This timely Handbook explores the use of emerging digital technologies in education, demonstrating how learning analytics, adaptive technologies and artificial intelligence can be implemented to achieve pedagogical goals. As digital technologies become integral to education, chapters discuss how the focus is shifting from whether to use these tools, to how they can best support teaching and learning. Contributors address concerns surrounding data privacy, transparency and practical use, emphasising the importance of professional development and collaboration among educators, leaders and stakeholders. Drawing on empirical insights, chapters highlight the potential of learning analytics and adaptive learning to personalise education and improve outcomes for all students. This insightful Handbook promotes thoughtful policy, robust infrastructure and a thorough understanding of the professional and ethical contexts in which these tools are deployed.The Handbook of Learning Analytics and Adaptive Learning in Schools is an essential resource for scholars and students interested in educational technology, particularly those exploring the impact of data mining and learning analytics. It is also highly beneficial for educators and policymakers looking to ensure these emerging tools are used purposefully and in alignment with curriculum goals.

This timely Handbook explores the use of emerging digital technologies in education, demonstrating how learning analytics, adaptive technologies and artificial intelligence can be implemented to achieve pedagogical goals. As digital technologies become integral to education, chapters discuss how the focus is shifting from whether to use these tools, to how they can best support teaching and learning. Contributors address concerns surrounding data privacy, transparency and practical use, emphasising the importance of professional development and collaboration among educators, leaders and stakeholders. Drawing on empirical insights, chapters highlight the potential of learning analytics and adaptive learning to personalise education and improve outcomes for all students. This insightful Handbook promotes thoughtful policy, robust infrastructure and a thorough understanding of the professional and ethical contexts in which these tools are deployed.The Handbook of Learning Analytics and Adaptive Learning in Schools is an essential resource for scholars and students interested in educational technology, particularly those exploring the impact of data mining and learning analytics. It is also highly beneficial for educators and policymakers looking to ensure these emerging tools are used purposefully and in alignment with curriculum goals.

This timely Handbook explores the use of emerging digital technologies in education, demonstrating how learning analytics, adaptive technologies and artificial intelligence can be implemented to achieve pedagogical goals. As digital technologies become integral to education, chapters discuss how the focus is shifting from whether to use these tools, to how they can best support teaching and learning. Contributors address concerns surrounding data privacy, transparency and practical use, emphasising the importance of professional development and collaboration among educators, leaders and stakeholders. Drawing on empirical insights, chapters highlight the potential of learning analytics and adaptive learning to personalise education and improve outcomes for all students. This insightful Handbook promotes thoughtful policy, robust infrastructure and a thorough understanding of the professional and ethical contexts in which these tools are deployed.The Handbook of Learning Analytics and Adaptive Learning in Schools is an essential resource for scholars and students interested in educational technology, particularly those exploring the impact of data mining and learning analytics. It is also highly beneficial for educators and policymakers looking to ensure these emerging tools are used purposefully and in alignment with curriculum goals.

This open access book expands the scholarly and policy debates surrounding digital transformation in higher education. The authors adopt a pluralistic conceptual framework which uncovers three analytical elements – contexts, mediations, and type of effects – for unpacking empirical manifestations. The publicly funded higher education systems in Nordic countries provide solid empirical insights into how digital transformations have gained ground before and during the COVID-19 pandemic, and chapter contributions demonstrate how international digitalisation trends (such as in the global EdTech industry) impact on the core activities of higher education institutions (HEIs). The findings underscore the importance of assessments that consider multiple sub-systems within HEIs, as well as the complex relationships between them. By unpacking Nordic dynamics in the light of global processes and developments, the approach adopted and the results generated are of relevance to a much broader, global audience of students and researchers in higher education.

This timely Handbook explores the use of emerging digital technologies in education, demonstrating how learning analytics, adaptive technologies and artificial intelligence can be implemented to achieve pedagogical goals. As digital technologies become integral to education, chapters discuss how the focus is shifting from whether to use these tools, to how they can best support teaching and learning. Contributors address concerns surrounding data privacy, transparency and practical use, emphasising the importance of professional development and collaboration among educators, leaders and stakeholders. Drawing on empirical insights, chapters highlight the potential of learning analytics and adaptive learning to personalise education and improve outcomes for all students. This insightful Handbook promotes thoughtful policy, robust infrastructure and a thorough understanding of the professional and ethical contexts in which these tools are deployed.The Handbook of Learning Analytics and Adaptive Learning in Schools is an essential resource for scholars and students interested in educational technology, particularly those exploring the impact of data mining and learning analytics. It is also highly beneficial for educators and policymakers looking to ensure these emerging tools are used purposefully and in alignment with curriculum goals.

This timely Handbook explores the use of emerging digital technologies in education, demonstrating how learning analytics, adaptive technologies and artificial intelligence can be implemented to achieve pedagogical goals. As digital technologies become integral to education, chapters discuss how the focus is shifting from whether to use these tools, to how they can best support teaching and learning. Contributors address concerns surrounding data privacy, transparency and practical use, emphasising the importance of professional development and collaboration among educators, leaders and stakeholders. Drawing on empirical insights, chapters highlight the potential of learning analytics and adaptive learning to personalise education and improve outcomes for all students. This insightful Handbook promotes thoughtful policy, robust infrastructure and a thorough understanding of the professional and ethical contexts in which these tools are deployed.The Handbook of Learning Analytics and Adaptive Learning in Schools is an essential resource for scholars and students interested in educational technology, particularly those exploring the impact of data mining and learning analytics. It is also highly beneficial for educators and policymakers looking to ensure these emerging tools are used purposefully and in alignment with curriculum goals.

This timely Handbook explores the use of emerging digital technologies in education, demonstrating how learning analytics, adaptive technologies and artificial intelligence can be implemented to achieve pedagogical goals. As digital technologies become integral to education, chapters discuss how the focus is shifting from whether to use these tools, to how they can best support teaching and learning. Contributors address concerns surrounding data privacy, transparency and practical use, emphasising the importance of professional development and collaboration among educators, leaders and stakeholders. Drawing on empirical insights, chapters highlight the potential of learning analytics and adaptive learning to personalise education and improve outcomes for all students. This insightful Handbook promotes thoughtful policy, robust infrastructure and a thorough understanding of the professional and ethical contexts in which these tools are deployed.The Handbook of Learning Analytics and Adaptive Learning in Schools is an essential resource for scholars and students interested in educational technology, particularly those exploring the impact of data mining and learning analytics. It is also highly beneficial for educators and policymakers looking to ensure these emerging tools are used purposefully and in alignment with curriculum goals.

This open access book expands the scholarly and policy debates surrounding digital transformation in higher education. The authors adopt a pluralistic conceptual framework which uncovers three analytical elements – contexts, mediations, and type of effects – for unpacking empirical manifestations. The publicly funded higher education systems in Nordic countries provide solid empirical insights into how digital transformations have gained ground before and during the COVID-19 pandemic, and chapter contributions demonstrate how international digitalisation trends (such as in the global EdTech industry) impact on the core activities of higher education institutions (HEIs). The findings underscore the importance of assessments that consider multiple sub-systems within HEIs, as well as the complex relationships between them. By unpacking Nordic dynamics in the light of global processes and developments, the approach adopted and the results generated are of relevance to a much broader, global audience of students and researchers in higher education.