Keyword: ethics

ABSTRACT: The rapid integration of artificial intelligence (AI) into higher education is reshaping how future educators are prepared for multilingual, multicultural, and ethically complex environments. This study employed a mixed-methods sequential explanatory design to investigate how educators and students in Luxembourg and Ukraine perceive and adopt AI in teacher preparation. In Luxembourg, AI was largely framed as a tool to extend inclusive, multilingual practices and institutional innovation, whereas in Ukraine, it was often adopted out of necessity under conditions of crisis and infrastructural disruption. Quantitative analyses demonstrated that perceived benefits of AI were positively correlated with readiness for instructional integration (r = 0.61, p < .001), while ethical concerns were negatively correlated with willingness to adopt AI (r = –0.45, p < .001). No significant group differences were observed in overall reported levels of ethical concern (t(140) = 1.25, p = .21), though qualitative findings revealed striking contrasts in the nature of these concerns. Luxembourgish participants expressed preventative concerns about quality and pedagogy, while Ukrainian participants described immediate ethical dilemmas shaped by wartime conditions, including studying in bomb shelters and balancing personal safety with academic integrity. Findings highlight that while AI can enhance instructional innovation, it simultaneously amplifies inequalities through language bias and access gaps. The study contributes by linking empirical insights to instructional design frameworks (ADDIE, TPACK) and multicultural education theory, offering concrete guidance for teacher preparation in both stable and crisis-affected contexts.

ABSTRACT: The integration of AI technologies into the writing process has significantly altered traditional notions of authorship, creativity, and intellectual labor. Historically, writing was seen as a human-driven cognitive and creative exercise, but with the rise of generative AI tools such as ChatGPT and Claude, the line between human and AI contributions has become increasingly ambiguous. This paper addresses the limitations of the current sliding scale model, which views AI involvement as ranging from “none” to “complete”. In its place, we propose a new multidimensional framework that more accurately reflects the complexity of human-AI collaboration in writing. The model includes axes for content generation, structural assistance, creative input, and analytical contribution, emphasizing the varying degrees of interaction between human writers and AI tools. This framework highlights how AI can assist in different aspects of writing without fully replacing human agency, while also underscoring the importance of ethical and intellectual accountability. By providing a more comprehensive understanding of the collaborative dynamics between humans and AI, this paper offers a foundation for future research into optimizing these interactions in creative and academic contexts.

ABSTRACT: The mandate of universities and higher education institutes is to shape students’ ethical wisdom and catalyze sustainable development. However, everyone does not have equal access to higher education which drives the above mindsets, leading to unequal quality of education. Today, most ethics teaching in engineering schools is narrowly micro-ethics and does not attempt to define macro-ethics’ special challenges. Micro-ethics concentrates on concerns related to the individual and the innermost workings of the profession. However, macro-ethics encompasses sustainable development with a focus on the collective social responsibility of the profession and public concerns about technology. This study examined undergraduate engineering programs in 25 major Canadian universities to see if they are adequately prepared to navigate both the micro- and macro-aspects of ethics education. The curricula of the programs show many courses focusing on micro-ethical concepts. The lack of explicit macro-ethical agendas for advancing society invites further work on curricula to enhance the efficacy of the content and delivery modes. This inadequate commitment to socially responsible engineering is conceptualized as a “culture of disengagement”. The study introduces important moments of change to strengthen ethics education. These include twinning engineering and computing ethics; embedding overlapped ethics, sustainability, and responsibility mindsets; and promoting the scholarship of integration through research, synthesis, practice, and teaching. By adopting these approaches to curriculum and pedagogy, the students will effectively cultivate a critical understanding of and obligation to the profession’s collective responsibility and the well-being of the greater society. These changes provide crucial insights into broadening socio-technical-minded prospects of engineering ethics education.

ABSTRACT: Contemporary advances in generative AI technology have sparked considerable interest regarding its application in language education. This article explores the innovative impact that AI-powered linguistic educational tools may have, such as customized learning journeys, dynamic content, and individualized feedback mechanisms, which collectively have the potential to enhance language acquisition. At the same time, it is important to recognize the constraints associated with such technologies. Concern about maintaining precision and genuineness within AI-crafted language texts is an issue in the literature. There is also caution about AI’s current inclination to standardize language expression and to propagate limited cultural narratives, alongside the risks of overreliance on technology which may diminish analytical thought and inventiveness. This article examines the ethical considerations involving generative AI, such as the authenticity of creative work and the ownership of intellectual output. Emphasizing the necessity for clarity and conscientiousness in the application of AI, this conceptual article outlines the opportunities, limitations, and ethical concerns associated with generative AI in language instruction. This article advocates for a well-rounded strategy that
leverages the positive aspects of generative AI within language education, while also addressing possible drawbacks and championing an ethical and equitable approach to language learning in the emerging AI-centric digital landscape. A model for forging thinking in this new research and practice space is offered to synthesize many of the possibilities of generative AI in language education.