At the 2013 MOOC Research Initiative Conference back in December, Carolyn Rosé Associate Professor of the Language Technologies Institute and Human-Computer Interaction Institute for Carnegie Mellon University was interviewed by Phil Hill from Stanford University.
Her research grant is centered on studying emerging social behavior in MOOC discussion forums. She has been using a MOOC from the University of Pittsburg, Accountable Talk Conversation that Works to gather data. Since this course has much rich discussion, it is a great place for us to learn discussion behavior from.
What if we could imagine her research helping future students find a cohort of students within the massive course? In an earlier blog, Can we use machines to analyze students 21st Century Learning skills in a MOOC? I mentioned that Udacity’s holds the Guinness Book of World Records for largest MOOC (see Massive Open Online Course > North America). Their CS101 has had enrollments of over 300,000 students! One could only assume that the personability of this course being lost.
While a student isn’t alone amongst 300k they may feel alone with such an “abundant” group of students. I put abundance in quotes because I love how Dave Cormier describes what makes a MOOC a MOOC which I mentioned earlier in another post (see MOOCs should afford the use of abundance provided by The Internet! ). So this type of research from Carolyn is greatly valued and having a strategic way to place students in cohorts could really help with attrition perhaps? If anything they would have a more organized form to discuss the content and learn from their peers in a more personal setting. I like to think of this as “lists” on Twitter.
Carolyn shares that she is hoping her research will show how students in a MOOC find others to interact with? Who is talking with whom? Are they happy with how the discussions are being facilitated? She is currently gathering data through a qualitative review of discussion boards, looking for structure in the data and perhaps apply some graphical modeling techniques, and reviewing post course surveys where students are talking about their experiences.
She also discussed how her team is trying to quantify some of the data is by identifying patterns that predict dropout along the way. While I believe that we cannot apply traditional measures when evaluating a MOOC, the dropout rates are still very low. I have seen numbers as low as less than 5%. Although if her research will help us to identify and support those students who may be at risk then perhaps there would be more learning and a wider acceptance of MOOCs in higher education?
She does address that many of the students who enroll in a MOOC often never intended to complete the MOOC but there are still some that do struggle and end up completing. By watching some of these students who perhaps struggle and drop out, can we learn important lessons on how we might create a social environment that is more conducive for their learning?
I too am interested in the social aspect of learning and believe this “sociability” is criterion for a successful MOOC experience for a learner who is looking for that type of experience. As an instructional designer for online courses I am always looking for ways to put the learner at the center of the design and figure out ways to increase their interaction between the content, their peers, and the instructor. Without these three types of interactions being dominant in the course then the learning in my opinion isn’t truly authentic and then what is the point for the student to be in the course? Learn some facts perhaps or take away some resources? Maybe that is all they want.
What do you think?
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