With new coverage of how conceptual frameworks are conceptualized and developed and of a student's perspective on the role of conceptual frameworks, this book presents conceptual frameworks as a mechanism - process and product.

Written with those with limited mathematical and statistical knowledge in mind, this concise and practical guide helps researchers to do their research in new and alternative ways.

This is a complete social worker's guide to undertaking qualitative, quantitative and mixed-methods research.

With a strong emphasis on reflectivity and reflexivity, this book provides placement students with a guide to critically studying an organization from the inside, and is particularly suited to those needing to do a reflective journal or essay as part of their studies.

An insider's guide to what university tutors really want from an essay or assignment, this witty guide gives you practical tips and techniques on how to craft the perfect assignment and achieve the best grades.

Providing readers with an introduction to how to conduct a research synthesis of literature, this Fifth Edition has new material on the use of the internet and other new developments in technology, including new statistics for describing meta-analytic results

A new edition of this popular student guide to content analysis. Widely adopted on research methods courses across the social sciences.

Ideal for those new to teaching Research Methods, as well as more experienced instructors looking for new ways to engage their students, this applied resource places 100 activities - each accompanied by tutor notes and students handouts (also downloadable) - right at the instructor's fingertips.

With a strong focus on using less traditional forms of data, the Third Edition provides a new perspective on issues such as the role of the researcher and the impact they have on data, and also considers the impact of social, cultural and political complexities across a range of disciplines.

This practical book uses a step-by-step analysis of realistic examples to help students understand the theory and code for implementing propensity score analysis with the R statistical language.