Toward motivating participants to assess peers' work more fairly: Taking programing language learning as an example

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.