Technology Support for Discussion Based Learning: From Computer Supported Collaborative Learning to the Future of Massive Open Online Courses



This article offers a vision for technology supported collaborative and discussion-based learning at scale. It begins with historical work in the area of tutorial dialogue systems. It traces the history of that area of the field of Artificial Intelligence in Education as it has made an impact on the field of Computer-Supported Collaborative Learning through the creation of forms of dynamic support for collaborative learning, and makes an argument for the importance of advances in the field of Language Technologies for this work. In particular, this support has been enabled by an integration of text mining and conversational agents to form a novel type of micro-script support for productive discussion processes. This research from the early part of the century has paved the way for emerging technologies that support discussion-based learning at scale in Massive Open Online Courses (MOOCs). In the next 25 years, we expect to see this early, emerging work in MOOC contexts grow into ubiquitously available social learning approaches in free online learning environments like MOOCs, or what comes next in the online learning space. These ambitious social learning approaches include Problem Based Learning, Team Project Based Learning, and Collaborative Reflection. We expect to see the capability of drawing in and effectively supporting learners of all walks of life, especially impacting currently under-served learners. To that end, we describe the current exploratory efforts to deploy technology supported collaborative and discussion-based learning in MOOCs and offer a vision for work going forward into the next decade, where we envision learning communities and open collaborative work communities coming together as persistent technology supported and enhanced communities of practice.


Conversational agents Computer-supported collaborative learning Massive open online courses 



This work was funded in part through NSF grants OMA-0836012 and IIS-1320064 as well as funding from the Gates Foundation Digital Learning Research Network and funding from Google and Bosch. The authors gratefully acknowledge useful discussions with collaborators George Siemens, Dragan Gašević, Ryan Baker, and Candace Thille.


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© International Artificial Intelligence in Education Society 2016

Authors and Affiliations

  1. 1.Language Technologies Institute and Human-Computer Interaction InstituteCarnegie Mellon UniversityPittsburghUSA

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