This book explores Learning Analytics (LA) programmes and practices in Malaysia as well as looking at the underlying forces, dilemmas and policy challenges for quality assurance in higher education institutions (HEIs). This chapters provide a comprehensive discussion of trends in academic quality assurance in higher education. It articulates a combination of theoretical issues and empirical analysis and offers a comprehensive guide to stakeholders in Management and Faculty on LA implementation in HEIs where the model in this book can be used to pave the way for a successful LA initiative. Learning Analytics is an emerging multidisciplinary technological practice with the ultimate goal of producing effective learning to improve students’ achievement in the tertiary level. The Learning Analytics model of Quality Assurance in this book is an essential guide for any faculty or manager in higher education, or researchers in higher education and learning analytics.

This book explores Learning Analytics (LA) programmes and practices in Malaysia as well as looking at the underlying forces, dilemmas and policy challenges for quality assurance in higher education institutions (HEIs). This chapters provide a comprehensive discussion of trends in academic quality assurance in higher education. It articulates a combination of theoretical issues and empirical analysis and offers a comprehensive guide to stakeholders in Management and Faculty on LA implementation in HEIs where the model in this book can be used to pave the way for a successful LA initiative. Learning Analytics is an emerging multidisciplinary technological practice with the ultimate goal of producing effective learning to improve students' achievement in the tertiary level. The Learning Analytics model of Quality Assurance in this book is an essential guide for any faculty or manager in higher education, or researchers in higher education and learning analytics.

Learning analytics (or educational big data) tools are increasingly being deployed on campuses to improve student performance, retention and completion, especially when those metrics are tied to funding. Providing personalized, real-time, actionable feedback through mining and analysis of large data sets, learning analytics can illuminate trends and predict future outcomes. While promising, there is limited and mixed empirical evidence related to its efficacy to improve student retention and completion. Further, learning analytics tools are used by a variety of people on campus, and as such, its use in practice may not align with institutional intent. This monograph delves into the research, literature, and issues associated with learning analytics implementation, adoption, and use by individuals within higher education institutions. With it, readers will gain a greater understanding of the potential and challenges related to implementing, adopting, and integrating these systems on their campuses and within their classrooms and advising sessions. This is the fifth issue of the 43rd volume of the Jossey-Bass series ASHE Higher Education Report. Each monograph is the definitive analysis of a tough higher education issue, based on thorough research of pertinent literature and institutional experiences. Topics are identified by a national survey. Noted practitioners and scholars are then commissioned to write the reports, with experts providing critical reviews of each manuscript before publication.

The emergence of fully online, hybrid and blended forms of higher education has led governments, quality assurance agencies and higher education institutions (HEIs) across the OECD to reflect on how to ensure that digital education provides learners with opportunities to reach learning and employment outcomes similar to those achieved through traditional in person instruction. Building on stakeholder engagement and comparative analysis, this report offers an assessment of Hungary’s quality assurance system for higher education and, more specifically, its strengths and weaknesses for assuring the quality of digital higher education.

"Examining the Australian and Indian higher education systems, one is first struck by the contrast in size. Australia has about 200 institutions, including 39 universities, while India has over 26,000 institutions, including 504 universities. Notwithstanding the difference in size, structure and regulatory mechanisms and sometimes the priorities, the two systems have several institutional arrangements and process in common. ... The publication covers areas specific to the trends, emerging challenges and opportunities related to higher education and quality assurance when education crosses national borders."--Preface.

This book examines the critical aspect of quality assurance maintenance of competitive-standards in African higher education. It explores both the micro and macro-levels of continental African higher education regulatory authorities, and analyses different institutional, regional and national practices for moving towards continental quality assurance approaches. Contributed to by scholars across Eastern and Southern Africa, the book considers conceptual, practical, epistemological and policy dimensions of quality and quality assurance, especially in relation to higher education in Africa. It therefore draws on research and local expertise to open up debate about how to assure and enhance the quality of higher education, providing a comprehensive review of eight countries and considers societal challenges. It aims to satisfy the need of more thoughtful and critical works on African education as produced by African educators. The uniqueness of this book lies in integrating both the theoretical and practical dimensions of quality to devise appropriate strategies for ensuring quality and standards in higher education in continental Africa and beyond. This authoritative book advocates for a timely discussion around the prpvision of good quality higher education and research in African universities, and will be of great interest to academics, policy makers, researchers and post-graduate students in the fields of higher education, comparative education and African studies.

In the rapidly evolving landscape of industrial activities, artificial intelligence (AI) has emerged as a powerful force driving transformative change. Among its many applications, AI has proven to be instrumental in reducing processing costs associated with optimization challenges. The intersection of AI with optimization and multi-criteria decision making (MCDM) techniques has led to practical solutions in diverse fields such as manufacturing, transportation, finance, economics, and artificial intelligence. Using Traditional Design Methods to Enhance AI-Driven Decision Making delves into a wide array of topics related to optimization, decision-making, and their applications. Drawing on foundational contributions, system developments, and innovative techniques, the book explores the synergy between traditional design methods and AI-driven decision-making approaches. The book is ideal for higher education faculty and administrators, students of higher education, librarians, researchers, graduate students, and academicians. Contributors are invited to explore a wide range of topics, including the role of AI-driven decision-making in leadership, trends in AI-driven decision-making in Industry 5.0, applications in various industries such as manufacturing, transportation, healthcare, and banking services, as well as AI-driven optimization in mechanical engineering and materials.