Oct 2026· Advances in computational intelligence and robotics book series· 47 references
Blockchain Technology in Education and Learning
Abstract
This chapter examines decentralized education ecosystems by integrating blockchain, artificial intelligence, and the metaverse for next-generation learning. It explains how blockchain can provide trust, secure credentials, learner-owned records, and verifiable micro-certifications, while AI supports personalization, adaptive learning, intelligent tutoring, analytics, and competency-based assessment. The metaverse adds immersive classrooms, simulations, digital campuses, and experiential skill development. The chapter argues that these technologies can transform education from institution-centered systems to learner-centered, portable, flexible, and lifelong learning ecosystems. It also discusses challenges such as data privacy, algorithmic bias, digital inequality, credential fraud, platform control, metaverse safety, and quality assurance.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.