Analytics for Tracking Student Engagement

Although there has been much research in the area of data analytics in recent years (e.g. Shum & Ferguson 2012), there are questions regarding which analytic methodologies can be most effective in informing higher education teaching and learning practices (Gibson & de Freitas 2016). This project focuses on one module within the School of Computing and Communications in the STEM faculty of The Open University, UK, to gain a clearer understanding on why students might, or might not, engage with computer aided learning and teaching (CALT) resources. We explore the use of specific CALT resources on the module ‘Communications Technology’, a print-based module with a range of online resources designed to supplement the text. In particular we explore the possible correlation between use of CALT resources and student examination performance. The research questions cover two key areas; the effectiveness of the analytics tools and students’ perception of the CALT resources. Data analytics were used to determine when students engaged with the CALT resources and whether this was at predicted times during the module. Student feedback via interview was used to explore what motivates students to engage with CALT resources, whether students understand a topic more deeply as a result of using CALT resources, and if students are deterred if the resources are too complicated or time consuming. Our conclusion from this case study is that learning analytics are useful for tracking student engagement. The analytics were very useful to review during module presentation, specifically for analysing students’ online behaviour. The supplementary interviews helped to shed light on the potential significance of the data gleaned