The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Frameworks for learner assessment in medicine: AMEE Guide No. 78
Open accessAbstract
In any evaluation system of medical trainees there is an underlying set of assumptions about what is to be evaluated (i.e., which goals reflect the values of the system or institution), what kind of observations or assessments are useful to allow judgments 1 ; and how these are to be analyzed and compared to a standard of what is to be achieved by the learner. These assumptions can be conventionalized into a framework for evaluation. Frameworks encompass, or "frame," a group of ideas or categories to reflect the educational goals against which a trainee's level of competence or progress is gauged. Different frameworks provide different ways of looking at the practice of medicine and have different purposes. In the first place, frameworks should enable educators to determine to what extent trainees are ready for advancement, that is, whether the desired competence has been attained. They should provide both a valid mental model of competence and also terms to describe successful performance, either at the end of training or as milestones during the curriculum. Consequently, such frameworks drive learning by providing learners with a guide for what is expected. Frameworks should also enhance consistency and reliability of ratings across staff and settings. Finally, they determine the content of, and resources needed for, rater training to achieve consistency of use. This is especially important in clinical rotations, in which reliable assessments have been most difficult to achieve. Because the limitations of workplace-based assessment have persisted despite the use of traditional frameworks (such as those based on knowledge, skills, and attitudes), this Guide will explore the assumptions and characteristics of traditional and newer frameworks. In this AMEE Guide, we make a distinction between analytic, synthetic, and developmental frameworks. Analytic frameworks deconstruct competence into individual pieces, to evaluate each separately. Synthetic frameworks attempt to view competence holistically, focusing evaluation on the performance in real-world activities. Developmental frameworks focus on stages of, or milestones, in the progression toward competence. Most frameworks have one predominant perspective; some have a hybrid nature.
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Cites
Situated Learning: Legitimate Peripheral Participation
Lave, J., & Wenger, E. (1991) · Cambridge University Press eBooks · doi:10.1017/cbo9780511815355 · Cited by 35,324
A revision of bloom's taxonomy: an overview
Krathwohl, D. R. (2002) · Theory Into Practice · doi:10.1207/s15430421tip4104_2 · Cited by 8,132
The assessment of clinical skills/competence/performance
Miller, G. E. (1990) · Academic Medicine · doi:10.1097/00001888-199009000-00045 · Cited by 4,883
Medical Problem Solving: An Analysis of Clinical Reasoning
Elstein, A. S., Shulman, L. S., & Sprafka, S. A. (1978) · doi:10.4159/harvard.9780674189089 · Cited by 1,377
Cited by
Cognitive Load Theory: Implications for medical education: AMEE Guide No. 86
Young, J. Q., Van Merrienboer, J., Durning, S., & Ten Cate, O. (2014) · Medical Teacher · doi:10.3109/0142159x.2014.889290 · Cited by 935
Self-citationThe Case for Use of Entrustable Professional Activities in Undergraduate Medical Education
Chen, H. C., van den Broek, W. E. S., & ten Cate, O. (2015) · Academic Medicine · doi:10.1097/acm.0000000000000586 · Cited by 431
Self-citationLakhtakia, R., Otaki, F., Alsuwaidi, L., & Zary, N. (2022) · JMIR Medical Education · doi:10.2196/35820 · Cited by 38
Mukurunge, E., Nyoni, C. N., & Hugo, L. (2024) · BMC Medical Education · doi:10.1186/s12909-024-05264-x · Cited by 16
Metadata
- Authors
- Pangaro, L., & ten Cate, O.
- Venue
- Medical Teacher
- Publisher
- Informa UK Limited
- Published
- 2013-05-16
- Volume
- 35
- Issue
- 6
- Pages
- e1197-e1210
- ISSN
- 0142-159X (ISSN-L)
- 1466-187X
- OpenAlex
- W2151694392
- Cited by
- 260
- References
- 4
- FWCI
- 11.66
- Type
- journal article
- Language
- en
- Open access
- bronze
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