In many social professions employees require skills in affect- and situation-aware social interaction. One option for teaching and training such social interaction skills by computer-based training methodology is the use of dialogue simulations. Here, a student interacts with a simulated dialogue partner and the dialogue flow explores specific interaction situations and affectual settings. Conversational agents provide a basic technology for creating such dialogue simulations. However, they usually lack a means for managing affect-related dialogue state. In this paper we propose an approach to integrate affective reasoning into a conversational agent for intelligent tutoring applications in order to improve the agent’s ability to recognise dialogue intents, generate emotionally aligned responses, and provide a metric for evaluating student performance.
CITATION STYLE
Abuazizeh, M., Yordanova, K., & Kirste, T. (2021). Affect-Aware Conversational Agent for Intelligent Tutoring of Students in Nursing Subjects. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12677 LNCS, pp. 497–502). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-80421-3_54
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