'SSEEN': A Networked Approach to Uncover Connections between Sentiment, Social, and Epistemic Elements of Student Online Forum Discourse

Educational researchers have pointed to socioemotional dimensions of learning as important in gaining a more nuanced description of student engagement and learning. However, to date, research focused on the analysis of emotions has been narrow in its focus, centering on affect and sentiment analysis in isolation while neglecting how emotions potentially interact with social elements and course objectives in learning environments. In this paper, we present a case study analysis of seven asynchronous online discussions delivered as part of a blended-learning bachelor level course; we demonstrate the utility of a novel analysis workflow and visualization method which we refer to as SSEEN (social sentiment embedded epistemic networks) to uncover insights into the connection between social networks, course content, and detected student sentiment. The findings show that negative sentiment was most often associated with course content, but contrary to insights from prior research, negative sentiment served as a marker of engagement as students connected content to their own personal experiences. By simultaneously considering the social network alongside the sentiment-colored edges, we note that negative sentiment is not consistent within the discourse of particular students or between pairs indicating that sentiment did not appear to be an indicator of peer conflict or breaches in social contracts. The findings demonstrate how the proposed approach (SSEEN) can support educational researchers to gain a more nuanced understanding of the social, emotional, and epistemic dimensions of learning in asynchronous online discussions.