Does artificial neural network support connectivism’s assumptions?

• This paper examines the relationship between connectivism’s assumptions and AI

• Learning as pattern recognition can describe a learning process under certain conditions

• Artificial intelligence tools use almost all learning theories including connectivism

• Connectivism unsupervised learning model in artificial neural network design

Abstract

Connectivism was presented as a learning theory for the digital age and connectivists claim that recent developments in Artificial Intelligence (AI) and, more specifically, Artificial Neural Network (ANN) support their assumptions of knowledge connectivity. Yet, very little has been done to investigate this brave allegation. Does the advancement in artificial neural network studies support connectivism’s assumptions? And if yes, to what extent? This paper addresses the aforementioned question by tackling the core concepts of ANN and matching them with connectivist's assumptions. The study employed the qualitative content analysis approach where the researcher started with purposely selected and relatively small content samples in connectivism and ANN literature. The results revealed that ANN partially supports connectivism’s assumptions but this does not mean that other learning theories such as behaviorism and constructivism are not supported as well. The findings enlighten our understanding of connectivism and where it may be applied.

Keywords:

• learning theory

• connectivism

• artificial neural network

• artificial intelligence

• AI

• e-learning

• online learning

• distance learning

Cited as:

Aldahdouh, A. A. (2017). Does artificial neural network support connectivism’s assumptions? International Journal of Instructional Technology and Distance Learning, 14(3), 3–26. Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3063496