This book introduces a novel approach to data analysis in the social sciences: personal knowledge management (PKM) as and for postqualitative inquiry (PQI).
Both PKM and PQI approaches are increasingly gaining traction amongst global audiences, yet scholars continue to grapple with how best to apply these principles in practice. Exploring how the ideas of ‘postqualitative analysis’ and ‘personal knowledge management’ speak to each other, and how this dialogue can be of use to those who engage in research and communication, the book seeks to answer these questions in an accessible, practical way. It draws not only on scholarly literature, but also real-world case studies and experiences to showcase how knowledge workers can apply these concepts in their own context. It specifically describes how PKM techniques – which are typically conceived as a way to organise information – can also be used to facilitate the interpretation and analysis of research data.
The book is appropriate for readers who are new to PKM, PQI, or both, including undergraduate or postgraduate dissertation students, postdocs, and more established researchers.
Table of Contents:
Acknowledgements
Chapter 1: Introduction and definition of key terms
Chapter 2: Introduction to personal knowledge management
Chapter 3: Introduction to posthumanism and postqualitative inquiry
Chapter 4: PKM as/for postqualitative inquiry: examples from the literature
Chapter 5: PKM as/for postqualitative inquiry: examples from my practice
Chapter 6: What should be the role of AI in PKM?
Chapter 7: Final thoughts
About the Author :
Caitlin R. Kight is a Senior Lecturer in Education Studies at the University of Exeter, UK.
