Enabling cross-continent provider fairness in educational recommender systems

• Type: Article in International Scientific Journal
• Date: 2022

Authors

Elisabeth Gómez (Author) Other; Carlos Shui Zhang (Author) Other; Ludovico Boratto (Author) Other; Maria Salamó (Author) Other; Guilherme Ramos (Author) FEUP

Journal

Title: Future Generation Computer Systems

Vol. 127

Pages: 435-447

ISSN: 0167-739X

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 0 Citations

Other information

Authenticus ID: P-00V-K78

DOI: 10.1016/j.future.2021.08.025

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 13