Using the Engagement Profile to Design an Engaging Robotic Teaching Assistant for Students
2019 (English)In: Robotics, E-ISSN 2218-6581, Vol. 8, no 1, article id 21Article in journal (Refereed) Published
Abstract [en]
We report on an exploratory study conducted at a graduate school in Sweden with a humanoid robot, Baxter. First, we describe a list of potentially useful capabilities for a robot teaching assistant derived from brainstorming and interviews with faculty members, teachers, and students. These capabilities consist of reading educational materials out loud, greeting, alerting, allowing remote operation, providing clarifications, and moving to carry out physical tasks. Secondly, we present feedback on how the robot's capabilities, demonstrated in part with the Wizard of Oz approach, were perceived, and iteratively adapted over the course of several lectures, using the EngagementProfile tool. Thirdly, we discuss observations regarding the capabilities and the development process. Our findings suggest that using a social robot as a teachingassistant is promising using the chosen capabilities and Engagement Profile tool. We find that enhancing the robot's autonomous capabilities and further investigating the role of embodiment are some important topics to be considered in future work. © 2019 by the authors.
Place, publisher, year, edition, pages
Basel: MDPI, 2019. Vol. 8, no 1, article id 21
Keywords [en]
Evaluation, Robot, Robotic teaching assistant, Teaching, User engagement
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:hh:diva-39446DOI: 10.3390/robotics8010021ISI: 000464266600001Scopus ID: 2-s2.0-85063490169OAI: oai:DiVA.org:hh-39446DiVA, id: diva2:1317280
Note
The first author received funding from the Swedish Knowledge Foundation (Sidus AIR no. 20140220 and CAISR 2010/0271) and also some travel funding from the REMIND project (H2020-MSCARISE No 734355). The Engagement Profile has been developed in the context of the project VISITORENGAGEMENT funded by the Research Council of Norway in the BIA programme, grant number 228737
2019-05-222019-05-222019-05-28Bibliographically approved