In recent years, higher education has increasingly emphasized the integration of Learning Design and Learning Analytics to foster more engaging, personalized, and effective learning environments. This systematic literature review investigates how these two domains interact to enhance teaching learning processes and improve educational outcomes. The review identifies key benefits and opportunities associated with this integration across three stakeholder groups: students, lecturers, and educational institutions by analyzing 55 peer-reviewed publications. The results show that learning effectiveness can be significantly enhanced through the visualization of students’ learning interactions using straightforward and user-friendly analytical approaches. Furthermore, successful implementation requires the development of lecturers’ data literacy and programming competencies, as well as the incorporation of sociocultural, psychological, and physical data to achieve a more holistic understanding of learners. The review also identifies four major research directions to guide future efforts in bridging Learning Analytics and Learning Design. Finally, the paper underscores the importance of establishing clear ethical and privacy frameworks to ensure the responsible application of Learning Analytics in higher education.

The purpose of the current study is to examines the impact of AI awareness, perceived AI bias, and ethical concerns on pharmaceutical marketing decisions, with trust as a mediating variable. Artificial Intelligence has changed the world and everything is in the process of transformation. In the pharmaceutical sector the AI integration has great impact on its marketing and decision-making. Many problems are faced in its proper integration because of algorithmic bias, ethical issues, and trust among professionals. The research adopts a quantitative survey-based approach and collects data from medical representatives also known as the real marketers, working for pharmaceutical companies. A sample of 274 respondents was selected using Cochran’s sampling formula. The study used simple random sampling technique and the data were analyzed in SPSS 25. The findings reveal that AI awareness significantly and positively influences pharmaceutical marketing decision-making. The PAI bias negatively affects decision outcomes while the ethical concerns positively influence decision-making. Moreover, the mediation analysis confirms that trust plays a crucial role in strengthening the relationship between AI awareness and decision-making, while reducing the negative effects of perceived bias. The study highlights the importance of AI literacy. The pharma sector must ensure transparency and implement ethical frameworks to develop trust for successful AI adoption.

Decentralized clinical trials (DCTs) leverage digital health technologies to conduct trials outside traditional settings, offering numerous benefits such as increased participant diversity and breaking down geographic and transportation barriers. However, they also present significant ethical challenges. Current regulatory and ethical frameworks are not fully equipped to address these issues, highlighting a critical gap in effective governance and oversight of DCTs. This scoping review aims to systematically identify and synthesise the ethical challenges reported in the literature and to outline recommendations that can inform future guidance and practice. This scoping review followed Arksey and O'Malley's framework. We searched PubMed, Web of Science, and SCOPUS for peer-reviewed articles in English and applied predefined inclusion and exclusion criteria to guide study selection. The initial search yielded 757 documents. After applying inclusion and exclusion criteria and conducting a rigorous two-stage screening process, 32 articles were selected for detailed analysis. These articles identified six main areas of ethical challenges: electronic informed consent, equity and access, privacy and confidentiality, participant safety and welfare, scientific validity, and ethical and regulatory oversight. This review underscores the necessity for clear guidelines, enhanced digital literacy, robust data protection measures, and comprehensive regulatory frameworks to address the ethical challenges of DCTs. By synthesizing existing literature, this paper provides actionable recommendations, such as simplifying consent processes and improving technical support, and identifies areas for future research to ensure DCTs are conducted ethically and effectively.

The operation of Indonesian schools abroad reflects broader tensions between national identity formation and the cultural forces shaping transnational education. Yet, insufficient attention has been given to how multicultural learning is negotiated in diaspora early childhood settings. This study interrogates the implementation of multicultural education at Sekolah Indonesia Kuala Lumpur (SIKL), examining the mechanisms by which teachers strategically integrate local Malaysian wisdom into the character formation of Indonesian kindergarten students while maintaining core national values. Employing a qualitative case study design, the research draws on participant observation of classroom routines, in-depth interviews with teachers, and systematic document analysis, with data interpreted through the interactive framework of Miles, Huberman, and Saldaña to capture processes of cultural mediation. The findings reveal a pedagogical formation conceptualized as blended habituation, in which teachers function as cultural brokers who mediate the dialectical relationship between Indonesian cultural values and Malaysian local wisdom, navigating nuanced sociocultural differences while enabling the coexistence of Indonesian moral frameworks with Malaysian public norms, such as disciplined queuing and regulated collective silence. These dynamics cultivate a functional hybrid identity aligned with the notion of Cross-Cultural Kids (CCKs), positioning transnational early childhood environments as formative sites for cosmopolitan nationalism and underscoring the imperative for diaspora curricula to move beyond preservation toward deliberate cultural accommodation in fostering adaptive competence.

Culturally responsive practices (CRPs) (i.e., practices that affirm students’ cultural backgrounds) can reduce educational inequities, but these practices have yet to become normative within U.S. education. A national study of K-12 teachers conducted in late 2023 found that teachers’ use of CRPs depended not only on their individual moral frameworks regarding diversity (i.e., endorsement of multiculturalism and colorblindness) but also on their communities’ and administrators’ support for efforts to increase equitable educational outcomes among students (i.e., equity work). Since 2023, federal guidance has shifted, and educational equity work is now discouraged. We conducted a second national survey of K-12 teachers (N = 980) in early 2025 to examine whether contextual influences on teachers’ decisions regarding CRP use have also shifted in light of changes to federal guidance. While the 2023 study found that teachers with weaker multiculturalism beliefs were more likely to use CRPs when their administrators supported equity work, findings from the 2025 study revealed that administrator support only predicted greater CRP use when these teachers worked in politically liberal (but not conservative) communities. The shift suggests that recent federal policy changes have weakened the influence of district and school leadership on teachers’ decisions to use CRPs, particularly among teachers who are not individually inclined to use these practices. This study offers timely insights into teachers’ use of CRPs after new federal guidance on educational equity efforts and reaffirms that teachers’ practices are not solely shaped by their personal beliefs, but are instead responsive to the broader contexts in which they work.

The digital revolution has introduced important ethical challenges for younger generations, including the spread of hoaxes, plagiarism, and cyberbullying. This research examines the integration of generative Artificial Intelligence (AI) as a pedagogical partner in civic education to strengthen digital ethics grounded in Pancasila as Indonesia’s local wisdom. Employing a mixed-methods approach, data were collected through questionnaires administered to 332 senior and vocational high school students, Focus Group Discussions (FGDs) with 10 civic education teachers in Central Java Province, and in-depth interviews with experts in Civic and Character Education. The study findings reveal that, despite students' active use of AI, their critical thinking skills and digital ethics require further development. Teachers expressed an urgent need for adaptive, context-specific learning resources. Pancasila values provide a relevant and robust philosophical foundation for developing a digital ethics framework. Based on these findings, the study proposes an innovative framework that positions AI chatbots not merely as tools but as simulative and reflective learning partners. The framework seeks to transform learning from simple knowledge transmission to value-oriented education, enabling teachers to act as facilitators who guide students in actualising Pancasila values within the digital space.

This philosophical discourse examines the relationship between temporality and ethical practice in nursing, with particular attention to the distinction between chronos (quantitative time) and kairos (qualitative, opportune time). Drawing upon ancient Greek philosophical thought, contemporary nursing scholarship, and empirical research on moral judgement, the author argues that temporal awareness fundamentally shapes ethical deliberation and action in nursing practice. Despite the existence of multiple ethical decision-making frameworks in nursing (including principle-based approaches, dignity-enhancing care models, and professional codes of ethics) these frameworks remain largely atemporal, emphasising processes and components of ethical decisions rather than their temporal dimensions. Furthermore, empirical evidence demonstrates that time pressure systematically alters moral judgement, yet this phenomenon has received limited attention in nursing ethics literature. Building on classical virtue ethics (particularly the Aristotelian concept of phronesis, practical wisdom, which encompasses knowing not only what to do but when to act) and integrating insights from moral distress, moral resilience, and decision-making literature, the author introduces the construct of kairotic sensitivity (the capacity to recognise moments when patients are particularly receptive to difficult conversations or crucial decisions). This construct represents a significant contribution to nursing ethics, offering a conceptual framework for understanding how experienced nurses navigate the temporal complexities of ethical practice and providing a bridge between established ethical frameworks and the lived experience of temporal decision-making in clinical settings. The author proposes that kairotic sensitivity, alongside moral resilience, constitutes an essential yet undertheorised dimension of ethical expertise in nursing, with significant implications for patient outcomes, professional satisfaction, and nursing education. Practical implications for patient care and recommendations for nursing education and practice development are discussed.

ABSTRACT The article explores the facilitators and barriers to integrating Ubuntu values into social work and social development practice. Ubuntu values justice, freedom, community, reciprocal relations, responsibility, service to humanity, culture, and spirituality. Drawing from an empirical study involving participants from 19 African countries, the research highlights Ubuntu not merely as a philosophical abstraction but as a lived and culturally embedded reality. Findings reveal six key facilitators, namely, research, literature, education and training, public awareness, socio-democratic governance, and mentorship, that promote the adoption of Ubuntu principles in both educational and professional contexts. Conversely, the study identifies five structural and ideological barriers, including neoliberal capitalism, colonial legacies in policy and education, globalization, limited literature, and unsupportive organizational governance. The article contributes to the decolonial discourse in social work by advocating for indigenous knowledge systems and culturally grounded practices. It emphasizes the need for multi-level interventions to create enabling environments that validate and support Ubuntu as a transformative ethical framework for African social work.

Purpose This study examines the dual impact of artificial intelligence (AI) on business processes by systematically identifying and prioritizing both its value-creating benefits (bright-side) and risk-inducing consequences (dark-side). The study further aims to develop an integrated theoretical framework that explains how organizations can balance these opposing effects to achieve sustainable AI-driven business transformation. Design/methodology/approach A content-driven review of recent peer-reviewed literature was conducted to identify key positive and negative impacts of AI across five business process dimensions. Expert evaluations from 42 professionals were analyzed using the Fuzzy Technique for Order Preference by Similarity to Ideal Solution method to prioritize these impacts under uncertainty. Sensitivity analysis was performed to validate the robustness of the results, and an integrated theoretical framework was developed based on the empirical findings. Findings The results reveal that AI delivers its strongest benefits through enhanced financial risk forecasting, internal control, sustainability reporting and customer-facing automation, significantly improving operational efficiency and decision quality. However, the findings also highlight critical risks associated with inadequate governance, privacy invasion, ethical lapses and excessive reliance on automated systems. Governance-related risks emerged as the most severe challenges, indicating that the absence of robust ethical and regulatory frameworks can undermine the long-term value of AI adoption. Practical implications The study provides managers and policymakers with a structured decision-support approach to prioritize AI applications while proactively managing ethical, governance and data-related risks. Originality/value This research offers a novel integration of fuzzy multi-criteria decision analysis with theory development to present a balanced, data-driven understanding of AI's dual impact on business processes and organizational sustainability.

Abstract This paper examines the participation of Algerian women in the 2019 Hirak protests and their efforts to claim gendered and economic recognition within a society shaped by authoritarian and patriarchal structures. Drawing on ethnographic fieldwork and forty-three interviews conducted in 2019 and 2023, the study explores how women navigate both public protest spaces and more intimate “sociospaces”—such as markets, schools, homes, and informal gatherings within the Hirak—to assert claims for autonomy and recognition. The article introduces the concept of a “gendered moral contract,” showing how Algerian women across social classes mobilize moral, religious, and familial frameworks to demand state-backed compensation for unpaid domestic labor by positioning themselves as essential contributors to family and society. By linking these claims to broader economic resources, including oil wealth, women negotiate recognition within culturally intelligible forms. This study contributes to understanding agency and strategies within social movements, highlighting how women employ culturally grounded, morally framed approaches to frame and share their demands under restrictive political and social conditions.

Identifying completely unknown individuals is a major challenge in forensic and emergency medicine. Radiology offers a promising solution by using unique anatomical features on medical images to identify both living and deceased persons. Although emergency or postmortem images could be matched against large clinical databases, such applications remain largely experimental. This review examines current methods in automatic radiology-based personal identification, evaluates their performance, and highlights potential applications in forensic and clinical settings.A narrative review of studies published from 2018 onwards was conducted using PubMed and Google Scholar. Included studies applied automated or semi-automated personal identification to panoramic radiographs (PR) or computed tomography (CT) using reference datasets. A narrative approach was used to synthesize results descriptively due to heterogeneity in study design, dataset size, and methodology.Of the 32 included studies, 15 focused on PR-to-PR, 8 on head CT-to-CT, 7 on body CT-to-CT, and 2 on CT-to-PR identification. The most commonly applied approach was descriptor-based computer vision (CV), used in 9 studies. Deep learning was applied in 8 studies for feature extraction, and in 2 studies each for classification and bone segmentation.Several methods perform well in controlled settings. Descriptor-based CV provides the most flexibility and strongest evidence, especially for large-database comparisons and postmortem applications. Deep learning approaches, including feature extraction, classification, and automatic bone segmentation, also show promise for cross-individual matching but require further validation. Automatic radiology-based personal identification holds significant potential for forensic and clinical use, yet the development of standardized large-scale reference databases and robust automated pipelines remains a key challenge. · Radiological images enable automated personal identification of unknown individuals.. · Descriptor-based computer vision is flexible and robust for large database matching.. · Deep learning shows promise for cross-individual matching, but requires further validation.. · Postmortem applications are feasible, yet under-investigated.. · Ethical frameworks are necessary for handling sensitive imaging data.. · Heinrich A. A Review on Automatic Personal Identification Using Panoramic Radiographs and Computed Tomography. Rofo 2026; DOI 10.1055/a-2808-8851.

This article presents an examination of the intersection between generative AI and psycho-educational assessments, offering a comprehensive overview of their integration. It begins by exploring the fundamentals of artificial intelligence, emphasizing the role of generative AI in Natural Language Processing (NLP) and its potential implications for psychological research and clinical practices. Concurrently, the manuscript delves into the intricate steps of a psycho-educational assessment for children, elucidating the multifaceted process encompassing cognitive, emotional, and academic evaluations. Through this integrated exploration, the article not only provides detailed guidelines, an ethical framework, and nuanced insights into potential challenges but also addresses the global shortage of trained clinicians. By examining how advanced technologies including Generative AI can assist in enhancing diagnostic efficiency, when outputs are interpreted and validated by trained professionals. Drawing on the perspectives highlighted by Duff and Roberts (2016) and insights from generative AI, the article proposes guidelines that streamline assessments, prioritize ethical considerations, and maximize the benefits of human expertise.

The rapid adoption of generative artificial intelligence (GenAI) in nursing education presents urgent ethical challenges, particularly as students employ these tools in high-stakes clinical prioritization tasks. Although general AI literacy initiatives exist, nursing-specific resources for addressing risks of bias, inequity, and misinformation in GenAI-mediated decision making remain limited. This study adapts an interdisciplinary, open-access AI ethics learning toolkit to develop a conceptual, nursing-focused mini-toolkit. The adaptation integrates three complementary ethical frameworks: Rest's Four-Component Model at the learner level (moral sensitivity, judgment, motivation, and character), cyberethics principles at the professional level (autonomy, nonmaleficence, beneficence, justice, and explicability), and Chan's ecological model at the institutional level (pedagogy, governance, and operations). Collectively, these frameworks scaffold ethical reasoning across individual, professional, and systemic domains. The resulting mini-toolkit includes case vignettes that simulate GenAI-supported prioritization scenarios, reflection prompts to cultivate bias recognition and accountability, and rubric criteria to guide faculty in assessing ethical reasoning and oversight. Rather than prescribing fixed answers, the toolkit creates structured opportunities for dialogue, inquiry, and professional judgment. By embedding ethical reasoning into prioritization pedagogy, the toolkit positions faculty and students as critical evaluators rather than passive users of GenAI, reinforcing nursing's commitment to equity, justice, and patient-centered care. Situated within a broader global movement toward responsible and human-centered AI integration, this study contributes to nursing ethics by translating abstract principles into pedagogically actionable tools and modeling a methodology for adapting interdisciplinary frameworks into nursing-specific applications. Future work should pilot and evaluate the toolkit in authentic educational contexts, examining its impact on ethical reasoning, bias recognition, and collaborative decision making.

In the context of the accelerating digital transformation of higher education worldwide, Artificial Intelligence (AI) has emerged as a pivotal driver for innovating online learning models, enhancing teaching quality, and optimizing learners’ experiences. In Vietnam, private universities - characterized by institutional flexibility, intense competitive pressure, and a high degree of financial and academic autonomy - are increasingly required to adopt AI as a strategic instrument to improve educational quality and institutional competitiveness. Despite its significant potential, the implementation of AI in online training across Vietnamese private universities remains fragmented, unsystematic, and constrained by multiple challenges related to technological infrastructure, human resources, financial capacity, governance mechanisms, as well as ethical and legal frameworks. This study aims to provide a comprehensive examination of the current state of AI application in online education at private universities in Vietnam, to identify key barriers hindering effective implementation, and to propose strategic solutions tailored to the national and institutional context. Employing a mixed-methods research design, the study integrates quantitative survey data with qualitative insights derived from in-depth interviews with university leaders, faculty members, and students. The findings indicate that AI has been preliminarily applied in areas such as intelligent learning management systems, personalized learning pathways, AI-powered chatbots, and learning analytics. However, the depth and effectiveness of these applications remain limited, and their transformative potential has yet to be fully realized. Drawing on empirical evidence and international best practices, the paper proposes a strategic framework encompassing institutional governance reform, digital and AI-oriented capacity building, investment in data-driven infrastructure, and the development of a sustainable AI-enabled educational ecosystem for private higher education institutions. This study contributes to the growing body of literature on AI in higher education within developing country contexts, while also offering practical managerial and policy implications for advancing the digital transformation and long-term sustainability of Vietnam’s private university sector

Quantum-enhanced throughput pathways: Integrating Rodgers' TPM with quantum ethical frameworks for AI-driven cybersecurity.

Artificial intelligence in academic research publishing: updates, controversies, and considerations for pregnancy and perinatal research.

Beyond the genome: Ethical, social and legal implications of epilepsy genetics.

This study examines the historical development of medical ethics and the philosophy of medicine, emphasizing the significance of the Hippocratic Oath in contemporary medical practice. It outlines the Oath’s role as the earliest ethical framework regulating the doctor–patient relationship and its lasting influence on modern professional ethics. The study also highlights key ethical and philosophical challenges that arise from applying Hippocratic principles to today’s medical context. Using descriptive-analytical and historical methods, the research underscores the central importance of “medical ethics and the philosophy of medicine in the Hippocratic Oath and modern medicine.” The findings show that the Hippocratic Oath is the foundation of traditional medical ethics, yet modern medical-ethical issues have surpassed the standards set by Hippocrates and Galen. Given the profound transformations in the medical profession and the risk of dehumanization, returning to traditional Hippocratic values is no longer feasible. This calls for rethinking medical professionalism in a way that reflects the significant changes the field has undergone in recent decades.

To map the digital ethics studies published to date in the field of nursing. The integration of digitalization in the healthcare sector, especially in nursing care, is increasing. However, digitalization in nursing can raise professional, personal, and ethical concerns among nurses. A thorough discussion of digital ethics in nursing is still lacking in the literature. A scoping review was registered in the Open Science Framework and reported here according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews guidelines. The PubMed, CINAHL, and Scopus databases were searched. The reference lists of included studies were also screened. The results were summarized and discussed using the patterns, advances, gaps, evidence, and recommendations methodology. A total of 394 studies were identified, of which seven met the inclusion criteria and were included. Digital ethics have been investigated in the nursing field around three main themes: (i) knowledge and awareness of digital ethics; (ii) digital ethical violations in nursing care; and (iii) digital ethical violations regarding ethical principles. Overall, the concept of digital ethics in nursing is still in its early stages. It should be further developed and harmonized to help researchers search the literature and clinicians find available evidence. Additionally, the patterns identified in studies can serve as the basis for a digital ethics framework, which should be further refined. Digital technologies present several potential ethical implications at the (a) individual levels, affecting nurses and patients, and (b) collective levels, impacting all nurses, health systems, and citizens. Increasing awareness and knowledge, and developing guidelines specific to nursing, should be a priority to prevent and minimize risks. Codes of conduct should address these emerging issues and promote the ethical use of digital tools. Audits and monitoring systems should be established to detect additional risks and address them appropriately.

Forensic mental health research: The potential of Danish national registers.