Data · dataset · 2022
Situational Judgement Testing (SJT) in Licentiate Assessment in Canada
Listed in Borealis and Agri-environmental Research Data Dataverse — shown once because both records carry DOI 10.5683/sp3/81ozwo
The Medical Council of Canada (MCC) is reviewing medical licensing, asking whether there are gaps in short-term and long-term processes, and how these gaps might be addressed.
Description
As a team, we were asked to reflect on the current state of science regarding Situational Judgement Testing (SJT) and to consider what role this form of testing could have in high stakes licensing activity in Canada. To that end, this white paper is not a systematic review but a critical reflection on the strengths and weaknesses of SJTs and their potential role in licentiate assessment both today and tomorrow.
Simply put, situational judgement testing is about questions that assess a candidate’s ability to apply their knowledge and skill to solve problems in the domain in which they are being tested. SJTs therefore expect a candidate to be able to: recognize what the problem is in the situation presented to them; identify possible actions and rank them according to suitability; and select a course of action from the possibilities suggested by their interpretation of the situation.
Read the rest (2 more)
They don’t ask what the best way to do something in general is, rather they ask ‘how would you act in this particular situation?’ SJTs are complex assessment tools – a wrong answer does not map to a single gap in knowledge or skill but to a failure somewhere in the interactions of their interpretation, knowledge, and decision-making in the situation presented to them. Thus, while SJTs are closer to practice (for instance according to Miller’s pyramid)1 than knowledge testing instruments such as MCQs (and can therefore be argued to have good inferential validity), quite what they are assessing other than the aggregate and vague construct of judgment is often left unspecified.
In order to answer our question of what role SJTs might play in licentiate assessment, we explore: 1) what they can and cannot do, 2) what their affordances can offer licentiate assessment, and 3) how practically they might be employed in licentiate assessment. While the main thrust of this paper is about using SJTs in LMCC exams, we also hope that MCC will consider some of the recommendations that may pertain to various forms of ongoing professional assessment and revalidation.
Links
Where it is published
- Dataverse dataset page borealisdata.ca/dataset.xhtml?persistentId=doi%3A10.5683%2FSP3%2F81OZWO ↗
landing page · from borealisdata ca
- DOI doi.org/10.5683/sp3/81ozwo ↗
DOI / persistent id · from borealisdata ca
Catalogue records · 1
- Dataverse API borealisdata.ca/api/datasets/:persistentId/?persistentId=doi%3A10.5683%2FSP3%2… ↗
metadata API · from borealisdata ca
Topics
- Stated by source
- Medicine, Health and Life Sciences · Medicine, Health and Life Sciences
Provenance · 2 source records, 21 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Borealis | doi:10.5683/SP3/81OZWO | 12 d ago | JSON v1 |
| Agri-environmental Research Data Dataverse | doi:10.5683/SP3/81OZWO | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].dataverse_subject:medicine-health-and-life-sciences | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /subjects |
| concepts[field].dataverse_subject:medicine-health-and-life-sciences | source · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:chemistry | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:computer-science-ai | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:earth-environmental | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:economics-finance | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:engineering | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:humanities | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:life-sciences | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:life-sciences | mapping · borealisdata ca | connector:borealisdata_ca@1.0.0 | /subjects |
| concepts[field].local:field:mathematics-statistics | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:medicine-health | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:medicine-health | mapping · borealisdata ca | connector:borealisdata_ca@1.0.0 | /subjects |
| concepts[field].local:field:ocean-atmospheric | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| created_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| description | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /description |
| publication_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| title | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /name |
| updated_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| version_label | source · borealisdata ca | connector:borealisdata_ca@1.0.0 |