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Curriculum Mapping with Academic Analytics in Medical and Healthcare Education
M. Komenda, M. Víta, C. Vaitsis, D. Schwarz, A. Pokorná, N. Zary, L. Dušek,
Jazyk angličtina Země Spojené státy americké
Typ dokumentu časopisecké články, práce podpořená grantem
NLK
Directory of Open Access Journals
od 2006
Free Medical Journals
od 2006
Public Library of Science (PLoS)
od 2006
PubMed Central
od 2006
Europe PubMed Central
od 2006
ProQuest Central
od 2006-12-01
Open Access Digital Library
od 2006-10-01
Open Access Digital Library
od 2006-01-01
Open Access Digital Library
od 2006-01-01
Medline Complete (EBSCOhost)
od 2008-01-01
Nursing & Allied Health Database (ProQuest)
od 2006-12-01
Health & Medicine (ProQuest)
od 2006-12-01
Public Health Database (ProQuest)
od 2006-12-01
ROAD: Directory of Open Access Scholarly Resources
od 2006
- MeSH
- kurikulum * MeSH
- lidé MeSH
- statistické modely * MeSH
- studium lékařství * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: No universal solution, based on an approved pedagogical approach, exists to parametrically describe, effectively manage, and clearly visualize a higher education institution's curriculum, including tools for unveiling relationships inside curricular datasets. OBJECTIVE: We aim to solve the issue of medical curriculum mapping to improve understanding of the complex structure and content of medical education programs. Our effort is based on the long-term development and implementation of an original web-based platform, which supports an outcomes-based approach to medical and healthcare education and is suitable for repeated updates and adoption to curriculum innovations. METHODS: We adopted data exploration and visualization approaches in the context of medical curriculum innovations in higher education institutions domain. We have developed a robust platform, covering detailed formal metadata specifications down to the level of learning units, interconnections, and learning outcomes, in accordance with Bloom's taxonomy and direct links to a particular biomedical nomenclature. Furthermore, we used selected modeling techniques and data mining methods to generate academic analytics reports from medical curriculum mapping datasets. RESULTS: We present a solution that allows users to effectively optimize a curriculum structure that is described with appropriate metadata, such as course attributes, learning units and outcomes, a standardized vocabulary nomenclature, and a tree structure of essential terms. We present a case study implementation that includes effective support for curriculum reengineering efforts of academics through a comprehensive overview of the General Medicine study program. Moreover, we introduce deep content analysis of a dataset that was captured with the use of the curriculum mapping platform; this may assist in detecting any potentially problematic areas, and hence it may help to construct a comprehensive overview for the subsequent global in-depth medical curriculum inspection. CONCLUSIONS: We have proposed, developed, and implemented an original framework for medical and healthcare curriculum innovations and harmonization, including: planning model, mapping model, and selected academic analytics extracted with the use of data mining.
Department of Learning Informatics Management and Ethics Karolinska Institutet Stockholm Sweden
Faculty of Informatics Masaryk University Brno Czech Republic
Institute of Biostatistics and Analyses Faculty of Medicine Masaryk University Brno Czech Republic
Citace poskytuje Crossref.org
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- $a BACKGROUND: No universal solution, based on an approved pedagogical approach, exists to parametrically describe, effectively manage, and clearly visualize a higher education institution's curriculum, including tools for unveiling relationships inside curricular datasets. OBJECTIVE: We aim to solve the issue of medical curriculum mapping to improve understanding of the complex structure and content of medical education programs. Our effort is based on the long-term development and implementation of an original web-based platform, which supports an outcomes-based approach to medical and healthcare education and is suitable for repeated updates and adoption to curriculum innovations. METHODS: We adopted data exploration and visualization approaches in the context of medical curriculum innovations in higher education institutions domain. We have developed a robust platform, covering detailed formal metadata specifications down to the level of learning units, interconnections, and learning outcomes, in accordance with Bloom's taxonomy and direct links to a particular biomedical nomenclature. Furthermore, we used selected modeling techniques and data mining methods to generate academic analytics reports from medical curriculum mapping datasets. RESULTS: We present a solution that allows users to effectively optimize a curriculum structure that is described with appropriate metadata, such as course attributes, learning units and outcomes, a standardized vocabulary nomenclature, and a tree structure of essential terms. We present a case study implementation that includes effective support for curriculum reengineering efforts of academics through a comprehensive overview of the General Medicine study program. Moreover, we introduce deep content analysis of a dataset that was captured with the use of the curriculum mapping platform; this may assist in detecting any potentially problematic areas, and hence it may help to construct a comprehensive overview for the subsequent global in-depth medical curriculum inspection. CONCLUSIONS: We have proposed, developed, and implemented an original framework for medical and healthcare curriculum innovations and harmonization, including: planning model, mapping model, and selected academic analytics extracted with the use of data mining.
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