Please use this identifier to cite or link to this item: http://hdl.handle.net/10497/22076
Title: 
Authors: 
Keywords: 
Peer tutoring
Predictive
Prescriptive analytics
Remote tutoring
Issue Date: 
2-Dec-2019
Citation: 
Chung, S.-H., & Tan, S. C. (2019). MENTOR – Intelligent mobile online peer tutoring application for face-to-face and remote peer tutoring. In S. Chew Yi Wei, C. Kah Mun, & A. Alphonso (Eds.), Australasian Society for Computers in Learning in Tertiary Education (ASCILITE) 2019 Conference Proceedings (Vol. 36, pp. 386-391). ASCILITE.
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 of smartphones’ location data and online operation of remote tutoring sessions.
Description: 
This paper was published in the 2019 proceedings of the 36TH International Conference on Innovation, Practice and Research in the Use of Educational Technologies in Tertiary Education, ASCILITE 2019: Personalised Learning. Diverse Goals. One Heart, held at the Singapore University of Social Sciences, 2 - 5 December 2019.
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Appears in Collections:Conference Papers

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