Tuesday 11:00-12:30 (2), Darwin Suite
Type: Lightning talk
Theme: Academic practice, development and pedagogy
Panagiotis D Bamidis, Assist. Prof., Medical School, Aristotle University of Thessaloniki, Greece
Stathis Konstantinidis, NORUT, Tromso, Norway
In Open Medical Education, the overall aim is to improve and enhance the experience of the medical learner by offering a wider choice of thematic areas. Empowering learners with knowledge and skills to navigate and meaningfully interact with open educational resources and other learners is a key challenge. Learners are supposed to adopt active learning styles and exploit much the principles of self-directed, personalised approaches within contemporary collaborative learning environments.
Numerous toolkits exist to help navigation through resources. The modern trend in Open Medical Education is that such environments are powered by what we define as Medical Learning Analytics, that is the prediction of student’s performance using data readily available in e-learning (or collaborative in that sense) environments. We argue that this is facilitated through relevant interaction/attention metadata that are required to enable tagging learning approaches; current standards lack suitable sets of such metadata though. Big educational open data structures are deemed necessary for such an attempt, and therefore, a Linked-Data approach must be followed with an Open, Standards-Based Service Architecture. These contemporary notions are coupled by a focus group approach with key members of the Medical School in our University, all members of the Medical Education Office.
This paper describes attempts to extend tools and processes for collecting, storing, exploring and reasoning on large-scale educational data from scenario based learning accessible in open educational or federated and syndicated educational environments, thereby giving rise to a massive collection of (big) data from medical students' learning activities. Emphasis is drawn on building those capacities that will help in improving learning and teaching overall. The contradicting nature off this demand especially in Medical Education is discussed through a series of questions and answers in the focus group approach, where it is shown that Medical Teachers are still conservatory in their teaching approaches, especially when it comes to their actual course, and despite any international positive and contemporary experiences they may have.
As technical developments in the domain of Open Education allow for more and more tools and educational innovations, it is imperative that some emphasis given to staff developments and policy formation. These seem to form key objectives of the forthcoming Horizon 2020 programme of the European Commission, especially in view of the EU-US collaboration programme.
2. Paton C, Bamidis PD, Eysenbach G, Hansen M, Cabrer M. Experience in the Use of Social Media in Medical and Health Education. Contribution of the IMIA Social Media Working Group. Yearb Med Inform. 2011;6(1):21-9.
3. Miron-Shatz T, Hansen MM, Grajales FJ 3rd, Martin-Sanchez F, Bamidis PD. Social Media for the Promotion of Holistic Self-Participatory Care: An Evidence Based Approach. Contribution of the IMIA Social Media Working Group. Yearb Med Inform. 2013;8(1):162-8.
4. Konstantinidis, S., Fernandez-Luque, L., Bamidis, P.D., Karlsen, R. The role of taxonomies in social media and the semantic web for health education: A study of SNOMED CT terms in youtube health video tags (2013) Methods of Information in Medicine, 52 (2), pp. 168-179.
Part of this work is funded by the CAMEI project of EC (Project full title: "Coordination Actions in the scientific era of Medical Education
Informatics for fostering IT skills for healthcare workforce in the EU and USA"
Grant agreement no: 611967)
A recording of this presentation is available to view at https://campus.recap.ncl.ac.uk/Panopto/Pages/Viewer/Default.aspx?id=3f963b4e-243b-ac34-060c-2cf260e7212a ©Aristotle University of Thessaloniki 2014 Panos Bamidis cc-by 4.0
Keywords: big data, open education, learning analytics, medical education, focus group, policy