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Feature based sentiment analysis for evaluating the mobile pedagogical affordances of apps

conference contribution
posted on 2017-01-01, 00:00 authored by Muneera Bano, D Zowghi, M Kearney
© 2017, IFIP International Federation for Information Processing. The launch of millions of apps has made it challenging for teachers to select the most suitable educational app to support students’ learning. Several evaluation frameworks have been proposed in the research literature to assist teachers in selecting the right apps for their needs. This paper presents preliminary results of an innovative technique for evaluating educational mobile apps by analysing the feedback of past app users through the lens of a mobile pedagogical perspective. We have utilized a sentiment analysis tool to assess the opinions of the app users through the lens of the criteria offered by a rigorous mobile learning pedagogical framework highlighting the learners’ experience of Personalization, Authenticity and Collaboration (iPAC). The investigation has provided initial confirmation of the powerful utility of the feature based sentiment analysis technique for evaluating the mobile pedagogical affordances of learning apps.

History

Event

IFIP Computers in Education. World Conference (2017 : Dublin, Ireland)

Volume

515

Series

IFIP Advances in Information and Communication Technology

Pagination

281 - 291

Publisher

Springer

Location

Dublin, Ireland

Place of publication

Cham, Switzerland

Start date

2017-07-03

End date

2017-07-07

ISSN

1868-4238

ISBN-13

9783319743097

Language

eng

Publication classification

E1.1 Full written paper - refereed

Title of proceedings

WCCE 2017 : Tomorrow's Learning: Involving Everyone. Learning with and about Technologies and Computing

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