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A Conceptual Model for Institutional Adoption of Learning Technologies in Higher Education

9 pagesPublished: October 25, 2019

Abstract

As learning technologies advance and become more ubiquitous, particularly in e- learning, new opportunities are emerging for higher education institutions to address significant academic and administrative challenges. Driven by increasing competition, changing environments and other market forces, institutions are considering learning technologies in order to thrive and remain relevant. This study gathered insights from existing literature to propose a conceptual model that supports decision making in the adoption of learning technologies by higher education institutions. The conceptual model adopts the Transformative Framework for Learning Innovation as its foundation and superimposes the Emerging Learning Technologies Model. The resulting model provides a clear guidance for higher education institution to achieve five key learning characteristics. This paper found that combining these two approaches provides a logical approach for higher education institutions to address organisational, strategic and learning-specific dimensions in a coherent format. Furthermore, academics and practitioners can benefit from valuable insights in the proposed alternative approach to learning technology adoption.

Keyphrases: adaptive learning, e-learning, higher education, learning analytics, learning technologies

In: Kennedy Njenga (editor). Proceedings of 4th International Conference on the Internet, Cyber Security and Information Systems 2019, vol 12, pages 123--131

Links:
BibTeX entry
@inproceedings{ICICIS2019:Conceptual_Model_for_Institutional,
  author    = {Mncedisi Mabhele and Jean-Paul Van Belle},
  title     = {A Conceptual Model for Institutional Adoption of Learning Technologies in Higher Education},
  booktitle = {Proceedings of 4th  International Conference on the Internet, Cyber Security and Information Systems 2019},
  editor    = {Kennedy Njenga},
  series    = {Kalpa Publications in Computing},
  volume    = {12},
  pages     = {123--131},
  year      = {2019},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2515-1762},
  url       = {https://easychair.org/publications/paper/JV9C},
  doi       = {10.29007/9bks}}
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