同伴互评是在线课程中一种有效的学习评价方式，能够解决大规模在线学习评价问题，提高评价效率。针对同 伴互评中存在的评阅匹配问题，提出了一种基于互评训练的评阅者匹配推荐策略。通过对训练数据的分析，挖掘学习者的评 价特征，生成同伴互评推荐列表。实践表明，该策略能够保证同伴互评的有效性和可靠性，促进学习者进行学习内省。

Peer assessment is an effective evaluation method for online courses, which can solve the problem of large-scale online learning evaluation and improve the evaluation efficiency. Aiming at the problem of matching in peer assessment, a reviewer matching recommendation strategy based on training is proposed. According to the analysis of training data, it mines the evaluation characteristics of learners and generates the peer assessment recommendation list. The practice result shows that this strategy can ensure the effectiveness and reliability of peer assessment and promote learners' learning introspection