Recommender systems for technology-enhanced learning are examined in relation to learners’ agency, that is, their ability to define and pursue learning goals. These systems make it easier for learners to access resources, including peers with whom to learn and experts from whom to learn. In this systematic review of the literature, we apply an Evidence for Policy and Practice Information (EPPI) approach to examine the context in which recommenders are used, the manners in which they are evaluated and the results of those evaluations. We use three databases (two in education and one in applied computer science) and retained articles published therein between 2008 and 2018. Fifty-six articles meeting the requirements for inclusion are analyzed to identify their approach (content-based, collaborative filtering, hybrid, other) and the experiment settings (accuracy, user satisfaction or learning performance), as well as to examine the results and the manner in which they were presented. The results of the majority of the experiments were positive. Finally, given the results introduced in this systematic review, we identify future research questions.

中文翻译：

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在学习环境中支持学习者代理的推荐系统：系统评价

技术增强学习的推荐系统根据学习者的能动性进行检查，即他们定义和追求学习目标的能力。这些系统使学习者更容易访问资源，包括与谁一起学习的同伴和向谁学习的专家。在对文献的系统回顾中，我们应用政策和实践信息证据 (EPPI) 方法来检查推荐者的使用背景、评估方式以及这些评估的结果。我们使用了三个数据库（两个在教育领域，一个在应用计算机科学领域）并保留了 2008 年至 2018 年期间在其中发表的文章。 分析了 56 篇满足收录要求的文章，以确定它们的方法（基于内容、协同过滤、混合、其他）和实验设置（准确性、用户满意度或学习表现），以及检查结果和呈现方式。大多数实验的结果是积极的。最后，鉴于本系统综述中介绍的结果，我们确定了未来的研究问题。