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A Motivation Model of Peer Assessment in Programming Language Learning

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. Non-consensus 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 radicalization to identify non-consensus 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 this measure and trigger teacher's arbitration when it detects possible non-consensus. An empirical study conducted in a university-level C programming course showed that the proposed model and its implementation helped to improve the peer assessment practices in many aspects.

preprint2014arXivOpen access

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