Keywords

1 Introduction

The modern open and distance education technologies define the need to digitize the process of training specialists using intelligent information technologies. The innovative process of transition to the model of open education is based on the principles of interaction between participants (administrators, students and teachers) in a single information and educational environment. To organize such an environment, a powerful platform is required with support for big data technologies and mechanisms for adaptive adjustment of training and retraining programs for specialists, taking into account new technological, digital and economic realities. These realities cover all institutional processes in regional labor markets and dictate to all participants the need to search for new models of the educational process. This situation is especially relevant for the federal education system, where, due to the specifics, there is a significant inertial lag when educational standards change. On the other hand, it is educational institutions that must quickly respond to changing trends in the state’s economy. High-quality training of in-demand specialists ensures sustainable development of enterprises and preserves their competitive advantages. The features of the learning process in an open educational environment are:

  • Independent work with electronic educational resources (e-learning) in the mode of ubiquitous access.

  • Distance learning with support for online interaction with teachers for all types of classes, consultations, testing through instant messengers and video conferencing (Zoom, Skype, Google Meet, etc.).

  • Use of mobile systems (m-learning) for training.

  • Support of interaction in network communities with students, teachers and employers to adjust the educational process.

  • Use of Internet resources and cloud technologies (cloud learning) to search for educational and methodological materials.

  • Use of gaming and augmented reality technologies for obtaining practical skills.

The educational information environment provides support for horizontal links between all participants in the educational process and stakeholders. Horizontal ties determine the sustainability of the educational system, which is achieved through the continuous updating of educational programs and methodological resources, leading to changes in the competence requirements of professionals on the part of employers. The current situation is characterized by a trend towards convergence of the required competencies for specialists in various industries, which is associated with information and telecommunication technologies and transition to digitalization of all spheres of human life. The convergence management can be implemented within the framework of the convergent model [1] using a feedback mechanism, which is a set of tools for adaptive adjustment of the educational environment based on the regional labor markets analysis [2]. At the same time, the educational environment should be built on the basis of open and accessible learning technologies [3]. This means the use of mobile technologies to support all forms of the educational process. New technologies and tools are needed to update electronic educational resources, synthesize personalized trajectories for training specialists in the process of changing educational standards and the emergence of new requirements of employers.

2 Background

An innovative approach to education involves solving four basic problems: a) providing personalized access to the information environment with identification and tracking of the student's personality, b) managing educational data and electronic resources, c) visualizing interactive teaching materials and resources in a collective mode, d) immersing in learning environment with virtual and augmented reality tools for mastering practical skills. An example of the synthesis of a personal information environment is the Smart Classroom model [4]. Here, users’ smartphones, smartwatches and wearable RFID tags are used to personalize, locate, and gauge student responses during learning. The approach allows synthesizing predictive behavioral models of students to assess their emotional response to the impact of teachers and testing systems in order to select the necessary actions to improve academic performance and learning efficiency [5]. The process of managing educational data and resources is closely related to the use of technologies for collecting and analyzing big data [6]. The big data toolkit is becoming popular in the educational field [7, 8]. It combines many technologies, tools and methods for big data processing [9].

Educational big data forms a field in which attention is paid to the analysis of the educational process [10]. For example, big data analysis is used to monitor and predict student performance [11]. Support for transparency, confidentiality, personalized access, minimization of adverse impacts, etc. is of particular importance. [12]. The educational process analysis includes the operations of measuring, collecting, analyzing and presenting data to the students, optimizing and personalizing the learning process [13]. An open information environment is becoming a virtual space where you can learn and teach anywhere and anytime [14]. Online training is implemented through videoconferencing systems (Zoom, Google Meet, Skype, etc.), as well as using instant messengers and social media tools.

Many educational institutions create their own developments for remote work, presentation of multimedia resources for the preparation and assessment of knowledge and competencies [15]. For open access to training courses, regardless of place of residence and student status, the concept of MOOC (Massive Open Online Course) is being implemented. Thanks to cloud and web technologies, the cost of content for MOOC courses is reduced, which allows providers to provide it for free [16]. Research in the field of creating an environment for training specialists is being carried out in the direction of the transition from traditional forms of the educational process to mixed forms of electronic, mobile and cloud learning. An important task here is the introduction of virtual and augmented reality technologies to gain practical skills [17]. The work [18] defines the basis for the use of augmented reality tools. The positions and interaction of the trainees and the objects under study in such an environment is realized using RFID and GPS sensors [19].

The introduction and use of artificial intelligence technologies is also an educational trend. In [20], the problems of implementation and exchange of knowledge on the organization and application of intelligent educational systems are considered. The article [21] presents an intellectual learning characteristics and the problems that need to be overcome in the development of educational environments. The article [22] discusses in detail the adaptive training systems of the new generation. The article [23] provides a definition of intellectual education and presents its conceptual basis. The authors consider the features of intelligent educational environments and present their own architecture of such an environment. In [24], the definition and criteria of the intellectual educational environment are presented in the framework of the development of technologies for ubiquitous education. It offers a platform for developing components of intelligent learning environments and supporting online education. The article [25] discusses in detail examples of the use of information and communication technologies for intelligent educational environments. A typical framework for developing a smart educational platform is proposed in [26]. An intelligent system includes intellectual and interactive content, means of personalizing the educational process [27]. Features are the ability to adapt to the level of training of the student and the implementation of the functional analysis of the learning process. Smart boards [28], smart classrooms [29], RFID and NFC nodes, touch sensors and other devices of the Internet of Things [30] can be used as smart components of the educational environment. To organize the operation of such an environment with multiple devices, a scalable telecommunications and computing infrastructure is required, which is a hyper-converged ecosystem [31]. Other problems in the development and use of educational platforms are described in article [32]. The work [33] examines technological and social constraints, which are a factor in the introduction of such mechanisms of intellectual education.

3 Materials and Methods: Convergence, Actualization and Personalization of Education

Open and distance education technologies are driving the learning environment beyond educational institutions. Training of specialists in such an environment requires a change in the educational process in order to implement a new convergent model of the educational process with the continuous updating of educational programs and content and the synthesis of individual learning trajectories for specialists.

The convergence of educational trajectories of different specialties occurs when the requirements of professional standards and employers change in the same way, which determines a new convergent educational model. The convergence process is realized as a result of the interpenetration and functioning of complex systems under certain conditions [34]. For example, the digitalization process currently determines the need for compulsory mastering of competencies related to information and telecommunication technologies by specialists in almost all areas of knowledge. The result is the convergence of educational programs, the creation of a single content, the use of similar methods and teaching technologies for specialists. The converged educational model means the consolidation of many similar educational resources and technologies in a single information environment.

Let us define the problem of assessing the convergence of educational content. Educational content is a hierarchical structure that consists of related sections, topics and concepts. Therefore, it is easy to represent it in the form of a variety of graph models. Teachers from different educational institutions actually work according to uniform educational standards and often create or use similar electronic educational resources in the educational process. Thus, in the information space of the Internet there are many similar resources that can be used to train specialists. One of the tasks of the transition to a converged model is the search, analysis and integration of many similar resources into the educational environment. It can also be thought of as a content graph model that has similar (isomorphic) subgraphs of related topics and sections. Thus, the task of assessing the degree of similarity of educational resources is reduced to the task of finding and determining isomorphic subgraphs. At the same time, by the isomorphism of educational content we mean the identity and identity of its parts studied in different disciplines for different specialties. To solve this problem, we use the algorithmic typing method, which is often used in computer-aided design problems. It consists in splitting the general content graph model into parts with minimization of identical (isomorphic) subgraphs, which will later serve as components in the process of synthesizing a new educational resource.

In such an environment, there is a constant updating of existing educational programs and content in order to meet changes in society and the economy, the emergence of new requirements for the competencies of specialists. The validity of updating is determined by changes in the competence requirements of professional and educational standards and employers. The results are the modernization of educational programs and content to reduce the risks of receiving low-quality and obsolete education. The task of updating is solved after the appearance of new standards, their changes, after changes in the requirements for competencies on the part of employers. In the course of updating, the tasks of synchronizing the models of the life cycles of educational programs and content for the development of new competencies are solved.

The main problems of updating include:

  • Vagueness or impossibility of formulating the required competencies on the part of employers.

  • Differentiation in the formulations of knowledge, abilities and skills as components of competencies.

  • Lack of qualified specialists in regions.

  • Lack of necessary competencies in the educational programs of regional educational institutions.

  • The changes in the employer’s requirements to the knowledge of specialists.

  • The time gap between changes in employers’ requirements and actualization of federal educational and professional standards.

  • The need for bureaucratic coordination of the changes introduced with the relevant ministries and departments, with the requirements of standards.

Information on competencies for updating can be found in Internet sources, such as enterprises, recruitment agencies sites, on forums and chats of social networks and messengers, etc. Due to the huge number of possible information sources on the Internet for monitoring and analyzing data, it is here that big data and mining technologies are in demand [35].

Open and distance education technologies are driving the learning environment beyond educational institutions. Personalized training of specialists is a way of designing and implementing the educational process, in which the student is the subject of educational activity [36]. The model of personalization of training is based on the hypothesis that the educational process will be more effective when focusing on the individual characteristics of the student. The trainee has the ability to plan educational trajectories, select educational goals, manage time and the rate of assimilation of knowledge, select tasks and ways to solve them, choose individual or group training, etc. The process of personalization of learning is implemented in the educational environment through the synthesis of individual trajectories and the selection of educational resources, taking into account the level of qualifications and characteristics of the students. As an example of a digital platform for the implementation of personalized learning, we note the Russian development “SberClass”, developed by the specialists of the joint-stock company “Sberbank” within the framework of the program “Digital platform for personalized education for schools”. The platform implements personalized learning technology that allows you to create individual trajectories for students, as well as automatically track students’ progress and problems using elements of artificial intelligence.

4 Results: Components of an Intelligent Educational Environment

An intelligent educational environment includes many tools for collecting, consolidating and analyzing big educational data. To organize the environment, a platform is being developed in the form of a hyper-converged computing ecosystem, within which tools are functioning for updating educational content, synchronizing the life cycles of educational programs, personalization of educational trajectories. The intelligent environment includes:

  1. 1.

    Computing facilities of the data processing center.

  2. 2.

    Tools for collecting, consolidating and loading educational resources.

  3. 3.

    Tools for searching, collecting and analyzing educational data and employers’ requirements.

  4. 4.

    Tools for the synthesis and customization of individual trajectories for training specialists.

  5. 5.

    Tools for updating educational programs and content.

  6. 6.

    Applications for access and work with educational resources and technologies.

  7. 7.

    Instrumentation for monitoring and managing the educational process.

  8. 8.

    Instruments of administration and information security.

The tools are intended for collecting, processing and analyzing big data, managing learning processes, modernizing electronic educational resources, synthesizing personalized learning paths, adapting educational programs. The architecture is based on modular solutions that are connected as needed. The power of the ecosystem varies through horizontal scalability and integration of standalone modules, and functionality is provided by software agents. The main components of the ecosystem are:

  • Learning Management System (LMS), which is used for management the elements of the educational space, customize the trajectories of training specialists, etc.

  • Educational Content Management System (ECMS), which is used for management of electronic educational content. This system is based on CMS Alfresco.

  • Learning Activity Management System (LAMS), which is used for administrative management.

  • A system for searching, collecting and analysis of employers’ requirements, which implements analytical technologies for working with big data and is necessary for the prompt correction of training trajectories.

  • System for storing educational content in the cloud storage and providing access to electronic educational resources.

The components automate the learning process in accordance with the convergent model of the educational environment (Fig. 1).

Fig. 1.
figure 1

Model of information and educational space.

Full size image

In an intelligent environment for managing the life cycles of educational programs and content, as well as for the synthesis and customization of individual educational trajectories, tools are used that are part of the learning management system [37]. This toolkit is also necessary to automate administrative tasks, including the functions of user registration, control of access to content, synthesis of reports, and work with educational content. Access to educational content for students and teachers is realized through the web portal. Here you can also select and enroll in training courses, work with educational and methodological materials, technologies for intermediate and final testing, knowledge assessment, maintaining electronic journals and diaries, synthesis of statements and reports for administration. Various multimedia resources are integrated into educational content, such as text of lectures and presentations, lecture audio and video courses, materials for practical and pre-laboratory classes, electronic tests, collaboration tools, links to external materials, etc. To manage the training of specialists, the LMS system Moodle (Modular Object-Oriented Dynamic Learning Environment) was chosen as a system. After analyzing the basic functionality, the functionality of the system was expanded, educational and methodological content was filled, group policies were set up and users were registered. LMS Moodle storage structure includes categories and courses.

Learning content is placed directly in courses. Categories group courses according to subject matter. The course uses a set of tools to support the educational process: questionnaires, lectures, polls, forums, tests, hyperlinks, books, SCORM packages, files, etc. To import e-courses, scripts have been developed that implement representational state transfer technology requests. Scripts represent classes in PHP. The folder structure and curriculum files are used as input. Folders are imported as nested categories. The result of the import of educational content is the structure of training categories for navigation in the information and educational space and the structure of courses within the category, broken down by years and semesters of training.

For Web publishing of educational and methodological materials, an educational content management system has been implemented based on the replicated content management system CMS (content management system) Alfresco. The system serves as a tool for electronic resources management, and also provides opportunities for finalizing and optimizing the information and educational environment. Additional software tools (web scripts and dashlets) have been developed to manage the life cycles of educational content.

The system of collection, consolidation and analysis of employers’ requirements acts as a feedback mechanism for setting up the information and educational environment.

5 Conclusion

During the research, it was noted that the modern trend in education is the evolutionary transformation of learning models towards a convergent model. The main idea of this model lies in the convergence of the trajectories of training specialists in different sectors of the economy, which is associated with the processes of digitalization and informatization of all spheres of human life. The platform and ecosystem for the implementation and development of the converged model is the information and educational environment with intelligent means and technologies for synchronizing the life cycle models of educational programs and content with the changing requirements of educational and professional standards and employers’ requirements. The goals of synchronization processes are the actualization of educational content and learning technologies, as well as personalization of the educational environment through the synthesis and adaptive adjustment of the trajectories of training specialists. The result of project research of the study is the development of new technologies for managing big educational data for the modernization of educational programs and content based on the collection and analysis of changing requirements for competencies on the part of employers. The processes of actualization and personalization in a converged educational model help to reduce the risks of receiving low-quality and outdated education, the risks of releasing unclaimed specialists in the labor market.

The analysis of research in this area showed that there is a problem of obtaining unnecessary competencies by specialists, since educational institutions cannot quickly change educational programs and content. Also relevant is the need to manage the processes of personalization of educational trajectories for specialists in different fields of activity, taking into account the requirements of educational standards and employers. The methods and tools of the information and educational ecosystem are considered as a platform for the implementation of this process. As an example of the implementation of methods and tools, we note the experience of the Penza State University. The development of an information and educational environment has been implemented since 2015. Educational content is hosted by LMS Moodle. The main component for managing the learning process in a higher educational institution with the possibility of online control and monitoring of the work of students and teachers in the educational environment is the electronic dean’s office system.