EXPLORE THE POTENTIALS OF APPLYING SOCIAL LEARNING ANALYTICS TO UNDERSTAND STUDENTS’ LEARNING EXPERIENCES IN A NING-BASED ONLINE LEARNING COMMUNITY
University of Minnesota (UNITED STATES)
About this paper:
Appears in: EDULEARN15 Proceedings
Publication year: 2015
Conference name: 7th International Conference on Education and New Learning Technologies
Dates: 6-8 July, 2015
Location: Barcelona, Spain
Abstract:Online social learning is conceptualized as a collective and participatory social process occurs during the online interactions. Online interactions include student-to-student interaction (SS interaction), student-to-instructor interaction (SI interaction), and student-to-content interaction (SC interaction) (Anderson, 2003). According to Shum and Ferguson (2012), online social learning can take place when people are able to clarify their intention, ground their learning, and engage in learning conversations. In addition, Shum and Ferguson (2012) proposed that social learning analytics include social network analytics, discourse analytics, content analytics, disposition analytics, and context analytics.
This study is an explanatory case study focused on an undergraduate-level online course in University of Minnesota (UMN). The research purpose of this study is to explore the potentials of applying network-focused, discourse & content-focused, and context-focused learning analytics to understand students’ learning experiences in a Ning-based online learning community. The course is a completely online undergraduate course and I, as the instructor, designs this online course in Ning website. Ning is an online platform for people and organizations to create custom social networks, which is totally different from common Web 2.0 social networking sites, such as Facebook, Twitter. Ning provides opportunities for people who want to create their own communities and social networks around specific interests with their own visual design, choice of features and member data. The central feature of Ning is that anyone can create their own social network for a particular topic or need, catering to specific membership bases or community needs.
1) Social network-focused learning analytics help me to explore and know the students’ positions in the network of online interactions, the connections between students and the instructor, and the relationships between the learning community and online learning resources. I will use Gephi to analyze social networks in this paper. Gephi is a free, open-source platform that supports visualization and exploration of all kinds of networks.
2) Discourse & content-focused learning analytics Quantitative and qualitative content analysis will be used to analyze all texts and discourses generated by students and the instructor in the online learning environment. In addition, content analytics may be used to provide recommendations of resources that are tailored either to the needs of an individual or to the needs of a group of learners.
3)Context-focused learning analytics Context could be a dynamic process, constructed through learners’ interactions with learning materials and the surrounding world over time. Since this online course platform is based on a social network site – Ning and I integrated both asynchronous and synchronous discussions, it is necessary and imperative to analyze in what ways are students’ online learning processes impacted by using Ning as an online learning community.
 Anderson, T. (2003). Modes of interaction in distance education: Recent developments and research questions. In M. Moore (Ed.), Handbook of Distance Education. Mahwah, NJ: Lawrence Erlbaum.
 Buckingham Shum, S., & Ferguson, R. (2012). Social Learning Analytics. Educational Technology & Society, 15(3), 3–26.
Keywords: Online social learning, social learning analytics, social network analysis, discourse analysis, content analysis, context analysis.