Raúl Jaime Maestre, Javier Bermejo Higuera, Nadia Gámez Gómez, Juan Ramón Bermejo Higuera, Juan A Sicilia Montalvo, Lara Orcos Palma
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引用次数: 0
摘要
区块链在许多领域都是一种新的应用技术，在教育领域也是如此。因此，研究区块链技术的需求日益显现，因为区块链技术在教育等不同领域仍在迈出第一步。本文对区块链技术在教育领域的应用现状进行了综述，重点明确了教育领域引入区块链技术的优势、劣势和挑战。此外，还介绍了通过 BeCertify 项目利用区块链技术实施职称证书解决方案的情况。在这一解决方案中，已经完成了平台的开发阶段、系统架构和 API 的操作，最终形成了一个平台，为以更加透明和技术先进的方式管理学生的资格认证迈出了第一步。
The application of blockchain algorithms to the management of education certificates.
Blockchain is a new application technology in many sectors and the same is true in the world of education. Therefore, there is an increasingly emerging need to research blockchain technology, as it is still taking its first steps in different sectors, such as education. This article presents a review of the state of the art of blockchain technology in the education sector, focusing on identifying the advantages, disadvantages, and challenges associated with the introduction of blockchain technology in the education sector. In addition, the implementation of a title certificate solution through blockchain technology through the BeCertify project is presented. In this solution, the development stages of the platform, the system architecture, and the operation of the API have been carried out, resulting in a platform that constitutes the first step towards a more transparent and technologically advanced way of managing the certifications of the students' qualifications.
期刊介绍：
This Journal provides an international forum for the timely publication and dissemination of foundational and applied research in the domain of Evolutionary Intelligence. The spectrum of emerging fields in contemporary artificial intelligence, including Big Data, Deep Learning, Computational Neuroscience bridged with evolutionary computing and other population-based search methods constitute the flag of Evolutionary Intelligence Journal.Topics of interest for Evolutionary Intelligence refer to different aspects of evolutionary models of computation empowered with intelligence-based approaches, including but not limited to architectures, model optimization and tuning, machine learning algorithms, life inspired adaptive algorithms, swarm-oriented strategies, high performance computing, massive data processing, with applications to domains like computer vision, image processing, simulation, robotics, computational finance, media, internet of things, medicine, bioinformatics, smart cities, and similar. Surveys outlining the state of art in specific subfields and applications are welcome.
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