This is your indispensable guide to navigating the rise of generative AI as an academic. It thoughtfully explores rapidly evolving AI capabilities reshaping higher education, examining challenges and ethical dilemmas across the sector.

Our world is becoming ever more data-driven, transforming how business is conducted, governance enacted, and knowledge produced. Yet, the nature of data and the scope and implications of the changes taking place are not always clear. The Data Revolution is a must read for anyone interested in why data have become so important in the contemporary era.

Thoroughly updated, including ten new chapters, the book provides an accessible and comprehensive: introduction to thinking conceptually about t...

This title works to provide students with an introduction to different types of artistic expression within early childhood. Combining theory, research and practical strategies, the authors present how the arts can be beneficial in fostering inclusion through a range of settings.

Now in its fourth edition, this bestselling title provides an easy to navigate roadmap for anyone undertaking a research project in the applied social sciences

With the latest theory and research, this book provides a multidimensional model of how positive psychology can be applied in far-ranging contexts such as society, religion, the classroom and the workplace.

The only accessible, practical and discipline-specific qualitative methods textbook on the market. Introduces theoretical issues in parallel with step-by-step guidance on ‘how to do qualitative research’ and ‘how it has been done’ in seminal published research.

Let this practical, easy-to-use toolkit guide you through embedding critical SEL competencies into your virtual classrooms and make SEL a way of being for you and your students-anytime, anywhere.

An Introduction to Political and Social Data Analysis (With R) provides students with an accessible overview of practical data analysis while also providing a gentle introduction to the R programming environment. Author Thomas M. Holbrook patiently explains each step in statistical analysis with R, avoiding complicated tools or packages.