MétaCan
Menu
Back to cohort
Record W2794232514 · doi:10.2196/mededu.9237

Mobile Technology in E-Learning for Undergraduate Medical Education on Emergent Otorhinolaryngology–Head and Neck Surgery Disorders: Pilot Randomized Controlled Trial

2018· article· en· W2794232514 on OpenAlexvenueno aff
Li‐Ang Lee, Shu‐Ling Wang, Yi‐Ping Chao, Ming‐Shao Tsai, Li‐Jen Hsin, Chung‐Jan Kang, Chia‐Hsiang Fu, Wei‐Chieh Chao, Chung‐Guei Huang, Hsueh‐Yu Li, Cheng‐Keng Chuang

Bibliographic record

VenueJMIR Medical Education · 2018
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsnot available
FundersMinistry of Science and Technology, TaiwanChang Gung Medical Foundation
KeywordsOtorhinolaryngologyCompetence (human resources)MedicineRandomized controlled trialHead and neck surgeryMedical educationPsychologyPhysical therapySurgery

Abstract

fetched live from OpenAlex

BACKGROUND: The use of mobile technology in e-learning (M-TEL) can add new levels of experience and significantly increase the attractiveness of e-learning in medical education. Whether an innovative interactive e-learning multimedia (IM) module or a conventional PowerPoint show (PPS) module using M-TEL to teach emergent otorhinolaryngology-head and neck surgery (ORL-HNS) disorders is feasible and efficient in undergraduate medical students is unknown. OBJECTIVE: The aim of this study was to compare the impact of a novel IM module with a conventional PPS module using M-TEL for emergent ORL-HNS disorders with regard to learning outcomes, satisfaction, and learning experience. METHODS: This pilot study was conducted at an academic teaching hospital and included 24 undergraduate medical students who were novices in ORL-HNS. The cognitive style was determined using the Group Embedded Figures Test. The participants were randomly allocated (1:1) to one of the two groups matched by age, sex, and cognitive style: the IM group and the PPS group. During the 100-min learning period, the participants were unblinded to use the IM or PPS courseware on a 7-inch tablet. Pretests and posttests using multiple-choice questions to evaluate knowledge and multimedia situational tests to evaluate competence were administered. Participants evaluated their satisfaction and learning experience by the AttrakDiff2 questionnaire, and provided feedback about the modules. RESULTS: Overall, the participants had significant gains in knowledge (median of percentage change 71, 95% CI 1-100, P<.001) and competence (median of percentage change 25, 95% CI 0-33, P=.007) after 100 min of learning. Although there was no significant difference in knowledge gain between the two groups (median of difference of percentage change 24, 95% CI -75 to 36; P=.55), competence gain was significantly lower in the IM group compared with the PPS group (median of difference of percentage change -41, 95% CI -67 to -20; P=.008). However, the IM group had significantly higher scores of satisfaction (difference 2, 95% CI 2-4; P=.01), pragmatic quality (difference 1.7, 95% CI 0.1-2.7; P=.03), and hedonic stimulation (difference 1.9, 95% CI 0.3-3.1; P=.01) compared with the PPS group. Qualitative feedback indicated that the various games in the IM module attracted the participants' attention but that the nonlinearly arranged materials affected their learning. CONCLUSIONS: Using M-TEL for undergraduate medical education on emergent ORL-HNS disorders, an IM module seems to be useful for gaining knowledge, but competency may need to occur elsewhere. While the small sample size reduces the statistical power of our results, its design seems to be appropriate to determine the effects of M-TEL using a larger group. TRIAL REGISTRATION: ClinicalTrials.gov NCT02971735; https://clinicaltrials.gov/ct2/show/NCT02971735 (Archived by WebCite at http://www.webcitation.org/6waoOpCEV).

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)0.002
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.359
Teacher spread0.341 · 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.

Study designRandomized trial
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

Citations29
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Medical EducationSame topicSurgical Simulation and TrainingFrench-language works237,207