Visualizations of Online Course Interactions for Social Network Learning Analytics

Abstract

Abstract-Social network learning analytics aims to extract useful information to improve the learning process, but the variety of learning management systems makes this task burdensome and difficult to manage. This study shows how Gephi, a general-purpose, open-source social network analysis application, can be used by instructors and institutions to extract and visualize relevant information that is commonly hidden or difficult to observe for course coordinators and teachers. The empirical case study uses data from one cross-curricular course with 656 students at the Open University of Catalonia (UOC) and showcases the use of Gephi as a social network learning analytics tool. The study further discusses the potential of social network learning analytics to improve online instruction by visualization of educational data.

Online module login data as a proxy measure of student engagement: the case of myUnisa, MoyaMA, Flipgrid, and Gephi at an ODeL institution in South Africa

“…Gephi is an open-source software programme that plots visual representations of social networks through maps and graphs. It can also calculate SNA parameters and the ranking, partitioning and filtering of nodes and ties (Bozkurt et al, 2016;Hernández-García et al, 2016). In SNA each actor is regarded as a node or a vertex in the overall network, and the various relationships occurring between actors are links, ties or edges connecting actors.…”

“…One instructive observation from this this study is that significant but low relationship was found between the number of times students read or replied to messages and academic performance. Among other things, this tends to emphasise one of the benefits Gephi has as a social network tool that can be used to visualise not only student participation but student engagement as well within OLEs (Hernández-García et al, 2016).…”

“…There has been a growing number of research studies on student engagement as it applies to online and blended learning especially at higher education institutions (HIEs) by scholars from different regions across the globe. Among scholars who have conducted studies on this area are Beer, Clark, and Jones (2010); Bodily, Graham, and Bush (2017); Boulton, Kent, and Williams (2018); Chen, Chang, Ouyang, and and Cann (2012), Conde, Hérnandez-García, García-Peñalvo, & Séin-Echaluce, 2015;Hernández-García and Suárez-Navas (2017), Hernández-García, González-González, Jiménez Zarco, and Chaparro-Peláez (2016), Hernández-García, Acquila-Natale, and Chaparro-Peláez (2017), Poon, Kong, Yau, Wong, and Ling (2017), and Rabbany, Takaffoli, & Zaïane, 2011). In this context, some of the benefits of visualising student engagement login data recorded and stored on LMSs in terms of social network representations have been reported.…”

“…In this context, some of the benefits of visualising student engagement login data recorded and stored on LMSs in terms of social network representations have been reported. These include allowing one to apply social network analysis (SNA) to the log data at hand (Hernández-García et al, 2016;Hernández-García & Suárez-Navas, 2017) and helping one make sense of how students engage with the content, with the teacher and with each other (Barría, Scheihing, & Parra, 2014;Hernández-García et al, 2016;Liu et al, 2015). Others include predicting student outcomes such as increased student engagement with course content and with peers (Atherton et al, 2017).…”

Social Learning Analytics in Higher Education. An experience at the Primary Education stage

“…According to Hernández, González, Jiménez and Chaparro (2016), online social learning analytics are a relatively new field so we are only just becoming aware of their possibilities and applications in education. By seeking to analyze what students are doing we may find information about spontaneous interactions, which will provide valuable information about the teaching-learning process.…”