Revisiting Techno-Optimism

Artificial Intelligence (AI) has rapidly emerged as a transformative force across diverse sectors worldwide, with policy initiatives signalling its rising prominence. In the realm of education, AI holds promise for revolutionising learning and teaching. However, the incorporation of AI in basic education faces significant challenges for many schools, particularly when explicit curriculum guidelines are absent, and teachers have limited exposure to AI technologies. This study delves into the importance of integrating Artificial Intelligence in Education (AIED), particularly in primary and secondary school settings, with a specific emphasis on the obstacles and facilitators. The research examines the impact of digital leadership and its role in mitigating teachers' barriers to AIED incorporations. These external variables are systematically outlined within the conceptual framework proposed by this study. Furthermore, it conceptualises and considers three AIED approaches—Learning from AI, Learning about AI, and Learning with AI—as internal variables central to basic-education AIED incorporations, as highlighted in previous research. The study gathers quantitative data through a self-constructed questionnaire survey from 204 school principals and management-level teachers across 60 primary and secondary schools in Hong Kong, capturing their perceptions of AIED incorporation. A structural equation model (SEM) is adopted to analyse the relationships between digital leadership, internal and external teacher barriers, and the three AIED approaches. The findings underscore that digital leadership is a significant factor in facilitating AI incorporations in schools, and that teachers' internal and external barriers considerably affect Learning about AI. The paper concludes by proposing strategies to enhance the capabilities of school leaders and teachers in promoting AIED in basic education.

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 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 purpose of the study is to develop a model of a hybrid intelligent educational environment according to the intellectual partnership between humans and artificial intelligence, based on an analysis of the practice of using artificial intelligence in school and university education. To achieve this goal, it was necessary to solve the following tasks: to assess the opinions of participants in educational relations about the use of artificial intelligence in education, the associated threats and opportunities; to identify the features of using artificial intelligence in higher education; and to develop methodological approaches to forming an intellectual partnership between students and artificial intelligence as the basis for a model of a hybrid intelligent educational environment. Materials and methods. The study used a range of methods, including inductive-deductive, statistical and comparative analysis, modeling, and visualization of graphical data.The information base was compiled from scientific publications, materials of the All-Russian Public Opinion Research Center, research results of the scientists of the Higher School of Economics, open sources of the Internet. Results. The integration of artificial intelligence into the educational environment is accompanied by a number of problems (technological, social, psychological, ethical), which requires the management of educational organizations to take them into account when creating a new pedagogical ecosystem, in which artificial intelligence acts as a new tool of the educational process. An analysis of the parental community’s opinions regarding the use of artificial intelligence in children’s education revealed diverse assessments: while acknowledging the high educational potential of the technology, there were also concerns about the associated threats, with the main concern being the potential decline in the quality of knowledge. The article identifies the broad opportunities for using artificial intelligence by students and teachers in school and university education. It also highlights the fundamental differences in the use of artificial intelligence in higher education, which are related to the depth and complexity of solving scientific and educational tasks. The article proposes methodological approaches to creating an intellectual partnership between students and artificial intelligence, aimed at preventing the passive use of technology that leads to intellectual stagnation. The model of a hybrid intellectual educational environment is developed, which requires not only the modernization of technological infrastructure, but also pedagogical and cultural transformation based on ethical principles. The tasks have been formulated to train new qualified personnel who can use artificial intelligence technology as a tool for their professional activities. Conclusion. In the era of unprecedented growth in technological achievements and the widespread and deep penetration of artificial intelligence into all areas of life, including the educational environment, the modern education system is in the process of reevaluating the role and place of artificial intelligence in the learning, development, and upbringing of young people. Recognizing the need to adapt to new technological trends, educational organizations are carefully assessing the potential and threats associated with the implementation of artificial intelligence in the educational process, as well as evaluating their own resources to implement the concept of “collaborative intelligence”, which combines human and artificial intelligence. The intellectual partnership of participants in educational relationships with artificial intelligence has a high potential for solving pedagogical tasks: artificial intelligence, by solving routine tasks, frees up the teacher for creative work, emotional support, and the development of new methods for forming meta-cognitive competencies among students; artificial intelligence expands scientific and educational opportunities for students in a proactive position of using technology.

The purpose of the study is to predict possible trends in the impact of generative artificial intelligence, in particular ChatGPT technologies, on education. Predictive estimates are formed on the basis of expert discussions of the consequences of using these digital technologies in education, which are currently going on in the public space and in the scientific community. The main groups of expert opinions and scientific approaches are being identified and compared, which makes it possible to present a perspective vision of the processes of integrating generative artificial intelligence into education. Analysis and forecasting are mostly carried out on the example of the practice by using generative artificial intelligence in higher education, however, the main provisions and conclusions can be extrapolated to other levels of education.Materials and methods. In the course of the study, methods of qualitative analysis of expert opinions presented in the public space (in the media, social networks, on the websites of educational organizations and analytical agencies, in public speeches), as well as methods of meaningful analysis of scientific publications, were used. Grouping and classification of expert opinions and scientific approaches were carried out. The analysis also used the results of a sociological study conducted by means of online survey of students from the Plekhanov Russian University of Economics on a sample of more than 3 thousand people. Methods of social forecasting were used to form predictive estimates.Results. The analysis made it possible to conclude that public discourse on employing generative artificial intelligence in education is controversial. Five groups of expert opinions were identified regarding the impact of generative artificial intelligence on education, which differ as to the need for its use in educational organizations and the scope of educational transformations that can occur under its influence. The analysis of scientific discussions showed that scientific community has not finally determined the consequences of the practical impact of generative artificial intelligence on the field of education. At the same time, possible promising areas and problem areas of its use are being identified, as well as its potential to initiate new reforms in education. The following possible trends in the integration of generative artificial intelligence into education are predicted: gradual change in the paradigm of education towards creativity-oriented education; increase of the share and scope of using artificial intelligence technologies in education; formation of new legal and ethical standards governing the use of generative artificial intelligence in education; increasing the importance and changing the role of the lecturer.Conclusions. Generative artificial intelligence has all the potential for solving long-term tasks of developing education. However, rapid technological development is inevitably associated with numerous risks, which require the creation of a methodology for using generative artificial intelligence in education, improvement of regulatory framework and solution of ethical problems. A new qualitative level of integration of a human being and artificial intelligence in the educational sphere is the thing of the future. Such integration will contribute to improving the quality of human capital in line with rapidly developing technologies of 5.0 Industrial Revolution.

In order to guide the effective application of artificial intelligence (AI) in education (AIEd), China has set up a number of national AI education demonstration areas (AIEDA). Teachers in this AIEDA have carried out action research about AIEd for over two years. For the purpose of assessing teachers’ intelligent teaching preparation during the process, we conducted consecutive two years of evaluation through questionnaires and AI-based teaching platform data. This study developed a questionnaire of teachers’ intelligent teaching preparation, including teachers’ perception of and behavioral intention to AIEd, AI technological pedagogical and content knowledge (TPACK), and AI ethics knowledge. Besides, the data obtained from an AI-based teaching platform were analyzed, which indicated teachers’ acceptance and trust towards AIEd. A total of 101 valid samples of English as a foreign language (EFL) teachers participated in data collection for two years. The results showed that teachers’ trust in AIEd increased, but their effort expectancy and perception of facilitating conditions of AIEd decreased; Teachers’ AI ethics knowledge increased, while their self-report TPACK decreased.

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 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.

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.

The current study aims to reveal possible opportunities for applying artificial intelligence in higher education, and to identify the most important challenges that such application faces and the maximum benefits that can be acquired from employing artificial intelligence techniques in developing the educational process and the educational services in higher education institutions. This study followed the descriptive analytical approach in addressing the topic of applying artificial intelligence in higher education by reviewing the literature and previous studies that addressed this topic. The study concluded that it is possible to benefit from the application of artificial intelligence in higher education in the fields of teaching, learning, administration, research, and others, if the requirements of this application are dealt with effectively and the facilities that support the use of artificial intelligence techniques are provided. The study recommends confronting the challenges that weaken the effectiveness of the application of artificial intelligence in higher education. The most important challenges in this regard are: the lack of educational policies related to the application of artificial intelligence in education, the weakness of the infrastructure needed to supports the use of artificial intelligence techniques, the need to train academics and learners on how to deal with new applications, and the lack of due awareness of the importance of artificial intelligence applications and its role in developing higher education. KEY WORDS: artificial intelligence, higher education, opportunities, challenges, foreseeing the future

In order to explore the maturity of online concerts and the digital content of music resources, this article analyzes the role of artificial intelligence in music education, discusses the application of artificial intelligence in music education and the development trend of artificial intelligence in education, and studies the quality of vocal music teaching based on artificial intelligence technology. In this paper, ARM and SA algorithms, as well as internal and external probability algorithms, are combined for research and analysis. Through this study, the authors show that human intelligence skills have a certain impact on vocal music teaching, with an impact rate of 56.42%. It can be seen that artificial intelligence can directly optimize the level of music teachers and promote the improvement of teachers' teaching quality and efficiency. This article improves the effective understanding of artificial intelligence in music education and strengthens the scientific and rational application of artificial intelligence in education.

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.

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.

This paper aims to explore the characteristics and challenges of Artificial Intelligence (AI) education in the liberal arts curriculum of domestic universities. The revision of the curriculum to strengthen digital literacy has been in the field of the liberal arts in major universities. However, universities haven’t been aligning their curriculum with the core competencies developed in earlier stages. This has resulted in a disconnect occurring between AI education at the primary/secondary level and the university level. This gap can lead to students struggling to advance in AI-related topics as they transition to higher education. The liberal arts education of universities does not consider or reflect any linkage with the coherent system of the national curriculum, such as the 2022 revised national curriculum, of primary and secondary schools, which prevents the progress of students’ learning agency. For example, universities should take steps to open and run AI-related courses, regardless of government-supported projects, such as software (SW)-centered university projects. In fact, these project-based courses have not successfully addressed the need for a comprehensive AI and digital literacy education within the liberal arts. This paper, therefore, makes the following suggestions. Firstly, the liberal arts curriculum for AI education should restore its essence of humanity, preparing students to critically assess both the benefits and risks of AI in experiencing the digital transition. Secondly, universities should open and support AI-related courses in the liberal arts, ensuring that lecturers and professors receive the necessary resources to teach comprehensive AI education effectively.

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.