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Record W2117071413 · doi:10.5014/ajot.59.3.314

A Comparative Analysis of Case Presentation Modalities Used in Clinical Reasoning Coursework in Occupational Therapy

2005· article· en· W2117071413 on OpenAlexaff
Rosemary Lysaght, Margaret Bent

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2005
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsQueen's University
Fundersnot available
KeywordsCourseworkModalitiesPresentation (obstetrics)Modality (human–computer interaction)Treatment modalityPsychologyOccupational therapyMedical educationThe InternetCategorizationLearning stylesComputer scienceMathematics educationMedicineArtificial intelligenceRadiologySurgery

Abstract

fetched live from OpenAlex

This study used mixed methods to compare four different styles of case presentation in a course designed to develop the clinical reasoning skills of master's level occupational therapy students. Modalities used to present cases were printed text, videotape, live interview, and CD-ROM movies delivered on an Internet platform. The researchers sought to determine the relative merits and limitations of each modality from both pedagogical and practical standpoints. Results indicate that the choice of modality does not compromise the ability of students to meet learning objectives related to clinical reasoning; however, several advantages and disadvantages with respect to practical aspects of presentation and learning were identified from instructor and student perspectives. The strength of the overall instructional format, and decisions concerning the amount and type of information provided in the cases were found to be more relevant to the quality of the learning experience than the modality of presentation. Recommendations are provided for structuring clinical reasoning learning experiences that combine the best features from the case modalities examined in this study.

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)0.017
metaresearch head score (Gemma)0.099
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 score0.017
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.099
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.153
GPT teacher head0.522
Teacher spread0.369 · 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

Citations34
Published2005
Admission routes1
Has abstractyes

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