Related Data for: Holistic design of a mobile peer tutoring application based on learning and user needs analysis

Research has shown that peer tutoring at the university level could improve students’ performance and, enhance their motivation and learning, increase self-determination and learner autonomy, and reinforce conceptual knowledge by providing opportunities for reapplication of concepts. This paper describes the development of a mobile peer tutoring application – Mobile Education Networked Tutoring On Request (MENTOR). We start with a review of the literature to identify the relevant affordances that this mobile app should possess. In addition, questionnaires were administered with students studying in higher education to understand the needs of peer tutoring with tutors and tutees. The findings of the survey data showed that a majority of the students are receptive to peer tutoring and found it to be a user-friendly and intuitive method of mobile peer tutoring. One feature of MENTOR is the tutor-tutee matching – tutees are individually paired with tutors by using predictive modeling based on student data. Tutor-tutee matching can be efficiently accomplished via MENTOR mobile application by granting tutees the choice of tutors based on mutual tutor-tutee availabilities, students' background and tutor ratings. The other main features of the mobile peer tutoring application, such as online peer tutoring are presented in this study. The study contributes to the application of learning sciences and learning technologies to provide a holistic design for supporting student peer tutoring at the university level.