Refine the beta version of the software developed in the 2007 ALTC Grant to develop automated processes for the extraction of LMS data in order to visualise student social networks;
Further develop the software interface for teaching staff to more easily visualise and interpret levels of student engagement, including;
Provide the evaluative tools necessary to rapidly identify individuals disconnected from the learning network;
Provide educators with the necessary tools to focus the often limited student learning support resources more effectively; and
Investigate longitudinally and across various Australian institutions, the relationship between student position within the learning network and engagement, and achievement of stated learning outcomes.
The project will provide a methodology, software product and evaluative tools necessary for visualising student learning networks as they occur in a learning management system – which in turn provide a scalable non-obtrusive approach for identifying and evaluating student learning behaviours. Early identification affords practitioners with the kind of learning cues that are currently lamented as missing from the online learning environment and thus allow teachers to modify their approaches and support accordingly. It will also allow teachers to identify students disconnected and isolated from the learning network. By mapping the development of student social networks within the HE setting the study provides an opportunity to evaluate 1) how student social networks (including ego-networks) influence learning; 2) the relationship between network centrality and learning styles and 3) students' capacity to network and form peer support groups. In so doing, the study addresses the issues surrounding the alignment of implemented pedagogy with student learning, and the early identification of students requiring additional learning support.
