AI-Enhanced Education

This special session is organised and supported by King’s College London- University of London- United Kingdom  

Session Chair:

Dr. Sahar Al-Sudani, UK


Education institutes including universities have embraced a blended education model as a response to the COVID-19 pandemic. This model included using online technologies to deliver teaching and assessment online in addition to face-to-face smaller size sessions.  Software companies and because of these changes have equipped the market with existing technologies to support online learning, teaching, and assessment.  However, there are challenges related to the difficulty of learning online, such as the lack of systems and platforms that capture certain aspects of the online learning for example those related to capturing feedback on how students are engaging with the online study materials and lectures and flag if the students are confused i.e need support, stressed or bored. This is become especially important during the pandemic as many students are suffering from isolation and “MS Teams fatigue”. Given that the online model of education has been the panacea during the pandemic and will continue for a certain amount of time, research on incorporating Artificial Intelligence techniques to enhance online learning is an emerging research area.  This area of research includes but not limited to using AI techniques and models that capture students’ perceptions, feelings, and analyse students’ and teachers’ data.  


Therefore, this special session invites authors to submit high-quality research papers on emerging technology for biomedical application, covering topics which include (but are not limited to) the following:

  • Emotion AI and online learning.
  • Technology Enhanced Learning and Assessment.
  • Applications of AI in Education.
  • Educational AI (AIED).
  • AI and STS (Science & Technology Studies).
  • Pedagogical Decision Making.
  • Simulation-Based Online Learning .
  • Social Robots in Education.  

Paper Submission:

Prospective authors are invited to submit full-length papers (not exceeding 6 pages) conform to the IEEE format . All papers will be handled and processed electronically via the EDAS online submission system.