Informace o projektu

Building Curriculum Infrastructure in Medical Education (BCIME)

Kód projektu
2018-1-SK01-KA203-046318
Období řešení
9/2018 - 8/2021
Investor / Programový rámec / typ projektu
Evropská unie
Fakulta / Pracoviště MU
Lékařská fakulta
Spolupracující organizace
Univerzita P.J.Šafárika
Uniwersytet Jagielloński w Krakowie
The University of Medicine and Pharmacy

Today no systematic solution based on proven pedagogical approaches and methodologies exists to define, create, manage and analyse the curricula of medical and healthcare institutions of higher education within one robust system. Moreover, there is a global need for a uniform curriculum model providing a general and standardized way to describe the building blocks and the attributes of education using predefined parameters. For the purposes of speeding and improving the long-term process of medical and healthcare curricula harmonization, Building Curriculum Infrastructure in Medical Education (BCIME) project brings an innovative and well-structured system for curriculum optimisation, easily applicable in practice.
Based on detailed needs analysis, which generates a set of local institutional requirements related to the goals, aspirations and current features of curriculum organization, BCIME will provide a coherent, comprehensive framework encompassing all necessary instruments for easy curriculum management.
The project objectives are:

  • To share know-how in the field of curriculum design, innovating on and optimising the proven methodology of parametric description (curriculum building blocks) and guidelines for curriculum definition.
  • To create new descriptions of selected curriculum parts in partner institutions in accordance to the local needs analysis and institutional requirements, while in full compliance with international standards.
  • To define and solve new curriculum mapping research questions and issues and to explore hidden relations in described curricula with the use of natural language processing, data/text mining, machine learning, analysis and visualization.

Publikace

2019