Cheng articulates the extent to which knowledge management approaches can create Intellectual Capital (IC) and contribute to improvements in education quality. He argues that public schools have long contended with the requirements of quality assurance in a competitive environment of decreasing student numbers, increasing parental choice and rising standards of accountability. As public organisations, schools have to demonstrate appropriate resource management and show evidence that they are meeting defined development plans and goals. Cheng proposes a strategic approach, IC management, to help schools respond to and cope with the increasingly competitive environment while enhancing school capacity for improving student learning. First, the book guides readers to understand the development of IC theory in the context of education to address the requirements of quality assurance and accountability. It then introduces Lesson Study, e-Learning, and Information and Communication Technology (ICT) as key resources and drivers for building school IC, and examines the organisational factors that enable knowledge management approaches for developing IC in schools from both Asia and Europe. It concludes by offering strategies and implementation methods to manage school IC for sustainable development. Combining research from Asia and Europe, this edited volume will be useful for school leaders and policy makers, as well as those researching school leadership and IC.

This edited book is a collection of selected research papers presented at the 2021 2nd International Conference on Artificial Intelligence in Education Technology (AIET 2021), held in Wuhan, China on July 2-4, 2021. AIET establishes a platform for AI in education researchers to present research, exchange innovative ideas, propose new models, as well as demonstrate advanced methodologies and novel systems. Rapid developments in artificial intelligence (AI) and the disruptive potential of AI in educational use has drawn significant attention from the education community in recent years. For educators entering this uncharted territory, many theoretical and practical questions concerning AI in education are raised, and issues on AI's technical, pedagogical, administrative and socio-cultural implications are being debated. The book provides a comprehensive picture of the current status, emerging trends, innovations, theory, applications, challenges and opportunities of current AI in education research. This timely publication is well-aligned with UNESCO's Beijing Consensus on Artificial Intelligence (AI) and Education. It is committed to exploring how best to prepare our students and harness emerging technologies for achieving the Education 2030 Agenda as we move towards an era in which AI is transforming many aspects of our lives. Providing a broad coverage of recent technology-driven advances and addressing a number of learning-centric themes, the book is an informative and useful resource for researchers, practitioners, education leaders and policy-makers who are involved or interested in AI and education.

This book analyses the organisation cultures that promote Japanese Lesson Study, identifies the soul of lesson study, which is missing in other cultures, and discusses the conditions for successfully transplanting the Lesson Study to other cultures. Adopting Nonaka and Tateuchi's (1995) SECI knowledge creation model as the analytical lens, it explores the tacit and explicit knowledge convention and creation processes in lesson study. Unpacking the mechanism of the knowledge management process and practices could assist policy makers and school administrators, educators in contextualising lesson study to their school systems. The book provides an accessible discussion of the benefits and challenges of introducing lesson study, and presents three new research dimensions to analyse it: reviewing the historical development of lesson study in terms of the pendulum swings between professional accountability and state accountability in developing the school-based curriculum and the national curriculum; examining lesson study as a knowledge management tool for creating pedagogical knowledge for curriculum implementation: and studying the "kaizen kata" embedded in the PDCA cycles of lesson study as an organization routine for school improvement.

This edited book is a collection of selected research papers presented at the 2021 2nd International Conference on Artificial Intelligence in Education Technology (AIET 2021), held in Wuhan, China on July 2-4, 2021. AIET establishes a platform for AI in education researchers to present research, exchange innovative ideas, propose new models, as well as demonstrate advanced methodologies and novel systems. Rapid developments in artificial intelligence (AI) and the disruptive potential of AI in educational use has drawn significant attention from the education community in recent years. For educators entering this uncharted territory, many theoretical and practical questions concerning AI in education are raised, and issues on AI’s technical, pedagogical, administrative and socio-cultural implications are being debated. The book provides a comprehensive picture of the current status, emerging trends, innovations, theory, applications, challenges and opportunities of current AI in education research. This timely publication is well-aligned with UNESCO’s Beijing Consensus on Artificial Intelligence (AI) and Education. It is committed to exploring how best to prepare our students and harness emerging technologies for achieving the Education 2030 Agenda as we move towards an era in which AI is transforming many aspects of our lives. Providing a broad coverage of recent technology-driven advances and addressing a number of learning-centric themes, the book is an informative and useful resource for researchers, practitioners, education leaders and policy-makers who are involved or interested in AI and education.

This edited book is a collection of selected research papers presented at the 2022 3rd International Conference on Artificial Intelligence in Education Technology (AIET 2022), held in Wuhan, China, on July 1-3, 2022. AIET establishes a platform for AI in education researchers to present research, exchange innovative ideas, propose new models, as well as demonstrate advanced methodologies and novel systems. The book is divided into five main sections - 1) AI in Education in the Post-COVID New Norm, 2) Emerging AI Technologies, Methods, Systems and Infrastructure, 3) Innovative Practices of Teaching and Assessment Driven by AI and Education Technologies, 4) Curriculum, Teacher Professional Development and Policy for AI in Education, and 5) Issues and Discussions on AI In Education and Future Development. Through these sections, the book provides a comprehensive picture of the current status, emerging trends, innovations, theory, applications, challenges and opportunities of current AI in education research. This timely publication is well aligned with UNESCO's Beijing Consensus on Artificial Intelligence (AI) and Education. It is committed to exploring how AI may play a role in bringing more innovative practices, transforming education in the post-pandemic new norm and triggering an exponential leap toward the achievement of the Education 2030 Agenda. Providing broad coverage of recent technology-driven advances and addressing a number of learning-centric themes, the book is an informative and useful resource for researchers, practitioners, education leaders and policy-makers who are involved or interested in AI and education.

The book illustrates how Lesson Study can be applied to craft metacognitive teaching strategies to enhance students' learning to learn competencies. Based on the findings of an empirical study of a university-funded teaching development project, this book reports how to apply Lesson Study and Learning Study to enhance teachers' metacognitive teaching competencies with a view to tackling the impacts and challenges created by and underlying the learning to learn curriculum. The book allows readers to experience metacognitive learning by sorting the prior knowledge on the metacognition, setting the goal and planning reading schedule, checking their understanding and progress, evaluating what they have or have not learned and reflected on their reading experience and feelings. Readers can grasp the key concept underpinning metacognitive teaching, including teaching strategies for developing students' metacognitive abilities that include working on problem-solving activities, working on small collaborative groups, making metacognitive and learning strategies explicit, and encouraging students to reflect upon and talk about their learning.

This book introduces the application of knowledge management (KM) theories, practices, and tools in school organization for sustainable development. Schools in Asia Pacific have long faced a variety of challenges in terms of sustainable development under the education reforms and curriculum reforms to meet the demands of a knowledge society. Schools are inevitably expected to develop human capital for the knowledge society within the competitive global economy, and to interact with its policy environment and know how to leverage pedagogical knowledge. The high speed of expansion change and expansion of knowledge have dramatically influence the development of flexibility of teacher and school works. The nature of teacher work becomes increasingly less routine, more analytical, and disruptive yet often come with a sense of urgency and need to be more collaborative. Teachers not only require data and information, but also knowledge and experience of individual, they also need to collaborative task execution, decision making and problem solving. Helping school leaders and teachers to manage their knowledge and become "know how" to cope with the change is important.