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Record W2002716848 · doi:10.1503/cjs.004513

“iBIM” — Internet-based interactive modules: an easy and interesting learning tool for general surgery residents

2014· article· en· W2002716848 on OpenAlexaffvenueabout
Nader Azer, Xinzhe Shi, Chris de Gara, Shahzeer Karmali, Daniel W. Birch

Bibliographic record

VenueCanadian Journal of Surgery · 2014
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsRoyal Alexandra HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicineCompetence (human resources)The InternetCurriculumTest (biology)AutonomyMultiple choiceFlexibility (engineering)Medical educationSignificant differenceInternal medicineWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: The increased use of information technology supports a resident- centred educational approach that promotes autonomy, flexibility and time management and helps residents to assess their competence, promoting self-awareness. We established a web-based e-learning tool to introduce general surgery residents to bariatric surgery and evaluate them to determine the most appropriate implementation strategy for Internet-based interactive modules (iBIM) in surgical teaching. METHODS: Usernames and passwords were assigned to general surgery residents at the University of Alberta. They were directed to the Obesity101 website and prompted to complete a multiple-choice precourse test. Afterwards, they were able to access the interactive modules. Residents could review the course material as often as they wanted before completing a multiple-choice postcourse test and exit survey. We used paired t tests to assess the difference between pre- and postcourse scores. RESULTS: Out of 34 residents who agreed to participate in the project, 12 completed the project (35.3%). For these 12 residents, the precourse mean score was 50 ± 17.3 and the postcourse mean score was 67 ± 14 (p = 0.020). CONCLUSION: Most residents who participated in this study recommended using the iBIMs as a study tool for bariatric surgery. Course evaluation scores suggest this novel approach was successful in transferring knowledge to surgical trainees. Further development of this tool and assessment of implementation strategies will determine how iBIM in bariatric surgery may be integrated into the curriculum.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.068
GPT teacher head0.299
Teacher spread0.232 · 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 designObservational
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

Citations11
Published2014
Admission routes3
Has abstractyes

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