MétaCan
Menu
Back to cohort

Virtual Reality to Teach Human Anatomy – An Interactive and Accessible Educational Tool

2018· article· en· W3173594294 on OpenAlexaffabout
William Albabish, Lorraine Jadeski

Bibliographic record

VenueThe FASEB Journal · 2018
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsVirtual realityComputer scienceHeadsetMultimediaHuman–computer interactionPresentation (obstetrics)InteractivityMedicineTelecommunications

Abstract

fetched live from OpenAlex

Virtual reality (VR) is a revolutionizing technology. Prior to 2016 VR systems were cost prohibitive, and user‐unfriendly. The Oculus Rift, first introduced in 2013, revolutionized the VR field by bringing forth the first commercialized VR system. In 2017, many affordable VR systems have been introduced into the commercial market, some costing less than a typical cellphone. The VR systems consist of a wearable headset, two controllers that allow the user to naturally interact with objects in the VR space, and lastly sensors connected to a computer allow for precise tracking of all head and hand movements. VR is a tool with endless possibilities, it can be implemented in any course as a teaching or supplementary resource. Within the VR space, users may play a PowerPoint presentation or a video, open a document, draw in 3D VR space any object. In VR, users can also host a live class; students may watch on their mobile devices, or enter the interactive VR space with their own system. Additionally, in VR, a user can change their environment to anything they desire, including access to any space, anywhere in the world with internet access. Therefore, bringing the laboratory to the student and the instructor. VR is the tool that can revolutionize the delivery of distance education material. The University of Guelph offers a comprehensive dissection‐based human anatomy course to approximately 400 third‐ and fourth‐year undergraduate students yearly. Additionally, in collaboration with Guelph Humber, a first‐year anatomy course is offered off‐site to 120 kinesiology students, with a laboratory component hosted weekly at the University of Guelph. In the fall of 2017, a strike affecting all colleges in Ontario limited the ability to deliver off‐site lectures for 5 weeks. During the strike, innovate ways of lecture delivery were successfully used to meet course objectives, including narrated PowerPoint presentations and virtual reality lessons. Various anatomical lessons were delivered online to students in various formats, addressing the thorax and abdominal regions. In week 3, students were sent a video (Abd1) demonstrating the blood supply of the abdomen (Celiac Trunk, SMA, IMA and all associated branches, relationships, and developmental concepts) (Fig. 1). A week later, students were sent another video, demonstrating the same lesson, however in VR format (AbdVR) (Fig. 2). Abd1 is 22.5 minutes in length, attained an average view duration of 4.05 min, a total view time of 280 min, and average view percentage of 18%. Whereas AbdVR is 20 minutes in length, attained an average view duration of 9.1 min, a total view time of 542 min, and an average view percentage of 45%. Abd1 audience retention decreased gradually throughout the video, whereas AbdVR performed with an above‐average retention rate, and had several large peaks of retention throughout, all corresponding to important concepts being shown, such as the visualization of anterior and posterior branches of the superior pancreaticoduodenal artery – a concept that would be difficult to show two‐dimensionally (Fig 3). Through an online survey, students indicated that VR videos allowed them a better understanding of the complex 3D nature of the human body. Concepts such as the blood anastomosis of the elbow became easier to understand and visualize. Students also appreciated having a “person” speak to them as opposed to a narrated video. Overall, VR educational videos performed exceptionally well in showcasing anatomical concepts with depth. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.323
Teacher spread0.307 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueThe FASEB JournalSame topicAnatomy and Medical TechnologyFrench-language works237,207