Mass Customization in Continuing Medical Education: Automated Extraction of E-Learning Topics
To satisfy the individual learning needs of the high number of the Early Nutrition (EN) eAcademy participants, and to reduce development costs, the mass customization (MC) approach was applied. Key concepts of the learning needs, and corresponding learner subgroups with similar needs were extracted from learner-generated text using the natural language processing tool ReaderBench. Two collections of key concepts where built, which enabled EN experts to formulate topics for e-learning modules to be developed. Ongoing work will assess learner satisfaction and e-learning development costs, in order to evaluate the MC application in continuing medical education.
KeywordsContinuing medical education Mass customization Natural language processing Massive open online courses Online courses
This research was partially supported by the FP7 2008-212578 LTfLL project, and by European Union’s Seventh Framework Programme (FP7/2007-2013), project EarlyNutrition under grant agreement n°. This work has received an unrestricted educational grant by Wyeth Nutrition.
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