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Record W2176203658 · doi:10.1108/itse-05-2015-0013

Augmented reality m-learning to enhance nursing skills acquisition in the clinical skills laboratory

2015· article· en· W2176203658 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInteractive Technology and Smart Education · 2015
Typearticle
Languageen
FieldComputer Science
TopicMobile Learning in Education
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFocus groupMedical educationAugmented realityExploratory researchResource (disambiguation)PsychologyComputer scienceMedicine

Abstract

fetched live from OpenAlex

Purpose – This paper aims to report on a pilot research project designed to explore if new mobile augmented reality (AR) technologies have the potential to enhance the learning of clinical skills in the lab. Design/methodology/approach – An exploratory action-research-based pilot study was undertaken to explore an initial proof-of-concept design in using AR resources to supplement clinical skills lab teaching. A convenience non-probability sample of 72 undergraduate nursing students tested these resources during lab sessions, and participated in post-exposure surveys and focus groups to help evaluate them. This pilot design aimed to test logistics and gather information prior to further developmental work. Findings – Key similarities emerged between the survey and focus group findings regarding the technical issues and support for student learning. Students clearly expressed a comfort with the technology, and both students and faculty identified the ability to access resources to support self-directed learning and review of skills as positive attributes of using AR. However, technical issues such as slow response times and incompatible smartphones interfered with resource access and frustrated some students, potentially having a negative impact on their learning. Students gave positive feedback regarding the value of mobile access and having AR resources available “at the bedside” where they were practicing. Research limitations/implications – This empirical pilot study was limited to a small number of participants in a single location. However, a deeper understanding of the potential value of AR in clinical health professional education, and best practices in implementing these new technologies, was achieved. Practical implications – This study provides a valuable practical contribution, as the approach for AR resource development described can be readily replicated by teachers with limited technical skills. The practical limitations of AR technologies discovered by use in real-world settings will provide developers and educators with valuable information as they begin to explore the use of AR in the lab and beyond. Social implications – AR represents a rapidly developing field, with increasing social impact. This study provides some initial ideas that will help inform future uptake of AR in wider educational settings, beyond health professional education. Originality/value – This study represents original work in the field, and specifically, an original implementation of AR in an educational context.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.772
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.384
Teacher spread0.372 · 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