Mixing and Matching Learning Design and Learning Analytics

Nguyen, Quan; Rienties, Bart and Toetenel, Lisette (2017). Mixing and Matching Learning Design and Learning Analytics. In: Learning and Collaboration Technologies: Technology in Education - 4th International Conference, LCT 2017 Held as Part of HCI International 2017 Vancouver, BC, Canada, July 9–14, 2017 Proceedings, Part II (Zaphiris, Panayiotis and Ioannou, Andri eds.), Springer, pp. 302–316.

DOI: https://doi.org/10.1007/978-3-319-58515-4_24


In the last five years, learning analytics has proved its potential in predicting academic performance based on trace data of learning activities. However, the role of pedagogical context in learning analytics has not been fully understood. To date, it has been difficult to quantify learning in a way that can be measured and compared. By coding the design of e-learning courses, this study demonstrates how learning design is being implemented on a large scale at the Open University UK, and how learning analytics could support as well as benefit from learning design. Building on our previous work, our analysis was conducted longitudinally on 23 undergraduate distance learning modules and their 40,083 students. The innovative aspect of this study is the availability of fine-grained learning design data at individual task level, which allows us to consider the connections between learning activities, and the media used to produce the activities. Using a combination of visualizations and social network analysis, our findings revealed a diversity in how learning activities were designed within and between disciplines as well as individual learning activities. By reflecting on the learning design in an explicit manner, educators are empowered to compare and contrast their design using their own institutional data.

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