Potential Abstract:
This research examines the intricate relationship between politics, directed acyclic graphs (DAGs), and the evolving landscape of Web3 technologies in the context of education. As decentralized technologies gain momentum, it becomes essential to investigate their potential impact on educational systems and the implications for educational policy and practice. The study employs a mixed-methods approach, combining qualitative interviews, document analysis, and network analysis to explore the gestalt of Web3 technologies and their integration into educational processes.
The theoretical framework of this research draws upon the concept of gestalt, which highlights the interconnectedness and holistic nature of complex systems. By applying this lens to the analysis of Web3 technologies, we aim to uncover the underlying patterns, emergent properties, and interdependencies within educational contexts. Additionally, the study explores the role of politics in shaping the adoption, governance, and implementation of decentralized technologies in education.
Central to Web3 technologies is the utilization of directed acyclic graphs (DAGs), which provide an organic framework for data storage, transmission, and verification. This research investigates the potential benefits and challenges associated with incorporating DAGs into educational systems, such as enhanced security, privacy, and transparency. Moreover, the study examines the implications of DAGs for data ownership, control, and access rights in education.
Through an in-depth exploration of various case studies and empirical data, this research aims to contribute to the growing body of literature on Web3 technologies in education. The findings will help inform educational policymakers, administrators, and practitioners about the opportunities and challenges presented by the integration of decentralized technologies into educational systems. Ultimately, this research seeks to foster a better understanding of the potential transformative effects of Web3 technologies on education and to guide future research in this domain.
Potential References:
- Predicting NFT Classification with GNN: A Recommender System for Web3 Assets
- Web 3.0: The Future of Internet
- Token Economy: How the Web3 reinvents the internet
- Blockchain-Assisted Privacy-Preserving Data Computing Architecture for Web3
- Web3: A comprehensive review on background, technologies, applications, zero-trust architectures, challenges and future directions
