中学多主体空间的建模与开发

IF 2.1 Q1 EDUCATION & EDUCATIONAL RESEARCH Informatics in Education Pub Date : 2020-07-04 DOI:10.32517/0234-0453-2020-35-4-53-62

I. Krasteva, T. Glushkova, S. Stoyanov

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引用次数: 1

摘要

第四次工业革命的指导原则之一是终身学习的必要性。这决定了智能教育系统在任何时间、任何地点为用户提供必要的学习资源和服务的作用越来越大。本文介绍了保加利亚Plovdiv“Paisii Hilendarski”大学DeLC实验室的一个团队为中学开发的智能多代理学习环境的建模和开发。学习者被置于环境的焦点，由个人助理支持与环境一起工作。

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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Modeling and development of a multi-agent space for the secondary school

One of the guiding principles of the Fourth Industrial Revolution is the need for lifelong learning. This determines the growing role of intelligent educational systems to provide the necessary learning resources and services to users at any time and any place. This article presents the modeling and development of an intelligent multi-agent learning environment for the secondary school, developed by a team of the DeLC laboratory at the University of Plovdiv “Paisii Hilendarski”, Bulgaria. The learners are placed at the focus of the environment by personal assistants supporting work with the environment.

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来源期刊

Informatics in Education EDUCATION & EDUCATIONAL RESEARCH-

CiteScore

6.10

自引率

3.70%

发文量

审稿时长

20 weeks

期刊介绍： INFORMATICS IN EDUCATION publishes original articles about theoretical, experimental and methodological studies in the fields of informatics (computer science) education and educational applications of information technology, ranging from primary to tertiary education. Multidisciplinary research studies that enhance our understanding of how theoretical and technological innovations translate into educational practice are most welcome. We are particularly interested in work at boundaries, both the boundaries of informatics and of education. The topics covered by INFORMATICS IN EDUCATION will range across diverse aspects of informatics (computer science) education research including: empirical studies, including composing different approaches to teach various subjects, studying availability of various concepts at a given age, measuring knowledge transfer and skills developed, addressing gender issues, etc. statistical research on big data related to informatics (computer science) activities including e.g. research on assessment, online teaching, competitions, etc. educational engineering focusing mainly on developing high quality original teaching sequences of different informatics (computer science) topics that offer new, successful ways for knowledge transfer and development of computational thinking machine learning of student''s behavior including the use of information technology to observe students in the learning process and discovering clusters of their working design and evaluation of educational tools that apply information technology in novel ways.