{"title":"The concept of the formation and development of a digital intellectual ecosystem of blended university learning","authors":"S. Grigoriev, R. Sabitov, G. Smirnova, S. Sabitov","doi":"10.32517/0234-0453-2020-35-5-15-23","DOIUrl":null,"url":null,"abstract":"The article proposes the concept of the formation and development of an adaptive ecosystem of university learning. The concept can allow not only to eliminate the shortcomings inherent in the distance education system, but also to create the basis for building a full-fledged educational technology. The basis for constructing such an ecosystem, in addition to purely didactic developments, can be modern achievements in the field of systems theory, digitalization and artificial intelligence. The education market is seriously affected by advances in artificial intelligence and the rapid development of Industry 4.0. It is also necessary to consider rather unpredictable natural disasters and pandemics. Under these conditions, the only way to maintain and strengthen their positions in the education market, which will rapidly change in the coming decades, is the transformation of processes within the framework of new technological trends and integrated network cluster ecosystems. Decentralized training and outsourcing can become two key functions for the successful application of artificial intelligence in education. Modeling, optimization and analytics of big data make it possible to form a complete set of technologies for creating an outsourcing network and digital educational chains, which allows us to identify the state model of all processes in real time. At each moment in time, the digital twin displays the status of outsourcing processes and educational chains with actual data on planning, preparing the necessary equipment, directly preparing educational programs, loading teachers, accounting and monitoring learning outcomes, etc. The digital twin can be used both for making decisions in real-time, and for forecasting and planning outsourcing. In fact, the university and the companies providing outsourcing services within the framework of this approach are integrated into a single mechanism for solving tasks of flexible individual training. Within the framework of the proposed approach, it is possible to build an educational university environment integrated with real objects of the economy of the territory, which is a component of the educational ecosystem. The concept under consideration allows predicting and planning the training of required specialists, since the model of its work is closely connected with enterprises in the real sector. This becomes possible due to the fact that training takes place according to flexible programs that reflect the ever-changing requirements of enterprises to the competencies of their employees. In fact, a university or a group of universities is becoming an essential component of territorial industrial clusters, which makes it possible to increase the efficiency and quality of specialist training and to quickly develop new curricula and courses that will quickly develop competencies demanded by the real sector of the economy. The use of artificial intelligence technology in combination with the capabilities of the Internet of things and digitalization of the main business processes provides, in fact, the functioning and development of the university’s ecosystem by analogy with the ecosystems of large sectoral system-forming enterprises.","PeriodicalId":45270,"journal":{"name":"Informatics in Education","volume":"15 1","pages":"15-23"},"PeriodicalIF":2.1000,"publicationDate":"2020-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Informatics in Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32517/0234-0453-2020-35-5-15-23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 8
Abstract
The article proposes the concept of the formation and development of an adaptive ecosystem of university learning. The concept can allow not only to eliminate the shortcomings inherent in the distance education system, but also to create the basis for building a full-fledged educational technology. The basis for constructing such an ecosystem, in addition to purely didactic developments, can be modern achievements in the field of systems theory, digitalization and artificial intelligence. The education market is seriously affected by advances in artificial intelligence and the rapid development of Industry 4.0. It is also necessary to consider rather unpredictable natural disasters and pandemics. Under these conditions, the only way to maintain and strengthen their positions in the education market, which will rapidly change in the coming decades, is the transformation of processes within the framework of new technological trends and integrated network cluster ecosystems. Decentralized training and outsourcing can become two key functions for the successful application of artificial intelligence in education. Modeling, optimization and analytics of big data make it possible to form a complete set of technologies for creating an outsourcing network and digital educational chains, which allows us to identify the state model of all processes in real time. At each moment in time, the digital twin displays the status of outsourcing processes and educational chains with actual data on planning, preparing the necessary equipment, directly preparing educational programs, loading teachers, accounting and monitoring learning outcomes, etc. The digital twin can be used both for making decisions in real-time, and for forecasting and planning outsourcing. In fact, the university and the companies providing outsourcing services within the framework of this approach are integrated into a single mechanism for solving tasks of flexible individual training. Within the framework of the proposed approach, it is possible to build an educational university environment integrated with real objects of the economy of the territory, which is a component of the educational ecosystem. The concept under consideration allows predicting and planning the training of required specialists, since the model of its work is closely connected with enterprises in the real sector. This becomes possible due to the fact that training takes place according to flexible programs that reflect the ever-changing requirements of enterprises to the competencies of their employees. In fact, a university or a group of universities is becoming an essential component of territorial industrial clusters, which makes it possible to increase the efficiency and quality of specialist training and to quickly develop new curricula and courses that will quickly develop competencies demanded by the real sector of the economy. The use of artificial intelligence technology in combination with the capabilities of the Internet of things and digitalization of the main business processes provides, in fact, the functioning and development of the university’s ecosystem by analogy with the ecosystems of large sectoral system-forming enterprises.
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.