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Applying Diffusion of Innovation Theory to Learning Management System Feature Implementation in Higher Education: Lessons Learned

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11284))

Abstract

In today’s rapidly changing world, information technology is transforming the higher education (HE) domain through an increase in accessibility of fast, multimedia-capable computers and broadband access. HE institutions are adopting new ways of enhancing their traditional ways of teaching, resulting in the emergence of seamless learning scenarios with a consequential need for flexible tools able to support experiences across various dimensions in such seamless learning environments. Learning Management Systems (LMS) in turn have fulfilled this requirement for enablement, however, technology alone is not sufficient as the potential it offers in order to be able to use it effectively in redesigning their educational scenarios, are often not understood or implemented. In order to achieve seamless learning while optimizing capital investment in learning management systems, this paper focuses on LMS feature implementation by applying the diffusion of innovations theory as a guideline. This paper presents two real-world examples that illustrate the proposed steps taken for LMS feature implementation and presents a number of lessons learned in doing so. It was established that there was synergy between the lessons learned for HE and industry and that HE could draw on the findings from industry.

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Correspondence to Adriana Botha .

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Botha, A., Smuts, H., de Villiers, C. (2018). Applying Diffusion of Innovation Theory to Learning Management System Feature Implementation in Higher Education: Lessons Learned. In: Hao, T., Chen, W., Xie, H., Nadee, W., Lau, R. (eds) Emerging Technologies for Education. SETE 2018. Lecture Notes in Computer Science(), vol 11284. Springer, Cham. https://doi.org/10.1007/978-3-030-03580-8_7

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  • DOI: https://doi.org/10.1007/978-3-030-03580-8_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03579-2

  • Online ISBN: 978-3-030-03580-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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