Affective Computing for Education and Industrial Training

Learning is never purely rational. Think back to a moment when you felt deeply engaged in a task, frustrated by a challenge, or bored despite understanding the content. These feelings were not incidental, they actively shaped how you learned, how long you persisted, and what you ultimately took away from the experience.

This course explores affective computing and its role in education, training, and upskilling. It shows how learners’ emotions, engagement, motivation, and learning states can be understood, modelled, and responsibly integrated into digital learning systems. Rather than focusing only on performance or correctness, the course highlights why how learners feel matters just as much as what they do.

Across the lessons, you move from foundational concepts to applied perspectives. You learn how affective computing supports adaptive learning systems, serious games, and immersive XR-based training environments. Real educational and industrial examples are used throughout, culminating in an in-depth exploration of the XR2Learn project as a concrete, large-scale implementation of affect-aware and adaptive learning principles.

By the end of the course, you will not only understand what affective computing is, but also how it can be applied thoughtfully in vocational education, industrial training, and lifelong learning, balancing innovation with ethics, transparency, and human-centred design.

If you are interested in designing learning technologies that respond to learners as people, not just users, this course will equip you with the concepts, language, and perspectives needed to take that next step.

What you will learn

• The fundamentals of affective computing and its relevance for learning and training
• How emotions, engagement, motivation, and flow influence skill acquisition
• Core affect models and how to select them for educational and industrial contexts
• How affective information can inform adaptive learning systems and XR-based training
• Practical and ethical considerations for applying affect-aware approaches in vocational education and upskilling

Who should attend

• Educators and instructional designers
• Vocational education and training (VET) professionals
• Industrial trainers and learning and development specialists
• Researchers and students interested in learning technologies and human-centred AI
• Developers and practitioners working on digital, adaptive, or XR-based training solutions

Key benefits

• Gain a structured and coherent understanding of affective computing for learning
• Learn how to design more engaging, adaptive, and learner-centred training experiences
• Understand how affective data can be used responsibly and ethically
• Connect research concepts with practical applications in industrial and vocational training contexts