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Strengthening dialogic peer feedback aiming for deep learning in SPOCs
ARTICLE

, UMC Utrecht ; , , , Utrecht University ; , , UMC Utrecht

Computers & Education Volume 125, Number 1, ISSN 0360-1315 Publisher: Elsevier Ltd

Abstract

This study is focused on how peer feedback in SPOCs (Small Private Online Courses) can effectively lead to deep learning. Promoting deep learning in online courses, such as SPOCs, is often a challenge. We aimed for deep learning by reinforcement of ‘feedback dialogue’ as scalable intervention.Students provided peer feedback as a dialogue, both individually and as a group. They were instructed to rate each other's feedback, which was aimed at deep learning. Data from questionnaires from 41 students of a master epidemiology course were used to measure for each feedback assignment to what extent deep learning was perceived. The feedback received by students who scored extremely high or low on the questionnaire was analyzed in order to find out which features of the feedback led to deep learning. In addition, students were interviewed to retrieve information about the underlying mechanisms.The results support the view that peer feedback instruction and peer feedback rating lead to peer feedback dialogues that, in turn, promote deep learning in SPOCs. The value of peer feedback appears to predominantly result from the dialogue it triggers, rather than the feedback itself. Especially helpful for students is the constant attention to how one provides peer feedback: by instruction, by having to rate feedback and therefore by repeatedly having to reflect. The dialogue is strengthened because students question feedback from peers in contrast to feedback from their instructor. As a result, they continue to think longer and deeper, which enables deep learning.

Citation

Filius, R.M., de Kleijn, R.A.M., Uijl, S.G., Prins, F.J., van Rijen, H.V.M. & Grobbee, D.E. (2018). Strengthening dialogic peer feedback aiming for deep learning in SPOCs. Computers & Education, 125(1), 86-100. Elsevier Ltd. Retrieved May 21, 2019 from .

This record was imported from Computers & Education on January 29, 2019. Computers & Education is a publication of Elsevier.

Full text is availabe on Science Direct: http://dx.doi.org/10.1016/j.compedu.2018.06.004

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