Abstract
<p>In this paper, we describe a novel methodology, grounded in techniques from the field of machine learning, for modeling emerging social structure as it develops in threaded discussion forums, with an eye towards application in the threaded discussions of massive open online courses (MOOCs). This modeling approach integrates two simpler, well established prior techniques, namely one related to social network structure and another related to thematic structure of text. As an illustrative application of the integrated technique’s use and utility, we use it as a lens for exploring student dropout behavior in three different MOOCs. In particular, we use the model to identify twenty emerging subcommunities within the threaded discussions of each of the three MOOCs. We then use a survival model to measure the impact of participation in identified subcommunities on attrition along the way for students who have participated in the course discussion forums of the three courses. In each of three MOOCs we find evidence that participation in two to four subcommunities out of the twenty is associated with significantly higher or lower dropout rates than average. A qualitative post-hoc analysis illustrates how the learned models can be used as a lens for understanding the values and focus of discussions within the subcommunities, and in the illustrative example to think about the association between those and detected higher or lower dropout rates than average in the three courses. Our qualitative analysis demonstrates that the patterns that emerge make sense: It associates evidence of stronger expressed motivation to actively participate in the course as well as evidence of stronger cognitive engagement with the material in subcommunities associated with lower attrition, and the opposite in subcommunities associated with higher attrition. We conclude with a discussion of ways the modeling approach might be applied, along with caveats from limitations, and directions for future work.</p>
Highlights
The contribution of this paper is an exploration into a new methodology that provides a view into the evolving social structure within threaded discussions, with an application to analysis of emergent social structure in massive open online courses (MOOCs)
The aim of our work is to identify the emerging social structure in MOOC threaded discussions, which can be thought of as being composed of bonds between students, which begin to form as students interact with one another in the discussion forums provided as part of many xMOOCs (e.g., MOOCs provided by Coursera, EdX, or Udacity)
As just one example of its possible use, in this quantitative analysis we illustrate how our integrated modeling framework can be used to measure the impact of subcommunity participation on attrition using a survival analysis. This enables us to validate the importance of the identified structure in an objective measure that is known to be important in this MOOC context
Summary
The contribution of this paper is an exploration into a new methodology that provides a view into the evolving social structure within threaded discussions, with an application to analysis of emergent social structure in massive open online courses (MOOCs). In the current generation of MOOCs, only a small percentage of students participate actively in the provided discussion forums (Yang et al, 2013; Rosé et al, 2014). In this paper we focus on the first step down this path, namely developing a methodology that can be used to gain a bird’s eye view of the emerging social structure in threaded discussion. As such, this is a methods paper that describes a modeling approach, and illustrates its application with a problem that is of interest to the online and distance education community
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