Caring Pedagogies in Action

Utilising Student Engagement Data to Develop Sustainable Learning Environments

Abstract

In the context of growing class sizes and limited institutional resources, student-centred and respon- sive education is increasingly important although challenging to implement effectively. A central part of responsiveness involves interpreting and acting on student-generated data -a task that can be par- ticularly challenging for novice engineering educators, as their background and training often guide both how they understand the data and how they respond to it. This paper reflects on our experiences, as teaching assistants and course lead, in developing and running a data analysis process for a large- scale problem-based learning engineering mathematics course. Using autoethnographic data from written reflections and transcripts, we applied an adapted version of Sochacka et al.’s (2009) three-tier reflexivity model to analyse how our understandings evolved regarding (i) what counts as data, (ii) how it can be interpreted, and (iii) what matters in its analysis. Through dialogic exchange, we identified significant shifts in our conceptualisations of the task of educational data analytics, as well as the value we placed on the different types of data.