title: Curriculum Mapping with Academic Analytics in Medical and Healthcare Education.
abstract: 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.
authors.affiliation: Institute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, Brno, Czech Republic.|Faculty of Informatics, Masaryk University, Brno, Czech Republic.
authors.forename: Martin
authors.initials: M
authors.lastname: Komenda
authors.affiliation: Faculty of Informatics, Masaryk University, Brno, Czech Republic.
authors.forename: Martin
authors.initials: M
authors.lastname: Víta
authors.affiliation: Department of Learning, Informatics Management and Ethics, Karolinska Institutet, Stockholm, Sweden.
authors.forename: Christos
authors.initials: C
authors.lastname: Vaitsis
authors.affiliation: Institute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, Brno, Czech Republic.
authors.forename: Daniel
authors.initials: D
authors.lastname: Schwarz
authors.affiliation: Institute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, Brno, Czech Republic.
authors.forename: Andrea
authors.initials: A
authors.lastname: Pokorná
authors.affiliation: Department of Learning, Informatics Management and Ethics, Karolinska Institutet, Stockholm, Sweden.
authors.forename: Nabil
authors.initials: N
authors.lastname: Zary
authors.affiliation: Institute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, Brno, Czech Republic.
authors.forename: Ladislav
authors.initials: L
authors.lastname: Dušek
mesh_terms: D003479:Curriculum; D004501:Education, Medical; D006801:Humans; D015233:Models, Statistical