引用次数: 0
Abstract
This ROB-I-LEARN research utilizes a versatile framework (e.g., Business Model Canvas or BMC) for robot design and curriculum development aimed at students diagnosed with autism spectrum disorder (ASD). Robotic interventions / human-robot interaction (HRI) field experiments with high school students were conducted as a recommendation or an outcome of the BMC framework and customer discovery interviews. These curriculum-related robotic interventions / interactive scenarios were designed to improve cognitive rehabilitation targeting students with ASD in high schools, thus enabling a higher quality learning environment that corresponds with students' learning requirements to prepare them for future learning and workforce environments.
期刊介绍:
ACM Transactions on Human-Robot Interaction (THRI) is a prestigious Gold Open Access journal that aspires to lead the field of human-robot interaction as a top-tier, peer-reviewed, interdisciplinary publication. The journal prioritizes articles that significantly contribute to the current state of the art, enhance overall knowledge, have a broad appeal, and are accessible to a diverse audience. Submissions are expected to meet a high scholarly standard, and authors are encouraged to ensure their research is well-presented, advancing the understanding of human-robot interaction, adding cutting-edge or general insights to the field, or challenging current perspectives in this research domain.
THRI warmly invites well-crafted paper submissions from a variety of disciplines, encompassing robotics, computer science, engineering, design, and the behavioral and social sciences. The scholarly articles published in THRI may cover a range of topics such as the nature of human interactions with robots and robotic technologies, methods to enhance or enable novel forms of interaction, and the societal or organizational impacts of these interactions. The editorial team is also keen on receiving proposals for special issues that focus on specific technical challenges or that apply human-robot interaction research to further areas like social computing, consumer behavior, health, and education.