Mobile learning adoption at the Science Museum Group

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Welch, Ruel, Alade, Temitope and Nichol, Lynn (2020) Mobile learning adoption at the Science Museum Group. In: Proceedings of the 16th International Conference Mobile Learning 2020, ML 2020. Proceedings of the 16th International Conference Mobile Learning 2020, ML 2020 . IADIS, BGR, pp. 39-46. ISBN 9789898704160

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Abstract

Mobile learning (mLearning) at the Science Museum Group (SMG) in the United Kingdom (UK) could reduce ICT support calls, increase productivity and develop technical knowledge SMG staff. However, challenges are pervasive in any technological adoption. This paper uses the unified theory of acceptance and use of technology (UTAUT) model to explain the determinants of mLearning adoption at the Science Museum Group (SMG). Results indicate that the UTAUT constructs, performance expectancy, effort expectancy, social influence and facilitating conditions are all significant determinants of behavioral intention to use mLearning. A newly proposed construct, self-directed learning was not a significant determinant of behaviour intentions. Further examination found age and gender moderate the relationship between the UTAUT constructs. These findings present several useful implications for mLearning research and practice for ICT service desk at SMG. The research contributes to mLearning technology adoption and strategy.

Item Type:	Book Section
Additional Information:	Publisher Copyright: © International Conference Mobile Learning 2020.All rights reserved.
Uncontrolled Keywords:	mobile learning,technological adoption,workplace learning,computer science applications,hardware and architecture,software,information systems ,/dk/atira/pure/subjectarea/asjc/1700/1706
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Data Science and AI
Related URLs:	http://www.scopus.com/inward/record.url?...
Depositing User:	LivePure Connector
Date Deposited:	22 Nov 2023 03:47
Last Modified:	10 Dec 2024 01:13
URI:	https://ueaeprints.uea.ac.uk/id/eprint/93676
DOI:	10.33965/ml2020_202004l005

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