Evidence map›Paper›PMID 39582790›Full record

ArticlePerspectives on medical education2024

Digital Evidence: Revisiting Assumptions at the Intersection of Technology and Assessment.

Andrew E Krumm, Saad Chahine, Abigail M Schuh, Daniel J Schumacher, Sondra Zabar, Brian C George, Kayla Marcotte, Stefanie S Sebok-Syer, Michael A Barone, Alina Smirnova

Abstract read
In one paragraph

Article in Perspectives on medical education, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Andrew E KrummLearning Health Sciences, Surgery, and Information, Medical School and School of Information, University of Michigan, Ann Arbor, Michigan, United States.ORCID 0000-0001-9714-1632
Saad ChahineFaculty of Education, Queen's University, Canada.ORCID 0000-0003-0488-773X
Abigail M SchuhDivision of Emergency Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin, United States.ORCID 0000-0002-6422-2361
Daniel J SchumacherDivision of Emergency Medicine, Cincinnati Children's Hospital Medical Center/University of Cincinnati College of Medicine, Cincinnati, Ohio, United States.ORCID 0000-0001-5507-8452
Sondra ZabarDivision of General Internal Medicine and Clinical Innovation at the NYU Grossman School of Medicine, New York, New York, United States.ORCID 0000-0002-9223-1898
Brian C GeorgeSurgery and Learning Health Sciences, University of Michigan, Ann Arbor, Michigan, United States.ORCID 0000-0002-9404-5255
Kayla MarcotteDepartment of Learning Health Sciences, University of Michigan, Ann Arbor, Michigan, United States.ORCID 0000-0001-8773-213X
Stefanie S Sebok-SyerEmergency Medicine, Stanford University, Stanford, California, United States.ORCID 0000-0002-3572-5971
Michael A BaroneThe American Board of Pediatrics, Chapel Hill, North Carolina, United States.ORCID 0000-0002-4724-784X
Alina SmirnovaDepartment of Family Medicine, University of Calgary, Calgary, Alberta, Canada.ORCID 0000-0003-4491-3007

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing use of technology in health care and health professions education is an invitation to examine how digital sources of evidence are used in making assessment claims. In this paper, we describe how four sets of terms-primary and secondary data; structured and unstructured data; development and use; and deterministic and generative-can aid in examining how data from digital sources are used in evaluating what learners know and can do. Drawing on multiple examples, this paper shows how the four sets of terms can help both developers and users of technology-based assessment systems.

Indexed as

Educational MeasurementHumansTechnology Assessment, Biomedical

Identifiers

PMID39582790
PMCPMC11583624

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.