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  • Improving undergraduate soft skills using m-learning and serious games

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    Burd475307-Accepted.pdf (425.1Kb)
    File version
    Accepted Manuscript (AM)
    Author(s)
    Smith, SP
    Hickmott, D
    Bille, R
    Burd, E
    Southgate, E
    Stephens, L
    Griffith University Author(s)
    Burd, Liz
    Year published
    2016
    Metadata
    Show full item record
    Abstract
    Soft skills such as effective communication are becoming increasingly important for engineering graduates. Employers prize excellent written and oral abilities and literacy proficiency. High levels of academic literacy can significantly improve students' success in their university study. Traditional approaches to literacy improvement can limit student engagement. However, mobile learning and the use of smart phone apps present new opportunities to support literacy education. This paper describes current work exploring the use of apps, as serious games, to improve literacy in undergraduate students and outlines initial results ...
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    Soft skills such as effective communication are becoming increasingly important for engineering graduates. Employers prize excellent written and oral abilities and literacy proficiency. High levels of academic literacy can significantly improve students' success in their university study. Traditional approaches to literacy improvement can limit student engagement. However, mobile learning and the use of smart phone apps present new opportunities to support literacy education. This paper describes current work exploring the use of apps, as serious games, to improve literacy in undergraduate students and outlines initial results from a cross-discipline evaluation of an m-learning literacy app.
    View less >
    Conference Title
    Proceedings of 2015 IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2015
    DOI
    https://doi.org/10.1109/TALE.2015.7386049
    Copyright Statement
    © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subject
    Artificial Intelligence and Image Processing
    Specialist Studies in Education
    Publication URI
    http://hdl.handle.net/10072/403387
    Collection
    • Conference outputs

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