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Record W2144327791 · doi:10.1080/0142159031000136743

The Supplemental Instruction Project: peer-devised and delivered tutorials

2003· article· en· W2144327791 on OpenAlexaffabout
Katrina Hurley, Donald W. McKay, Thomas M. Scott, Bonnie M. James

Bibliographic record

VenueMedical Teacher · 2003
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsTUTORSession (web analytics)Medical educationMedical schoolMedicinePsychologyComputer scienceMathematics educationWorld Wide Web

Abstract

fetched live from OpenAlex

The purpose of this study was to determine whether student devised and delivered supplemental instruction is beneficial and acceptable to first-year medical students. A student-run Supplemental Instruction Project (SIP) was developed and delivered by second-year medical students and offered free of charge to all first-year medical students at Memorial University of Newfoundland taking the Integrated Study of Disease I course in 1999 and again in 2000. Small-group tutorials focused on subject material that second-year medical students identified as 'difficult'. Five 60- to 90-minute sessions covering topics in cardiology, nephrology and respirology were offered. Student and tutor perceptions about the project were collected using anonymous questionnaires. Students were quizzed before and after each tutorial session. Post-tutorial quiz scores were significantly greater than pre-tutorial scores. Student and tutor perceptions of SIP were positive. It is concluded that the SIP is an acceptable, practical and effective method to supplement delivery of challenging material to first-year medical students.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.022
GPT teacher head0.348
Teacher spread0.326 · 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 source (direct Gemma or distilled Codex), 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

Citations71
Published2003
Admission routes2
Has abstractyes

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