Abstract
Social robots are at the beginning of their promising careers in various fields where social interactions take place. Whether they will be used in the classroom in the future, in what role and for what tasks, is still an open question. While pilot studies often emphasize the great potential in education, the social robots commercially available today cannot yet meet the high expectations. However, given the rapid pace of development, it is worth exploring the characteristics and usefulness of social robots for different learning and teaching purposes. We conducted semi-structured interviews with preservice teachers in business education as potential users of robot-assisted education to evaluate for what classroom teaching tasks a social robot would be suitable. The interviews were analyzed drawing from a framework for teaching quality comprising classroom management, student support, and cognitive activation. It became clear that, when considering ethical concerns, prospective teachers see the robot primarily in a supporting and assisting role to increase both student motivation and the competence experience. The interviewed preservice teachers have the intention to use social robots in the future. However, they stress the importance of more reliable technology and a highly interactive and ready-to-use learning scenario.
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References
Luckin, R., Holmes, W., Griffiths, M., Forcier, L.B.: Intelligence unleashed: an argument for AI in education (2016)
ISTE: ISTE standards for students. https://www.iste.org/standards/standards/for-students (2017)
Cooney, M., Leister, W.: Using the engagement profile to design an engaging robotic teaching assistant for students. Robotics 8(1), 21(2019). https://doi.org/10.3390/robotics8010021
Leyzberg, D., Spaulding, S., Toneva, M., Scassellati, B.: The physical presence of a robot tutor increases cognitive learning gains. In: Proceedings of the Annual Meeting of the Cognitive Science Society (2012)
Belpaeme, T., Kennedy, J., Ramachandran, A., Scassellati, B., Tanaka, F.: Social robots for education: a review. Sci. Robot. 3(21), eaat5954 (2018). https://doi.org/10.1126/scirobotics.aat5954
Papakostas, G.A., et al.: Social robots in special education: a systematic review. Electronics 10(12), 1398 (2021). https://doi.org/10.3390/electronics10121398
van den Berghe, R., Verhagen, J., Oudgenoeg-Paz, O., van der Ven, S., Leseman, P.: Social robots for language learning: a review. Rev. Educ. Res. 89(2), 259–295 (2019). https://doi.org/10.3102/0034654318821286
Belpaeme, T., Tanaka, F.: Social Robots as Educators. OECD Digital Education Outlook 2021 Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots: Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots 143 (2021)
Woo, H., LeTendre, G.K., Pham-Shouse, T., Xiong, Y.: The use of social robots in classrooms: a review of field-based studies. Educ. Res. Rev. 33, 100388 (2021). https://doi.org/10.1016/j.edurev.2021.100388
Guggemos, J., Seufert, S., Sonderegger, S.: Humanoid robots in higher education: evaluating the acceptance of Pepper in the context of an academic writing course using the UTAUT. Br. J. Educ. Technol. 51(5), 1864–1883 (2020). https://doi.org/10.1111/bjet.13006
Veling, L., McGinn, C.: Qualitative research in HRI: a review and taxonomy. Int. J. Soc. Robot. 13(7), 1689–1709 (2021). https://doi.org/10.1007/s12369-020-00723-z
Zawacki-Richter, O., Marín, V.I., Bond, M., Gouverneur, F.: Systematic review of research on artificial intelligence applications in higher education – where are the educators? Int. J. Educ. Technol. High Educ. 16(1), 1–27 (2019). https://doi.org/10.1186/s41239-019-0171-0
Praetorius, A.-K., Klieme, E., Herbert, B., Pinger, P.: Generic dimensions of teaching quality: the German framework of Three Basic Dimensions. ZDM Math. Educ. 50, 407–426 (2018). https://doi.org/10.1007/s11858-018-0918-4
Amirova, A., Rakhymbayeva, N., Yadollahi, E., Sandygulova, A., Johal, W.: 10 years of human-NAO interaction research: a scoping review. Front. Robot. AI 8 (2021). https://doi.org/10.3389/frobt.2021.744526
Mubin, O., Stevens, C.J., Shahid, S., Al Mahmud, A., Dong, J.-J.: A review of the applicability of robots in education. J. Technol. Educ. Learn. 1, 13 (2013)
Cheng, Y.-W., Sun, P.-C., Chen, N.-S.: The essential applications of educational robot: requirement analysis from the perspectives of experts, researchers and instructors. Comput. Educ. 126, 399–416 (2018). https://doi.org/10.1016/j.compedu.2018.07.020
Baraka, K., Alves-Oliveira, P., Ribeiro, T.: An extended framework for characterizing social robots. In: Human-Robot Interaction. Springer Series on Bio- and Neurosystems, vol. 12. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-42307-0_2
Jamet, F., Masson, O., Jacquet, B., Stilgenbauer, J.-L., Baratgin, J.: Learning by teaching with humanoid robot: a new powerful experimental tool to improve children’s learning ability. J. Robot. (2018). https://doi.org/10.1155/2018/4578762
Serholt, S., et al.: Teachers’ views on the use of empathic robotic tutors in the classroom. In: The 23rd IEEE International Symposium on Robot and Human Interactive Communication, Edinburgh, UK, pp. 955–960. IEEE (2014). https://doi.org/10.1109/ROMAN.2014.6926376
Klieme, E., Rakoczy, K.: Unterrichtsqualität aus Schülerperspektive: Kulturspezifische Profile, regionale Unterschiede und Zusammenhänge mit Effekten von Unterricht. In: PISA 2000 — Ein differenzierter Blick auf die Länder der Bundesrepublik Deutschland. VS Verlag für Sozialwissenschaften, Wiesbaden (2003). https://doi.org/10.1007/978-3-322-97590-4_12
Deci, E.L., Ryan, R.M.: Self-determination theory. In: van Lange, P., Kruglanski, A., Higgins, E. (eds.) Handbook of Theories of Social Psychology, vol. 1, pp. 416–437. Sage Publications, London (2012)
Mayring, P.: Qualitative Inhaltsanalyse. Grundlagen und Techniken, 12th edn. Beltz, Weinheim (2015)
Alnajjar, F., et al.: Roboter in der Bildung. Wie Robotik das Lernen im digitalen Zeitalter bereichern kann. Hanser, München (2021)
Dillenbourg, P.: Classroom analytics: zooming out from a pupil to a classroom. OECD Digital Education Outlook 2021 Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots: Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots (2021). https://doi.org/10.1787/336f4ebf-en
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Sonderegger, S., Guggemos, J., Seufert, S. (2022). How Social Robots Can Facilitate Teaching Quality – Findings from an Explorative Interview Study. In: Lepuschitz, W., Merdan, M., Koppensteiner, G., Balogh, R., Obdržálek, D. (eds) Robotics in Education. RiE 2022. Lecture Notes in Networks and Systems, vol 515. Springer, Cham. https://doi.org/10.1007/978-3-031-12848-6_10
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