Peer feedback to promote deep learning in online education: Unraveling the process

Abstract

Universities aim for deep learning. Two trends may threaten the achievement of deep learning, namely the massification of students and the increasing choice for online education by universities. Considering these trends, this dissertation examines the extent to which instructors can promote deep learning in online higher education. As a consequence of the often asynchronous and typed interaction, instructors experience specific challenges in online education. Scalable instructor interventions are described that can be used to meet these challenges. Additionally, mechanisms have been identified that are triggered and lead to deep learning. The intervention 'peer feedback' is zoomed in on. This intervention leads to deep learning because students question the feedback of peers more than that of an instructor, and therefore think longer about it. Providing peer feedback is shown to be just as valuable as receiving it. Results can be used by instructors in designing and teaching. Universities are advised to review their teaching strategy on the basis of current trends and the results of this dissertation.