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How AI shapes student agency and educational stratification: a qualitative interpretive meta-synthesis

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Abstract
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Existing research on artificial intelligence in education has largely addressed technical applications and learning outcomes while leaving sociological dimensions of AI-mediated stratification and student agency inadequately theorised. Drawing on Bourdieu's cultural capital framework, digital divide scholarship, and Yosso's Community Cultural Wealth model, this qualitative interpretive meta-synthesis examines how AI-mediated learning environments interact with established stratification mechanisms and transform student agency. Systematic searches across Scopus, Web of Science Core Collection, and ERIC identified five qualitative and mixed-methods studies encompassing 3,849 students across the United States, Norway, Israel, and China; thematic analysis followed Braun and Clarke's framework with four-analyst triangulation. Five mechanisms emerged through which AI technologies simultaneously reproduce traditional educational inequalities while generating alternative stratification forms: cultural capital mobilization through resistant, communal, and creative capital; differential engagement patterns across four distinct agency expressions; digital divide persistence and evolution; trust calibration in human-AI interaction; and educational equity implications with career dimensions. Students from underserved communities demonstrated sophisticated algorithmic bias recognition, yet gender-differentiated engagement patterns and socioeconomic disparities indicate emergent stratification with professional consequences. Lower AI trust paradoxically correlated with stronger educational outcomes, tentatively suggesting that healthy skepticism promotes more agentic learning relationships. These findings indicate that AI-mediated stratification operates through qualitative differences in how students position themselves relative to algorithmic systems and mobilize cultural resources, rather than through differential access alone, with implications for how educational institutions conceptualise equity-oriented AI integration.

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  • Cite Count Icon 1
  • 10.21303/2504-5571.2024.003663
Research of the global higher education market and of the use of artificial intelligence in this field
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  • EUREKA: Social and Humanities
  • Viktor Malyshev + 5 more

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.

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Generative Artificial Intelligence in Education From 2021 to 2025: A Scientometric Review
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  • Journal of Curriculum and Teaching
  • Junmin Guo + 2 more

This study presents a bibliometric analysis of 965 peer-reviewed articles on generative artificial intelligence (GenAI) in education published from 2021 to 2025 in the Web of Science Core Collection. Through keyword co-occurrence, co-citation, and collaboration network analyses, it identifies core research themes, intellectual structures, and developmental trends. Findings reveal an exponential rise in GenAI-related publications, with dominant themes centred on technological applications of GenAI in teaching and assessment—especially ChatGPT—alongside technology acceptance mechanisms and learner outcomes such as motivation and self-efficacy. Three major thematic clusters emerge: GenAI educational applications, user adoption theories, and learning impacts. Co-citation patterns show strong reliance on traditional acceptance models like TAM, indicating limited development of GenAI-specific theoretical frameworks. Collaboration analyses reveal fragmented author networks and uneven global participation, concentrated mainly in North America and East Asia. The study highlights research gaps, including ethical governance, creativity development, interdisciplinary applications, and insufficient qualitative or mixed-method studies. It recommends developing theoretical models tailored to GenAI’s interactive and multimodal characteristics, strengthening ethical and cross-cultural frameworks, expanding interdisciplinary innovation, and enhancing global research cooperation to support the sustainable and responsible integration of GenAI in education.

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  • 10.54097/ehss.v22i.12469
Advantages and Challenges of Using Artificial Intelligence in Primary and Secondary School Education
  • Nov 26, 2023
  • Journal of Education, Humanities and Social Sciences
  • Heyuan Guan

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.

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  • Cite Count Icon 9
  • 10.4018/ijwltt.340030
Influencing Factors and Modeling Methods of Vocal Music Teaching Quality Supported by Artificial Intelligence Technology
  • Mar 13, 2024
  • International Journal of Web-Based Learning and Teaching Technologies
  • Yang Yuan

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.

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  • Scholarly Notes of Transbaikal State University
  • Svetlana Starostina + 2 more

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.

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  • OPEN EDUCATIONAL E-ENVIRONMENT OF MODERN UNIVERSITY
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  • Jul 15, 2025
  • Arid International Journal of Educational and physcological sciences
  • Mohammed Ali Al Ofi + 1 more

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

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  • Cite Count Icon 42
  • 10.21686/1818-4243-2023-2-36-48
Generative Artificial Intelligence in Education: Discussions and Forecasts
  • Mar 26, 2023
  • Open Education
  • L V Konstantinova + 4 more

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.

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  • Cite Count Icon 48
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  • Mar 14, 2024
  • International Research Journal on Advanced Engineering and Management (IRJAEM)
  • Iffath Unnisa Begum

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.

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  • Journal of Educational and Psychological Sciences
  • Zohor Mohammed Al-Areeshi

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.

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  • HUMANITIES STUDIES
  • Yuriy Melnik + 2 more

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.

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  • Feb 28, 2025
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Artificial intelligence (AI) is rapidly entering various sectors of the economy, including in the education. AI applications are gradually starting to transform the way we learn and teach, offering both advantages and disadvantages. The purpose of the publication is to investigate the degree of use of artificial intelligence in Bulgarian educational institutions – schools and universities. To achieve the goal, the following main tasks are set: to make a literature review of scientific and specialized literature on the specifics of using artificial intelligence in education; to conduct a survey in secondary schools and universities regarding the degree of use of artificial intelligence in Bulgarian education; to bring out advantages and disadvantages of the use of artificial intelligence in education.

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  • Cite Count Icon 31
  • 10.5539/ies.v14n11p94
A Common Framework for Artificial Intelligence in Higher Education (AAI-HE Model)
  • Oct 28, 2021
  • International Education Studies
  • Thiti Jantakun + 2 more

This research aims to 1) Develop a common framework for artificial intelligence in higher education (AAI-HE model) and 2) Assess the AAI-HE model. The research process is divided into two stages: 1) Develop an AAI-HE model, and 2) Assessment the model. The sample consists of five experts chosen through purposive sampling. The data is analyzed by means and standardized deviations statistically. The research result shows that 1) the AAI-HE model consists of seven key components which are 1.1) User Interactive Components and Technology of AI, 1.2) Components and Technology of AI, 1.3) Roles for Artificial Intelligence in Education 1.4) Machine Learning and Deep Learning 1.5) DSS Modules 1.6) Applications of Artificial Intelligence in Education, and 1.7) AI to enhance campus efficiencies, and 2) The result of the assessment of the AAI-HE model is rated as absolutely appropriate overall.

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Learning Motivation via Artificial Intelligence: A Bibliometric and Systematic Literature Analysis
  • Jul 17, 2024
  • International Journal of Academic Research in Business and Social Sciences
  • Fatema Al Nabhani + 2 more

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.

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