Artificial Intelligence in Education and Ethics

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.

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).

Currently, the development of technologies affects all spheres of society. Artificial intelligence technologies are intensively developing and are beginning to be actively used to solve various problems both at the everyday and at the scientific level. Accordingly, there are discussions in the pedagogical circle about the possibilities of using artificial intelligence to solve educational tasks: from finding educational material, translating educational material into another language, creating a curriculum, computer presentation for an educational session, creating a computer program or project to communication in another language with an IA-assistant (Artificial Intelligence). That is, a scientific and pedagogical worker can delegate the performance of certain tasks to artificial intelligence technologies (but with further verification of the completed tasks by artificial intelligence technologies) and reduce his time for preparing for educational classes. Increasingly, scientists emphasize the possibility of using artificial intelligence technologies in the educational process and the need to train scientific and pedagogical workers to use artificial intelligence. Accordingly, the purpose of the article was to analyze the concept of "artificial intelligence" and describe existing scientific approaches to the use of artificial intelligence in the educational process. The methodology of the research was the analysis of the concept of "artificial intelligence" by both Ukrainian and foreign scientists, analysis of scientific approaches, explanation, comparison and systematization of directions, advantages, disadvantages of using artificial intelligence in education. The definition of the concept of "artificial intelligence" by both Ukrainian and foreign scientists is presented. We defined the concept of "artificial intelligence" as an information technology that ensures the performance of certain complex intellectual tasks. Examples of artificial intelligence technologies that can be used in the educational process include: Anima, Grammarly, CENTURY, IntelliMetric, API DeepL, OpenArt, GodeRabbit, etc. The areas of use of artificial intelligence in education are described and highlighted: individualized training, intelligent training systems, automated assessment, group training. The advantages and disadvantages of using artificial intelligence in the educational process are characterized. The results of the study emphasize the importance of studying and using artificial intelligence in the educational process, because this technology is developing rapidly, has prospects for further active development and is used in various spheres of human activity: scientific, medical, military, pedagogical, industrial, household, etc.

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.

The acceptance of, perceived advantages to, and skepticism toward the integration of artificial intelligence (AI) in undergraduate education is investigated in this paper. In this study, a total of 675 students from six Romanian universities answered a self-administered online questionnaire evaluating three main aspects: AI acceptance, AI benefits, and AI skepticism. While AI skepticism has a modest but substantial negative influence (β = −0.113, p = 0.001), results show that AI benefits favorably predict AI acceptance (β = 0.541, p = 0.001). Whereas AI skepticism negatively correlates with AI acceptance (r = −0.124, p = 0.001), correlational analysis reveals a high positive association between AI acceptance and AI benefits (r = 0.544, p = 0.001). Despite concerns about its limitations, the regression model suggests that students’ willingness to embrace AI in education is mostly driven by its perceived advantages. This explains 30.8% of the variance in AI acceptance (R2 = 0.308, F(2, 641) = 142.909, p < 0.001). These results highlight the importance of techniques that improve perceived benefits while addressing uncertainty since they offer insightful analysis of student attitudes regarding artificial intelligence integration in higher education. By guiding policy decisions and educational activities meant to maximize AI-driven learning environments, this study adds to the current conversation on artificial intelligence adoption in education.

The integration of Artificial Intelligence (AI) in non-formal, informal and formal education is an emerging area with great potential to transform the world. However, the capacity of educators, youth workers and teachers to capitalise on this potential remains limited due to a lack of well-defined frameworks for AI integration in practices. The scope of this study is to explore the needs, challenges, and perspectives of youth work professionals regarding AI integration.The research methodology employed mixt research methods. The literature review was followed by four semi-structured focus groups involving 72 youth workers and professionals with diverse backgrounds, nationalities and experience levels. A common guideline was used to ensure consistency, including facilitator instructions, discussion prompts, and reporting templates. The data collected during the focus groups were analysed using a Computer-Assisted Qualitative Data Analysis Software (CAQDAS), ATLAS.ti software dedicated to qualitative research. The authors conducted qualitative analysis, through coding, identification of main categories, thematic map for visualization of results, and interpretation of findings to uncover patterns and deeper insights. The results revealed a generally positive attitude toward AI tools and an awareness of their potential benefits in youth work, particularly in content creation. However, participants reported significant challenges regarding the use of AI for administrative tasks efficiency, for personalised learning, ethical concerns, and difficulty in interpretation of data. Cross-country similarities emerged, suggesting a shared need for capacity building and continuous training, while differences highlighted the influence of national contexts and digital infrastructure.This study provides a foundational understanding of the competence needs of youth workers in relation to AI adoption. The findings are relevant for course designers wishing to offer targeted training for youth workers. Future research is also needed into policy-level support mechanisms that can enhance AI literacy and ethical integration across the sector.

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.

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 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.

: The educational system, unlike other social systems, is distinguished at the same time by conservatism, necessary to protect itself from frequent and thoughtless changes as a result of temporary conjunctural moods, and modernism, expressed in the desire to prepare learners for the current needs of society. This duality also gives rise to many arguments for and against the introduction of artificial intelligence (AI) in education - if it does not, the education system will fall behind the realities, if it does, it may compromise its main purpose - to provide validated and verified knowledge to students and the students. The purpose of this article is to examine the possibilities of using AI in universities and to reveal the limitations that hinder it. In this sense, the object of the study is artificial intelligence, and the subject - its application in the higher education system. The purpose of the study is to examine, through a SWOT analysis, the opportunities and threats in the use of AI applications in universities, as well as their strengths and weaknesses, determining their readiness for it. A study has been conducted that shows that the opportunities for using artificial intelligence in education slightly outweigh the threats, and the strengths of universities as a terrain for implementing AI. The analysis also highlights what are the main levers for the development of AI in universities, what are the limitations to it, what are the risks that may occur in the future and what are the problems that can be expected if threats are not overcome and weaknesses are minimized. It is concluded that AI applications can be very useful in the work of teachers, and students want them, but this should be done carefully, respecting certain principles of equality, credibility, ethics and guaranteeing human rights.

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.

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).

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.

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