Effectiveness of Augmented Reality in the Teaching of Health University Students: Quasi-Experimental Study
Bibliographic record
Abstract
Background: The exponential growth of new technologies has resulted in the need for updating the field of education. From the educational point of view, there are some studies that have promoted the implementation of new technologies. These facts have raised the need to implement augmented reality in the university environment, especially among students of health sciences. The use of augmented reality can mean a new approach to teaching by teachers and better learning by students. Objective: We aimed to analyze the degree of usability of two augmented reality applications and to compare the academic performance between the control group and the experimental group at the Universities of Cádiz and Málaga. The students at the University of Málaga used the Zapworks augmented reality software, while those at the University of Cádiz used the Aumentaty augmented reality software for their respective experimental groups. The secondary objective was to measure the relationships between all the studied variables. Methods: This was a quasi-experimental design with a posttest as the only evaluation measure. We followed the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) statement and the ethical and legal aspects of the Principles of the Declaration of Helsinki. An intervention was carried out using two augmented reality applications on the subject of General Procedures in Physiotherapy II at the Universities of Málaga and Cádiz. Results: A total of 199 participants took part in the study. Demographic variables, ratings, and usability were assessed, followed by statistical analysis, with the results and their interpretation being described in the study. Significant differences (P<.001) were found in the ratings at both the universities. In addition, significant differences (P<.001) were found between the experimental group and the control group. Regarding the degree of usability in the univariate analysis, no significant differences were found (P=.049). A multiple regression analysis of the rating and usability was performed. The rating showed significant differences, with a beta of 1.4 (P<.001), and usability was also significant (P=.03) in favor of the Aumentaty group. Conclusions: Significant differences were observed in those who used augmented reality compared to the control group, with higher values observed in the University of Cádiz. There are no correlations between the variables of usability and qualifications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".