Enhancement of interaction for anatomy visual learning interfaces in augmented reality learning

Mobile applications using Augmented Reality (AR) technology have been widely used in many fields, including education, computer games, advertising, tourism and more. AR is considered an exciting technology for users as they interact with 3D virtual models in the real world. AR is also widely used in medical education, as it helps medical students to see and understand the structure of human/animal anatomy more closely and this helps them visualize the model because their textbooks show only 2D images. Some existing AR applications are not widely used and are less user-friendly. The guidelines used in these existing application applications make it less attractive for users to continue using AR applications for long periods. The main purpose of this study is to encourage medical students to fully utilize AR applications to assist in their self-study after taking the relevant classes. The main contribution of this research is to identify the challenges in interacting with AR applications in medical education. To identify the proposed guidelines, the Mobile AR Application called the Brain Anatomy Revision Application (BARA) was developed. BARA is developed in stages and each level will be tested by the user for feedback before advancing to the next level. Get started with BARA following the existing guidelines in the current AR application. Subsequently, several preliminary experiments were conducted according to the BARA phase and version, as well as User Evaluation by medical students from UPM. The final Acceptance Test was performed for UiTM Sg Buloh medical students on three different versions of BARA namely printed markers, digital markers, and object target markers. All three versions of BARA have been applied using ten new guidelines, and medical students will choose which version makes it easier for them to use this learning application, including issues of contents, ease of use of apps, and experience using AR in these applications as they can look at the entire AR 3D model view. Future work is to increase the level of details of the 3D model as if it were real texture to make it more interesting and real. Next, 3D models can be an interaction where the user can separate each part of the brain by pulling the parts together