Doing a PhD: An optimal self-help AI-proof guide (11/2026)
HARDCOPY FORMAT: 212 pages in A4 size (8.5 x 11ins/ 210x 297 mm)
ISBN 978176488006 (eBook), 978176488013 (paperback), 978176488020 (hardback)
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SUBJECTS: 1. University postgraduate researchers, 2. PhD student drop-out rates, 3. ‘The lost PhD’, 4. AI academic writing tools and technologies, 5. The emergent method of research-based academic writing 6. Optimal academic knowledge-building as ‘deep learning’ 7. Socratic models of academic inquiry
OVERVIEW :
‘Doing a PhD’ is a self-help AI-proof guide to more effective academic dissertation (or other) writing and knowledge-building
How can researchers learn to think, write, and build knowledge more effectively—and avoid losing their way in the process? Drawing on several decades of experience working with PhD students, this book develops a practical “emergent method of academic writing” designed to bring thinking and language-use into a more productive relationship. At its core is a simple idea: academic writing is not merely a way of reporting what we already know. It is a means of developing ideas, exploring questions, making connections, and constructing knowledge. By working from a focused question or problem and following a related thread of inquiry, researchers can develop their thinking through the process of writing itself. The approach has relevant application well beyond doctoral research. But its particular value lies in addressing the distinctive challenges of research-based academic writing and the experience and process of “doing a PhD.”
The book develops the emergent method into a broader “foolproof approach to optimal knowledge building,” including an analysis of the four ways and stages in which researchers can “lose their way.” This provides a framework for understanding the phenomenon of the “lost PhD” and for recognizing some of the difficulties that can interrupt or derail doctoral research. Central to the approach is deep learning—not simply acquiring information, but developing the capacity to understand, transform, apply, and communicate knowledge. In particular, the ability to generate and express ideas in our own words becomes a fundamental part of developing intellectual independence and scholarly mastery. These issues have become even more significant with the rapid development of generative AI, specialised AI agents, and chatbot-based technologies. The book examines the important distinction between using AI as a tool to support research and writing, and allowing AI to become a co-creator that increasingly directs or takes over the intellectual process.
Ultimately, this book presents a framework for (optimal) thinking through writing, writing through inquiry, and building knowledge through the process of research and related problem-solving inquiry. It is intended not simply to help researchers complete a PhD, but to support the development of the intellectual independence, scholarly judgement, and mastery of knowledge that doctoral education is supposed to achieve.
SUBJECTS: University postgraduate researchers; PhD student drop-out rates; ‘the lost PhD’; AI academic writing tools and technologies; emergent method of research-based academic writing; optimal knowledge-building as deep learning; Socratic models of academic inquiry
CONTENTS
Preface – Why this book? [1-6]
- The temptation of AI (and other ‘shortcuts’) as part of the 21st Century ‘publish or perish’ challenge to human knowledge?[7-19]
Part A. A ‘foolproof’ self-help guide to remedying the four ways and stages in which inexperienced academic researchers and (other) writers so often ‘get lost’
- The ‘headless chicken PhD’? The related four key ways and stages that postgraduates (and others) ‘get lost’ in the research-based academic writing process [23-30]
- The relevance of the emergent method of academic inquiry for knowledge-building [31-50]
- A foolproof ‘AI-proof’ guide as antidote for the four key symptoms of a ‘lost PhD ’ [51-72]
Part B . Words, ideas, and optimal-knowledge-building
- Word, Ideas, and optimal-knowledge-building as ‘deep learning’: Elements of an emerging ‘foolproof’ (and AI-proof) approach’ to academic writing and research inquiry (etc.) [75-132]
Part C. Related essays
6.The example of a PhD design using an emergent ‘foolproof’ approach: The challenge of refining WTO e-commerce policies to be more relevant to emerging economies (a ‘supervisory collaboration’ with F. Farroknia) [135-141]
- Optimal grounded theory’? Words, ideas, and optimal policy-building using an adapted version of grounded theory [143-155]
- Re-framing ‘Academic English proficiency’? The teaching and learning of academic writing in ESL and intercultural as well as native speaker contexts [157-175]
- Re-framing ‘Academic English proficiency’? The teaching and learning of academic writing in ESL and intercultural as well as native speaker contexts [173-189]
References [195-199]