X‐Reality and the Microsoft HoloLens: A Hollow Tool for Anatomical Education
Bibliographic record
Abstract
Recent technological advancements in X‐Reality (XR) seem to create remarkably realistic models for anatomical education. Despite a lack of evidence regarding the efficacy of XR in this context, several institutions have adopted these technologies as primary educational tools in anatomy as an alternative to traditional cadaveric laboratories. In our earliest study, we evaluated a 3D, interactive projection on a 2D screen against a physical model of a female pelvis. This data demonstrated that those who learnt on the physical model performed significantly better during testing. Subsequently, we explored the efficacy of more intricate XR systems. Thus, we compared the efficacy of the Microsoft HoloLens, a mixed‐reality (MR) device, to a physical model in anatomy education. We recruited 20 McMaster University students and ran a preliminary study to gather qualitative data regarding the optimal MR environment. We gathered participant preference based on their experience observing several virtual objects against different coloured backgrounds and various lighting combinations. We used this data to build the testing environment for the MR model, such as adding black curtains and floor tiles to the room, and using a single light over the projection. These conditions were also used for the physical model, thus placing it at a slight disadvantage. We then recruited 40 McMaster University students with no prior anatomical education, and randomized them into two groups: one learning on a physical model of a female pelvis and one learning on the MR model of a female pelvis. We measured two possible covariates, spatial and stereoscopic ability, through two pretest assessments: a Mental Rotations Test (MRT) and a Titmus Fly Test, respectively. Our participants were then given 10 minutes to learn 20 structures using their respective models, and were tested on a female cadaveric pelvis on the basis of a 25‐question test with no time limit. This test included 15 nominal questions, which asked participants to name the indicated structure, and 10 functional questions, which asked participants to determine the function of a structure based on its location and form. We hypothesized that due to the realistic model that the MR system created, it should perform at least equivalent to the physical model in the context of anatomical education. Our assessments found that participants learning on the physical model performed significantly better in comparison to their MR counterparts on both nominal (65% vs 41%, respectively; p = 0.0051) and functional measures (42% vs. 31%, respectively; p = 0.0134). Additionally, when controlling for the aforementioned covariates, we found these results to remain consistent. Ultimately, our results indicate that the MR device is an inefficient tool for anatomical education when compared to traditional physical models. Our future directions involve exploring possible determinants influencing the superiority of the physical model, such as stereoscopic vision, as well as the assessment of other XR systems, such as virtual reality headsets, in the context of anatomy education. Support or Funding Information Self‐funded. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".