Social robots in applied settings: a long-term study on adaptive robotic tutors in higher education
Zitieren Sie bitte immer diese URN: urn:nbn:de:bvb:20-opus-266012
- Learning in higher education scenarios requires self-directed learning and the challenging task of self-motivation while individual support is rare. The integration of social robots to support learners has already shown promise to benefit the learning process in this area. In this paper, we focus on the applicability of an adaptive robotic tutor in a university setting. To this end, we conducted a long-term field study implementing an adaptive robotic tutor to support students with exam preparation over three sessions during one semester. In aLearning in higher education scenarios requires self-directed learning and the challenging task of self-motivation while individual support is rare. The integration of social robots to support learners has already shown promise to benefit the learning process in this area. In this paper, we focus on the applicability of an adaptive robotic tutor in a university setting. To this end, we conducted a long-term field study implementing an adaptive robotic tutor to support students with exam preparation over three sessions during one semester. In a mixed design, we compared the effect of an adaptive tutor to a control condition across all learning sessions. With the aim to benefit not only motivation but also academic success and the learning experience in general, we draw from research in adaptive tutoring, social robots in education, as well as our own prior work in this field. Our results show that opting in for the robotic tutoring is beneficial for students. We found significant subjective knowledge gain and increases in intrinsic motivation regarding the content of the course in general. Finally, participation resulted in a significantly better exam grade compared to students not participating. However, the extended adaptivity of the robotic tutor in the experimental condition did not seem to enhance learning, as we found no significant differences compared to a non-adaptive version of the robot.…
Autor(en): | Melissa Donnermann, Philipp Schaper, Birgit Lugrin |
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URN: | urn:nbn:de:bvb:20-opus-266012 |
Dokumentart: | Artikel / Aufsatz in einer Zeitschrift |
Institute der Universität: | Fakultät für Mathematik und Informatik / Institut für Informatik |
Sprache der Veröffentlichung: | Englisch |
Titel des übergeordneten Werkes / der Zeitschrift (Englisch): | Frontiers in Robotics and AI |
ISSN: | 2296-9144 |
Erscheinungsjahr: | 2022 |
Band / Jahrgang: | 9 |
Aufsatznummer: | 831633 |
Originalveröffentlichung / Quelle: | Frontiers in Robotics and AI (2022) 9:831633. doi:10.3389/frobt.2022.831633 |
DOI: | https://doi.org/10.3389/frobt.2022.831633 |
Allgemeine fachliche Zuordnung (DDC-Klassifikation): | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 006 Spezielle Computerverfahren |
Freie Schlagwort(e): | adaptive tutoring; higher education; human-robot interaction; robot-supported training; robotic tutor; technology-supported education |
Datum der Freischaltung: | 30.01.2023 |
Datum der Erstveröffentlichung: | 15.03.2022 |
Open-Access-Publikationsfonds / Förderzeitraum 2022 | |
Lizenz (Deutsch): | CC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International |