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Experiential and Simulated Learning: An Interdisciplinary Approach

Experiential and Simulated Learning: An Interdisciplinary Approach

Gan, D. ORCID: 0000-0002-0920-7572, Chadwick, D., Gresty, D., Vuong, T. and Phillips, E. (2017) Experiential and Simulated Learning: An Interdisciplinary Approach. In: Proceedings of the 2017 International Conference on Computational Science and Computational Intelligence (CSCI'17). IEEE, Las Vegas, Nevada, USA. ISBN 978-1-5386-2652-8 (doi:https://doi.org/10.1109/CSCI.2017.313)

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Abstract

This paper describes a collaborative initiative of lecturing staff in a Computing and Information Systems Department working together with lecturing staff from a Law Department in the same university. It involved their combined efforts to construct an experiential and simulated learning experience for students from both departments in which both sets could use their different discipline-based skills practically in a simulated real-life scenario of professional interest to both sets of students. Educators must provide reflective real-life practice to facilitate the transition from university to the work place, producing graduates with the skills that employers value requiring minimal further training

Item Type: Conference Proceedings
Title of Proceedings: Proceedings of the 2017 International Conference on Computational Science and Computational Intelligence (CSCI'17)
Additional Information: This is a refereed paper and the paper acceptance rate for this conference was 21%; 2017
Uncontrolled Keywords: collaborative learning, experiential learning, simulated learning, PBL, peer-group learning
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Department / Research Group: Faculty of Architecture, Computing & Humanities
Faculty of Architecture, Computing & Humanities > Internet of Things and Security (ISEC)
Faculty of Architecture, Computing & Humanities > Department of Computing & Information Systems
Related URLs:
Last Modified: 30 Jun 2018 02:33
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: GREAT c
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/20179

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