Ioannis Doumanis

Background

About Ioannis Doumanis

I began my journey in IT education 21 years ago, eventually transitioning to Higher Education (HE) in 2003. Over these two decades, I've delivered more than 20 modules in both postgraduate and undergraduate Computer Science programmes, both online and in-person. This comprises teaching over 700 students, and mentoring 50+ in their research endeavors, including MSc and PhD supervisees.At the core of my pedagogy is fostering deep learning in Computer Science students. I aim to equip them with the knowledge and skills to solve open-ended problems. This necessitates cultivating the ability to formulate well-reasoned and comprehensive answers. My teaching philosophy began during my time as a college instructor, post my undergraduate studies. The true potential of Problem-Based Learning (PBL) became apparent to me after obtaining my teaching qualification (PGCAP). I've since incorporated both individual and collaborative PBL into various teaching contexts.Parallel to my educational pursuits, I've been deeply invested in research. My primary research revolves around Human-Computer Interaction (HCI). Specifically, I delve into the intricacies of how application interfaces, especially Graphical User Interfaces (GUIs) and intelligent systems, influence human cognition. This encompasses human responses to Web and Mobile applications, Games, Virtual/Augmented Reality, Embodied Conversational Agents, Virtual Agents, and Network Music Performance systems. Another facet of my research involves understanding human cognition while engaging with digital content, such as videos. I've extensively studied how various applications affect perception, attention, memory, and emotional responses in domains like education, academia, cultural content, and video distribution. My methods have included automated systems to gauge emotional reactions through facial expressions as users interact with diverse interfaces.Currently, my focus has shifted to the realm of Conversational Artificial Intelligence (AI) and its implications on human cognition, specifically in collaborative problem-solving. Here, AI refers to Machine Learning and Deep Learning models that facilitate natural language communication between AI and human users. My ambition is to design, develop, and assess high-fidelity prototypes, with a particular interest in Large Language Models (LLMs).