Development of a system for adaptive control of the components of an intelligent educational environment

The article discusses the issues of creating software and tools for managing the processes of training specialists in an intellectual educational environment. The complex of tools is being developed as part of a hyper-converged computing ecosystem to support open personalized learning technologies and is designed to customize and adaptively update educational programs and content, taking into account the requirements of federal standards and regional labor markets. At the first stage, the tools solve the problems of searching, collecting, consolidating and intelligent analysis of requirements for specialists extracted from open sources on the Internet, such as sections with employers’ vacancies on the websites of enterprises, recruitment agencies, labor exchanges, message boards, forums, chats, groups of social networks and messengers. At the next stage, the process of adaptive adjustment and synchronization of educational programs is implemented, taking into account the consolidated information and predicted data on the required competencies in the short and medium term in a given region. Setting up the educational process in an open information environment occurs during the evolutionary transition to a convergent learning model, continuous updating of educational programs and content, personalization of training trajectories. The convergent model determines the convergence of educational programs and content for different specialties in accordance with the digitalization processes of all spheres of human life, which is reflected in the requirements for competencies in professional and educational standards, as well as on the part of employers. The processes of actualization and personalization make it possible to increase the efficiency and quality of training specialists by reducing the risks of obtaining a low-quality and morally obsolete education. The architecture of the adaptive management system of the educational environment includes the following components: a) Learning Management System (LMS), b) Education Content Management System (ECMS), c) Learning Activity Management System (LAMS), d) tools for searching, collecting and analyzing employers’ requirements, e) cloud storage of educational content.

[1]  Miftachul Huda,et al.  Big Data Emerging Technology: Insights into Innovative Environment for Online Learning Resources , 2018, Int. J. Emerg. Technol. Learn..

[2]  Zhi-Ting Zhu,et al.  A research framework of smart education , 2016, Smart Learning Environments.

[3]  Muhammad Shahid Bhatti,et al.  AREd: Anatomy Learning Using Augmented Reality Application , 2019, 2019 International Conference on Engineering and Emerging Technologies (ICEET).

[4]  Anealka Aziz Hussin Education 4.0 Made Simple: Ideas for Teaching. , 2018 .

[5]  Jeffrey M. Voas,et al.  Smarter Education , 2018, IT Professional.

[6]  Gwo-Jen Hwang,et al.  Definition, framework and research issues of smart learning environments - a context-aware ubiquitous learning perspective , 2014, Smart Learning Environments.

[7]  Boban Vesin,et al.  Learning in smart environments: user-centered design and analytics of an adaptive learning system , 2018, Smart Learning Environments.

[8]  Begoña Gros The design of smart educational environments , 2016, Smart Learning Environments.

[9]  Jui-Yuan Su,et al.  A Context Aware Smart Classroom Architecture for Smart Campuses , 2019, Applied Sciences.

[10]  Sri Murugarasan Muthukrishnan,et al.  Big data framework for students' academic performance prediction: A systematic literature review , 2018, 2018 IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE).

[11]  Jorge Cordero,et al.  Learning analytics tasks as services in smart classrooms , 2017, Universal Access in the Information Society.

[12]  Hany S. Hussein,et al.  Spectral Efficient Spatial Modulation Techniques , 2019, IEEE Access.

[13]  Maryam Bagheri,et al.  The Effect of the Internet of Things (IoT) on Education Business Model , 2016, 2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS).

[14]  Salam Ullah Khan,et al.  Learning analytics in the era of big data: A systematic literature review protocol , 2017, 2017 International Symposium on Wireless Systems and Networks (ISWSN).

[15]  Jefri Yushendri,et al.  Design the Smart Board system in ubiquitous computing for teaching and learning process , 2015, 2015 International Conference on Science in Information Technology (ICSITech).

[16]  Mihail C. Roco,et al.  Managing Nano-Bio-Info-Cogno Innovations: Converging Technologies in Society , 2006 .

[17]  Ben Daniel,et al.  Big Data and analytics in higher education: Opportunities and challenges , 2015, Br. J. Educ. Technol..

[18]  Maria João Ferreira,et al.  Higher Education Disruption Through IoT and Big Data: A Conceptual Approach , 2017, HCI.

[19]  Mohamed Elhoseny,et al.  Ubiquitous smart learning system for smart cities , 2017, 2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS).

[20]  Lela Mirtskhulava,et al.  Smart Education Environment System , 2014 .

[21]  Ali Yavari,et al.  CoALA: Contextualization Framework for Smart Learning Analytics , 2017, 2017 IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW).

[22]  George Siemens,et al.  Penetrating the fog: analytics in learning and education , 2014 .

[23]  Liang Xiao,et al.  Towards Smart Educational Recommendations with Reinforcement Learning in Classroom , 2018, 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE).

[24]  Adalia L. Martin,et al.  The Role of Big Data Management and Analytics in Higher Education , 2017 .

[25]  Mihail C. Roco,et al.  Managing nano-bio-info-cogno innovations , 2006 .

[26]  Sheetal Kalra,et al.  Smart computing based student performance evaluation framework for engineering education , 2017, Comput. Appl. Eng. Educ..

[27]  Alfred Essa A possible future for next generation adaptive learning systems , 2016, Smart Learning Environments.

[28]  Imran A. Zualkernan,et al.  IoT Technologies to Enhance Precision and Response Time of Mobile-Based Educational Assessments , 2016, 2016 International Conference on Computational Science and Computational Intelligence (CSCI).

[29]  Rebecca Eynon,et al.  The rise of Big Data: what does it mean for education, technology, and media research? , 2013 .

[30]  Jon K. Price Transforming learning for the smart learning environment: lessons learned from the Intel education initiatives , 2015, Smart Learning Environments.

[31]  Alexey Finogeev,et al.  Convergent approach to synthesis of the information learning environment for higher education , 2019, Education and Information Technologies.

[32]  Penelope J. Lister A smarter knowledge commons for smart learning , 2018, Smart Learning Environments.

[33]  Alexey Finogeev,et al.  Life-cycle management of educational programs and resources in a smart learning environment , 2018, Smart Learning Environments.

[34]  Clare Stanier,et al.  Defining Big Data , 2016, BDAW '16.

[35]  Miftachul Huda,et al.  Demystifying Learning Analytics in Personalised Learning , 2018, International Journal of Engineering & Technology.

[36]  Elyjoy Micheni,et al.  Big Data Analytics in Higher Education: A Review , 2017 .