Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 178

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Workplace-based assessment: raters’ performance theories and constructs

Open access
Govaerts, M. J. B., Van de Wiel, M. W. J., Schuwirth, L. W. T., Van der Vleuten, C. P. M., Muijtjens, A. M. M.·2013·Advances in Health Sciences Education

Abstract

Weaknesses in the nature of rater judgments are generally considered to compromise the utility of workplace-based assessment (WBA). In order to gain insight into the underpinnings of rater behaviours, we investigated how raters form impressions of and make judgments on trainee performance. Using theoretical frameworks of social cognition and person perception, we explored raters' implicit performance theories, use of task-specific performance schemas and the formation of person schemas during WBA. We used think-aloud procedures and verbal protocol analysis to investigate schema-based processing by experienced (N = 18) and inexperienced (N = 16) raters (supervisor-raters in general practice residency training). Qualitative data analysis was used to explore schema content and usage. We quantitatively assessed rater idiosyncrasy in the use of performance schemas and we investigated effects of rater expertise on the use of (task-specific) performance schemas. Raters used different schemas in judging trainee performance. We developed a normative performance theory comprising seventeen inter-related performance dimensions. Levels of rater idiosyncrasy were substantial and unrelated to rater expertise. Experienced raters made significantly more use of task-specific performance schemas compared to inexperienced raters, suggesting more differentiated performance schemas in experienced raters. Most raters started to develop person schemas the moment they began to observe trainee performance. The findings further our understanding of processes underpinning judgment and decision making in WBA. Raters make and justify judgments based on personal theories and performance constructs. Raters' information processing seems to be affected by differences in rater expertise. The results of this study can help to improve rater training, the design of assessment instruments and decision making in WBA.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/s10459-012-9376-x

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

Metadata

Authors
Govaerts, M. J. B., Van de Wiel, M. W. J., Schuwirth, L. W. T., Van der Vleuten, C. P. M., & Muijtjens, A. M. M.
Venue
Advances in Health Sciences Education
Published
2012-05-17
Volume
18
Issue
3
Pages
375-396
ISSN
  • 1382-4996 (ISSN-L)
  • 1573-1677
OpenAlex
W2083559293
Cited by
178
References
3
FWCI
10.42
Type
journal article
Language
en
Open access
hybrid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.