Evidence map›Paper›PMID 26624281›Full record

ArticlePloS one2015

Curriculum Mapping with Academic Analytics in Medical and Healthcare Education.

Martin Komenda, Martin Víta, Christos Vaitsis, Daniel Schwarz, Andrea Pokorná, Nabil Zary, Ladislav Dušek

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Practical Guide to Undergraduate Medical Curriculum Alignment and Mapping.Advances in medical education and practice · 2023
    Article
  5. Mapping Australian pharmacy school curricula for content related to pharmacogenomics.Exploratory research in clinical and social pharmacy · 2022
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Biomedical Language Analysis as a Tool for Curriculum Analysis and Mapping.Journal of medical education and curricular development
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Martin KomendaInstitute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, Brno, Czech Republic.
Martin VítaFaculty of Informatics, Masaryk University, Brno, Czech Republic.
Christos VaitsisDepartment of Learning, Informatics Management and Ethics, Karolinska Institutet, Stockholm, Sweden.
Daniel SchwarzInstitute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, Brno, Czech Republic.
Andrea PokornáInstitute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, Brno, Czech Republic.
Nabil ZaryDepartment of Learning, Informatics Management and Ethics, Karolinska Institutet, Stockholm, Sweden.
Ladislav DušekInstitute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, Brno, Czech Republic.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

CurriculumEducation, MedicalModels, StatisticalHumans

Identifiers

PMID26624281
PMCPMC4666663

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.