Gathering, visualising and interpreting learning design analytics to inform classroom practice and curriculum design
Building on an emerging body of literature on the use of learning analytics by educators, this chapter will explore the Open University (OU) approach to learning design that is currently being implemented on a large-scale. We aim to explain how this approach can be used to generate, visualise and interpret learning analytics that can be used by the educator to create learning design visualisations and data sets. Through comparison and analysis these can inform future design decisions. The basis for this OU approach can be found in the work of Conole (2012), whereby collaborative design teams use the Activity Type Classification Taxonomy to answer questions such as: What will students do in this module? How much will they be reading? What practical activities will they do? And, what does a ‘good’ learning design profile look like? The use of this taxonomy helps to establish a common language with which teachers can compare their teaching and learning practice with other teachers, schools and cluster groups. Where teachers are teaching from the same curriculum this data set, when visualised and analysed, can provide insight into the student learning experience. The approach allows for the measuring of what the student is doing, giving a different and unique view from those that only measure students by their academic ability. At the end of each section there is a short discussion entitled In the Classroom which suggests ways teachers in a classroom setting could adapt the approach for their circumstances.