Neurotechnology and artificial intelligence as key factors in the customization of the lifelong learning route

A. A. Fedorov, S. Kurkin, M. Khramova, A. E. Hramov
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引用次数: 1

Abstract

Artificial Intelligence (AI) technologies are being actively developed and the number of applications is growing rapidly. The education sector is no exception, which in the future can be significantly transformed using AI, for example, in terms of the development of approaches to the customization of the educational route. At the same time, the active development of neuroimaging technologies, as well as progress in neuroscience and neurotechnology, allows providing AI algorithms with important data about the functioning of the learner’s brain.The article considers the issues of customization of the lifelong learning route (CLLR) using the mentioned assistive technologies: neurotechnologies and artificial intelligence. The basic principle of functioning of the proposed CLLR is formulated: based on the analysis of recorded multimodal data about the learner algorithms based on AI propose actions to implement feedback, which will increase the efficiency and customization of the educational process.The modular principle of constructing the CLLR system is proposed, and the methods of AI that can find application as the core of an intelligent subsystem of CLLR are discussed. In conclusion, various strategies of application of the proposed CLLR system, which will allow to implement a universal system of educational decision-making support on its basis, are presented.
神经技术和人工智能是终身学习路径定制的关键因素
人工智能(AI)技术正在积极发展,应用数量正在迅速增长。教育领域也不例外,未来可以使用人工智能进行重大变革,例如,在开发定制教育路线的方法方面。与此同时,神经成像技术的积极发展,以及神经科学和神经技术的进步,可以为人工智能算法提供有关学习者大脑功能的重要数据。本文考虑了使用上述辅助技术:神经技术和人工智能来定制终身学习路线的问题。提出了CLLR的基本功能原理:在分析基于AI的学习者算法的记录多模态数据的基础上,提出行动来实现反馈,从而提高教育过程的效率和定制化。提出了构建CLLR系统的模块化原则,并讨论了人工智能作为CLLR智能子系统核心的应用方法。最后,本文提出了应用CLLR系统的各种策略,这些策略将在此基础上实现一个通用的教育决策支持系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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