A diversity-aware recommendation system for tutoring

Abstract

Diversity plays a major role when a student is looking for a tutor to better understand some concepts or an entire course. In fact, algorithms for recommending potential tutors have to take into account several aspects of diversity that may be critical to successful tutoring. The tutor must have the appropriate competencies in the subject matter. In addition, he/she must be able to convey the knowledge and skills associated with the tutoring topic. Moreover, the personality traits of the tutee and the tutor can facilitate or hinder the learning process during tutoring. This study presents the experience of ‘SOS TUTORÍA UC’, a responsive web application aimed at facilitating academic assistance among students. Special emphasis is placed on the importance of incorporating dimensions of diversity that can inform the artificial intelligence algorithms of the potential tutor recommendation system. Indeed, competence in the topic tutored is the first diversity criterion for recommending more knowledgeable potential tutors. In addition, the tutee has to choose whether to look for tutors with personalities that are “different”, “similar” or “indifferent” to his or her own preferences for academic assistance on the specific topic. To achieve this, ‘SOS TUTORÍA UC’ is integrated with the WeNet platform, which provides user management services and user recommendation algorithms. The results of the testing of the recommendation system were positive with regard to the criterion of competence, while the criterion of personality should be addressed for improvement. In order to improve the tutor-tutee matching process, participants emphasized the importance of considering the criterion of personality traits in addition to competence. They also requested additional information and parameters to facilitate tutor selection.