Anthony Basiel

Southampton Solent University, UK

Title: An Artificial Intelligence (AI) Modelfor Healthcare Learning Simulation Evaluation

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Biography

Dr. Anthony ‘Skip’ Basiel is a Module Leader in Computing Science at Solent University, Southampton, UK, specializing in User Experience (UX) Design and Human-Computer Interaction (HCI). Previously a Postdoctoral Research Fellow at the Faculty of Health and Social Sciences at Bournemouth University, Dr. Basiel has been actively involved in research and development in blended learning since 1996, with over 60 published works in the field.

An Adobe International Education Leader, he offers expert consultancy and engaging workshops focused on enhancing webinar interactivity and digital learning design. Dr. Basiel is open to research collaborations and project partnerships.

Abstract

Learning simulations are arguably the best way for healthcare professionals to demonstrate mastery of specific knowledge and skills. The objective of this research is to provide an innovative blended learning model that synthesises artificial intelligence and augmented reality. A case study approach was used with a post-graduate research methods module. Students generated questions and referenced answers for an online multiple-choice quiz as part of the ipsative[1] assessment design. An AI generator was also used by the healthcare practitioners to produce pre-test samples. A blended learning simulation was conducted with students in the classroom and via Teams. Additionally, the event was recorded using an augmented reality 360* camera to create a video recording which the viewer could click on to see anywhere in the room while reviewing the simulation. The debriefing session was also 360* recorded. Auto-transcription of the session was then analysed by an AI generator to match the module learning outcomes with evidence of attainment. This mapping of the learning outcomes was to text examples and skills demonstrated. The conclusion of the study has identified the need for further refinement of the model. The student-made quiz needs to be built into the marking scheme, so students are recognised for contributions. During the simulation the simulated patients (Facilitators not Students) need to be given a script of key words linked to the learning outcomes. This will aid the AI analysis to better map the evidence of mastery. The next stage of the study plans to add digital twins (AI generated Avatars) as and additional debriefing on-screen facilitator to prompt the stakeholders to reflect on how they could improve. The script is based on the Plus-Delta debriefing design for a co-debriefing session. This blended learning model provides healthcare professionals with an applied approach to provide evidence needed for continuing professional development.