A Preliminary Study on Connectivism—Constructivism Learning Theory Based on Developmental Cognitive Neuroscience and Spiking Neural Network

Based on a new theoretical perspective, this paper attempts to unify the seemingly incompatible learning theories of Connectivism and Constructivism into a scientific theoretical framework. The Connectivism-Constructivism learning theory is not a simple superposition of the two theories. Instead, it absorbs the essence of the learning theory of Constructivism, Connectivism and Neo-Constructivism, and takes the two empirical scientific experimental results of developmental cognitive neuroscience and spiking neural network as the factual basis, and develops two theories from the perspective of development. Integration, to achieve the resolution of contradictions, complement each other, and then rebuild. This paper discusses Connectivism-Constructivism learning theory. The theory holds that the essence of knowledge is the connection between the subject and the environment. There are two forms: physical form and logical form. The only logical form can be realized and utilized by people. Learning can be divided into two stages: connection and construction. Connection is the premise, construction is the core, and the network action generated in the connection stage as a raw material is pruned, and processed by various systems in the construction stage to become psychological representation. When the psychological representation is used, the relevant network shaping is finished, and the meaningful network is formed, which completes the change of knowledge from physical form to logical form and from logical form to physical form. Therefore, learning is the process of constructing meaningful network. We should not only promote the students’ connection stage, but also help the students’ construction stage. The innovation and breakthrough contribution of this paper is that it is the first time to look at the topic of learning theory from a new research perspective. In order to explore a more convincing learning theoretical framework, this article takes the lead in seeking theoretical support and factual basis from developmental cognitive neuroscience and Spiking neural network. As a result, Connectivism learning theory and Constructivism learning theory are successfully integrated into a rather complete and effective theoretical framework to reconstruct Connectivism-Constructivism learning theory.

AWeb 3.0 ontology based on similarity:a step toward facilitating learning in the Big Data age

Web 3.0 technology will revolutionize the learning process,enabling data linking to connect learning resources and create ontologies for different areas of knowledge that enable‘smart searches.’Smart or semantic searches perceive relationships among various pieces of information and present them to the learner.Connectivism has been proposed as a theory to guide learning in this new Web 3.0 environment.This paper discusses the relevance of connectivism and then develops an ontology for learning resources.The authors propose a hybrid similarity measure to evaluate the similarity among different learning resources.The paper presents a case study that was conducted to evaluate the proposed similarity measure on education data sets and demonstrates the effectiveness of the proposed methods.