Design lessons about participatory self-directed online learning in a graduate-level instructional technology course.

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Title: Design lessons about participatory self-directed online learning in a graduate-level instructional technology course.
Authors: Yamagata-Lynch, Lisa C.1 (AUTHOR) LisaYL@utk.edu, Do, Jaewoo1 (AUTHOR), Skutnik, Anne L.1 (AUTHOR), Thompson, Duren J.1 (AUTHOR), Stephens, Adam F.1 (AUTHOR), Tays, Cheryl A.1 (AUTHOR)
Source: Open Learning. Jun2015, Vol. 30 Issue 2, p178-189. 12p.
Subject Terms: *Distance education, *Educational technology, *Autodidacticism, *Adult learning, *Self-managed learning (Personnel management), *Young adults, *Higher education, *Education
Abstract: This article reports on a case of participatory self-directed online learning within the context of a graduate-level instructional technology course. The course was about online learning environments and relied on both asynchronous and synchronous technologies. In this case, the instructor and students engaged in collaborative course design through one of the assignments where student teams and the instructor led one week’s worth of course activities and discussions. This article begins with a discussion of the literature on participatory self-directed online learning. Then, the article presents an overview of the course design, detailed discussion of the assignment that framed student participatory self-directed learning and two examples of student assignments. The framing question for organising this case was as follows: What lessons can a team of graduate students and the instructor learn about self-directed participatory online learning from a collaborative design project? The article ends with the overall lessons learned from the case and implications to future design of online activities. [ABSTRACT FROM PUBLISHER]
Copyright of Open Learning is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Design lessons about participatory self-directed online learning in a graduate-level instructional technology course.
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  Data: <searchLink fieldCode="JN" term="%22Open+Learning%22">Open Learning</searchLink>. Jun2015, Vol. 30 Issue 2, p178-189. 12p.
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  Data: This article reports on a case of participatory self-directed online learning within the context of a graduate-level instructional technology course. The course was about online learning environments and relied on both asynchronous and synchronous technologies. In this case, the instructor and students engaged in collaborative course design through one of the assignments where student teams and the instructor led one week’s worth of course activities and discussions. This article begins with a discussion of the literature on participatory self-directed online learning. Then, the article presents an overview of the course design, detailed discussion of the assignment that framed student participatory self-directed learning and two examples of student assignments. The framing question for organising this case was as follows: What lessons can a team of graduate students and the instructor learn about self-directed participatory online learning from a collaborative design project? The article ends with the overall lessons learned from the case and implications to future design of online activities. [ABSTRACT FROM PUBLISHER]
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  Data: <i>Copyright of Open Learning is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Jun2015
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