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

Christian M. Stracke

doi:10.1109/ICALT.2017.109

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

Christian M. Stracke

Research output: Chapter in Book/Report/Conference proceeding › Conference Article in proceeding › Academic › peer-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 language	English
Title of host publication	2017 IEEE 17th International Conference on Advanced Learning Technologies
Subtitle of host publication	ICALT
Publisher	IEEE
Pages	13-15
Number of pages	3
DOIs	https://doi.org/10.1109/ICALT.2017.109
Publication status	Published - Jul 2017
Event	2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT) - Timisoara, Romania Duration: 3 Jul 2017 → 7 Jul 2017 https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?&filter=issueId%20EQ%20%228001692%22&searchWithin=unlocking&pageNumber=1&resultAction=REFINE

Conference

Conference	2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT)
Abbreviated title	ICALT 2017
Country/Territory	Romania
City	Timisoara
Period	3/07/17 → 7/07/17
Internet address	https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?&filter=issueId%20EQ%20%228001692%22&searchWithin=unlocking&pageNumber=1&resultAction=REFINE

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10.1109/ICALT.2017.109

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@inproceedings{4a3511c4b65e45c6aab4ab9776de92ec,

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

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.",

author = "Stracke, {Christian M.}",

note = "DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.; 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT), ICALT 2017 ; Conference date: 03-07-2017 Through 07-07-2017",

year = "2017",

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doi = "10.1109/ICALT.2017.109",

language = "English",

pages = "13--15",

booktitle = "2017 IEEE 17th International Conference on Advanced Learning Technologies",

publisher = "IEEE",

address = "United States",

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Stracke, CM 2017, Why We Need High Drop-Out Rates in MOOCs: New Evaluation and Personalization Strategies for the Quality of Open Education. in 2017 IEEE 17th International Conference on Advanced Learning Technologies: ICALT. IEEE, pp. 13-15, 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT), Timisoara, Romania, 3/07/17. https://doi.org/10.1109/ICALT.2017.109

Why We Need High Drop-Out Rates in MOOCs: New Evaluation and Personalization Strategies for the Quality of Open Education. / Stracke, Christian M.
2017 IEEE 17th International Conference on Advanced Learning Technologies: ICALT. IEEE, 2017. p. 13-15.

Research output: Chapter in Book/Report/Conference proceeding › Conference Article in proceeding › Academic › peer-review

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N1 - DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

PY - 2017/7

Y1 - 2017/7

N2 - 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.

AB - 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.

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Y2 - 3 July 2017 through 7 July 2017

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

Abstract

Conference

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