ArticlePloS one2015
Curriculum Mapping with Academic Analytics in Medical and Healthcare Education.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- A research roadmap for AI opportunities in student assessment for medical education.BMC medical education · 2025Review
- Updated ASM Curriculum Guidelines describe core microbiology content to modernize the framework for microbiology education.Journal of microbiology & biology education · 2024Article
- Pharmacogenomic curriculum in Australian medical schools: a content analysis study.Pharmacogenomics · 2024Article
- Practical Guide to Undergraduate Medical Curriculum Alignment and Mapping.Advances in medical education and practice · 2023Article
- Mapping Australian pharmacy school curricula for content related to pharmacogenomics.Exploratory research in clinical and social pharmacy · 2022Article
- Restructuring of an evidence-based practice curriculum and assessment with structural mapping by course outcome verb.The Journal of chiropractic education · 2022Article
- Ten ways to get a grip on designing and implementing a competency-based medical education training program.Canadian medical education journal · 2021Article
- Curriculum Mapping and Needs Assessment to Inform the Training of Health Policy Leaders.Ethnicity & disease · 2019Article
- Curriculum mapping as a tool to facilitate curriculum development: a new School of Medicine experience.BMC medical education · 2018Article
- Biomedical Language Analysis as a Tool for Curriculum Analysis and Mapping.Journal of medical education and curricular developmentArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNo 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.
objectiveWe 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.
methodsWe 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.
resultsWe 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.
conclusionsWe 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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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.