With the widespread diffusion of Massive Online Open Courses (MOOCs), educational recommender systems have become central tools to support students in their learning process. While most of the literature has focused on students and the learning opportunities that are offered to them, the teachers behind the recommended courses get a certain exposure when they appear in the final ranking. Underexposed teachers might have reduced opportunities to offer their services, so accounting for this perspective is of central importance to generate equity in the recommendation process. In this paper, we consider groups of teachers based on their geographic provenience and assess provider (un)fairness based on the continent they belong to. We consider measures of visibility and exposure, to account ($i$) in how many recommendations and ($ii$) wherein the ranking of the teachers belonging to different groups appear. We observe disparities that favor the most represented groups, and we overcome these phenomena with a re-ranking approach that provides each group with the expected visibility and exposure, thus controlling fairness of providers coming from different continents (cross-continent provider fairness). Experiments performed on data coming from a real-world MOOC platform show that our approach can provide fairness without affecting recommendation effectiveness.

随着大规模在线开放课程 (MOOC) 的广泛传播，教育推荐系统已成为支持学生学习过程的核心工具。虽然大多数文献都集中在学生和提供给他们的学习机会上，但推荐课程背后的教师在出现在最终排名中时会获得一定的曝光度。暴露不足的教师可能会减少提供服务的机会，因此考虑到这一观点对于在推荐过程中产生公平性至关重要。在本文中，我们根据教师的地理来源考虑教师群体，并根据他们所属的大陆评估提供者（不）公平性。我们考虑可见度和曝光度的衡量标准，以考虑（$\mathrm{一世}$) 在多少推荐和 ($\mathrm{一世}\mathrm{一世}$) 其中出现了属于不同组的教师的排名。我们观察到有利于最具代表性的群体的差异，我们通过重新排名的方法克服这些现象，为每个群体提供预期的可见性和曝光度，从而控制来自不同大陆的提供商的公平性（跨大陆提供商公平性）。对来自真实世界 MOOC 平台的数据进行的实验表明，我们的方法可以在不影响推荐效果的情况下提供公平性。