Humanoid Robots in Higher Education: Evaluating the Acceptance of Pepper in the Context of an Academic Writing Course Using the UTAUT

Autor/inn/en	Guggemos, Josef; Seufert, Sabine; Sonderegger, Stefan
Titel	Humanoid Robots in Higher Education: Evaluating the Acceptance of Pepper in the Context of an Academic Writing Course Using the UTAUT
Quelle	In: British Journal of Educational Technology, 51 (2020) 5, S.1864-1883 (20 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Guggemos, Josef) ORCID (Seufert, Sabine)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0007-1013
DOI	10.1111/bjet.13006
Schlagwörter	Robotics; Technology Uses in Education; Higher Education; Social Sciences; College Freshmen; Writing (Composition); Introductory Courses; Man Machine Systems; Interaction; Intention; Privacy; Adoption (Ideas) + Suchen Sie Ihr Suchwort? Robotertechnik; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Hochschulbildung; Hochschulsystem; Hochschulwesen; Social science; Sozialwissenschaften; Gesellschaftswissenschaften; Studienanfänger; Schreibübung; Einführungskurs; Mensch-Maschine-System; Interaktion; Privatsphäre; Ideas; Ideenfindung
Abstract	This study investigates the acceptance of social robots by higher education students in the social sciences. Pepper, a humanoid social robot from SoftBank Robotics, provided a sample of its capabilities during a first semester, large-scale, university course, "Introduction to academic writing."From this course, 462 freshmen participated in our survey. The unified theory of acceptance and use of technology (UTAUT) acts as the conceptual framework, and partial least squares structural equation modelling (PLS-SEM) as the method for data analysis. The four perceived characteristics--trustworthiness, adaptiveness, social presence and appearance--all predict the intention to use the robot for learning purposes; anxiety regarding making mistakes in handling the robot and about privacy issues are not significant predictors. An importance-performance map analysis indicated adaptiveness as the robot's most important characteristic for predicting student behavioural intention. Overall, however, the study shows that students do not have the intention to rely on social robots for learning purposes at the current level of state-of-the-art technology: behavioural intention reaches only 36.6% of the theoretical maximum. (As Provided).
Anmerkungen	Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01