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The growing prevalence of learner-centred forms of learning as well as an increase in the number of learners actively participating on a wide range of digital platforms and devices give rise to an ever-increasing stream of learning data. Learning analytics (LA) may enable learners, teachers, and their institutions to better understand and predict learning and performance. However, the pedagogical perspective and matters of learning design have been underrepresented in research thus far. We identify technology-supported peerfeedback and self-assessment as particularly promising from an educational point of view. We present a use case to demonstrate how these measures can be implemented. Using the technology acceptance model and a sample of 484 undergraduate students, we identify factors for a successful implementation of technologysupported peer-feedback and self-assessment.

Learning Analytics in Higher Education using Peer-feedback and Self-assessment: Use Case of an Academic Writing Course