Title: PhD research projects on educational technology in the School of Electronic Engineering and Computer science
Talk 1:
Speaker: Job Adeleke Oyebisi
Title: A study of the effect of an Ai-Aided Multimedia Content Authoring Tool For Haptic Virtual Dental Simulators on the Pedagogical Ownership of Dental Instructors
Abstract: This research explores the impact of emerging experiential technologies, particularly virtual reality (VR) and haptic feedback, on dental education. The proposed study investigates the potential of an AI-aided multimedia content authoring tool for haptic VR dental simulators to empower dental instructors with pedagogical ownership. VR's immersive capabilities and integration with haptic feedback offer valuable opportunities for experiential learning, especially in fields like dentistry. However, the challenge lies in creating diverse, high-quality content for these simulators. This study addresses this issue, aiming to enhance pedagogical ownership among dental clinical instructors, ultimately advancing dental education and educational technology research.
Short Bio: Job Oyebisi is a second year EngD student at Queen Mary University of London. His research interest relates exploring AI and VR applications in educational content creation to empower educators with material ownership and improve learning outcomes.
He is a tech entrepreneur and the founder of StanLab Ltd, an-edtech startup company which offers immersive STEM learning experiences to students through a 3D virtual laboratory.
Talk 2:
Speaker: Chathura Kalpanee Sooriya Arachchi
Title: What’s stopping academics from making data-informed decisions in teaching?
Abstract: In the higher education context, the adoption of learning analytics within the practices of teaching, learning and assessment is limited, and educators often encounter challenges with the integration of learning analytics into their learning design. This research aims to explore how educators, can make use of learning analytics to make informed teaching decisions. This talk will address three key components: firstly, a systematic literature review which highlighted the need for methods and evidence-based research for actioning learning analytics to make informed teaching decisions to improve learner outcomes; secondly, a survey to investigate barriers faced by educators in adopting learning analytics in their teaching; and thirdly, the construction of a toolkit to facilitate educators in their data-informed teaching decisions, where experiments will be carried out with educators to streamline different methods educators could practice to make meaningful learning design decisions, using learning analytics, to improve learning outcomes and create a productive learning environment for learners.
Short Bio: Chathura Sooriya-Arachchi is a 3rd-year doctoral candidate and Teaching Fellow in EECS, her research interests are in EdTech, with a keen focus on the intersection of learning analytics and learning design explored in her ongoing PhD research.
Talk 3:
Speaker: Yuli Sutoto Nugroho
Title: Study of The Effect of Instructor and Learners' Presence in Lecture Videos and in The Metaverse on Learners' Learning Gain, Eye Tracking Measures and Affective States
Abstract: Teaching and learning continue to develop in many ways. Various learning delivery modes, such as videos and environments like the metaverse, have tremendous potential, so it is essential to examine their effects, especially the effect of instructor and learners' presence on learners' responses. Therefore, this study aims to explore how teachers' and learners' presence in different video lectures and metaverse environments affect students' learning gain, eye-tracking measures (cognitive load), and affective states. The methods that will be used to collect and analyze the data are threefold: (1) Learners’ Learning Gain using pre-test and post-test; (2) Student’s Eye Tracking Measures (cognitive load) using Eye-tracking Technology; and (3) Affective State (Valence and Arousal) by facial expression recognition using system APIs. The expected result would be to conclude the best way to distance learning.
Short Bio: Yuli Sutoto Nugroho is a second-year PhD student at Queen Mary University of London. His research interests explore how lecturer presence impacts learning by measuring learners' body condition, such as eye and face and distance learning. He is a civil servant lecturer at State University of Surabaya, Indonesia.