Utilizing Generative AI to Counter Learner Groupthink by Introducing Controversy in Collaborative Problem-Based Learning Settings

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.

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.

In a state of a full-scale war, educational institutions in Ukraine were forced to switch to distance learning. This transformation of the educational space contributed to the rapid introduction of digital technologies, which are actively integrated into the educational process, and therefore have significantly changed the methodological approaches and techniques used to provide language training to foreign students at the initial stage of learning. For quite some time now, information and communication technologies have been part of the educational process, having improved and diversified to the point that in any Ukrainian higher education institution, preparatory departments and faculties have been using all available equipment (from a light projector to a multimedia board), software (from simple editors integrated into MS Office to multifunctional MLS like hot potatoes and Moodle), various Internet resources (e.g. virtual boards, live worksheets) and educational game platforms (like Kahoot!, Quizzes etc.) to ensure the basic principles of learning – systematicity, consistency and visualization – to increase its efficiency and effectiveness, as well as the students’ motivation. However, in the early 2020s, a new trend in the development of technologies took place, which was marked by the emergence and lightning-fast spread of Generative Artificial Intelligence (otherwise known as GenAI). This article focuses on its role in education and everyday life, during which the authors will try to prove the effectiveness, feasibility and advantages of using AI in language training for foreign citizens at the initial stage of learning. After all, although the use of artificial intelligence in the educational system is a relatively new direction, it has significant potential. To truly understand its capabilities, it is important to understand the essence of artificial intelligence and the principles of its operation, as well as to be capable of working with it. Accordingly, this article considers the key definitions of artificial intelligence and its philosophical interpretations. The areas of this advanced technology application are also to be discussed. Particular attention is paid to promising aspects of using artificial intelligence in language education, in particular USL (Ukraininan as a Second Language) training, such as personalized and adaptive learning, knowledge assessment, intermediate testing, the use of gaming technologies (or gamification of the educational process), the development of other innovative approaches using programs and applications that are powered by artificial intelligence algorithms, significantly simplifying the learning process for both teachers and students. Key words: artificial intelligence, automated assessment, chat-bot, educational space, gamification, generative AI, personalization.

This chapter traces the ethical issues around applying artificial intelligence (AI) in education from the early days of artificial intelligence in education in the 1970s to the current state of this field, including the increasing sophistication of the system interfaces and the rise in data use and misuse. While in the early days most tools were largely learner-facing, now there are tools that are teacher-facing, supporting their management of the classroom, and administrator-facing, assisting in their management of cohorts of students. Learner-facing tools now take into account the affective and motivational aspects of learning as well as the cognitive. The rise of data collection and its associated analytic tools has enabled the development of dashboards for the dynamic management and reflective understanding of learners, teachers, and administrators. Ethical issues hardly figured in the early days of the field but now they loom large. This is because of the legitimate fears that learners’ and teachers’ autonomy will be compromised, that learner data will be collected and potentially misappropriated for other purposes, and that AI will introduce extra biases into educational decisions and increase existing inequity and also because of the scary reputation that AI has in general.

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).

The future of health professions education: Emerging trends in the United States.

In this study, we review 1830 research articles on artificial intelligence in education (AIED), with the aim of providing a holistic picture of the knowledge evolution in this interdisciplinary research field from 2010 to 2019. A novel three-step approach in the analysis of the keyword co-occurrence networks (KCN) is proposed to identify the knowledge structure, knowledge clusters and trending keywords within AIED over time. The results reveal considerable research diversity in the AIED field, centering around two sustained themes: intelligent tutoring systems (2010-19) and massive open online courses (since 2014). The focal educational concerns reflected in AIED research are: (1) online learning; (2) game-based learning; (3) collaborative learning; (4) assessment; (5) affect; (6) engagement; and (7) learning design. The highly connected keywords relevant to analytic techniques within this field include natural language processing, educational data mining, learning analytics and machine learning. Neural network, deep learning, eye tracking, and personalized learning are trending keywords in this field as they have emerged with key structural roles in the latest two-year period analyzed. This is the first article providing a systematic review of a large body of literature on artificial intelligence in education, and in it we uncover the underlying patterns of knowledge connectivity within the field, as well as provide insight into its future development. The three-step multi-scale (macro, meso, micro) framework proposed in this study can also be applied to map the knowledge development in other scientific research areas.

The use of Artificial Intelligence (AI) in university education poses various challenges, whose effects, both positive and negative, are still under debate. This article presents a theoretical essay based on a review of recent scientific literature on the role of agency, Artificial Intelligence (AI), and education. Drawing on this body of work, a conceptual framework is proposed and divided into three parts: the conception of ai as a continuum in the evolution of technological culture; the challenges that ai raises in the educational field; and, finally, the proposal of technological epistemic agency (TEA) as a key cognitive capacity to foster an active and critical role among students and teachers as users of Artificial Intelligence in Education (AIED).

According to various international reports, Artificial Intelligence in Education (AIEd) is one of the emerging fields in education technology. Whilst it has been around for about thirty years, educators remain unclear as to how to take full pedagogical advantage of AI on a broader scale and how it could actually have a meaningful impact on teaching and learning in higher education. This paper aims to evaluate Artificial Intelligence within Higher Education, focussing on the opportunities and challenges it presents. It also investigates the educational implications of emerging technologies on the way students learn and how institutions teach and evolve. The paper gathers some examples of the introduction of AI in education in a bid to establish equitable, quality education for all. Firstly, the paper analyses how AI can be used to improve learning outcomes, presenting examples of how AI technology can help education systems use data to improve equity and quality in Higher Education. The paper also addresses the benefits and challenges of introducing AI in educational settings, as well as the potential risks of such an endeavour. Finally, we put forward some recommendations for AI in education, with a focus on establishing discussions around the uses, possibilities and risks of AI in education for sustainable development.

Survey data on students' perceptions, knowledge, and use of learning analytics (LA) and generative artificial intelligence (GenAI) for the personalization of learning.

This study explores the potential of artificial intelligence–based information systems in supporting educational processes within higher education institutions in Indonesia. The rapid adoption of digital platforms in academic administration and learning management has increased the need for intelligent systems that can enhance efficiency, transparency, and data-driven decision-making. This research aims to examine how artificial intelligence–based information systems are utilized in educational contexts, particularly in relation to curriculum implementation, academic management, and institutional readiness. A qualitative research design was employed using semi-structured interviews with academic stakeholders, complemented by document analysis. The findings indicate that artificial intelligence–based information systems contribute positively to improving administrative efficiency, supporting systematic curriculum evaluation, and facilitating evidence-based academic decision-making. However, challenges related to system transparency, interpretability, and user readiness were also identified as critical factors influencing system effectiveness. These findings highlight that the successful integration of artificial intelligence in education is not solely determined by technological capability but also by organizational support and human factors. This study contributes to the interdisciplinary integration of information systems and educational research by providing empirical insights into the role of artificial intelligence in higher education. The results offer practical implications for institutions seeking to adopt responsible and effective artificial intelligence–based information systems.

This study explores the dual nature of artificial intelligence (AI) in education, focusing on its positive and negative impacts as well as the practical limitations that shape its implementation. Through a systematic document analysis of national and international studies published between 2010 and 2025, the research identifies major themes related to the integration of AI in teaching, learning, and administration. The findings indicate that AI technologies enhance instructional efficiency, enable personalized learning experiences, and support data-driven decision-making processes. However, ethical and social challenges—such as algorithmic bias, data privacy issues, and unequal access to AI resources—pose significant concerns that require proactive governance and pedagogical preparedness. The study concludes that while the positive effects of AI outweigh its negative implications, the sustainability of AI in education depends on comprehensive teacher training, transparent data management, equitable access to digital tools, and continuous monitoring of AI-driven systems. These findings underscore the importance of designing ethical, inclusive, and human-centered AI frameworks for the future of education.

This study investigated the extent of prospective teachers’ acceptance, attitudes, and perceived effectiveness of artificial intelligence (AI) in education. It also examined whether these perceptions varied according to gender and age group. Using a descriptive-correlational design, data were gathered from 392 teacher education students enrolled in a state-managed university in southwestern Mindanao. The results revealed that the respondents generally demonstrated moderate acceptance, favorable attitudes, and positive perceptions of AI effectiveness in the teaching and learning process. While no statistically significant differences were found between genders, moderate effect sizes suggested subtle variations worth further exploration. Significant differences were observed across age groups, with older individuals reporting higher levels of AI acceptance. Strong and significant correlations among acceptance, attitude, and perceived effectiveness affirmed the interconnected nature of belief, emotion, and evaluation in shaping readiness for AI integration. These findings support the Technology Acceptance Model and the Theory of Planned Behavior. In light of these results, it is recommended that teacher education programs integrate AI literacy and practical training, with targeted support for younger students to enhance digital confidence and preparedness.

This article updates the problem of professional training of the future teacher in the context of rethinking the education process, forming a system of knowledge, abilities and skills necessary for the professional competitiveness of the future specialist. An attempt was made to draw attention to the urgent need to modernize the educational process in the context of searching ways to effective adaptation of modern youth to the realities of the 21st century. The importance of the term “transversality”, which previously functioned in a highly specialized environment of mathematical sciences, is emphasized in order to explain its modern interpretation in the field of professional education. The rapid processes of globalization and the consequences of the fourth scientific and technical revolution 4.0 (since the middle of the 20th century), which encompassed the intellectual activity of mankind, contributed greatly to the informatization of society, highlighted the need to develop the ability to solve problems related to technological achievements and intercultural communication. A special role is assigned to the use of artificial intelligence (AI) in education and science; analyzed the research of Ukrainian and foreign scientists dedicated to the study of the processes of perception, understanding and use of artificial intelligence by a modern student. The positive and problematic aspects of the introduction of the capabilities of artificial intelligence in the educational process of higher education institutions are considered; impact of computerization on all spheres of social and economic life of society is proven. It was concluded that in modern education it is necessary to develop awareness and understanding of the complex nature of artificial intelligence, ethical norms of its application in the educational process; to form the skills of a conscious approach to determining the degree of effectiveness of the achievements of innovative processes.

The growth of Artificial Intelligence is no more shrouded to the world we are living in. The advancement of digital technology and Artificial Intelligence has occurred in almost every field, not leaving behind the field of education. Artificial intelligence has revolutionized the way of learning and teaching making the process of learning more efficient and personalized. Artificial Intelligence in education refers to the usage of artificial intelligence tools like machine learning, or natural language processing and technologies in variety of ways to make a better self-relied experience of learning for students. The objective of current study was to investigate the abundant use and effect of using Artificial Intelligence tools for different functions of education or study. This quantitative study used data form 400 research participants who were students from several government and private universities. The present study utilizes convenience sampling. Data collection was from students of higher education of government and private universities. The survey questionnaire of Prof. Dr. Jorg von Garrel was used to get the comprehensive view of student’s utilization of artificial intelligence. The findings provided evidence of usage of Artificial Intelligence tools like Chat GPT with highest frequencies/percentage of almost 80% among other tools. The significant associations were also found between variables. In conclusion, this research study give a valuable insight towards the trend of using the Artificial Intelligence tools by the students for different perspectives of learning and studying.