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Record W2145344077 · doi:10.1177/01632780022034633

An Eclectic Model for Evaluating Web Based Continuing Medical Education Courseware Systems

2000· article· en· W2145344077 on OpenAlex
Vernon Curran

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEvaluation & the Health Professions · 2000
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMedical educationContinuing medical educationComputer scienceContinuing educationMedicineMultimediaWorld Wide Web

Abstract

fetched live from OpenAlex

World Wide Web and compact disc-read only memory technologies have introduced new prospects for delivering continuing medical education (CME) to rural and remote physicians. However, evidence concerning the effectiveness of these technologies in providing CME, and approaches to their evaluation, is limited. The rationale for this study was to design a model for evaluating the effectiveness of computer-mediated CME courseware. An eclectic, evaluation-planning matrix was designed by selecting various concepts from the literature and was used in planning and developing the evaluation model. The model was field-tested by evaluating a computer-mediated courseware program on dermatological office procedures, and a meta-evaluation was conducted to assess the effectiveness of the evaluation methods and procedures. The findings suggest that the model was useful in collecting data to inform decision making and to improve the instructional product. The field test results revealed that computer-mediated instruction was effective in delivering CME at a distance.

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.

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)0.016
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.975
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.133
GPT teacher head0.548
Teacher spread0.415 · 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