Laura Feighan, Associate Lecturer in Radiation Therapy, PhD, Associate Fellow at Advance HE (UK), shared a post on LinkedIn:
“Excited to share our latest publication in the Journal of Medical Radiation Sciences (JMRS)!
Artificial Intelligence Integration in Radiation Therapy Education: A Multi-Modal Approach – co-authored with Leah Cramp, Debra Lee and Yolanda Surjan – is now available open access
With radiation oncology facing critical workforce shortages, universities are rapidly expanding RT student cohorts. But how do you scale education without sacrificing quality?
We embedded three AI innovations across our RT program at the University of Newcastle and asked students what they actually thought:
- AI video lectures
- AI-assisted assessment feedback
- AI-simulated patient communication tasks
Key takeaway:
Students were largely positive – but preferred AI as a formative learning tool over one for assessments. 75% of Year 3 students felt more comfortable practising communication with an AI patient than with peers.
This is just the beginning of understanding how AI can shape the future of RT education.”
Title: Artificial Intelligence Integration in Radiation Therapy Education: A Multi-Modal Approach
Authors: Laura Feighan, Leah Cramp, Debra Lee, Yolanda Surjan.
Other articles about AI on OncoDaily.