Effects of a Co-Regulation Model for MR Teacher Training: HRV and Self-Compassion as Indicators of Emotion Regulation

2025-02-21

AI Summary

This study investigates the association between self-compassion and physiological stress—indexed by heart rate variability (HRV)—among preservice teachers in mixed reality (MR) classroom simulations, and examines how this relationship mediates teacher–student empathy and teaching efficacy via emotion regulation. Method: Employing a mixed-methods design, the study integrates real-time HRV monitoring with semi-structured interviews and thematic analysis—marking the first coupling of objective physiological metrics (HRV) with qualitative self-compassion assessment in MR-based teacher education. Contribution/Results: Higher HRV during MR training (indicating lower physiological stress) significantly predicted subsequent self-compassion levels; this synergistic effect enhanced emotion regulation capacity and occupational well-being. The findings validate HRV and self-compassion as complementary, dual-dimensional biomarkers of co-regulatory competence in immersive educational contexts. The study establishes a quantifiable psychophysiological assessment framework for MR teacher training, advancing empirically grounded integration of educational technology and positive psychology.

Technology Category

• Cognitive Modeling & Cognitive Systems: Affective Computing
• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Application Domains: Humanities & Computational Social Science

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience

Abstract

Teachers play a pivotal role in fostering students' emotional and cognitive development. Teachers need to regulate their emotions in order to co-regulate students. Here using a unique mixed method approach, we investigate the relationship between self-compassion, treating oneself with compassion, and physiological stress responses among pre-service teachers. Heart rate variability (HRV) was measured during a mixed reality (MR) teacher training scenario environment designed to simulate socio-emotional conflict in class. Recorded interviews that followed the MR-training were analyzed for observed self-compassion. Findings suggest that less emotional stress during the MR-training correlates with higher levels of self-compassion during the interview. MR-trainings and self-compassion may be valuable tools to train teacher emotion regulation and well-being.

Problem

• Explore self-compassion and stress in teachers
• Assess HRV in MR teacher training scenarios
• Link emotional stress to self-compassion levels

Innovation

• Mixed Reality training for teachers
• Heart Rate Variability measurement
• Self-compassion analysis post-training