An extended discourse ensued in and around the status of connectivism as a learning theory for the digital age. This led to a number of questions in relation to existing learning theories. Do they still meet the needs of today’s learners, and anticipate the needs of learners of the future? Would a new theory that encompasses new developments in digital technology be more appropriate, and would it be suitable for other aspects of learning, including in the traditional class room, in distance education and e-learning? In this article, I highlight current theories of learning and critically analyze connectivism within the context of its predecessors, to establish if it has anything new to offer as a learning theory or as an approach to teaching for the 21st Century.
C. Otto, M. Stamatakis, A. Hoppe, and R. Ewerth. Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners' and Doctoral Consortium - 23rd International Conference, AIED 2022, Durham, UK, July 27-31, 2022, Proceedings, Part II, volume 13356 of Lecture Notes in Computer Science, page 458--462. Springer, (2022)
J. Kim, P. Guo, D. Seaton, P. Mitros, K. Gajos, and R. Miller. Proceedings of the First ACM Conference on Learning @ Scale Conference, page 31–40. New York, NY, USA, Association for Computing Machinery, (2014)
Z. Javed, H. Qazi, and S. Khoja. 2019 8th International Conference on Information and Communication Technologies (ICICT), page 124-128. (November 2019)