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Record W2962780761 · doi:10.1080/10401334.2019.1637742

Workplace-Based Assessment in Cross-Border Health Professional Education

2019· article· en· W2962780761 on OpenAlexaffabout
Kerry Wilbur, Erik W. Driessen, Fedde Scheele, Pim W. Teunissen

Bibliographic record

VenueTeaching and Learning in Medicine · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCurriculumContext (archaeology)Medical educationThematic analysisPsychologyHealth careDelphi methodCategorizationDebriefingMedicinePedagogyPolitical scienceSociologyQualitative research

Abstract

fetched live from OpenAlex

Construct: The globalization of healthcare has been accentuated by the export of health professional curricula overseas. Yet intact translation of pedagogies and practices devised in one cultural setting may not be possible or necessarily appropriate for alternate environments. Purposeful examination of workplace learning is necessary to understand how the source or “home” program may need adapting in the distributed or “host” setting. Background: Strategies to optimize cross-border medical education partnerships have been largely focused on elements of campus-based learning. Determining how host clinical supervisors approach assessment in experiential settings within a different culture and uphold the standards of home programs is relevant given the influence of context on trainees’ demonstrated competencies. In this mixed-methods study, we sought to explore assessor judgments of student workplace-based performance made by preceptors sharing a pharmacy curriculum in Canada and Qatar. Approach: Using modified Delphi consensus technique, we asked clinical supervisors in Canada (n = 18) and in Qatar (n = 14) to categorize trainee performance as described in 16 student vignettes. The proportion of ratings for three levels of expectation (exceeds, meets, or below) was calculated and within-country group consensus achieved if the level of agreement reached 80%. Between-country group comparisons were measured using a chi-square statistic. We then conducted follow-up semi-structured interviews to gain further perspectives and clarify assessor rationale. Transcripts were analyzed using thematic content analysis. Results: The threshold for between-country group differences in assessor impressions was met for only two of the 16 student vignettes. Compared to Canadian clinical supervisors, relatively more preceptors in Qatar judged one described student as meets rather than exceeds expectations and one as meets rather than falls below expectations. Analysis of follow-up interviews exploring how culture may inform variations in assessor judgments identified themes associated with the profession, organization, learner, and supervisor performance theories but not their particular geographic context. Clinical supervisors in both countries were largely aligned in expectations of student knowledge, skills, and behaviors demonstrated in patient care and multidisciplinary team interactions. Conclusions: Our study demonstrated that variation in student assessment was more frequent among clinical supervisors within the same national context than any differences identified between the two countries. In these program settings, national sociocultural norms did not predict global assessor impressions or competency-specific judgments; instead, professional and organizational cultures were more likely to inform student characterizations of performance in workplace-based settings. Further study situated within the specific experiential learning contexts of cross-border health professional curricula is assuredly warranted.

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)0.016
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.051
GPT teacher head0.574
Teacher spread0.523 · 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

Citations10
Published2019
Admission routes2
Has abstractyes

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