Data-informed Learning Design for Future Schools
1st January 2017 - 1st December 2017
The Data-informed Learning Design for Future Schools project uses learning analytics to investigate the efficacy of patterns of learning design activities in online courses.
Current online courses, including those at the Open University (OU), have tended to adopt a predominantly content-centric approach to teaching and learning. They often only provide access to resources such as e-text books and videos, rather than leveraging the affordances of online interactive technologies (e.g. to facilitate genuinely collaborative learning opportunities). In fact, effective online teaching involves active pedagogies and robust learning design in order to enhance learning outcomes.
Online technologies also bring opportunities to improve pedagogy. By analysing the large amounts of data generated by students in online learning environments, their ‘digital traces’, it becomes possible to go beyond learning theory to identify genuinely effective pedagogy, to understand the outcomes of learning design and to inform online teaching practices.
Previous work at the OU has established that learning design activities are able to explain up to 60% of the variability in student online activities, and that learning design does impact on learning performance. These important findings lay the foundation for further in-depth correlational and network analyses of learning designs and student experience, motivation and outcome data.
The project is funded by the Advanced Innovation Center for Future Education, Beijing Normal University, as part of their two-year Future Schools in 2030 programme.
BNU Beijin Normal University, China
- Beijing Normal University
- UCL (University College London)