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Peer assessment is an efficient and effective learning process that has been widely used in diverse fields in the higher education. Despite of its many benefits, collusion is a common challenge that makes the reliability of peer assessment a primary concern in practices, especially when self-assignment strategy is applied in reviewer assignment. This research aims to propose a model of collusion management that applies cooccurrence network as a means to identify collusion. The proposed model is implemented as a software module in a peer code review system called EduPCR. EduPCR is able to monitor this measure and trigger instructor’s inquiries to collusion suspects when it identifies suspected collusion. A verification implemented in a university-level C Programming course shows that the proposed collusion management model is reasonable and the identification algorithm is practical in diverse peer assessment contexts. Keywords—peer assessment, reviewer assignment, collusion, cooccurrence network, self-assignment strategy, EduPCR

Reviewer Assignment Strategy of Peer Assessment: Towards Managing Collusion in Self-assignment