# E-MOTE: A Conceptual Framework for Emotion-Aware Teacher Training Integrating FACS, AI and VR

**Authors:** Rosa Pia D’Acri, Francesco Demarco, Alessandro Soranzo

PMC · DOI: 10.3390/vision10010005 · Vision · 2026-01-19

## TL;DR

E-MOTE is a new framework for teacher training that combines FACS, AI, and VR to improve emotional awareness and classroom management.

## Contribution

E-MOTE introduces a structured blueprint for emotion-aware teacher training using FACS, AI, and VR.

## Key findings

- E-MOTE clarifies the multi-layered construct of emotion-aware teaching.
- It proposes an integrated AI–FACS–VR architecture for feedback on teachers’ perceptual performance.
- It outlines a staged experimental blueprint for future empirical validation.

## Abstract

This paper proposes E-MOTE (Emotion-aware Teacher Education Framework), an ethically grounded conceptual model aimed at enhancing teacher education through the integrated use of the Facial Action Coding System (FACS), Artificial Intelligence (AI), and Virtual Reality (VR). As a conceptual and design-oriented proposal, E-MOTE is presented as a structured blueprint for future development and empirical validation, not as an implemented or evaluated system. Grounded in neuroscientific and educational research, E-MOTE seeks to strengthen teachers’ emotional awareness, teacher noticing, and social–emotional learning competencies. Rather than reporting empirical findings, this article offers a theoretically structured framework and an operational blueprint for the design of emotion-aware teacher training environments, establishing a structured foundation for future empirical validation. E-MOTE articulates three core contributions: (1) it clarifies the multi-layered construct of emotion-aware teaching by distinguishing between emotion detection, perception, awareness, and regulation; (2) it proposes an integrated AI–FACS–VR architecture for real-time and post hoc feedback on teachers’ perceptual performance; and (3) it outlines a staged experimental blueprint for future empirical validation under ethically governed conditions. As a design-oriented proposal, E-MOTE provides a structured foundation for cultivating emotionally responsive pedagogy and inclusive classroom management, supporting the development of perceptual micro-skills in teacher practice. Its distinctive contribution lies in proposing a shift from predominantly macro-behavioral simulation toward the deliberate cultivation of perceptual micro-skills through FACS-informed analytics integrated with AI-driven simulations.

## Full-text entities

- **Diseases:** visual fatigue (MESH:D001248), anxiety (MESH:D001007), AUs (MESH:D009207), injury to (MESH:D014947), cognitive overload (MESH:D003072), confusion (MESH:D003221), AI (MESH:C538142)
- **Chemicals:** E-MOTE (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

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## Figures

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## References

75 references — full list in the complete paper: https://tomesphere.com/paper/PMC12921945/full.md

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Source: https://tomesphere.com/paper/PMC12921945