This paper aims to summarize recent trends in the field of intelligent education and build on the research findings to propose a conceptual model of an intelligent educational environment (IEE) along with possible applications. A bibliometric analysis explores the recent trends to obtain insights into the current research directions. The concept of an IEE is introduced and correlated to other popular concepts in the educational field. Relevant user requirements for the IEE are defined and discussed. They serve as the basis for creating the conceptual model as a UML class diagram. The proposed model gives an overall picture of the relationships among the essential elements of the IEE and provides insights into its future development. Two possible applications are outlined: personalized teaching and learning and the assessment process. Any particular application of the model to build an IEE must consider all specific user requirements and add relevant details. The proposed conceptual model can be used to enhance the teaching–learning process and improve learners’ performance.

Large language models (LLMs) are an emerging artificial intelligence-driven technology, based on transformer architecture. LLMs are widely used in modern education, both by learners and tutors, as standalone tools or integrated into e-learning systems, where they can support personalization, adaptive learning, automated assessment and feedback, content generation, and intelligent tutoring. LLMs offer many benefits for learners, but they also have significant limitations. One approach to address the limitations of LLMs is to combine them with other intelligent technologies. The primary goal of this systematic survey is to identify appropriate supporting technologies, mechanisms of use, and methodological approaches able to help overcome the limitations of LLMs and support their responsible and effective use in education. For this reason, analysis and discussion of recent scientific research (published over the last four years) accessible through Google Scholar, ACM, IEEE Xplore, or indexed in Scopus or Web of Science (WoS) is performed. A bibliometric analysis of results from the initial general query strings is used to refine and formulate more specific search queries during the literature retrieval process in the selected databases. Full-text exploration of relevant search results serves as a source for critical analysis and deductions leading to the following conclusion: LLMs should be integrated into e-learning systems, combined with knowledge graphs, ontologies, learning analytics, and multimodal reasoning to enhance reliability, improve pedagogical effectiveness, and enable true personalization. New pedagogical approaches are also needed to ensure the effective use of LLMs in both tutoring and assessment contexts. Therefore, the authors propose methodological guidelines for integrating LLMs in complex modular educational systems.

An active discussion of the questions of the advisability of forming new principles of national unity and creating an orderly harmonious world in the minds of people, strengthening the educational functions of the state, its concern for public morality do not primarily concern education, humanization of its content, and revision of the educational process. The formation and implementation of a state policy adequate to this problem must comply with the requirements of our time, create, on the one hand, conditions for ensuring the rights and freedoms of citizens, including the observance of the fundamental principles of religious freedom, and on the other, develop legislative norms that regulate these rights. A legal democratic state provides for the formation of public policy in accordance with the needs of society and taking into account public thought. The secular nature of public education is not an obstacle to the introduction of disciplines in the provision of religious knowledge in the educational process of schools, religious knowledge can and should be considered as an element of secular culture. Knowledge of religion should be carried out by secular teachers, be neutral in content and not be accompanied by religious rites. The problems of the formation of moral and spiritual values, the worldview of a person, the introduction of religious disciplines in secondary schools are vividly discussed in scientific, educational, government circles, as well as among representatives of the clergy. The religious component in secular education will give importance to folk culture and traditional religion, which will form concepts such as tolerance and respect for other faiths and cultures, which is important in the context of globalization of the world.

Education is a complex and multidisciplinary field. Effective personalization in education is grounded in both educational theory and hybrid AI practice. Personalization is typically driven by explicit, structured knowledge; however, the effective automated extraction of implicit knowledge from educational data is also of great importance. This research analyzes and classifies the knowledge required for personalization, as well as the effective technologies for its representation and storage in both human-readable and machine-processable forms. As a result, we propose a conceptual model of a layered, hybrid knowledge base architecture grounded in mathematical logic, designed to structure knowledge for supporting personalization in intelligent educational systems. Systems of mapped ontologies constitute a core component of the proposed architecture. The proposed architecture extends the well-known intelligent tutoring systems architecture by incorporating new types of knowledge as well as structural and organizational elements and by providing a detailed description of their interrelationships and integration mechanisms. It is important to make easier and effective development of ontologies for usage in knowledge models, integrated in practical e-learning systems. The proposed conceptual model also promotes ontology reuse, thereby reducing the time, effort, and cost associated with ontology development and evolution. To enhance ontology development and usage through effective reuse, we propose a structured organization of metadata for describing all components of hybrid AI-driven knowledge bases. This metadata framework can support the development of an ontology that facilitates the discovery, selection, and reuse of appropriate ontologies, rules, mappings, and tools stored in specialized knowledge repositories for educational purposes.