What counts as validity evidence? Examples and prevalence in a systematic review of simulation-based assessment View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2014-05

AUTHORS

David A. Cook, Benjamin Zendejas, Stanley J. Hamstra, Rose Hatala, Ryan Brydges

ABSTRACT

Ongoing transformations in health professions education underscore the need for valid and reliable assessment. The current standard for assessment validation requires evidence from five sources: content, response process, internal structure, relations with other variables, and consequences. However, researchers remain uncertain regarding the types of data that contribute to each evidence source. We sought to enumerate the validity evidence sources and supporting data elements for assessments using technology-enhanced simulation. We conducted a systematic literature search including MEDLINE, ERIC, and Scopus through May 2011. We included original research that evaluated the validity of simulation-based assessment scores using two or more evidence sources. Working in duplicate, we abstracted information on the prevalence of each evidence source and the underlying data elements. Among 217 eligible studies only six (3 %) referenced the five-source framework, and 51 (24 %) made no reference to any validity framework. The most common evidence sources and data elements were: relations with other variables (94 % of studies; reported most often as variation in simulator scores across training levels), internal structure (76 %; supported by reliability data or item analysis), and content (63 %; reported as expert panels or modification of existing instruments). Evidence of response process and consequences were each present in <10 % of studies. We conclude that relations with training level appear to be overrepresented in this field, while evidence of consequences and response process are infrequently reported. Validation science will be improved as educators use established frameworks to collect and interpret evidence from the full spectrum of possible sources and elements. More... »

PAGES

233-250

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10459-013-9458-4

DOI

http://dx.doi.org/10.1007/s10459-013-9458-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1033732525

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/23636643


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    "description": "Ongoing transformations in health professions education underscore the need for valid and reliable assessment. The current standard for assessment validation requires evidence from five sources: content, response process, internal structure, relations with other variables, and consequences. However, researchers remain uncertain regarding the types of data that contribute to each evidence source. We sought to enumerate the validity evidence sources and supporting data elements for assessments using technology-enhanced simulation. We conducted a systematic literature search including MEDLINE, ERIC, and Scopus through May 2011. We included original research that evaluated the validity of simulation-based assessment scores using two or more evidence sources. Working in duplicate, we abstracted information on the prevalence of each evidence source and the underlying data elements. Among 217 eligible studies only six (3 %) referenced the five-source framework, and 51 (24 %) made no reference to any validity framework. The most common evidence sources and data elements were: relations with other variables (94 % of studies; reported most often as variation in simulator scores across training levels), internal structure (76 %; supported by reliability data or item analysis), and content (63 %; reported as expert panels or modification of existing instruments). Evidence of response process and consequences were each present in <10 % of studies. We conclude that relations with training level appear to be overrepresented in this field, while evidence of consequences and response process are infrequently reported. Validation science will be improved as educators use established frameworks to collect and interpret evidence from the full spectrum of possible sources and elements.", 
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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10459-013-9458-4'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10459-013-9458-4'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10459-013-9458-4'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10459-013-9458-4'


 

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