학술논문

MoveToCode: An Embodied Augmented Reality Visual Programming Language with an Autonomous Robot Tutor for Promoting Student Programming Curiosity
Document Type
Conference
Source
2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN) Robot and Human Interactive Communication (RO-MAN), 2023 32nd IEEE International Conference on. :2533-2540 Aug, 2023
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Visualization
Computer languages
Mixed reality
Human-robot interaction
Assistive robots
Programming profession
Augmented reality
Language
ISSN
1944-9437
Abstract
Virtual, augmented, and mixed reality for human-robot interaction (VAM-HRI) is a new and rapidly growing field of research. The field of socially assistive robot (SAR) has made impactful advances in educational settings, but has not yet benefited from VAM-HRI advances. We developed MoveToCode - an open-source, embodied (i.e., kinesthetic) learning visual programming language that aims to increase student (ages 8-12) curiosity during programming. MoveToCode uses an augmented reality (AR) autonomous robot tutor named Kuri that models the students’ kinesthetic curiosity and acts to promote their curiosity in programming. MoveToCode design was informed by pilot studies and tested in Los Angeles elementary classrooms $(n =21)$. Results from main study validated our design decisions compared to the pilot study which was conducted in a real elementary school classroom environment $(n =15)$, showing an improvement in perceived robot helpfulness (median $+ \Delta1.25$ out of 5) and number of completed exercises (median $+ \Delta1$, maximum of 11). While no significant changes were found in pre/post student curiosity or intention to program later in life, students wrote more open-ended questions post-study on topics related to robots, programming, research, and if they would like to do the activity again. This work demonstrates the potential of using VAM-HRI in a kinesthetic context for SAR tutors, and highlights the existing conventions and new design considerations for creating AR applications for SAR.