Repositioning teachers in the age of AI: a cross-disciplinary study of perceptions and practices in China

The emergence of Artificial Intelligence (AI) has significantly transformed the landscape of teaching and learning in higher education. As AI technologies continue to evolve, they are redefining how educators deliver content, how students engage with learning materials, and how instructors assess student performance. Educators and researchers must continue to support a human-centered pedagogical system within our institutions while incorporating AI effectively. The ongoing research in this area seeks to explore best practices for integrating AI in a way which enhances learning outcomes without compromising academic integrity or human-centered, educational settings. Recent studies have indicated that AI technologies can facilitate student engagement, support differentiated instruction and provide curriculum which positively impacts the teaching and learning environment. The current research in this area explores best practices for integrating AI in a way that improves learning outcomes without compromising academic integrity or human-centered pedagogy. However, the effectiveness of AI in education depends on the digital literacy of both students and instructors. Students may unknowingly engage in AI practices that promote dishonest academic outcomes. Institutional guidelines and policies focused on using AI tools appropriately must be created and uniformly enforced in higher education. Furthermore, professional development and on-going, consistent training are crucial to ensure educators can successfully integrate AI tools in the classroom. The rapid pace of technological change has made it difficult for universities to remain informed about best practices, often leading to a trial-and-error approach to implementation. Faculty and administrators must continue to remain current with trends and the latest developments in AI technologies while ensuring institutional goals, pedagogical frameworks, and accreditation standards are being upheld.AI has the potential to transform higher education by fostering more efficient and engaging learning experiences. However, its successful adoption requires a thoughtful, evidence-based approach that considers using AI technologies in a human-centered pedagogical system. As institutions continue to adapt to this new dynamic within the education field, continued research, training, and planning will be critical to display the full potential of AI in higher education.

AimsThe contribution of mental illness towards total Disability Adjusted Life Years is increasing according to the Global Burden of Disease study. As the need for mental health services increases, technological advances are being deployed to improve the delivery of care and lower costs.The emergence of Artificial Intelligence (AI) technology in mental health and companionship is an evolving topic of discussion. There have been increasing debates about the use of AI in managing mental health problems. As the AI technology and its use grows, it is vital to consider potential harms and ramifications.There are very limited discussions about the use of chatbots and relevant AI by humans to commit crime especially in those suffering from mental illness. AI can potentially serve as an effective tool to misguide a vulnerable person going through a mental health problem e.g. encourage someone to commit a serious offence. There is evidence that some of the most used AI chatbots tend to accentuate any negative feelings their users already had and potentially reinforce their vulnerable thoughts leading to concerning consequences.The objective of this study is to review existing evidence for harmful effects of AI chatbots on people with serious mental illness (SMI).MethodsWe conducted a review of existing evidence in five databases for relevant studies. The search sources were 4 bibliographical databases (PsycINFO, EMBASE, PubMed, and OVID), the search engine “Google Scholar” and relevant grey literature. Studies were eligible if they explored the role of AI and related technology in causing harm in those with SMI.ResultsInitial searches constrained the scope of review to the harmful effects of AI use in mental health and psychiatry and not just the association with crime due to very limited existing data.ConclusionWhilst current AI technology has shown potential in mental healthcare, it is important to acknowledge its limitations. At present, the evidence base for benefits of AI chatbot in mental healthcare is only just getting established and not enough is known or documented around the harmful effects of this technology. Nevertheless, we are seeing increasing cases of vulnerable mental health patients negatively influenced by AI technology. The use of AI chatbots raises various ethical concerns often magnified in people experiencing SMI. Further research will be valuable in understanding the ramifications of AI in psychiatry. This will also help guide the developers of this important and emerging technology to meet recognised ethical frameworks hence safeguarding vulnerable users.

This study aims to examine the impact of artificial intelligence (AI) on pragmatic English language teaching in universities. The scope of the study is limited to the opportunities and challenges of English language teaching. This study was carried out using a mixed method of conducting surveys and in-depth interviews. A questionnaire link using Google Forms from Spreadsheet was sent to 6 English lecturers via WhatsApp group and personal contact. The study sample consisted of 6 English lecturers from state and private universities in Central Java. Observation, questionnaire analysis, and interview transcripts show that the emergence of artificial intelligence (AI) technology has created opportunities and challenges to teaching and learning English. AI has transformed English language teaching in higher education. The findings and discussion elaborate some novelties of this study; 1) the profile of utilizing ChatGPT in pragmatics ELT teaching, portrays that ChatGPT roles in teaching scenarios play 3 major sessions, like; designing creative and innovative pragmatics teaching materials, setting up the midterm test of pragmatics project, and lastly, assessing and evaluating the pragmatics final test project. 2) The opportunities of using ChatGPT for lecturers, ChatGPT is one of the most sophisticated AI tools available today, and it can write nearly anything that an instructor wants it to. ChatGPT can help lecturers with a variety of tasks, such as creating course outlines, student progress reports, test and quiz questions, and grading rubrics; developing more inclusive and accessible learning activities; interacting with students and their families; and contributing text for websites or bulletin boards to maintain a connection between students and their families. 3) The challenges of applying ChatGPT for lecturers; ChatGPT can provide immediate responses to student questions, ChatGPT can adapt to individual student needs, ChatGPT can increase accessibility and inclusivity by providing language support for students with diverse learning needs, ChatGPT can serve as a valuable tool for language practice and strengthening, ChatGPT can encourage active learning by encouraging students to ask questions, engage in discussions, and seek clarification on challenging concepts, Integrating ChatGPT into language teaching can inspire innovative teaching approaches, such as blended learning models, flipped classrooms, and gamified learning experiences, that leverage technology to improve student learning outcomes

The development of education in Indonesia in the 4.0 era is quite significant in terms of learning. The emergence of artificial intelligence (AI) technology provides opportunities and challenges for implementing history learning at the elementary to high school levels. This research aims to answer the problem of why AI technology is important in learning history and what its benefits are. The method used in research is the historical research method. The results of this research show that the development of history learning based on artificial intelligence (AI) in the digital era 4.0 continues to develop, making history learning a challenge for educators because it not only requires an understanding of historical facts but also interpretation and analysis as well as the application of learning strategies using AI. The benefits of using AI in history learning are increasing learning efficiency by reducing the time needed to search for information, increasing student interaction with learning material through the use of technology that attracts attention, and increasing students' understanding of the historical context through data visualization and analysis. The challenge in using AI is the teacher's lack of ability to follow developments in AI-based learning, and the use of AI technology in history learning is the lack of relevant and quality data. The challenge in using AI is the teacher's lack of ability to follow developments in AI-based learning, and the use of AI technology in history learning is the lack of relevant and quality data.

Academic engagement of Chinese college students has received increasing research attention due to its impact on Students' Mental health and wellbeing. The emergence of artificial intelligence (AI) technologies marked the beginning of a new era in education, offering innovative tools and approaches to enhance learning. Still, it can be viewed from positive and negative perspectives. This study utilizes the Theory of Planned Behavior (TPB) as a theoretical framework to analyze the mediating role of students' attitudes toward AI, perceived social norms, perceived behavioral control, and their intention to use AI technologies in the relationships between Students' academic engagement and Mental health. The study involved a total of 2,423 Chinese college students with a mean age of approximately 20.53 ± 1.51 years. The survey was conducted through Questionnaire Star, using a secure website designed specifically for the study. The Hayes' PROCESS Macro (Version 4.2) Model 80 with SPSS 29.0, a multivariate regression analysis with a chain mediation model that allows for multiple mediators to be tested sequentially, has been used. The statistical test explored the direct and indirect effects of students' engagement (X) on mental health (Y) through a series of mediators: attitude toward AI (M1), subjective norm (M2), perceived behavioral control over AI use (M3), and AI use behavioral intention (M4). The direct positive relationship between engagement and mental health (β = 0.0575; p < 0.05), as well as identifying key mediating factors such as perceived behavioral control (β = 0.1039; p < 0.05) and AI use of behavioral intention (β = 0.0672; p < 0.05), highlights the potential of AI tools in enhancing students' well-being. However, the non-significant mediating effects of attitude toward AI (β = 0.0135), and subjective norms (β = -0.0005), suggest that more research is needed to understand the nuances of these relationships fully. Overall, the study contributes to the growing body of literature on the role of AI in education and offers practical implications for improving mental health support in academic settings.

Objective: The study aimed to identify the attitudes of music skills teachers in Oman towards the use of artificial intelligence (AI) in teaching and to understand the challenges they face in integrating AI into their teaching methods. Theoretical Framework: The proliferation of modern learning resources and technological advancements, especially the emergence of artificial intelligence, have significantly impacted educational institutions. Oman is striving to align its education system with the digital transformation outlined in Oman Vision 2040, which emphasizes high-quality education, the integration of technology, innovation, entrepreneurship, and skill-building. Method: This study adopted a descriptive analytical method, analyzing a questionnaire completed by music skills teachers in Oman regarding their opinions on AI in teaching. The survey focused on three main axes: knowledge of AI, its use in teaching music skills, and the challenges faced by teachers in integrating AI into their practice. Results and Discussion: The results indicated that music skills teachers in Oman have a positive attitude towards the use of artificial intelligence in teaching. Regarding knowledge of AI, the statement "I strive to develop my knowledge about artificial intelligence and its applications in various fields" received the highest mean score of 4.14 with a standard deviation of 0.808, showing a strong commitment to learning about AI. In terms of using AI in teaching music skills, the statement "I intend to use artificial intelligence technologies in the future" ranked highest with a mean score of 4.24 and a standard deviation of 0.761, reflecting a positive intention to integrate AI into their future teaching practices. However, when it came to challenges, the statement "Lack of specialized training in artificial intelligence for music skills teachers" emerged as the most significant barrier, with the highest mean of 4.26 and a standard deviation of 0.782, pointing to the lack of adequate training as the primary obstacle in AI adoption for teaching music skills. Conclusion: The study concludes that music skills teachers in Oman generally have positive attitudes toward the use of AI in teaching. However, the main challenge identified was the lack of specialized training for teachers, which hinders the effective implementation of AI in music education. Research Implications: This research highlights the need for better training and resources for teachers to effectively incorporate AI in their teaching practices. It also emphasizes the importance of curriculum updates to align with AI advancements. Originality/Value: This study provides valuable insights into the perspectives of music skills teachers in Oman on the integration of AI in teaching, contributing to the growing body of research on AI in education in the Middle East. Contributions: The study contributes to the understanding of the role of AI in music education, specifically in Oman, and identifies key barriers that must be addressed for effective integration.

The emergence of artificial intelligence (AI) has revolutionised higher education teaching and learning. AI has the power to analyse large amounts of data and make intelligent predictions thus changing the whole teaching and learning processes. However, such a rise has led to institutions questioning the morality of these applications. The changes have left librarians and educators worried about the major ethical questions surrounding privacy, equality of information, protection of intellectual property, cheating, misinformation and job security. Libraries have always been concerned about ethics and many go out of their way to make sure communities are educated about the ethical question. However, the emergence of artificial intelligence has caught them unaware. This research investigates the preparedness of higher education librarians to support the ethical use of information within the higher and tertiary education fraternity. A qualitative approach was used for this study. Interviews were done with thirty purposively selected librarians and academics from universities in Zimbabwe. Findings indicated that many university libraries in Zimbabwe are still at the adoption stage of artificial intelligence. It was also found that institutions and libraries are not yet prepared for AI use and are still crafting policies on the use of AI. Libraries seem prepared to adopt AI. They are also prepared to offer training on how to protect intellectual property but have serious challenges in issues of transparency, data security, plagiarism detection and concerns about job losses. However, with no major ethical policies having been crafted on AI use, it becomes challenging for libraries to full adopt its usage.

The emergence of artificial intelligence (AI) technology has profoundly changed the value chain of the retail industry. However, there is a significant gap between the potential value of AI and its actual implementation in retail operations, which highlights the practical challenges of integrating AI into daily operations. Since the introduction of ChatGPT in 2022, the number of studies on the application of AI technology has surged. This study aims to systematically explore factors that promote and hinder AI adoption in retail businesses. The study employed a systematic literature review, focusing on peer-reviewed academic articles in English published between 2015 and early 2025. This review specifically covers the topics of AI technology. The results of this study identify five major drivers, including cost reduction, improving service quality, marketing activities, external factors, and supporting decision-making. In addition, seven major barriers were identified, including perceived ease of use, uncertainty in returns, lack of talent, digital environment, investment and cost, data privacy and ethics issues, and organization and culture. This study also developed a conceptual framework based on the Technology Acceptance Model (TAM) to describe the mechanisms in which driving and impediment factors take effect. This study assists researchers in assessing the current state of research on AI adoption. As attention to AI technology grows, the importance of integrating evaluations of existing systems becomes evident.

The process of conducting interviews plays a pivotal role in human resource management, as it directly influences the selection of candidates and ultimately shapes the composition of an organization's workforce. However, traditional interview methods are often subjective and prone to biases, leading to suboptimal decision-making. In recent years, the emergence of artificial intelligence (AI) technologies has provided new opportunities to revolutionize interview analysis and improve decision-making in the hiring process.This research paper explores the application of AI-enabled interview analysis in human resource management, aiming to unveil insights and enhance decision-making. The study focuses on three main areas: interview data collection, analysis, and decision-making support. AI technologies, including natural language processing (NLP) and machine learning algorithms, are leveraged to analyze interview transcripts, audio recordings, and other relevant data sources.By analyzing interview data using AI, this research uncovers hidden patterns, linguistic cues, and behavioural indicators that may be missed by human interviewers. These insights provide a deeper understanding of candidate suitability, skills, and competencies, enabling HR professionals to make more informed and objective decisions. Moreover, AI algorithms can be trained to identify biases and mitigate their impact, leading to fairer and more inclusive hiring practices. The research also investigates the potential challenges and ethical considerations associated with AI- enabled interview analysis. Concerns related to privacy, data security, algorithmic biases, and the role of human judgment in decision-making are examined, highlighting the need for responsible implementation and ongoing monitoring.To validate the effectiveness of AI-enabled interview analysis, a mixed-methods approach is employed, combining quantitative data analysis and qualitative feedback from HR professionals. The study presents empirical evidence demonstrating the benefits of AI technologies in improving decision-making accuracy, efficiency, and fairness. Key Index Terms: Digital AI-enabled interview analysis, Hiring process, Decision-making, Interview data analysis, Natural language processing (NLP), Machine learning algorithms, Candidate selection, Workforce composition, Objective decision-making, Hidden patterns, Linguistic cues.

The emergence of artificial intelligence (AI) technology has the capability to drastically change logistics and supply chain management across various business and industrial sectors. Logistic project management, a crucial sector in the supply chain management of companies, is regarded as a domain where AI will play a key role in enhancing efficiency, precision, and the speed of service delivery. Saudi Arabia's Vision 2030 aims to improve connectivity with other nations both regionally and globally by refining logistics services, streamlining trade exchanges, and incorporating digital technology into these processes. The aim of this study is to identify the challenges faced when implementing AI technologies in logistics project management at Saudi Telecom Company (STC). This research employs a qualitative approach that features a literature review on the topic. The findings revealed several challenges impeding the global implementation of AI in logistics project management, which can be classified into organizational, technological, economic, data, environmental, social, and ethical issues. In the Saudi context, within the STC, four key challenges of implementing AI in logistics project management were recognized: data privacy and security, hardware infrastructure needs, insufficient employee skills and adaptability, and social acceptance. Based on the findings of this study, it can be concluded that implementing AI technology in logistics project management, when executed correctly, could reveal significant opportunities at the STC. Further experimental studies are suggested to gain a better understanding of the challenges that restrict the application of AI technology in logistics project management.

Anatomy has been a pillar of medical education for centuries. The emergence of artificial intelligence (AI) technology has sparked significant interest among educators, especially regarding its application in anatomy learning. This article explores the current application of AI technology, such as AI-powered chatbots tailored for anatomy education. This short commentary examines the potential benefits of AI, such as personalised learning experiences, enhanced learning efficiency, enhanced visualisation, and interactivity. Conversely, it also examines challenges and drawbacks, including issues of accuracy in AI models, potential for over-reliance on technology, and fair access to AI technology.

This study presents a systematic literature review analysing the impact of artificial intelligence (AI) on higher education, focusing on its methods, results, and implications. By synthesising a diverse range of academic papers, the review explores how AI technologies influence educational standards and practices in higher education institutions. Findings reveal that AI has the potential to enhance the quality of higher education by diversifying teaching responsibilities, customising learning experiences, and employing intelligent, adaptive teaching strategies. These capabilities position AI as a transformative tool for improving educational delivery and outcomes. However, the study also highlights significant challenges associated with integrating AI into higher education. These challenges include delineating the appropriate scope of AI use, addressing inequalities in access to digital resources, and ensuring adequate training and support for educators and students. The review underscores the importance of understanding these complexities to guide the development of effective strategies and policies that optimise AI's potential while mitigating its limitations. The review offers critical insights into the dual role of AI in higher education, where it can either advance or hinder educational standards depending on how it is implemented. By examining the advantages, limitations, and broader consequences of AI-powered instructional tools, this study provides a comprehensive perspective on the intricate relationship between AI and educational quality. The findings aim to inform educators, policymakers, and stakeholders about the opportunities and challenges of adopting AI in higher education, contributing to the development of inclusive, innovative, and sustainable educational practices.

With the rapid development of artificial intelligence, social governance is facing new challenges and opportunities. This study aims to explore new models of social governance in the era of artificial intelligence, in order to contribute to social stability and development. Through literature review and empirical research, this paper first reviews the rapid application of artificial intelligence technology and the emergence of artificial intelligence. literature review and empirical research, this paper first reviews the rapid application of artificial intelligence technology and the emergence of Through literature review and empirical research, this paper first reviews the rapid application of artificial intelligence technology and the emergence of related issues, and then explores the new situations and challenges faced by social governance in the era of artificial intelligence. Based on in-depth analysis of various governance practices, this paper proposes an innovative new model of social governance, namely the co-governance model supported by artificial intelligence. By fully utilising artificial intelligence technology and establishing an intelligent social governance system, it promotes collaboration and interaction between government and the private sector. By fully utilising artificial intelligence technology and establishing an intelligent social governance system, it promotes collaboration and interaction between government and the public, as well as between enterprises and individuals, thereby achieving By fully utilising artificial intelligence technology and establishing an intelligent social governance system, it promotes collaboration and interaction between government and the public, as well as between enterprises and individuals, thereby achieving rationalization, efficiency, and sustainable development of social governance. Finally, through case studies and practical exploration, the implementation and effects of the proposed new model of social governance are demonstrated. The results of this study are of great significance for promoting innovation and practice in social governance theory.

A few weeks ago, we published an editorial discussion on whether artificial intelligence applications should be authors of academic articles [1] . We were delighted to receive more than one interesting reply letter to this editorial in a short time [2, 3] . We hope that opinions on this

Masters or Slaves? AI and the Future of Humanity