Educational Technology and Digital Learning

Background: Digital technologies increasingly shape educational access, communication, assessment, knowledge production, and institutional decision-making. However, technology adoption does not inherently improve learning and may reproduce inequalities, intensify surveillance, or weaken pedagogical relationships when implemented without clear educational purposes and appropriate safeguards. Objective: This study develops a human-centered framework for aligning educational technology with meaningful, equitable, and trustworthy digital learning. Methods: An integrative conceptual review was conducted by synthesizing research on online learning, learning sciences, digital competence, learning analytics, artificial intelligence, accessibility, and technology governance, together with major international policy frameworks. The literature was examined across five dimensions: educational purpose, pedagogy, technology, governance, and evidence. Results: The synthesis resulted in a Human-Centered Digital Learning Ecosystem model in which learner agency and public value guide pedagogical design, technology functions as adaptable infrastructure, and privacy, safety, transparency, and accountability govern data-intensive educational practices. The framework identifies six implementation priorities: universal and meaningful access, educator professional capacity, active and socially connected pedagogy, assessment redesign, responsible data and AI governance, and sustainable digital system architecture. A cyclical improvement process is proposed encompassing goal definition, collaborative design, human-supported implementation, and systematic review of educational outcomes and potential harms. Conclusions: Effective digital learning depends less on the novelty of technological tools than on the coherence and quality of the educational ecosystem in which they are embedded. Educational institutions should move beyond procurement-led digitization toward pedagogically grounded, evidence-informed, accessible, and democratically governed digital transformation. The proposed framework provides a practical foundation for designing and evaluating trustworthy digital learning systems while maintaining learner agency, educational equity, and institutional responsibility.

Authors

Youshan Ma

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Health Promotion and Lifelong Learning for Sustainable Human Development

Background: Health promotion and lifelong learning are often addressed as separate policy domains, despite their shared goal of strengthening individuals’ and communities’ capacity to respond to changing social, technological, environmental, and demographic conditions. Fragmented governance limits their potential contribution to equitable well-being and sustainable development. Objective: This conceptual study develops an integrated framework that conceptualizes lifelong health learning as a continuous capability-building process across the life course. Methods: An integrative review and framework synthesis were conducted across scholarship on health promotion, health literacy, adult learning, the capability approach, social determinants of health, and sustainable development. Foundational theories and international policy frameworks were systematically compared across four analytical dimensions: purpose, agency, context, and outcomes. Results: The synthesis identifies a recursive pathway linking structural enablers, lifelong health learning, human capabilities, and sustainable human development. Lifelong learning enhances individuals’ capacity to access, understand, appraise, apply, reflect on, and co-create health knowledge, while health promotion provides supportive environments, participatory governance, and action addressing social determinants. Their integration can strengthen personal agency, resilience, social participation, and adaptive livelihoods when equitable access, digital inclusion, cultural relevance, and institutional responsiveness are embedded as core conditions. A multi-level implementation model is proposed across schools, workplaces, health services, community organizations, learning cities, and digital platforms, supported by an evaluation architecture encompassing inputs, processes, capabilities, outcomes, and equity. Conclusions: Sustainable human development requires more than episodic health information or isolated adult education. It requires inclusive learning ecosystems in which individuals and communities continuously develop the knowledge, confidence, relationships, and decision-making capabilities needed to build healthy lives, participate meaningfully in society, and shape supportive environments. The proposed framework provides a conceptual basis for integrating lifelong learning and health promotion within sustainable and equity-oriented policy systems

Authors

Ziming Wang

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Artificial Intelligence-Driven Curriculum Innovation for Future-Oriented Educ ation

Background: Generative artificial intelligence (AI), learning analytics, intelligent tutoring systems, and automated content-generation technologies are reshaping how curricula are designed, implemented, assessed, and continuously renewed. However, current educational responses remain largely technology-centered and fragmented, with insufficient attention to pedagogical purpose, teacher agency, learner participation, and equity. Objective: This study develops an integrated model of AI-driven curriculum innovation to support future-oriented education. Methods: A qualitative conceptual review and thematic policy analysis were conducted by synthesizing research on curriculum theory, AI in education, competency-based learning, assessment, teacher agency, inclusion, and educational data governance. The analysis identified recurring principles and mechanisms through which AI can contribute to curriculum transformation. Results: Five interdependent functions of AI-supported curriculum innovation were identified: anticipatory curriculum intelligence, adaptive content orchestration, inquiry-centered learning design, authentic assessment and feedback, and continuous curriculum evaluation. These functions constitute the Future-Oriented AI Curriculum Innovation Model (FACIM), which is guided by six core principles: human purpose, professional agency, learner participation, equity, transparency, and evidence-based decision-making. Conclusions: AI should enhance curriculum responsiveness and adaptability without replacing professional educational judgment or reducing knowledge and learning to algorithmic personalization. Future-oriented curriculum development requires a balanced integration of enduring disciplinary knowledge, interdisciplinary competencies, ethical and social formation, and adaptive learning pathways. The FACIM framework provides a conceptual and practical foundation for guiding responsible AI integration, curriculum reform, and evidence-informed educational innovation.

Authors

Haihuan XU

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Artificial Intelligence Applications in Physical Education and Sport Science

Background: Artificial intelligence (AI) is rapidly transforming physical education and sport science through applications in movement analysis, personalized instruction, performance prediction, injury-risk management, and administrative decision-making. However, its educational and scientific value depends on effective pedagogical integration, reliable data, professional oversight, and equitable access. Objective: This study synthesizes emerging applications of AI in physical education and sport science and develops a human-centered framework for responsible and sustainable adoption. Methods: A structured conceptual review and thematic policy analysis were conducted based on research concerning computer vision, wearable sensing, machine learning, learning analytics, sport performance, and AI ethics. AI applications were systematically examined according to their primary purpose, data sources, users, potential benefits, and associated risks. Results: Five major application domains were identified: intelligent assessment, personalized learning, performance analytics, health and safety support, and program governance. Based on these domains, the study proposes the Human-Centered AI for Physical Education and Sport Science (HAIPESS) framework, structured around five principles: pedagogical purpose, multimodal evidence, professional judgment, learner agency, and accountable governance. Conclusions: AI should function as an augmentative technology rather than a substitute for teachers, coaches, clinicians, and researchers. Responsible adoption requires valid and reliable measurement, robust privacy protection, transparent and explainable systems, inclusive design, AI literacy, and continuous evaluation of educational, performance, and health outcomes. The HAIPESS framework provides a practical foundation for integrating AI into physical education and sport science while maintaining human agency, professional responsibility, and educational quality.

Authors

Hui Yu

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Reimagining Educational Policy for Sustainable Learning in the Digital Era

Background: Digital transformation, artificial intelligence (AI), climate uncertainty, demographic change, and widening inequality are reshaping the goals, structures, and governance requirements of contemporary education systems. Policy arrangements designed around institutional stability, standardized provision, and periodic reform are increasingly inadequate for supporting continuous, equitable, and resilient learning. Objective: This study reimagines educational policy through the concept of sustainable learning and develops an integrated framework for governing education in the digital era. Methods: A qualitative conceptual policy analysis was combined with a structured synthesis of international scholarship and policy documents, focusing on recurring principles related to digital education, AI governance, lifelong learning, inclusion, institutional resilience, and sustainable development. Results: The study proposes a Sustainable Educational Policy Innovation Model (SEPIM), comprising five mutually reinforcing dimensions: values-based policy leadership, inclusive digital innovation, collaborative governance, institutional adaptability, and continuous evaluation. The model demonstrates that technology contributes to educational sustainability only when embedded within public purposes, human agency, equitable capacity building, and accountable feedback mechanisms. Conclusions: Sustainable learning requires a shift from technology-centered modernization toward human-centered adaptive governance. Educational policy should conceptualize digital infrastructure as a public learning resource, safeguard rights and professional autonomy, strengthen institutional capacity through sustainable financing, and evaluate long-term educational value rather than short-term technology adoption. SEPIM provides a practical analytical framework for educational policy design, implementation, and comparative research in the context of digital transformation and sustainable development.

Authors

Cunwan Gong

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