With the development of Web2.0, MOOCs have been on a rapid rise around the world which are featured by free, con-venient, time saving, high quality and not restricted by time and space.However, as a kind of new courses, the phase of peer assess-ment which is used for assessing learners'work has some problems such as some students being treated rudely and low efficiency of as-sessment.Thus, a satisfying result cannot be attained.Researches on this problem are not very much.Therefore, this paper focus on improving the effect of learners'satisfaction and trying to build a recommendation model, which is used for assigning submissions to the suitable learners so that the process of peer assessment can be optimized and learners'satisfaction can be improved.%随着Web2.0技术的不断发展,大规模开放在线课程( MOOCs)以其免费、方便、省时、高质量和不受时间和空间限制等特征迅速在全球兴起。然而,作为一种新兴的课程模式,用于评估学习者作业的同伴互评环节由于设置过于简单,存在评阅者态度粗鲁、评价效率低下等问题,并不能取得令人满意的效果。针对如何提高大规模开放课程中同伴互评的效果这一问题,通过建立基于推荐机制的提高同伴互评效果的推荐模型,为学生作业分配较为合适的评阅人,从而达到优化同伴互评过程并提高学习者满意度的目的。
展开▼