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CUHK Expo 2019/20 has ended
Thursday, July 30 • 3:30pm - 3:45pm
Talk: An Innovative Anatomy Learning Tool: The combination of 3D Printing and Web Augmented Reality Technologies

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Anatomy is one of the crucial courses in the pre-clinical curriculum for the Medical Training Programme. Students feel easy to acquire the knowledge in the relationships of structures from the spatial visualization process. The 3D printing technology allows the replication of the plasnitated specimen without ethnical concern; whereas the Web AR technology enriches the digitized contextual information from the displayed object. Our team has investigated whether the combination of these technologies is an innovated tool for students’ visual–spatial learning in Anatomy teaching.

Our team developed courseware from integration both 3D Printing and Web AR technologies entitled as Virtual eLearning Tool (VeT), providing an excellent sight stimulation to study human organ, using the urinary system as a pilot module. Through the VeT, students can examine the model with rotation or manipulation and use the tablet OS to screen the 3D printed kidney model to gain the pop out digitized context of the internal anatomical structures in details. Students acquire the knowledge from such interactive multi-media material in positive experiential learning.

From our pilot study, the VeT provides several educational implications:
(1) Our team has designed the novel web AR-based experiential learning environment for health professional studying the Anatomy; and
(2) it bridges the interactive learning gap between the factual knowledge with text content type in the book and the 3D printed model for the flipped classroom learning.

The potential and affordance of the Web AR technology is being valued and extended to the strategic pedagogy in the future health professions education.

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Thursday July 30, 2020 3:30pm - 3:45pm HKT
Room A
  Virtual Reality (VR)/ Augmented reality (AR), Talk
  • Session Type Talk
  • Presentation Type Poster and Talk
  • Order in Theme Session 1
  • Submission No. 17