Connected Courses Working Research Group

What Is The Connected Courses Research Working Group?

The #Connected Courses Research Working Group consists of participants from the #ConnectedCourses c-MOOC who are interested in engaging in research to better understand the personal and group learning processes occurring in #ConnectedCourses.  This website is a virtual meeting space, a place for #ConnectedCourses researcher-participants to provide support for each other, collaborate, and share resources.  It’s also a place for participants of the larger #ConnectedCourses community to comment, voice concerns, find information, or join in or add to the research.  There is no formal “membership” related to the ConnectedCourses Research Working Group, just an opportunity for learning and sharing.

Below you will find information about the projects currently underway or being considered by members of the #ConnectedCourses Research Working Group.  We welcome your input and participation in the process.  Project leaders have included their contact information so that you might reach out to them directly if you have questions.  Because the group is not a regulatory body or gatekeeper for connected learning or #Connectecourses research,  we have no way of knowing if there are other #ConnectedCourses research projects occurring.  However, these are ours.
Project: Assessing Connectivity in Connected Learning Environments
***UPDATE 12/9/14 – This project is active, for latest details, see my latest “Stitching the Diss” post, on the draft mock prospectus hearing  The first three chapters of the dissertation will be coming soon (hopefully).
  • Overview: As part of my dissertation research I am investigating ways to identify student “connectedness” – with each other and with course content – in university-based connected learning settings.  The ultimate purpose of this investigation is to provide faculty with meaningful yet practical formative assessment tools for student participation in these social learning environments. To that end, I am studying data automatically collected by TAGS (Twitter Archiving Google Spreadsheet) from two c-MOOCs (#Thoughtvectors and #ConnectedCourses) to explore potential indicators of “connectedness” that might be found (and automatically collected) therein.
  • #CCourses data: The TAGS data related to the Twitter hashtag #ccourses, which is publicly available.
  • Participants: Those who have used the Twitter hashtag #ccourses
  • Consent arrangements: Public announcement of research with an “opt out” option.
  • How the data will be used: To explore what sort of indicators of “connectedness” (such as links, mentions, replies) might be documented in TAGS in ways that are accessible and meaningful for use in formative assessment.  Analysis is aggregate in nature – no names would be used.
Project: Self-narrated/autoethnographic accounts of participation in cMOOCs or similar (special case of #ccourses)
  • Investigator: Maha Bali, American University in Cairo 
  • Overview:(will add soon)
  • #CCourses data: Blogposts by individuals that are submitted by them for the specific purpose of this research (so we will not look at other data)
  • Participants: People who elect to share their #ccourses experience on their blog
  • How the data will be used: To find commonalities and differences in the way individuals in #ccourses perceive and enact their experience.
Project: Content analysis to surface patterns of participating with readings and other course materials
  • Investigator: Greg Mcverry, who may never get to the project.
  • Overview: I like to count things. Please don’t hate me, but numbers are a fun way for me to surface patterns. I would  examine posts included in #CCourses to discover what were the preferred sources used by participants. For example were webinars the most popular? Did reading correlate with a blogged about subject? Was it a source in combination with a prompt such as knowledge nugget? Did rank in organized or unorganized list determine the use? All of these questions could be investigated by tagging blog posts to the sources they mention. Then a matrix could be developed categorizing sources by mode type, page rank, author expertise, etc.
  • Participants: The tagging of sources could be done in the open with all results being published without author identification or pseudonyms
  • How the data will be used: The data can help shape future design of connected courses by determine what kind of sources people participate with while writing. The results may not be too generalizable as the make up of connected participants represent many MOOC veterans and a higher overall technological knowledge.. 


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