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Record W1984706038 · doi:10.1177/1553350614531660

Transatlantic Peer-to-Peer Learning

2014· article· en· W1984706038 on OpenAlexaffabout
Noel Lynch, Tulin Cil, Elaine Lehane, Michelle Reardon, Mark Corrigan

Bibliographic record

VenueSurgical Innovation · 2014
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsThe Wilson CentreUniversity of Toronto
Fundersnot available
KeywordsPeer feedbackUploadPeer learningMedical educationPeer reviewMedicinePeer supportPeer groupPsychologyWorld Wide WebComputer scienceMathematics educationNursingSocial psychology

Abstract

fetched live from OpenAlex

INTRODUCTION: Peer-to-peer learning is a well-established learning modality, which has been shown to improve learning outcomes, with positive implications for clinical practice. The purpose of this pilot study was to explore the feasibility of linking students from North America and Europe with a peer-to-peer learning approach. METHODS: Face and content validity studies were completed on the previously designed and validated online repository http://www.pilgrimshospital.com. Four medical students from the University of Toronto, Canada, were paired with four students from University College Cork, Ireland. Each student was invited to upload two pieces of information learned from a senior colleague that day. Each student was asked to review the information uploaded by their partner, editing with references if needed. Quantitative and qualitative evaluations of the e-peer system were conducted. RESULTS: Over the study period, the system recorded a total of 10 079 individual page views. Questionnaires completed by participants demonstrated that 6/8 found the system either "very easy" or "easy" to use, whereas all found that the system promoted evidenced-based and self-directed learning. Structured interviews revealed 3 main themes: The Peer Connection, Trust in Data Veracity, and Aid to Clinical Learning. CONCLUSION: This pilot study demonstrates it is feasible to link students from separate continents in a community of peer-to-peer learning. This is viewed positively by students and enhances evidenced-based learning, and the aspect of peer connectivity was important to participating students. Such an approach encourages peer cooperation and has the potential to disseminate key clinical learning experiences widely.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.894
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
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 head0.020
GPT teacher head0.336
Teacher spread0.316 · 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 designNot applicable
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

Citations3
Published2014
Admission routes2
Has abstractyes

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