As a species, we are currently experiencing dramatic shifts in our lifestyle, family structure, health, and global contact. Evolutionary Anthropology provides a powerful theoretical framework to study such changes, revealing how current environments and legacies of past selection shape human diversity. This book is the first major review of the emerging field of Applied Evolutionary Anthropology bringing together the work of an international group of evolutionary scientists, addressing many of the major public health and social issues of this century. Through a series of case studies that span both rural and urban situations in Africa, Asia, Europe and South America, each chapter addresses topics such as natural resource management, health service delivery, population growth and the emergence of new family structures, dietary, and co-operative behaviours. The research presented identifies the great, largely untapped, potential that Applied Evolutionary Anthropology holds to guide the design, implementation and evaluation of effective social and public health policy. This book will be of interest to policy-makers and applied researchers, along with academics and students across the biological and social sciences.
The book aims to advance global knowledge and practice in applying data science to transform higher education learning and teaching to improve personalization, access and effectiveness of education for all. Currently, higher education institutions and involved stakeholders can derive multiple benefits from educational data mining and learning analytics by using different data analytics strategies to produce summative, real-time, and predictive or prescriptive insights and recommendations. Educational data mining refers to the process of extracting useful information out of a large collection of complex educational datasets while learning analytics emphasizes insights and responses to real-time learning processes based on educational information from digital learning environments, administrative systems, and social platforms.
This volume provides insight into the emerging paradigms, frameworks, methods and processes of managing change to better facilitate organizational transformation toward implementation of educational data mining and learning analytics. It features current research exploring the (a) theoretical foundation and empirical evidence of the adoption of learning analytics, (b) technological infrastructure and staff capabilities required, as well as (c) case studies that describe current practices and experiences in the use of data analytics in higher education.