Peer assessment is an efficient and effective learning assessment method that has been used widely in diverse fields in higher education. Despite its many benefits, a fundamental problem in peer assessment is that participants lack the motivation to assess others' work faithfully and fairly. Nonconsensus is a common challenge that makes the reliability of peer assessment a primary concern in practices. This research proposes a motivation model that uses review deviation and radicalness to identify nonconsensus in peer assessment. The proposed model is implemented as a software module in a peer code review system called EduPCR4. EduPCR4 is able to monitor peer assessment results and trigger teacher's arbitration when it detects possible nonconsensus. An empirical study conducted in a university-level C programing course showed that the proposed model and its implementation helped to improve the peer assessment practices in many aspects.