The Role of Machine Learning and Artificial Intelligence for making a Digital Classroom and its sustainable Impact on Education during Covid-19

The article reveals various aspects of the use of artificial intelligence (AI) in higher education. Prospects for the use of AI in higher education are discussed, and specific examples of the use of AI for educational purposes are considered. AI, having great potential for improving the quality of higher education, also carries potential risks of use that must be taken into account. The role of artificial intelligence in the educational process of higher education, evaluation and management of educational processes is emphasized. That is why attention is focused on the issue of what aspects are behind the use of AI in education. The issue of ethical and social consequences of the use of AI in education is discussed.

The importance of artificial intelligence (AI) is growing in all economic sectors and thus also in higher education. In recent years, there have been significant developments in this concept of "Artificial Intelligence in Education (AIED)". The purpose of this study was to find out how the concept of artificial intelligence can be applied to teaching and learning in higher education and the implications of the use of artificial intelligence in higher education. The impact of the development of technologies on learning is often studied on the methods and scope of learning and teaching. Artificial intelligence enables higher education services to become easily accessible with extraordinary speed, not only in the classroom but also outside the classroom. This report seeks to explore how AI will become an integral part of universities and seeks to examine its immediate and future impact on various aspects of higher education. The challenges of implementing AI in these institutes were also explored. As artificial intelligence (AI) research in education increases, many researchers in the field believe that the role of teachers, schools and leaders in education will change. In this regard, the aim of this study is to investigate which are the possible scenarios for the arrival of artificial intelligence in education and what impact it can have on the future of schools. In this research, it confirmed that artificial intelligence has been widely adopted and used in various forms in education, especially educational institutions. Artificial intelligence was initially implemented in the form of computers and computer-related technologies, moving to web-based and web-based intelligent educational systems, and finally with the use of embedded computing systems and other technologies such as humanoid robots and web-based chatbots teachers & tasks and assignments independently or with tutors. With these platforms, teachers could perform various administrative tasks such as grading and Work more effectively and efficiently and achieve higher quality in your learning activities. On the other hand, because the systems use machine learning and adaptability, the curriculum and content are adapted which improved uptake and retention, which improved the student experience and the overall quality of education.

Purpose: The purpose of the study is to identify areas of student use of Artificial Intelligence (AI) in education, as well as to develop a model view of student use of AI in education. Design/methodology/approach: The study used an integrated research approach, combining descriptive, comparative and descriptive analysis methods to provide an in-depth and multifaceted understanding of the role and potential of artificial intelligence in education. The research process started with a biblio-metric analysis and a systematic literature review, which was conducted in Scopus and Google Scholar databases. The literature analysis carried out allowed artificial intelligence to be defined, as well as selected AI tools to be identified. Subsequently, an in-house study was carried out, which was in the form of a survey - a diagnostic poll; authors’ questionnaire containing ten closed questions was used as a research tool. The questionnaire was uploaded to Google and the link was distributed to selected students of Cracow University of Economics in Krakow. Responses were collected using the CAWI technique. A total of 295 responses were obtained. Results: It was found that students use AI in education, the main areas of use of AI tools by students are: writing term papers, reports, or creating presentations. What is very important, students use AI to obtain feedback on their work, and are also aware of the benefits and threats generated by modern technologies. The conducted research allowed for the development of a model approach to the use of AI in education by students. Research limitations/implications: The study was limited by the sample of people studying at Cracow University of Economics in Krakow. The authors showed that students use AI in education to a large extent, ChatGPT was most frequently indicated as the tool of preference, as well as the frequent use of Gemini by students. Students indicated risks as well as benefits of using AI in education which allowed the authors to conclude that they use AI consciously. Future research should include a more in-depth exploration of the directions of AI use in education and investigate the impact of AI on competence development. Research on the attitudes - behavioural, cognitive, emotional - of students towards ChatGPT may also be interesting, as well as examining the differences in attitudes depending on the field of study. Practical implications: The development of a model for the use of artificial intelligence in education by students can indicate current trends in education that are posed to both lecturers and students to adapt to changing market and educational conditions.Social implications: There is an increased awareness among lecturers and students regarding the use of AI in education and its impact on the sector. Originality/value: Discussion of AI, identification of AI tools, identification of the extent and areas of student use of AI in education. The added value is to identify the benefits and risks of student use of AI in education, as well as to develop a model view of student use of AI in education.

The world we live in has been radically changed by technology in recent decades. The field of artificial intelligence (AI) in education (AIEd) has developed into a sizable literature collection with a variety of viewpoints. The use of artificial intelligence in educational applications is growing in popularity, posing both benefits and difficulties for the classroom. This study aims to provide a comprehensive understanding of the current conceptual framework of AIEd and explore the future vision for this technology. The study aims to investigate the opportunities that AI technology offers to enhance teaching and learning, identify challenges in this field and outline the future vision for AI technology, and examine the learning outcomes for teachers and students influenced by AI technology. This method can offer a thorough understanding of the conceptual framework and the long-term goals for this area of technology. For a comprehensive literature evaluation, we chose 35 empirical research publications that included AIEd applications, study themes, and other aspects of the research design, including the general AIEd research field, AIED applications, research topics, and future vision including future benefits, opportunities, threats, and challenges. Although AIEd-based settings are improving student learning, research indicates that tailored learning is still in its early stages. Lack of money and moral dilemmas are obstacles. AIEd's benefits include the fact that AI chatbots and applications facilitate learning, but they also have drawbacks. Additionally, AI apps improved engagement through interactive features, promoted well-being with components and continual availability, and spurred creativity by offering new ideas and problem-solving strategies. While encouraging creativity and increasing participation have many advantages, there are also important obstacles that need to be overcome, such as limits on creativity and moral dilemmas. To maximize the use of AI in education, these elements must be balanced through careful deployment and ongoing assessment.

Purpose: of the article is to study the influence of artificial intelligence on the construction of an adaptive educational environment that takes into account the positive and negative impact of artificial intelligence, as the core of digital technologies, on the well-being of participants in the educational process. Methods: the work uses a complex of theoretical methods, including axiomatic, formalization, abstraction, logical analysis, historical retrospection. The most signifi cant practical research methods include statistical, operationalization and evaluation, comparative analysis. Results: the article provides a statistical substantiation of the demand for artifi cial intelligence in the education. The current educational problems are shown, in solving which it is advisable to use artifi cial intelligence. The article describes the trends in the use of artificial intelligence in the Russian education. The interpretation of the adaptive educational environment is given and the possibilities of using artificial intelligence as a tool for its construction are shown. The logical sequence for constructing an adaptive intelligent teaching system is proposed. The analysis of the impact of digital technologies used in hybrid learning (including artifi cial intelligence) on the well-being of participants in the educational process was carried out. The need for a rational, balanced and cautious approach to the use of artifi cial intelligence in education is emphasized, which gives rise to numerous ethical problems, ignoring which can negatively aff ect the values of education. Conclusions and Relevance: in the context of digitalization of the economy and society, the key technology of which is artifi cial intelligence, education is facing technological challenges that force it to adapt to new operating conditions. The penetration of artifi cial intelligence into the field of education is the pattern of scientific and technological progress that cannot be resisted. The positive aspects and threats of using artificial intelligence in education should be critically assessed, and informed decisions should be made on this basis. Considering the specifics of the educational environment in which the foundation of personality is laid, and the need to preserve the values of education as a factor of cultural progress, priority in goal-setting and the meanings of education should remain with a person whose assistant can be artifi cial intelligence.

The object of the study is the status, segment analysis, dynamics and prospects of the global markets for higher education and artificial intelligence in higher education. The analysis and systematization of literature data allowed to summarize the results of research in the field of marketing research of higher education markets and artificial intelligence in higher education. To conduct a marketing analysis, the method of literature search and the method of analysis were applied. The main trends, volumes, rates and factors of growth of the higher education and artificial intelligence markets in the field of higher education, as well as some limitations of their development are presented. The analysis of the higher education market is carried out by the following segments: geographical regions, mode of study, educational levels, sources of income, educational institutions, and the market of artificial intelligence in education – market components, deployment mode, technologies, applications, geographical regions. The potential demand and volume of higher education and artificial intelligence markets in the field of higher education in different countries of the world are determined, the dynamics and competition in the world markets are tracked. The state of the art and prospects for further research in the field of higher education and artificial intelligence in education are summarized. The following scientific methods were used: the method of searching for literature data on the topic under study; the method of analyzing literary sources; comparative analysis of different methodological approaches; content analysis of documents; the method of systematization and classification in conducting research on the achievements of modern science and technology in the field of higher education and the use of artificial intelligence in higher education. The systematization of literature data allowed to present the problems of higher education and the use of artificial intelligence in higher education in the form of tables and diagrams, which gives a certain advantage for understanding and using the material.

The research investigates the ethical implications of artificial intelligence (AI) in education (AIED) by examining current international organizations' rules and recommendations. It first discusses the prospects and possible ethical difficulties with AI in education, followed by a thematic study of important ethical concepts for AIED. The ramifications of these principles are examined for a variety of stakeholders, including learners, educators, software developers, legislators, and educational administrators. The objective is to establish a worldwide consensus on ethical AIED procedures. According to the study, resolving FATE in AIEd-related concerns is critical as the system advances alongside individuals and specific circumstances. It advises encouraging participants to establish responsibility for AIEd systems in order to adjust them to local settings, which is where major FATE challenges emerge. This article introduces Explainable Artificial Intelligence (XAI)-Education (XAI-ED), a platform for researching, planning, and implementing educational AI applications. It focuses on six important areas of explainability: stakeholders, benefits, explanations presentation approaches, AI models, human-centered interface designs, and potential dangers. The framework is implemented in scenarios demonstrating how XAI-ED can be leveraged with various educational AI technologies. The study emphasizes the special need of XAI in education. The government's educational tactics should prioritize perpetual learning, teacher training initiatives, and data protection. Reciprocal relationships must be established to enhance academic-industry collaboration. Relevant conceptual frameworks must guide technological development and testing. A discussion amongst supporters of "cold" technology and "warm" individuals might result in to an improved awareness of how technology, particularly the big data growth and AI revolution, can provide fresh challenges and possibilities for pedagogical practices and learning.

Future schools, by utilizing the capabilities of artificial intelligence, will experience novel approaches in the teaching-learning process, student assessment, and educational management. The aim of this study was to design a model of the future school in which artificial intelligence plays a key role in enhancing learning processes and the management of primary schools. The research method was mixed; the statistical population in the design phase included faculty members from the fields of Computer Engineering - Artificial Intelligence, IT, Information Technology Management Engineering, and Educational Management at higher education institutions, as well as senior managers and experts from the Informatics Department of the Education System and specialists in the fields of "Future Schools" and "Artificial Intelligence in Education." In the validation phase, the population consisted of faculty members of Information Technology Management Engineering and Educational Management at higher education centers in Golestan Province, along with senior managers of the Education Department of this province. In the quantitative phase, the population included all formal and contractual teachers of girls’, boys’, and coeducational primary schools in Golestan Province during the 2023-2024 academic year, totaling 5,919 teachers. In the qualitative phase, 18 experts were selected using the snowball sampling method; in the validation phase, 20 experts were selected using purposive sampling; and in the quantitative phase, 361 teachers were selected using cluster random sampling and Cochran's formula. For data analysis, in the qualitative section, the grounded theory method was employed through open, axial, and selective coding using semi-structured interviews; in the validation phase, the Delphi method was used over three stages with an expert checklist tool and SPSS software; and in the quantitative phase, structural equation modeling was used with a 100-item questionnaire in Smart PLS software. According to the results of the qualitative and validation sections, the paradigmatic model included 12 main categories and 24 subcategories, detailed as follows: Causal conditions (cultural readiness for accepting artificial intelligence, artificial intelligence infrastructure, family-centered interaction with artificial intelligence, intra-institutional participation with artificial intelligence, active learning based on artificial intelligence, and effective learning based on artificial intelligence); Contextual conditions (enhancement of virtual networks with artificial intelligence, social interactions based on artificial intelligence, civic behavior regarding artificial intelligence, teaching-learning policies based on artificial intelligence, and cultural education focused on artificial intelligence); Intervening conditions (institutional conflicts regarding artificial intelligence, technical challenges concerning artificial intelligence, management and supervision in intelligentization, and resource dependency regarding artificial intelligence); Strategy (ease of access to artificial intelligence, assessment based on artificial intelligence, gradual implementation of artificial intelligence, creative learning through artificial intelligence, and content and process changes focused on artificial intelligence); and Outcomes (improvement of speed and quality of education through artificial intelligence, educational equity through artificial intelligence, academic motivation through the application of artificial intelligence, and enhancement of creativity and innovation through the application of artificial intelligence), along with 100 indicators. The results of the quantitative section showed that all dimensions and components of the research model were confirmed.

This study investigated teachers’ opinions on using artificial intelligence (AI) in education. The aim was to gain insight into teachers’ expectations, desires, and concerns regarding AI applications that will be used more frequently in education shortly. Teachers were consulted about the purposes for which AIs can be used in their lessons and the current level of AI utilization. A qualitative research method was used in the study. Data on the use of AI in education was collected through semi-structured interviews with teachers. The collected data was analyzed using content analysis. According to the findings, teachers believe AIs can be used for language learning, personalized education, and individual student tracking. All teachers participating in the study had a positive view of the use of AI in education. Moreover, most teachers think that AI applications will increase academic success; however, they expect AIs to be suitable for the student level, provide feedback to the student, and evaluate the teaching process. Participants, who stated that teachers also have responsibilities in using AIs, emphasized that teachers need to improve by receiving training on this subject. The study revealed teachers’ concerns about using AI, bringing these reservations to light. In the study’s conclusion, suggestions were made, such as the necessity of using AI in education and considering teachers’ concerns. It also addressed what needs to be done to promote the widespread use of AIs nationwide.

Artificial intelligence technology plays a decisive role in various spheres of life, including education. Modern preschools are faced with the need to adapt to the requirements of the modern world, where technology is a mandatory component. The article defines the regulatory and legal principles of using artificial intelligence technologies in the field of education. Based on the study and systematization of the results of scientific research, directions and methods of using artificial intelligence in the educational field have been identified. Scientific-pedagogical guidelines for the use of generative models of artificial intelligence in a preschool education institution are justified from the author's point of view. Modern possibilities of using artificial intelligence technology in the educational process of a preschool education institution are presented, in particular, the features of using artificial intelligence by parents of preschool children. Also, practical aspects of the use of artificial intelligence by specialists in a preschool education institution are proposed, in particular, ChatGPT, Quillbot, Google Gemini, Vocal Remover. The importance of the right approach to the implementation of artificial intelligence in the educational process to ensure efficiency and safety for children is emphasized. The results of the surveys of parents of preschoolers and specialists of preschool education institutions regarding the potential of using artificial intelligence in preschool education for the development of children are summarized, which requires a careful approach and cooperation between teachers, parents, and the administration of preschool education institutions. The use of artificial intelligence in preschool education is a promising direction that can provide support for preschool education specialists, make the learning process more interesting for children, and contribute to their intellectual development. Therefore, research and development of practices for the use of artificial intelligence in preschool education is an important component of the effective implementation of these technologies.

The application of artificial intelligence in education is one of the focal research today. Researchers have discovered that with the continuous development of artificial intelligence, various artificial intelligence are being utilized in primary and secondary education. However, many issues in this field still lack a unified explanation and understanding. Therefore, the research theme of this paper focuses on the advantages and challenges of using artificial intelligence in education. Based on an analysis of relevant literature and survey data, this study explores the advantages and challenges of artificial intelligence in education. The research findings indicate that artificial intelligence can provide personalized education, offer abundant educational resources for teachers and students, and provide timely feedback on student progress. Thus, enhancing learning outcomes. However, the application of artificial intelligence in education still faces challenges such as funding limitations, inadequate policy support, privacy concerns, varying levels of teacher acceptance, and a lack of standardized curriculum. Nevertheless, the use of artificial intelligence in education holds tremendous potential. In the future, it is necessary to formulate policy and standardization at the national level and address issues such as information security and privacy protection to promote the comprehensive application and development of artificial intelligence in education.

The integration of artificial intelligence in education is a significant advancement that fundamentally transforms education delivery and reception. Artificial intelligence relies on technologies like machine learning and big data analysis to offer customized and interactive learning experiences. Analyzing students' performance and providing individualized advice may improve their knowledge. Artificial intelligence (AI) may also enhance the creation of cutting-edge educational materials using technologies like augmented and virtual reality, making the learning experience more engaging and interesting. Nevertheless, further comprehensive research is necessary to fully understand the lasting impact of AI approaches on student learning results. In order to address this deficiency, the present work proposes a novel strategy that integrates bibliometric analysis with systematic literature review (SLR) utilizing the PRISMA methodology. The first stage focused on a comprehensive bibliometric, which included key nations, educational establishments, publications, keywords, and influential authors in the realm of artificial intelligence in education. This phase facilitated a comprehensive understanding of the overall state of this field across different disciplines. The subsequent phase was a systematic literature review (SLR) of 12 specifically chosen scholarly articles. This review focused on the current use of artificial intelligence (AI) in education. This review also examined the impact of implementing artificial intelligence (AI) in education, specifically focusing on its influence on student motivation and the desire to learn.The present study aims to implement artificial intelligence (AI) technology in education and explore strategies for achieving sustainable education for future generations.

The article examines current trends and prospects for the implementation of artificial intelligence (AI) technologies in educational processes. The authors analyze various aspects of the use of AI, such as individualized learning, automated assessment of knowledge, the creation of intelligent educational platforms and personalized educational plans. The article also analyzes the ethical and social issues associated with the use of artificial intelligence in education and offers recommendations for the development of effective strategies for integrating technology into educational systems. Overall, the article seeks to shed light on the role of artificial intelligence in modern education and its potential in improving the quality of learning and developing educational practices.

This research paper offers the findings of a survey on much less researched regions of distance learning and studies during challenging situations for better schooling, all through the early COVID-19 pandemic (March-June 2020). The detailed assessment of Artificial Intelligence (AI) in education, the use of AI in education, typical learning in the pandemic era, and the role of artificial intelligence in disease outbreak learning, are all important for both current and future residents, according to the findings. In the week of May 28 to June 2, whilst many academic institutions throughout the United States had been in their term, 80% of parents residing with youngsters stated that their beginners had made the use of online assets while in lockdown. Prevailing situations and strain are associated with gaining knowledge during epidemics, in addition to a dyslexia prognosis. Results of the Household Pulse survey display that low-earning families now no longer get the right of entry to online instructional assets for distance learning on the equal fee as the better-earning families.

Today, artificial intelligence has penetrated all areas of human activity, including its technologies being actively implemented in the educational process. This article is devoted to issues related to the implementation of artificial intelligence in higher education. The purpose of this work was to determine the prospects and features of using artificial intelligence in the educational process of higher education. The novelty of the study lies in a comprehensive analysis of the areas of artificial intelligence use, its capabilities, risks, and limitations. The research methodology is based on a systems approach using theoretical and experimental methods. The article provides a brief analysis of the work of foreign and Russian researchers on the application of artificial intelligence. As part of the theoretical stage of the study: the main areas of artificial intelligence use are identified, which are systematized into three groups (educational process management, educational process organization, teacher optimization); the content and key benefits are determined for each group; the risks and limitations of using artificial intelligence in education are identified (technical, pedagogical, ethical, social and economic, legal). The experimental portion of the study involved conducting a survey among students and faculty at higher education institutions in the Trans-Baikal Territory and analyzing the results to determine the extent of artificial intelligence implementation in higher education and assess its impact on the educational process. The study demonstrated the need for careful implementation of artificial intelligence in higher education, maintaining a balance between technology and the human factor. Prospects for further research may include developing methods for the effective use of artificial intelligence in higher education.