This paper addresses the development of a persuasive IoT system for stress detection and management in students during classroom situations. An emotion-aware persuasive architecture is developed with four modules: Context Acquisition, Context Manager, Persuasion Manager and Context-Aware Applications. By using the galvanic skin response biomarker, the real-time stress level is measured by the wearable wristband Empatica E4. The data, processed and classified on discrete stress levels from 0 to 5, is sent to the context module that identifies situations of interest where the students need positive reinforcement from the persuasive system. Based on the situation of interest and the user’s profile, the persuasive module composes personalized persuasive messages displayed in a mobile application. The persuasive system was evaluated through an exploratory study during a class session, with encouraging results in detecting stress levels and the positive effect of persuasive messages on students.
CITATION STYLE
Calcina-Ccori, P., Rodriguez-Canales, E. S., & Sarmiento-Calisaya, E. (2022). A Persuasive System for Stress Detection and Management in an Educational Environment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13533 LNCS, pp. 239–249). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-20936-9_19
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