Potential Abstract:
This research article delves into the emerging field of connectivist learning within the context of the metaverse, drawing on concepts from organic systems and collective intelligence. Connectivist learning approaches emphasize the importance of networked connections and knowledge creation through interaction with diverse sources of information. Leveraging the potential of the metaverse – a virtual reality space where users can interact with each other and digital objects – this study investigates how connectivist learning can be enhanced by leveraging eigenvectors as a method of analyzing and visualizing knowledge networks.
The research adopts a mixed-methods approach, combining quantitative analysis of network structures and qualitative analysis of participant experiences. A pilot study was conducted with a group of undergraduate students, who engaged in a connectivist learning experience within the metaverse. The participants’ interactions and knowledge creation were tracked and analyzed using eigenvector centrality measures, which provide insights into the most influential nodes and pathways in the knowledge network.
Preliminary findings suggest that connectivist learning in the metaverse exhibits organic characteristics, with knowledge networks evolving and adapting in response to participant interactions. The application of eigenvector analysis reveals hidden patterns and structures within the network, illuminating key nodes and pathways of knowledge flow. These findings contribute to our understanding of the potential of the metaverse as a platform for connectivist learning, highlighting the importance of network analysis and visualization techniques in uncovering the complex dynamics of knowledge creation and sharing.
This research has significant implications for educational practitioners and policymakers. By embracing connectivist approaches within the metaverse, educators can facilitate collaborative and networked learning experiences that foster critical thinking, creativity, and the development of digital literacies. Moreover, understanding the underlying structures of knowledge networks can inform the design of interventions and instructional strategies to optimize connectivist learning experiences.
Potential References:
- An Exploratory Study on Effectively Upskilling Employees During COVID-19
- Pedagogical and Technical Analyses of Massive Open Online Courses on Artificial Intelligence
- The Idea That Digital Remote Learning Can Happen Anytime, Anywhere in Forced Online Teacher Education is a Myth
- Deep learning for intelligent human–computer interaction
- The utilitarian and hedonic value of immersive experiences on WeChat: examining a dual mediation path leading to users’ stickiness and the role of social …
