The impact of artificial intelligence on students’ academic development, critical thinking, cognitive skills, and learning outcomes

This study explores the implementation of artificial intelligence (AI) in an educational context and its impact on data-driven decision-making related to student engagement, academic success, and creativity. Contextually, considering the necessity of utilization AI tools in education as a predominant factor in educational practice, this research provides full-fledged knowledge and approach on the overall implementation and significance of AI tools using hypothetical situation evidence (background materials), which are required to understand their prominence. We use a mixed-methods approach, combining quantitative analysis of institutional records and surveys capturing student engagement, academic performance and innovative thinking pre-post AI implementation with qualitative case studies which provide detailed insights into how AI tools can be implemented effectively in educational settings. This study is based on secondary data source, major publications available in the Scopus database related to AI in education. Search terms for data search were "Artificial Intelligence in Education," "AI-driven tools," "Impact of AI on classroom dynamics", "Personalized learning", "Educational technology, AI, and creativity in education", Critical thinking in the classroom, Adaptive learning systems), intelligent tutoring systems)." Student engagement. The results demonstrate significant gains in multiple metrics, with engagement scores increasing by 20–23%, GPA from 9% to 14%, and innovative thinking skills levels swelling from 44% to 57%. About 65%-75% of teacher surveys indicated a positive impact of AI on teaching and learning. The study also notes constraints including confounding whereby the inability to control for factors that may affect odds of innovative thinking and conceptualization in measuring innovative thinking. This is role, it should also advocate for longitudinal inquiries, establish standardized ways of assessing, and be analytical about the ethical implications raised by AI in education. Overall, this study underscores that AI has considerable potential to improve educational achievement and the necessity of systematic research in order to actualize its benefits. This study reinforces the possibility of AI making a big difference in improving educational results. As such, it illuminates the importance of systematic investigations into AI´s function in education to obtain full knowledge on how best to take advantage.

This research aims to critically examine the ethical integration of artificial intelligence (AI) in education through the perspective of maqāṣid al-sharīʿah, emphasizing the alignment between technological innovation and Islamic moral principles. The methods used are a systematic literature review and thematic content analysis against peer-reviewed publications for the period 2015–2025, which discuss the application of AI in primary, secondary, and higher education. The study identified dominant ethical issues, such as data privacy, algorithmic bias, accountability, human agency, and moral development, which were then mapped to Islamic ethical goals, including ʿadl (justice), amānah (belief), karāmah al-insān (human dignity), and ḥifẓ al-ʿaql (protection of reason). The results of the analysis show that the adoption of AI in education often emphasizes efficiency, personalization, and predictive analytics, but has the potential to reduce learners' autonomy and ethical reasoning. The mapping of maqāṣid al-sharīʿah shows a strong normative conformity, so that Islamic principles can be a moral foundation as well as a practical guide for AI governance. The research contribution is theoretical by bridging the literature on AI ethics and Islamic educational philosophy, as well as practical by offering an integrative framework for AI policymakers, educators, and developers. The integration of maqāṣid al-sharīʿah in AI governance ensures justice, trust, inclusivity, and the development of the whole human being (insān kāmil).

Artificial Intelligence (AI) tools are constantly being released into the public domain. As with all new technological innovations, this brings a range of opportunities and challenges for education: primarily for educators and learners. There is an increasing interest in the academic community and beyond to use Artificial Intelligence in Education (AIED) to generate content. This presents opportunities and challenges for academic and research integrity. The European Network for Academic Integrity (ENAI) is an international association gathering educational institutions and individuals interested in maintaining and promoting academic integrity. As the use of AI tools may not always be consistent with academic integrity, we consider it important to familiarise all education stakeholders with how to use AI tools responsibly and in accordance with academic integrity practices and values. ENAI presents a set of recommendations with the aim of supporting academics, researchers and other educational stakeholders, including students' organisations, on the ethical use of AI tools. The recommendations focus on the importance of equipping stakeholders with the skills and knowledge to use AI tools ethically and the need to develop and implement relevant educational policies addressing the opportunities and challenges posed by AIED. To create these recommendations, we used our experience and knowledge, both about AI, and academic integrity. The authors collectively drafted the main structure and main ideas of the recommendation. The draft was circulated to the ENAI working group members, most of whom provided valuable comments and suggestions. Then the authors incorporated the comments and prepared the final wording of the document. The field of artificial intelligence is advancing fast, and the ways that it disrupts education are changing from one week to the next. We consider these recommendations as a working document, and we invite everyone to provide feedback. There will be a special session at the European Conference on Ethics and Integrity in Academia 2023 in Derby, UK, dedicated to this document.

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.

Introduction. The article addresses the problem of widespread use by students of conversational artificial intelligence technologies to substitute their own statements and conclusions with artificially generated texts. This issue plays a crucial role in language education due to the specifics of learning conditions and competencies being developed. The aim of this study is an attempt to systematize and substantiate ways to mitigate negative consequences under the spread of artificial speech activities.Materials and methods. To achieve this goal, various scientific research methods are employed: analysis and synthesis of scholars' works on issues related to student-teacher interaction with artificial intelligence tools, regulation and control over the use of such tools by foreign language learners at different educational levels; summarizing vulnerability points of such interactions concerning language education; modeling the educational process for teaching a foreign language while compensating for identified weaknesses through pedagogical means; pedagogical experiment. The methodology of the study was based on the work of Russian and international scientists in the field of problems and prospects of artificial intelligence in education (K. M. Belikova, P. G. Bylevsky, P. V. Sysoev, N. V. Tikhonova, A. V. Fedorov, and others).Results. Analysis and synthesis of scholarly literature on the peculiarities of applying artificial intelligence in education revealed five vulnerable aspects of this process: data obsolescence (delay) upon which text generation is based; data falsification; lack of depth and superficiality in neural network-generated responses; need for detailed prompts; bias and subjectivity. These findings allowed us to outline concrete directions towards solving the plagiarism problem in linguistic education: shifting from continuous texts toward new forms of speech products; reliance on consciously formed strategies of foreign language speech activity so that the process of creating a speech product becomes more important than its result; development of critical thinking and enhancement of cultural components in foreign language instruction using comparative and contrastive analysis methods; step-by-step reflection not only on outcomes but also on the entire cognitive process; strengthening the cognitive component throughout the language learning process.Discussion and conclusions. Research findings can be extrapolated to other areas of higher education. There arises a question about continuing the scientific search for effective solutions to the problem of student plagiarism. The authors call on psychologists, philosophers, and culturologists to join the academic discussion on the ethical, moral, and motivational aspects of addressing the negative effects of introducing new technologies into the sphere of education.

Artificial Intelligence (AI) is revolutionizing the field of health sciences, reshaping how we teach, learn, and practice medicine. As AI technologies become increasingly integrated into healthcare systems, their impact on health sciences education cannot be overstated. From personalized learning experiences to advanced diagnostic training, AI is poised to enhance the quality and accessibility of education for future healthcare professionals. However, this transformation also raises critical questions about ethics, equity, and the future role of educators in an AI-driven world. The transformative role of Artificial Intelligence (AI) in health sciences education is increasingly recognized as a pivotal factor in shaping the future of medical training and practice. As AI technologies continue to evolve, their integration into educational curricula presents both opportunities and challenges that must be carefully navigated to enhance the learning experience for future healthcare professionals. One of the most significant contributions of AI to health sciences education is its ability to personalize learning. Traditional teaching methods often follow a one-size-fits-all approach, which can leave some students struggling to keep up while others are not sufficiently challenged. AI-powered platforms, such as adaptive learning systems, analyze individual student performance and tailor content to meet their unique needs. For example, tools like Osmosis and AMBOSS use AI to provide customized study plans, ensuring that students focus on areas where they need the most improvement (Topol, 2019). This personalized approach not only improves learning outcomes but also fosters a more inclusive educational environment. AI is also transforming clinical training by simulating real-world scenarios. Virtual patient simulations, powered by AI, allow students to practice diagnosing and treating conditions in a risk-free environment. These simulations can replicate rare or complex cases that students might not encounter during their clinical rotations. For instance, platforms like Touch Surgery and SimX use AI to create immersive surgical and emergency care simulations, providing students with hands-on experience before they enter the operating room (McGaghie et al., 2011). Such tools bridge the gap between theory and practice, preparing students for the complexities of modern healthcare. Moreover, AI is enhancing the role of educators by automating administrative tasks and providing data-driven insights into student performance. Grading, attendance tracking, and even curriculum design can be streamlined using AI, allowing educators to focus on mentoring and engaging with students. AI-driven analytics can also identify at-risk students early, enabling timely interventions to support their academic success (Wartman & Combs, 2018). By augmenting the capabilities of educators, AI empowers them to deliver more impactful and student-centered teaching. AI's potential to revolutionize health sciences education lies in its ability to personalize learning experiences and improve educational outcomes. For instance, AI-driven tools can facilitate realistic simulations and automated assessments, allowing students to engage in practical scenarios that mimic real-world clinical situations (Santos & Lopes, 2024). This capability not only enhances the learning process but also prepares students for the complexities of patient care in a technology-driven environment (Grunhut et al., 2022). Furthermore, the incorporation of AI into curricula can foster critical thinking and decision-making skills, essential for navigating the ethical dilemmas that arise in medical practice (Grunhut et al., 2022). Despite the promising applications of AI in education, the integration of these technologies into medical curricula has been slow. A scoping review highlighted that many medical schools have yet to adopt AI training, primarily due to a lack of systematic evidence supporting its implementation (Lee et al., 2021). Additionally, concerns regarding data protection and the ethical implications of AI use in healthcare education have been raised, indicating a need for comprehensive AI education that addresses these issues (Veras et al., 2023; Frehywot & Vovides, 2023). Students have expressed a desire for more robust training in AI, emphasizing the importance of understanding its role in healthcare delivery and decision-making processes (Ahmad et al., 2023; Derakhshanian et al., 2024). Moreover, the rapid advancement of AI technologies necessitates continuous curriculum updates to keep pace with emerging trends. As noted in recent literature, the integration of AI into biomedical science curricula should include subjects related to informatics, data sciences, and digital health (Sharma et al., 2024). This approach not only equips students with the necessary skills to utilize AI effectively but also prepares them for the evolving landscape of healthcare, where AI will play an integral role in diagnostics, treatment personalization, and patient management (Santos & Lopes, 2024; Secinaro et al., 2021). However, the implementation of AI in health sciences education is not without challenges. Ethical considerations surrounding AI's impact on healthcare equity and the potential for bias in AI algorithms must be addressed (Frehywot & Vovides, 2023; Han et al., 2019). Ensuring that AI technologies are used responsibly and equitably in education and practice is crucial to avoid exacerbating existing disparities in healthcare access and outcomes (Rigby, 2019). Furthermore, the lack of faculty expertise in AI poses a significant barrier to its integration into medical education, highlighting the need for targeted training and resources for educators (Derakhshanian et al., 2024). However, the integration of AI into health sciences education is not without challenges. Ethical concerns, such as data privacy and algorithmic bias, must be addressed to ensure that AI tools are used responsibly. Additionally, there is a risk of over-reliance on AI, potentially undermining the development of critical thinking and clinical judgment skills. Educators must strike a balance between leveraging AI’s capabilities and preserving the human elements of teaching and learning. Equity is another pressing issue. While AI has the potential to democratize education, access to these technologies remains uneven. Institutions in low-resource settings may struggle to adopt AI-driven tools, exacerbating existing disparities in global health education. Policymakers and educators must work together to ensure that the benefits of AI are accessible to all, regardless of geographic or socioeconomic barriers. In conclusion, AI is a powerful tool that holds immense promise for transforming health sciences education. By personalizing learning, enhancing clinical training, and supporting educators, AI can help prepare the next generation of healthcare professionals to meet the demands of an increasingly complex healthcare landscape. However, its integration must be guided by ethical principles and a commitment to equity, However, the successful integration of AI into educational curricula requires a concerted effort to address ethical concerns, update training programs, and equip both students and faculty with the necessary knowledge and skills. As the healthcare landscape continues to evolve, embracing AI in education will be essential for fostering a new generation of healthcare providers who are adept at leveraging technology to improve patient care. As we embrace this technological revolution, we must remember that AI is not a replacement for human expertise but a complement to it. The future of health sciences education lies in the synergy between human ingenuity and artificial intelligence.

The article examines the problems of developing critical thinking of future teachers of computer science and mathematics using artificial intelligence tools. The experience of domestic and foreign researchers regarding the use of artificial intelligence in education for the development of critical thinking, in particular, the United States of America, the Republic of Poland, and the Republic of Slovenia, was analyzed. The necessary components of critical thinking are defined: the use of logical thinking to analyze problems, make decisions and solve problems; obtaining, interpreting and using knowledge/facts/data in the process of solving problems; demonstration (manifestations) of creativity and non-standard thinking. In order to investigate the specifics of the application of critical thinking skills by future teachers of computer science and mathematics when working with artificial intelligence systems, a survey was conducted. The "Klochko Questionnaire: Peculiarities of using critical thinking skills by future teachers of computer science and mathematics when working with artificial intelligence systems" was created. The possibilities of using artificial intelligence tools in education have been clarified, in particular: analysis of educational data, creation of educational content, professional development, adaptive learning, and others.The results of the study showed that 92.2% of respondents use or plan to use artificial intelligence tools in the educational process. The vast majority of students studying to become computer science and mathematics teachers actively use artificial intelligence to solve various problems, applying critical thinking and developing their critical thinking skills. The development of critical thinking skills of future computer science and mathematics teachers is a necessary condition for their academic success, personal and professional development, competitiveness, preparation for future challenges, solving new problems, teaching students to think critically. The implementation of artificial intelligence tools for the development of critical thinking in future teachers may have certain risks, such as excessive trust in artificial intelligence and the reduction of the role of one's own experience, intuition, etc. It is important to note that the field of using artificial intelligence technologies in education is just beginning to develop and needs additional research, however, it has great potential for the development of critical thinking of future teachers.

The way we teach and learn could be completely transformed by artificial intelligence (AI), which could make the process more efficient, personalized, and interesting. Artificial intelligence (AI) in education is the application of AI technologies, like natural language processing and machine learning, to improve the educational process. Through the use of algorithms, teachers are able to customize learning for each student by analyzing data, finding trends, and making predictions. Artificial intelligence (AI) and its potential impact on education have gained widespread attention because of ChatGPT's impressive performance on standardized academic assessments. For the development and implementation of AI-driven technologies in schools, colleges, and universities to be sustainable, a thorough knowledge of their effects on the current educational system is needed. The application of AI in education has a lot of potential advantages. One of the biggest benefits of AI in education is personalized learning, which allows students to learn at their own pace and in a fashion that best fits their learning preferences. This can improve student results. Chatbots, automated grading and evaluation, and intelligent tutoring systems can boost productivity, free up teachers' time, and deliver more precise and consistent feedback. Some of the challenges that need to be resolved are potential bias, cost, lack of confidence, and privacy and security concerns. AI can improve data analysis, empowering teachers to make facts-based decisions. There are some impacts of artificial intelligence in educational system that are covered in this review. These are the applications of artificial intelligence in automated assessment, intelligent tutoring systems, personalized learning, and collaborative teacher-student learning.

The article analyses the prospects, risks and benefits of using artificial intelligence in higher education. The author considers the state and prospects of artificial intelligence development, substantiates the importance of studying this issue and the need for further research on the impact on academic integrity, quality and learning outcomes. The purpose of the article is to study and analyse ethical and philosophical issues related to the use of artificial intelligence in higher education. Objectives of the study: 1) to analyse the impact of artificial intelligence on teachers, higher education students and the educational system as a whole; 2) to identify the potential benefits and risks of using artificial intelligence in higher education; 3) to consider ethical issues related to the use of artificial intelligence in the educational process and research; 4) to propose recommendations for the responsible use of artificial intelligence in higher education. The methods of general philosophical analysis were used to summarise and systematise the research results. It is considered that digital technologies are actively used in higher education. It is noted that this leads to positive trends, in particular, personalized training courses and methodological material adapted to their characteristics are offered to students. Artificial intelligence can significantly automate the development of technical specifications, teaching materials for the educational process, simplify document management. The risks that arise when using artificial intelligence are also noted, namely, confidentiality issues, lack of responsibility, non-compliance with the principles of academic integrity. To prevent and mitigate risks, it is necessary to adhere to the principles of transparency, confidentiality, social responsibility and prevention of harm to humans. All of this requires bringing legislation on the use of artificial intelligence in line with international standards, and for educators, rethinking not only the system of knowledge assessment and control of students, but also the entire paradigm of teaching methodology in higher education.

The accelerated diffusion of artificial intelligence (AI) tools in management education research presents both strategic opportunities and ethical challenges for business schools and higher education institutions. Even as AI applications promise enhanced analytical efficiency and research productivity, concerns regarding academic integrity, critical thinking development, and data confidentiality complicate their integration. Despite these tensions, empirical evidence explaining and predicting satisfaction with AI tools among management education researchers remains limited. Existing studies have focused largely on conceptual frameworks, ethical implications, often relying on student samples or cross-sectional studies. Consequently, little is known about the specific determinants of AI satisfaction among researchers. To address this gap, the present study investigates the determinants of user satisfaction with AI technologies within a management education context and develops a predictive framework to inform institutional decision-making. The study, based on a sample of 260 respondents, examined 9 key constructs. The Random Forest (RF) model was trained by running the bagging procedure on a dataset, and its performance was validated using out-of-bag error estimation to assess predictive accuracy. Structural Equation Modelling (SEM) findings reveal that perceived ease of use significantly enhances perceived usefulness, which in turn drives satisfaction with AI tools. Ethical concern attitudes are negatively associated with perceived usefulness, underscoring the managerial and pedagogical trade-offs inherent in AI adoption within business schools. The RF model complements the explanatory analysis by demonstrating strong predictive performance (R² = 0.73) and identifying perceived ease of use, access to AI technologies, and perceived usefulness as the most influential predictors of satisfaction. The convergence of theory-driven and machine learning results enhances the robustness and practical relevance of the findings. By integrating explanatory and predictive modelling, this study contributes to management education literature on digital transformation and responsible innovation. The findings offer actionable insights for business school leaders, curriculum designers, and policymakers seeking to support ethically-grounded, strategically-aligned AI integration in management research and education.

Introduction: Artificial Intelligence (AI) is reshaping education by facilitating adaptive, personalized, and data-informed learning experiences. Through intelligent tutoring systems, predictive analytics, and AI-powered feedback mechanisms, educators can tailor instruction to meet diverse learner needs while enhancing efficiency and engagement across both traditional and digital learning environments.Objective: this study aims to examine the effective use of artificial intelligence (AI) in education for promoting personalized learning, while upholding key ethical standards. Method: A short communication methodology was employed to synthesize recent developments in AI applications in education. Relevant literature published between 2018 and 2025 was identified through searches of databases including PubMed, Scopus, ResearchGate, and Google Scholar. Studies were selected based on criteria related to the use of AI in personalized learning, assessment, instructional design, and administrative automation. Data were thematically analyzed to evaluate the benefits, implementation strategies, and challenges associated with AI integration.Results: AI-driven tools were found to significantly enhance educational outcomes by enabling proactive (e.g., curriculum design, predictive enrollment analysis) and reactive (e.g., real-time tutoring, automated grading) engagement. Platforms like adaptive learning systems, intelligent tutoring tools, and AI-driven assessment software have enabled personalized learning experiences and eased administrative tasks. However, significant challenges persist, including concerns over data privacy, algorithmic bias, digital literacy gaps, and unequal access to technological infrastructure.Conclusion: AI technologies hold substantial promise in creating more personalized, inclusive, and effective educational ecosystems. By streamlining teaching processes and supporting learner-centered models, AI enhances both pedagogical impact and academic performance. However, ethical concerns and infrastructural barriers must be addressed to ensure responsible and sustainable adoption. Future efforts should focus on aligning AI development with equity, transparency, and accessibility 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 given systematic analysis reviews 40 articles published in 2015-2025 to discuss the examine the evolution, applications, and challenges of artificial intelligence (AI) in education, specifically in the bi/multilingual learning settings. The review relies on empirical and theoretical study and provides identification of the three major domains, including personalized learning, intelligent tutoring systems and chatbots, and automated assessment. The research results demonstrate that AI improves student engagement and learning performance and teaching efficiency due to the adaptive feedback and real-time analytics, particularly when used to support multiliteracy language learning practices. There are, however, major issues of concern that data privacy, algorithmic bias, unequal access, and the disappearance of relational and cultural facets of teaching and learning. The review highlights the empathy gap in the AI tools and demands the incorporation of AI into the mainstream in an inclusive, ethically based and linguistically responsive manner. It promotes the change in automation to intelligence augmentation and places AI at the service of educators offloading them with fair, human-centered, and AI assistive tools in multilingual learning students in English-dominant settings. The implications refer to the imperative to provide strong governance structures, human centered training of teachers in which AI serves as an addition to intelligence and not intelligence, and inclusive design to provide equitable and effective AI integration and to provide a balanced innovation with a focus on human-centered learning.

Today, the problem of using artificial intelligence (AI) in education is essential. Recent studies have detected several challenges in using AI for correct assessment, academic integrity, etc. So, the problem of finding positive practices for using AI in education needs to be studied more closely. We perceive ChatGPT as a digital tool for teacher training, which makes it possible to simulate students' problem-solving process and analyze it critically. It is shown that ChatGPT makes mistakes in solutions, so the generated false answers become an essential training tool in teacher training. It became the base for experimental teaching. The research aims to substantiate the effectiveness of using ChatGPT as a simulation environment to develop pre-service teachers' critical thinking. The statistical analysis of the experiment results proved that ChatGPT is an effective digital tool for developing mathematics and computer science teachers' critical thinking.

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.