MétaCan
Menu
Back to cohort

User experience and the influence on the evaluation of information presentation in an online brachial plexus module

2012· article· en· W3175681700 on OpenAlexaff
James G Turgeon, Kevin Armstrong, Timothy D. Wilson

Bibliographic record

VenueThe FASEB Journal · 2012
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsWestern University
Fundersnot available
KeywordsPresentation (obstetrics)Test (biology)Brachial plexusComputer scienceField (mathematics)ScholarshipHuman–computer interactionPsychologyMultimediaMedicineSurgeryMathematics

Abstract

fetched live from OpenAlex

E‐learning through computer modules is a growing trend amongst anatomical educators. However, little research has explored the translation of design components between users of different experience levels. This study explored the role of prior knowledge and its effect on user rating of an online learning module. Due to the brachial plexus’ complexity, difficulty in learning and the continued application within the medical field, a three‐dimensional model of the brachial plexus and surrounding structures was created. This model was integrated into two interactive interfaces demonstrating equivalent information in distinct presentation modes, guided and self‐guided. For a distribution of low (LK) and high (HK) prior knowledge participants, recruitment occurred from undergraduate and resident populations. Pre‐test scores verified participants as high or low prior knowledge. It is hypothesized that HK users prefer self‐guided module characteristics while LK users prefer the direction inherent in the guided module. It is expected that all users will show improvement between pre‐ and post‐test scores, and greater improvement will correspond with the higher rated module. Grant Funding Source : Queen Elizabeth II Graduate Scholarship in Science and Technology

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)0.012
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 score0.658
Threshold uncertainty score0.416

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.122
GPT teacher head0.437
Teacher spread0.315 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueThe FASEB JournalSame topicInnovative Teaching and Learning MethodsFrench-language works237,207