AI and wearable sensors in Higher Education to investigate Public Speaking Skills

Lorella Giannandrea; Francesca Gratani; Lorenza Maria Capolla; Georgios Dafoulas; Ariadni Tsiakara; Stelios Kapetanakis; Giacomo Nalli

Authors

Lorella Giannandrea https://orcid.org/0000-0002-1169-4795
Francesca Gratani https://orcid.org/0000-0003-2974-0101
Lorenza Maria Capolla https://orcid.org/0009-0008-3338-1096
Georgios Dafoulas
Ariadni Tsiakara
Stelios Kapetanakis https://orcid.org/0009-0002-1660-387X
Giacomo Nalli Middlesex University London https://orcid.org/0000-0002-5667-3429

Keywords: undergraduate students, public speaking anxiety, artificial intelligence, wearable devices, heart rate, emotion recognition

Abstract

In most professional fields, being able to effectively communicate to an audience is considered an essential skill for professional advancement. However, the literature shows that anxiety disorders are among the most common mental disorders encountered by public speakers and that public speaking anxiety can negatively impact on the learning experience of undergraduate students. The present study involves university students from two different contexts and countries and examines their public speaking anxiety by cross-referencing data on cognitive self-perceptions, physiological reactions (heart rate), and behavioural aspects (facial expressions and body movements). It also explores the potential of wearable devices and artificial intelligence in data collection and analysis to identify different student profiles according to their levels of stress and public speaking anxiety. Despite various limitations, the cross-analysis showed good consistency and revealed interesting differences between the two samples, including stress-related clusters and emotional states. The data obtained encourage further research into the variables associated with public speaking and oratory skills. In addition, future developments of this study aim to further explore the potential contribution of these tools in assisting teachers in designing effective personalised training, as well as sharing and discussing data with students to promote awareness of their weaknesses and strengths.

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