Date of Award
Doctor of Philosophy (PhD)
College of Computing and Engineering
Laurie P. Dringus
Martha M. Snyder
3D VR anatomy, convergent mixed method, flow theory, human-computer interaction, usability, user experience
Decreasing hours dedicated to teaching anatomy courses and declining use of human cadavers have spurred the need for innovative solutions in teaching anatomy in medical schools. Advancements in virtual reality (VR), 3D visualizations, computer graphics, and medical graphic images have enabled the development of highly interactive 3D virtual applications. Over recent years, variations of interactive systems on computer-mediated environments have been used as supplementary resource for learners. However, despite the growing sophistication of these resources for learning anatomy, studies show that students predominantly prefer traditional methods of learning and hands-on cadaver-based learning over computer-mediated platforms.
There is limited research on evaluating user experience in the use of interactive 3D anatomy systems, even though Human-Computer Interaction (HCI) studies show that usability (ease of use) and user engagement are essential to technology adoption and satisfaction. The addressable problem of the research was to investigate how ease of use and flow affected aspects of the students’ engagement experience with the use of a 3D virtual anatomy application. The aim of the study was to evaluate the use of a 3D virtual application in performing dissection learning tasks and to understand aspects of user engagement as assessed by ease of use and flow experience.
The flow experience was quantified using the Short Flow State Scale (S FSS-2) and the System Usability Scale (SUS) to measure perceptions about ease of use and user satisfaction. The research questions included: (1) What consequences of flow do students experience? (2) What aspects of the 3D virtual platform are distracting to performing the learning tasks? (3) How do students’ perception of ease of use affect the flow experience based on the SUS and S FSS-2 scores? (4) How do students rate their level of engagement as measured by flow based on their S FSS-2 scores? (5) How does flow help explain student satisfaction and motivation? (6) How do students perceive use of the application to learn anatomy compared with cadaver-based dissection? The study consisted of medical student participants who were asked to complete virtual dissection activities associated with learning objectives in the Structure of the Human Body course to perform using a 3D virtual anatomy application. A subset of participants who completed the learning task and the surveys had a follow-up Cognitive Walkthrough with Think-Aloud Protocol observation activity with an interview segment to gain deeper insights into their user experience with the application.
The data from the convergent mixed method analysis indicated that ease of use had some impact on the flow experience and that perceived user satisfaction and motivation were attributed to the interactive 3D visualization design. Seven super-ordinate themes were identified: Ease of Use, Learnability, Interface-Technical, User Satisfaction, Visuospatial, Focus/In the Zone, and CA vs Cadaver.
The results have implications for educators (particularly anatomists), educational technologists, and HCI and UX practitioners. Additional research should be conducted using the long version of the Flow State Scale to provide a better understanding of each flow dimension. Further study is recommended with students who have hands-on experience with human cadaver dissection that are also able to compare their experience with the use of a 3D virtual anatomy platform for a direct side-by-side assessment. It would also be helpful to conduct the study as part of the entire duration of the anatomy course and assess how the flow experience impacts student learning performance.
Winnyanne Kunkle. 2021. Investigating the User Experience with a 3D Virtual Anatomy Application. Doctoral dissertation. Nova Southeastern University. Retrieved from NSUWorks, College of Computing and Engineering. (1160)