HI Data Forum @ LeaF – Exploring how our bodies’ hidden signals such as heart rate and electrodermal activity shape learning and interaction

HI Data Forum @ LeaF brings together experts on the field. The program combines research insight with case examples and hands-on session of the new BIOPAC MP200 system featuring psychophysiological measurements.

The research insights highlight how physiological signals such as heart rate, heart rate variability, and electrodermal activity can reveal hidden aspects of learning and interaction. Through examples from both collaborative tasks and immersive VR trauma‑training scenarios, the presentations show how biosignals complement video observations, log data, and self‑reports by uncovering learners’ internal responses during complex activities.

The hybrid event is free and open to all!

Secure your spot and register here: onsite participation closes February 23, and online registration by February 25 at 12:00 (noon).

 Program

13:00 Opening

13:00 What can physiological signals reveal about how people interact and learn? - Dr. Marta Sobocinski and Dr. Tiina Törmänen

This presentation introduces how physiological signals such as heart rate and electrodermal activity can be used to study interaction and learning. We provide an overview of what these signals capture and how they are commonly used in research. Using empirical examples from learning and interaction both in individual and group settings, we show how physiological data can complement video observations, log data and self-reports by revealing participants’ hidden bodily responses during complex activities.

Dr. Marta Sobocinski is a postdoctoral researcher at the Learning and Educational Technology Research Lab (LET) in the University of Oulu, specializing in metacognition, collaborative learning, multimodal data, process measures and VR/XR. Her research focuses on capturing adaptive regulation patterns in individual and collaborative learning through multimodal data in XR and conventional learning contexts.

Dr. Tiina Törmänen is a postdoctoral researcher in the Hybrid Intelligence program and in the Learning and Educational Technology (LET) Research Lab. Her interests cover emotions, motivation, and socially shared regulation in collaborative learning, and how to study these processes with multimodal multichannel data (e.g., video observations, physiological data, situational self-reports).

13:30 Hidden signals of learning: What physiological data reveal in VR-based training - Dr. Delfin Tursin and Prof. Kristina Mikkonen

This presentation explores how physiological signals such as heart rate variability and electrodermal activity can provide insights into learning, engagement, and task demand in immersive VR environments. Using a VR-based trauma training case, we demonstrate how bio signals complement video analysis and self-reports by revealing learners’ hidden physiological responses during complex interactions.

Dr. Delfin Tursin is a postdoctoral researcher at the University of Oulu’s Hybrid Intelligence programme, funded by the Research Council of Finland. Her research interest area is on emerging Sustainable Effects of Human-Technology Interaction on Quality of Life theme.

Prof. Kristina Mikkonen is specialised in health pedagogy, with a particular focus on how pedagogical design, learning environments, and instructional practices support competence development, well-being, and professional growth in health and social care. At the University of Oulu, she is leading the Health Care Education and Competence (HealthEduCom) research group, an internationally oriented research environment focusing on human-centred, inclusive, and technologically enhanced health professions education.

14:00 Hands-on session featuring psychophysiological measurements – Antti Siipo

Experience the BIOPAC MP200 system featuring PPG, EDA, RSP and ECG measurement during a hands-on session led by Antti Siipo, a tech expert from the University of Oulu's LeaF Infrastructure. BIOPAC is a modular research-grade data acquisition system used for the synchronized measurement and analysis of physiological and psychophysiological signals in experimental settings

14:30 Closing

Warmly welcome!

Register here.