Mobile Learning Adoption at a Science Museum

Ruel Welch, Temitope Alade, Lynn Nichol

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Funding cuts by the Department for Culture, Media and Sport (DCMS) in the UK has led to Service Level Agreement (SLA) breaches. This is due to an overstretched service desk team. To mitigate this problem, this paper investigates serving just-in-time knowledge in the form of knowledge base articles to service users via mobile learning. Mobile learning (mLearning) could reduce ICT support calls, increase productivity for both service desk staff and the service user. Moreover, it presents an opportunity to develop useful technical knowledge among non-ICT 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 a Science Museum (SM). Results indicate that the UTAUT constructs including performance expectancy, effort expectancy, social influence and facilitating conditions are all significant determinants of behavioural 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 the SM. The research contributes to mLearning technology adoption and strategy.

Original languageEnglish
Title of host publicationIntelligent Computing - Proceedings of the 2020 Computing Conference
EditorsKohei Arai, Supriya Kapoor, Rahul Bhatia
PublisherSpringer-ESL
Pages726-745
Number of pages20
ISBN (Print)9783030522483
DOIs
Publication statusPublished - 2020
EventScience and Information Conference, SAI 2020 - London, United Kingdom
Duration: 16 Jul 202017 Jul 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1228 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

ConferenceScience and Information Conference, SAI 2020
Country/TerritoryUnited Kingdom
CityLondon
Period16/07/2017/07/20

Keywords

  • ICT service desk
  • Mobile learning
  • Technological adoption
  • Technology enhanced learning
  • Workplace learning

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