It has been long argued that learning analytics has the po-tential to act as a " middle space " between the learning sciences and data analytics, creating technical possibilities for exploring the vast amount of data generated in online learning environments. One common learn-ing analytics intervention is the learning dashboard, a support tool for teachers and learners alike that allows them to gain insight into the learning process. Although several related works have scrutinised the state-of-the-art in the field of learning dashboards, none have addressed the theoretical foundation that should inform the design of such inter-ventions. In this systematic literature review, we analyse the extent to which theories and models from learning sciences have been integrated into the development of learning dashboards aimed at learners. Our crit-ical examination reveals the most common educational concepts and the context in which they have been applied. We find evidence that cur-rent designs foster competition between learners rather than knowledge mastery, offering misguided frames of reference for comparison.
CITATION STYLE
Jivet, I., Scheffel, M., Drachsler, H., & Specht, M. (2017). Awareness Is Not Enough : Pitfalls of Learning Practice. Data Driven Approaches in Digital Education, 1(i), 82–96. Retrieved from http://dspace.ou.nl/bitstream/1820/7985/1/115_ECTEL_preprint.pdfhumanim
Mendeley helps you to discover research relevant for your work.