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Collaborative Authoring of OpenCourseWare: The Best Practices and Complex Solution

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Open Data for Education

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9500))

Abstract

The lack of high-quality educational resources is a key issue on the way to success of the OpenCourseWare movement. However, the state-of-art approaches of producing such content demand a lot of resources, thus limiting the percent of such courses in a total amount of content available. An important step towards decreasing costs while increasing the quality of the educational material is applying collaborative techniques to the production process. Such collaboration affects different aspects of OpenCourseWare production, such as: content annotation, personalization, sharing and other. In the current paper we aim to investigate the state-of-art of the collaborative authoring of OpenCourseWare in all its aspects, finding out the major gaps and the most promising approaches to fulfill them. Based on the study results we developed Slidewiki - an example application for the OpenCourseWare collaborative authoring that implements the most promising solutions for the gaps found.

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Notes

  1. 1.

    http://www.open.edu/openlearn.

  2. 2.

    http://moodle.org.

  3. 3.

    The final map is discussed further and presented at Fig. 3.

  4. 4.

    http://wikipedia.com.

  5. 5.

    http://en.wikipedia.org/wiki/Wiki.

  6. 6.

    https://goranzugic.wordpress.com/2010/09/09/semantic-wikis/.

  7. 7.

    http://en.wikipedia.org/wiki/Ontology_(information_science).

  8. 8.

    http://en.wikipedia.org/wiki/RSS.

  9. 9.

    http://aloha-editor.org/.

  10. 10.

    http://code.google.com/p/svg-edit/.

  11. 11.

    www.usabilitynet.org/trump/documents/Suschapt.doc.

  12. 12.

    Learning Resource Metadata Initiative: www.lrmi.net/.

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Tarasowa, D., Auer, S. (2016). Collaborative Authoring of OpenCourseWare: The Best Practices and Complex Solution. In: Mouromtsev, D., d’Aquin, M. (eds) Open Data for Education. Lecture Notes in Computer Science(), vol 9500. Springer, Cham. https://doi.org/10.1007/978-3-319-30493-9_6

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