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Please use this identifier to cite or link to this item: http://hdl.handle.net/1820/8642
Title: Why we need High Drop-out Rates in MOOCs: New Evaluation and Personalization Strategies for the Quality of Open Education
Authors: Stracke, Christian M.
Keywords: High Drop-Out
Drop-Out Rate
MOOCs
Open Education
Evaluation
Personalization
Strategies
Quality
IEEE
MOOQ
Issue Date: 2017
Publisher: IEEE
Citation: Stracke, C. M. (2017). Why we need High Drop-out Rates in MOOCs: New Evaluation and Personalization Strategies for the Quality of Open Education. In M. Chang, N.-S. Chen, R. Huang, Kinshuk, D. G. Sampson, & R. Vasiu (Eds.), The 17th IEEE International Conference on Advanced Learning Technologies (ICALT 2017) (pp. 13-15). IEEE: Computer Society. Online available on: DOI 10.1109/ICALT.2017.109
Abstract: This paper presents the current status of Open Education and MOOCs and discusses their quality following the main question: How can we introduce new design and evaluation methods and personalization strategies to improve the learning quality of Open Education? First, the dimensions of Open Education are differentiated. Then the dimensions of holistic quality development are transferred to Open Education and discussed for the design of MOOCs leading to recommendations for personalization. A new quality indicator for evaluating the quality of MOOCs is introduced: It is proposed not to measure the traditional drop-out rates but the completion of individual goals and intentions by the MOOC learner. Consequently high drop-out rates are preferable in MOOCs as they show the diversity of personal objectives by the MOOC learners. It is concluded that Open Education and MOOCs have got the potential for the next revolution in learning experiences.
URI: http://hdl.handle.net/1820/8642
Appears in Collections:1. TELI Publications, books and conference papers

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