Analytics for tracking student engagement

Project leader(s): Christine Gardner
Theme: Supporting students
Faculty: STEM
Status: Archived
Dates: October 2017 to February 2021

Although there has been much research in the area of data analytics in recent years (e.g. Shum and Ferguson 2012), there are questions regarding which analytic methodologies can be most effective in informing higher education teaching and learning practices (Gibson and de Freitas, 2016).

This study will explore the use of specific computer aided learning (CAL) resources on module TM355, Communications technology, using two data analysis tools developed by the Open University. Analytics for Action, A4A (2017) can provide detail of how students are engaging with specific online materials, with the aim to highlight the kind of interventions that module teams can make to support students. However, currently it does not identify activity at an individual student level. There are gaps in what can be derived from the analytics , so using the analytics tools in conjunction with interviews could provide a clearer insight into how students engage with a particular module and how module teams can better support students, specifically those identified as being at risk of failing the module.

The research questions cover two key areas; the effectiveness of the analytics tools (and identify what additional data might be useful for module teams) and students’ perception of the CAL resources.

Analytics:

When do the students engage with the CAL packages and is this at predicted times during the module?
Do students revisit the CAL packages?
Has the level of student engagement with the tools changed over two presentations (16J (October 2016)/17J (October 2017))?

Student feedback via interview:

What motivates OU students to engage with CAL tools?
Do students understand topic more deeply as a result of using CAL packages?
Are students deterred if the packages are too complicated/time consuming?

The findings of the project will inform module teams and might be of specific interest to those involved in Level 3 modules in the IT and Computing degree programme i.e. TM351 (Data management and analysis), TM352 (Web, mobile and cloud technologies), TM353 (IT systems: planning for success), TM354 (Software engineering) and TM356 (Interaction design and the user experience). One question that arises now: is there a need to integrate the online tools more fully into the module?