Curriculum Mapping with Academic Analytics in Medical and Healthcare Education

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.

[1]  Daniel Schwarz,et al.  A Unified Educational Platform of Multimedia Support in Education at Medical Faculties of MEFANET Project , 2012 .

[2]  R. Keeling,et al.  The Bologna Process and the Lisbon Research Agenda: the European Commission’s expanding role in higher education discourse , 2006 .

[3]  L. Freeman Centrality in social networks conceptual clarification , 1978 .

[4]  Inga Hege,et al.  Developing and analysing a curriculum map in Occupational- and Environmental Medicine , 2010, BMC medical education.

[5]  John B. Biggs,et al.  Teaching for Quality Learning at University: What the Student Does , 1999 .

[6]  Thomas Reinartz,et al.  CRISP-DM 1.0: Step-by-step data mining guide , 2000 .

[7]  Matthieu Latapy,et al.  Computing Communities in Large Networks Using Random Walks , 2004, J. Graph Algorithms Appl..

[8]  Linda Corrin,et al.  Academic Analytics in a Medical Curriculum: Enabling Educational Excellence. , 2012 .

[9]  Caroline Wachtler,et al.  A hidden curriculum: mapping cultural competency in a medical programme , 2003, Medical education.

[10]  Nabil Zary,et al.  Visual Analytics in Medical Education: Impacting Analytical Reasoning and Decision Making for Quality Improvement , 2015, MIE.

[11]  P. Bonacich Power and Centrality: A Family of Measures , 1987, American Journal of Sociology.

[12]  Cecilia M. Plaza,et al.  Curriculum mapping in program assessment and evaluation. , 2007, American journal of pharmaceutical education.

[13]  Kayoko Uchiyama,et al.  Curriculum Mapping in Higher Education: A Vehicle for Collaboration , 2009 .

[14]  Daniel Schwarz,et al.  Towards a System of Enhanced Transparency of Medical Curriculum , 2013 .

[15]  Brenda F. Roth,et al.  Concept Mapping as a Tool for Curriculum Quality , 2005 .

[16]  Martin Komenda,et al.  Practical use of medical terminology in curriculum mapping , 2015, Comput. Biol. Medicine.

[17]  R. Harden,et al.  AMEE Guide No. 21: Curriculum mapping: a tool for transparent and authentic teaching and learning , 2001, Medical teacher.

[18]  Nabil Zary,et al.  Visual analytics in healthcare education: exploring novel ways to analyze and represent big data in undergraduate medical education , 2014, PeerJ.

[19]  Rachel H Ellaway,et al.  Curriculum inventory: Modeling, sharing and comparing medical education programs , 2014, Medical teacher.

[20]  Daniel Schwarz,et al.  Building platform for optimization of medical education , 2013 .

[21]  Ronen Feldman,et al.  Book Reviews: The Text Mining Handbook: Advanced Approaches to Analyzing Unstructured Data by Ronen Feldman and James Sanger , 2008, CL.

[22]  H. Mannila,et al.  Data mining: machine learning, statistics, and databases , 1996, Proceedings of 8th International Conference on Scientific and Statistical Data Base Management.

[23]  Ian H. Witten,et al.  Data mining: practical machine learning tools and techniques, 3rd Edition , 1999 .

[24]  A. Wojtczak,et al.  Global minimum essential requirements: a road towards competence-oriented medical education , 2002, Medical teacher.

[25]  Manuel Filipe Santos,et al.  KDD, SEMMA and CRISP-DM: a parallel overview , 2008, IADIS European Conf. Data Mining.

[26]  Martin Komenda,et al.  OPTIMED Platform: Curriculum Harmonisation System for Medical and Healthcare Education , 2015, MIE.

[27]  Jirí Hrebícek,et al.  A Framework for Curriculum Management - The Use of Outcome-based Approach in Practice , 2014, CSEDU.

[28]  Preston R Aldrich,et al.  The curriculum prerequisite network: Modeling the curriculum as a complex system , 2015, Biochemistry and molecular biology education : a bimonthly publication of the International Union of Biochemistry and Molecular Biology.

[29]  Ian H. Witten,et al.  Weka: Practical machine learning tools and techniques with Java implementations , 1999 .

[30]  Nabil Zary,et al.  Big Data in Medical Informatics: Improving Education Through Visual Analytics , 2014, MIE.

[31]  Nabil Zary,et al.  AUVA - Augmented Reality Empowers Visual Analytics to explore Medical Curriculum Data , 2015, MIE.

[32]  Matthieu Latapy,et al.  Computing Communities in Large Networks Using Random Walks , 2004, J. Graph Algorithms Appl..

[33]  Ronald M. Harden,et al.  AMEE Guide No. 14: Outcome-based education: Part 1-An introduction to outcome-based education , 1999 .

[34]  Michael Derntl,et al.  Visual Modelling for Design and Implementation of Modular Curricula , 2008 .