Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/32881
Title: The Human Muscular Arm Avatar as an Interactive Visualization Tool in Learning Anatomy: Medical Students’ Perspectives
Authors: Cakmak, Yusuf Ozgur
Daniel, Ben Kei
Hammer, Niels
Yilmaz, Onur
IRMAK, Erdem 
Khwaounjoo, Prashanna
Issue Date: 2020
Publisher: IEEE COMPUTER SOC
Source: IEEE Transactions on Learning Technologies, 13 (3) , p. 593 -603
Abstract: The perception of body ownership creates a sense of embodiment, which can be a powerful learning tool. Embodied learning can occur by watching an individual's body movement and also via human-computer interactions, such as virtual reality (VR) and augmented reality (AR). In this article, we designed and implemented a novel virtual body-ownership AR/VR tool for human anatomy-the human muscular arm avatar (HMAA). HMAA utilizes embodiment-based body ownership to explore the human hand/forearm musculature. The HMAA was trialed with medical students to explore the extent to which it could be used to aid student learning. The key findings of the usability study suggest that 98% (N = 100) of students found the tool extremely useful; 83% reported that the tool allowed them to engage with the learning materials, peers, and content effectively. Also, 10% of students mentioned that the HMAA fostered an embodied learning experience. This triggered an intentional exploration of instances suggesting embodiment in the data. HMAA is believed to have allowed individuals to visualize and conceptualize abstract ideas that would have been otherwise challenging using static models. The outcomes of this article indicate the significant potential of body-ownership-based self-learning tools for anatomy. However, further studies using learning outcomes are needed to investigate the potential advantages of body-ownership-based tools compared to current learning techniques.
Notes: Cakmak, YO (corresponding author), Univ Otago, Dept Anat, Dunedin 9054, New Zealand.
yusuf.cakmak@otago.ac.nz; ben.daniel@otago.ac.nz;
niels.hammer@medunigraz.at; oyilmaz13@ku.edu.tr;
erdem.irmak@uhasselt.be; prash.khwaounjoo@otago.ac.nz
Other: Cakmak, YO (corresponding author), Univ Otago, Dept Anat, Dunedin 9054, New Zealand. yusuf.cakmak@otago.ac.nz; ben.daniel@otago.ac.nz; niels.hammer@medunigraz.at; oyilmaz13@ku.edu.tr; erdem.irmak@uhasselt.be; prash.khwaounjoo@otago.ac.nz
Keywords: Tools;Thumb;Avatars;Muscles;Usability;Cameras;Anatomy learning;augmented reality (AR);data visualization and learning;digital learning tools;embodied cognition;embodied learning;usability study;virtual reality (VR)
Document URI: http://hdl.handle.net/1942/32881
ISSN: 1939-1382
e-ISSN: 1939-1382
DOI: 10.1109/TLT.2020.2995163
ISI #: WOS:000571741000012
Rights: This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
Category: A1
Type: Journal Contribution
Validations: ecoom 2021
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
09095361.pdfPublished version4.77 MBAdobe PDFView/Open
Show full item record

SCOPUSTM   
Citations

25
checked on Feb 15, 2026

WEB OF SCIENCETM
Citations

16
checked on Feb 14, 2026

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.