Name
Abstract | ||
|---|---|---|
Learning in universities challenges students to engage in self-directed learning, which requires a high degree of self-motivation while individual support by teachers is limited. Research on social robots has already demonstrated their potential to support students in their learning process. In this paper, we focus on the benefits of adaptivity of a robotic tutor in a higher education scenario. To this end, we conducted a field study over three sessions over the course of a semester and implemented two conditions (adaptive and non-adaptive) of a robotic tutor to support students with exam preparation. After participant learned with both version in random order in the first two sessions, their preferred condition was used in the third session. Our results show that significantly more students preferred to learn with the adaptive robotic tutor. Additionally, participation resulted in significantly better exam performance compared to the average of the course. However, there was no significant difference in the learning experience such as motivation or need satisfaction between conditions. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/RO-MAN53752.2022.9900865 | 2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN) |
DocType | ISSN | ISBN |
Conference | 1944-9445 | 978-1-6654-0680-2 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Melissa Donnermann | 1 | 3 | 1.11 |
| Philipp Schaper | 2 | 4 | 2.81 |
| Birgit Lugrin | 3 | 0 | 1.01 |