Introduction to Session-Based Behaviour Detection in Educational Contexts

About this course

This course explores how session-based detection of user behaviour can be used in an educational contexts and how personalised feedback can be provided to users. Designed for learners interested in the intersection of AI, education, and human-computer interaction, this course explores how automated tools analyze human verbal and nonverbal cues to improve communication skills. Using a real-world case study, application designed or nursing and medical professionals conducting remote clinical appointments, students will examine how computer vision and speech recognition translate into multimodal personalised feedback to provide communication performance analytics. Without diving deep into machine learning, this program focuses on understanding use cases, transforming coordinate/categorical data into clear visual dashboards, and navigating technical, ethical, and privacy challenges.

Course structure

• Introduces session-based behavior detection within educational contexts, covering core concepts, methodology, and basic detection tools
• Explores real-world case study focusing on health professionals’ communication skills
• Addresses technical limitations, system constraints, and ethical/privacy considerations surrounding behavior detection

Learning outcomes

After completing the course, students will:

• Explain the basic concepts of session-based detection of user behaviour and emotions in educational settings
• Understand how user’s behaviour and emotion can be recognized from video and audio
• Understand how the technology can be applied in different context, such as in education and health applications
• Identify and critique key challenges, such as technical limitations, cultural differences, individual variation, privacy, and ethics