MENTOR – Intelligent Mobile Online Peer Tutoring Application for Face-to-Face and Remote Peer Tutoring

Authors

  • Sheng-Hung Chung
  • Seng Chee Tan

DOI:

https://doi.org/10.14742/apubs.2019.293

Keywords:

Peer tutoring, predictive, prescriptive analytics, remote tutoring

Abstract

E-learning platforms have been increasingly adopted by universities to extend and enhance learning. However, the literature review has shown that limited research has been conducted on the effects of electronic peer tutoring on student learning. Correspondingly, there is a lack of a suite of technological affordances to facilitate online peer tutoring sessions and appointments remotely. This paper describes the development of a novel smartphone app – Mobile Education Networked Tutoring On Request (MENTOR) – to facilitate face-to-face and remote peer tutoring. The MENTOR app aims to predict the tutoring needs of students using tutor-tutee matching, provides coordination of face-to-face tutoring sessions via the use ofsmartphones’ location data and online operation of remote tutoring sessions.

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Published

2019-12-02