Why We Need High Drop-Out Rates in MOOCs: New Evaluation and Personalization Strategies for the Quality of Open Education

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

    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.
    Original languageEnglish
    Title of host publication2017 IEEE 17th International Conference on Advanced Learning Technologies
    Subtitle of host publicationICALT
    PublisherIEEE
    Pages13-15
    Number of pages3
    DOIs
    Publication statusPublished - Jul 2017
    Event2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT) - Timisoara, Romania
    Duration: 3 Jul 20177 Jul 2017
    https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?&filter=issueId%20EQ%20%228001692%22&searchWithin=unlocking&pageNumber=1&resultAction=REFINE

    Conference

    Conference2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT)
    Abbreviated titleICALT 2017
    Country/TerritoryRomania
    CityTimisoara
    Period3/07/177/07/17
    Internet address

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