The book begins with real-world, international insights and experiences of AI as a research methodology and offers the history and principles of AI. Next, it provides ways of linking and differentiating these activities and exploring the range of ways to engage AI in change-focused research and practice - from research question and research design through data collection, data analysis, interpretation, and dissemination of findings. And perhaps most importantly, the book places AI in the context of other research paradigms and approaches, addressing positivist versus naturalistic stances, social constructionist concepts, and related methods and methodologies such as action research, PAR, ethnography, case studies, and narrative inquiry.
This book is appropriate for use in graduate-level methods courses devoted to appreciative inquiry, change- or community-based research, organizational development and change, and related topics across the social sciences, education, and management. It will also prove invaluable to researchers and professionals who are interested in using AI but need to know how to frame this approach within the greater context of traditional research.
- Comprehensive introduction to Appreciative Inquiry (AI) and the range of debates that it can generate for a researcher or professional used to employing otherwise traditional research models
- International examples from recent published and unpublished projects in which AI was used, with an emphasis on those that shaped policy, planning, and future practices
- Discussion and guidance on how to make the connections between AI and various research paradigms and approaches to research, including positivist versus naturalistic research, social constructionist concepts, action research PAR, ethnography, narrative inquiry, and case studies
- An assessment of the strengths and limitations of AI in research environments
- Practical guidance and ideas for generating different research questions, managing, organizing, and analyzing data, and communicating and disseminating the final results
- Individual and group exercises that draw on organizational development techniques as a way to bring AI concepts to life through practice.