摘要
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 match-ing recommendation strategy based on training is proposed.According to the analysis of training data,it mines the evaluation charac-teristics 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.
作者
曹阳
顾问
CAO Yang;GU Wen(Sanjiang College,Nanjing 210012,Jiangsu)
出处
《电脑与电信》
2021年第9期1-4,共4页
Computer & Telecommunication
基金
江苏省高校哲学社会科学研究项目“‘智能+’时代下在线开放课程同伴互评策略设计与应用研究”,项目编号:2019SJA0496
教育部产学合作协同育人项目“基于混合式教学的软件测试课程建设探索与实践”,项目编号:202002273049。
关键词
在线学习
训练
同伴互评
推荐
online learning
training
peer assessment
recommendation