Explore the vast range of titles available.

Moral development is crucial for a meaningful life. Many well-founded approaches and models are present in the moral development literature, which is a very diverse and populated field. The model of a 'person of moral growth' presented in this paper is a contribution to moral growth research based on personalist virtue ethics. Personalist virtue ethics puts the person at the centre of the moral reflection, addressing the holistic interplay of the person's dimensions in the process of moral growth. The model is an operationalization of the person's dimensions for educational and research purposes in the field of moral development. In this paper, the four components of the model are presented: emotional-cognitive, decisional (free commitment to moral growth), practical (moral growth through personal action), and self-understanding (the moral growth identity), and the process of the elaboration of the model is explained. For enhancing the construct validity of the model, its components and pedagogical implications are discussed in the light of recent moral education literature. This model is a contribution to a more cogent moral education and is helping to design and deliver moral educational experiences which address personal moral development in a clear, convincing, and well-structured way.

Firms increasingly deploy algorithmic pricing approaches to determine what to charge for their goods and services. Algorithmic pricing can discriminate prices both dynamically over time and personally depending on individual consumer information. Although legal, the ethicality of such approaches needs to be examined as often they trigger moral concerns and sometimes outrage. In this research paper, we provide an overview and discussion of the ethical challenges germane to algorithmic pricing. As a basis for our discussion, we perform a systematic interpretative review of 315 related articles on dynamic and personalized pricing as well as pricing algorithms in general. We then use this review to define the term algorithmic pricing and map its key elements at the micro-, meso-, and macro levels from a business and marketing ethics perspective. Thus, we can identify morally ambivalent topics that call for deeper exploration by future research.

This study examined whether the nominal personalization of a storybook about sharing impacted preschool-aged children’s perceived similarity with the main character or their likelihood of comprehending the moral lesson and applying it to their own behavior. Children were read either a personalized story about sharing, a non-personalized story about sharing, or a control story not about sharing. Perceived similarity with the main character was measured by participants’ self-references produced during a story retelling task, comprehension was measured through retelling and open-ended questions, and participants’ prosocial behavior was measured with a sticker sharing task both prior to and following the story reading. The amount of spontaneous speech produced by the participant during the storybook reading was also measured to gauge whether children’s engagement with and understanding of the story was affected by storybook type. Results showed that nominally personalized books did not encourage greater comprehension or more sharing behavior than the other two types of books, though both stories with a sharing moral did elicit more detailed retellings than the control story. These results suggest that books with nominal personalization do not necessarily help children understand the moral of a story and apply it to their own lives. Limitations to these findings and avenues for future research on the degree and type of personalization that may be effective for promoting prosocial behaviors in preschoolers are discussed.

The integration of Artificial Intelligence (AI) into early childhood education presents new opportunities and challenges in fostering cognitive, social, and emotional development. This theoretical discussion synthesizes recent research on AI’s role in personalized learning, educational robotics, gamified learning, and social-emotional development. The study explores theoretical frameworks such as Vygotsky’s Sociocultural Theory, Distributed Cognition, and the Five Big Ideas Framework to understand AI’s impact on young learners. AI-powered personalized learning platforms enhance engagement and adaptability, while robotics and gamification foster problem-solving and collaboration. Additionally, AI tools support children with disabilities, promoting inclusivity and accessibility. However, ethical concerns related to privacy, bias, and teacher preparedness pose challenges to effective AI integration. Furthermore, the long-term effects of AI on children’s social skills and emotional intelligence require further investigation. This theoretical discussion emphasizes the need for interdisciplinary collaboration to develop AI-driven educational strategies that prioritize developmental appropriateness, equity, and ethical considerations. The findings highlight AI’s potential as a transformative educational tool, provided it is implemented thoughtfully and responsibly. The paper aims to address the following research question: How can artificial intelligence (AI) be meaningfully and ethically integrated into early childhood education to enhance learning, while preserving developmental and relational values?

This study investigates undergraduate English majors' perceptions of ChatGPT in enhancing vocabulary and grammar in academic writing. Utilizing a mixed-methods convergent design, data were collected from 31 students via pre- and post-survey questionnaires, 20 participants’ reflective journals, and semi-structured interviews with 10 volunteers. Quantitative findings revealed significant improvements in students’ perceptions of vocabulary accuracy, relevance, and depth. Thematic analysis of qualitative data identified benefits such as enriched vocabulary, improved grammatical accuracy, and increased confidence in academic writing. Challenges included overdependence, difficulty interpreting feedback, and a lack of originality in AI-generated suggestions. Students employed strategies to optimize ChatGPT use, such as asking specific questions, selectively applying feedback, and balancing AI input with personal judgment. The study highlights ChatGPT's ability to provide tailored feedback, foster confidence, and support vocabulary development while underscoring the importance of responsible use to mitigate overreliance and maintain originality. The findings underscore ChatGPT's potential to enhance academic writing skills when integrated thoughtfully into curricula. However, overuse risks shallow learning (e.g., overdependence on the tool, or difficulty in interpreting feedback), suggesting a need for instructional strategies that can promote rigorous analysis with AI tools. Future research should explore long-term impacts, comparisons with other AI tools, and strategies for ethical and effective integration of ChatGPT in higher education.

Gamified education is undergoing a transformative shift, heralding a new era in the landscape of learning. This evolution is characterized by the advent of personalized learning experiences, underpinned by artificial intelligence (AI), and the seamless integration of virtual and augmented reality (VR/AR) technologies. These trends are not merely additive but are synergistically enhancing the learning experience, making it more dynamic, engaging, and effective than ever before. Personalized learning through AI is at the forefront of this transformation. AI algorithms are being leveraged to tailor educational content to the individual learner’s needs, preferences, and learning pace. This ensures that each student receives a customized learning experience that is optimized for their personal learning journey, maximizing engagement and efficacy. The integration of VR and AR technologies into gamified education is another significant trend. These technologies provide immersive learning environments that can simulate real-world scenarios or abstract concepts, thereby facilitating a deeper understanding and retention of knowledge. VR and AR make learning more interactive and enjoyable, which in turn, increases motivation and engagement among learners. Data-driven insights are playing a crucial role in the evolution of gamified education. By analyzing data on learner performance and behavior, educators can gain valuable insights into the effectiveness of teaching strategies and learning materials. This enables continuous improvement of the learning experience, ensuring that it remains relevant, engaging, and effective. Ethical considerations are paramount as gamified education continues to evolve. Issues such as privacy, data security, and equitable access to educational technologies are critical and must be addressed to ensure that gamified education benefits all learners, without compromising their rights or well-being. As technology, pedagogy, and game design converge, gamified education is evolving from a passive to an active, participatory model. This transformation empowers students to take charge of their educational journeys, offering a path to personalized, engaging, and data-driven learning experiences. The future of gamified education promises to be dynamic and inclusive, reshaping the future of learning in profound ways.

In addition to the longstanding threat posed by narrow economism, faith in the possibility of peace and progress through democratic politics – central to the humanistic vision of the 1972 Faure report – today faces additional challenges. These challenges include the ascendancy of neurocentrism in the global policyscape. Whereas the effects of neoliberalism on education have been extensively critiqued, the implications of a newer, related ideological framework known as neuroliberalism remain under-theorised. Neuroliberalism combines neoliberal ideas concerning the role of markets in addressing social problems with beliefs about human nature ostensibly grounded in the behavioural, psychological and neurological sciences. This article critically examines a recent initiative of one of UNESCO’s Category 1 Institutes – the Mahatma Gandhi Institute of Education for Peace and Sustainable Development (MGIEP) – that seeks to mainstream neuroscience and digital technology within global educational policy. Comparing the visions of the 1972 Faure, the 1996 Delors and the 2021 Futures of Education reports with MGIEP’s International Science and Evidence Based Education Assessment (ISEEA), the authors analyse continuity and change in UNESCO’s attempts to articulate a vision of “scientific humanism” which advocates the use of science for the betterment of humanity. They argue that ISEEA’s overall recommendations – as represented in its Summary for Decision Makers (SDM) – reinforce a reductive, depoliticised vision of education which threatens to exacerbate educational inequality while enhancing the profits and power of Big Tech. These recommendations exemplify a neuroliberal turn in global education policy discourse, marking a stark departure from the central focus on ethics and democratic politics characteristic of UNESCO’s landmark education reports. Reanimating, in cruder form, visions of a scientifically-organised utopia of the kind that attracted UNESCO’s inaugural Director-General, Julian Huxley, ISEEA’s recommendations actually point towards the sort of dystopian “brave new world” of which his brother, Aldous Huxley, warned.

AI driven language learning platforms and applications have revolutionized traditional teaching methods by offering interactive and adaptable tools. These platforms provide personalized study schedules and appropriate materials using natural language processing (NLP) and machine learning algorithms based on the participants’ proficiency level, learning preferences and skills. The integration of AI in foreign language education through virtual reality (VR) and augmented reality (AR) enables immersive learning experiences. With the help of such interactive virtual environments, our students may practice their speaking skills in authentic contexts while gaining a greater awareness of cultures. AI also has an impact on language assessment since automated evaluation systems examine students' spoken and written language. Immediate feedback on pronunciation, grammar and proficiency enables targeted interventions to effectively address specific knowledge gaps. AI-driven language translation services help overcome language barriers, fostering intercultural dialogue and international cooperation. These programs help people with different linguistic origins to exchange ideas, promoting multi-cultural understanding and fostering a more interconnected network. However, the use of AI in language learning raises ethical concerns, including data privacy and biases in language models. To ensure responsible and efficient foreign language learning, it is crucial to balance maximizing AI’s potential with addressing its challenges. AI's revolutionizes foreign language education by making it more individualized, immersive, and inclusive for students with different learning styles. In this regard, teachers’ role is decisive in unleashing AI's full potential to foster linguistic competency and embrace a linked global community by its conscious and ethical use.

La Inteligencia Artificial (IA) está transformando la educación superior al facilitar un aprendizaje personalizado. A través de algoritmos avanzados, ajusta los contenidos educativos a las necesidades individuales de los estudiantes, brindando una experiencia más eficiente y adaptada. Los sistemas de IA analizan datos de rendimiento estudiantil, ofreciendo retroalimentación y recursos personalizados según el nivel y estilo de cada alumno; sin embargo, su implementación presenta desafíos como la privacidad de datos, la equidad en el acceso, y el riesgo de deshumanizar la educación. Este estudio examina el impacto de la IA en la educación superior, abordando sus beneficios y retos para una integración ética y efectiva.

PurposeThe study aims to reflect on past research, uncover current trends and propose a future research agenda in the field of artificial intelligence (AI) for competency-based personalised learning.Design/methodology/approachThe study followed the SPAR-4-SLR protocol to retrieve 855 articles related to the field indexed in the Scopus database. Performance analysis, network analysis and science mapping were then performed using VOSviewer and the Biblioshiny app.FindingsThe analysis identified nine clusters of intellectual structure (healthcare, competencies, learning systems, digital transformation, AI literacy, computer-aided education, AI ethics, e-learning and active learning) and twelve themes (including motor, basic, emerging and niche).Originality/valueFollowing an extensive review of the literature, this would appear to be the first study to provide a panoramic view of AI for competency-based personalised learning based on the Scopus database. The core gaps in the current literature have been identified and the corresponding future agenda will be instrumental in shaping future research directions in the field.