Not The Ghost in The Machine: Transforming Patient Data into E-Learning Cases Within A Case-Based Blended Learning Framework For Medical Education. (13th May 2015)

• Record Type: Journal Article
• Authors: Turk, Bela R.; Krexner, Rabea; Otto, Ferdinand; Wrba, Thomas; Löffler-Stastka, Henriette
• Is Part Of: Procedia--social and behavioral sciences. Volume 186(2015)
• Page Start: 713
• Page End: 725
• Publication Date: 2015-05-13
• Subjects: Blended learning -- Case based learning -- Simulated Patients -- Clinical reasoning -- E-learning; Social sciences -- Periodicals; Social sciences -- Congresses; Arts -- Periodicals; Arts -- Congresses; Humanities -- Periodicals; Humanities -- Congresses; 300
• DOI: 10.1016/j.sbspro.2015.04.106
• Languages: English
• ISSNs: 1877-0428

Abstract

Abstract: Emergent challenges in medical education support an implementation of trans-disciplinary case-based learning. We propose a case-based blended learning framework, synergistically combining textbook, e-learning cases and a simulated patient course in medical education. A novel server system architecture allows patient data to be automatically transferred from the Vienna General Hospital to the Medical University of Vienna, and then imported into an e-learning template, in which online MCQ questions can be generated. We present one example of a transferred, imported and completed anxiety disorder e-learning case, currently implemented in the pre-clinical psychiatry course. This framework facilitates the creation of up to date teaching content, while addressing difficulties in transforming declarative knowledge into procedural-knowledge and -skill, (background knowledge into clinical reasoning) especially in domains which profit from a structured learning approach in creating a close link in understanding between functional morphology and clinical presentation.