Data-informed Learning Design for Future Schools
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.
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.
The role of IET
IET worked together with BNU to explore the feasibility of using learning design and learning analytics to map learning activities in a Chinese school context.
This research has helped to shape the vision of Future Schools in 2030 Programme at Beijing Normal University. As a result a range of policy documents and publications have been published, such as:
- Zhang, Jingjing; Gao, Ming; Holmes, Wayne; Mavrikis, Manolis and Ma, Ning (2019). Interaction patterns in exploratory learning environments for mathematics: a sequential analysis of feedback and external representations in Chinese schools. Interactive Learning Environments (Early Access).
- Holmes, Wayne; Nguyen, Quan; Zhang, Jingjing; Mavrikis, Manolis and Rienties, Bart (2019). Learning analytics for learning design in online distance learning. Distance Education, 40(3) pp. 309–329.