The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Applying the science of learning to medical education
Abstract
Medical Education 2010: 44 : 543–549 Objective The goal of this paper is to examine how to apply the science of learning to medical education. Science of Learning The science of learning is the scientific study of how people learn. Multimedia learning – learning from words and pictures – is particularly relevant to medical education. The cognitive theory of multimedia learning is an information‐processing explanation of how people learn from words and pictures. It is based on the idea that people have separate channels for processing words and pictures, that the capacity to process information in working memory is limited, and that meaningful learning requires appropriate cognitive processing during learning. Science of Instruction The science of instruction is the scientific study of how to help people learn. Three important instructional goals are: to reduce extraneous processing (cognitive processing that does not serve an instructional objective) during learning; to manage essential processing (cognitive processing aimed at representing the essential material in working memory) during learning, and to foster generative processing (cognitive processing aimed at making sense of the material) during learning. Nine evidence‐based principles for accomplishing these goals are presented. Conclusions Applying the science of learning to medical education can be a fruitful venture that improves medical instruction and cognitive theory.
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Cites
Mayer, R. E. (2009) · doi:10.1017/cbo9780511811678 · Cited by 7,800
Self-citationMayer, R. (2020) · doi:10.1017/9781316941355 · Cited by 7,777
Self-citationNine Ways to Reduce Cognitive Load in Multimedia Learning
Mayer, R. E., & Moreno, R. (2003) · Educational Psychologist · doi:10.1207/s15326985ep3801_6 · Cited by 4,207
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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
Norman, G. R., Monteiro, S. D., Sherbino, J., Ilgen, J. S., Schmidt, H. G., & Mamede, S. (2017) · Academic Medicine · doi:10.1097/acm.0000000000001421 · Cited by 594
Lau, W. W. F. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2016.11.043 · Cited by 462
Cutrer, W. B., Miller, B., Pusic, M. V., Mejicano, G., Mangrulkar, R. S., Gruppen, L. D., Hawkins, R. E., Skochelak, S. E., & Moore, D. E. (2017) · Academic Medicine · doi:10.1097/acm.0000000000001323 · Cited by 420
Cognitive Load Theory for the Design of Medical Simulations
Fraser, K. L., Ayres, P., & Sweller, J. (2015) · Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare · doi:10.1097/sih.0000000000000097 · Cited by 306
Metadata
- Authors
- Mayer, R. E.
- Venue
- Medical Education
- Publisher
- Wiley
- Published
- 2010-05-20
- Volume
- 44
- Issue
- 6
- Pages
- 543-549
- ISSN
- 0308-0110 (ISSN-L)
- 1365-2923
- OpenAlex
- W1521400106
- Cited by
- 587
- References
- 3
- FWCI
- 18.38
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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