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This book provides a comprehensive exploration of the integration of artificial intelligence (AI) into academic research, specifically tailored for higher education institutions and postgraduate research (PGR) students. It addresses the unique challenges and opportunities that these institutions and students encounter when incorporating AI into research. The work emphasises practical case studies, step-by-step guides on AI tools and techniques, ethical considerations in AI usage, and features contributions from experts across various disciplines. Following the introduction, the book delves into the specifics of how AI can enhance academic research such as literature review, data analysis and interpretation, and assistance in academic writing across different disciplines. The wide range of topics introduced in this book is supported by practical examples and guidance. This book also explores the landscape of current AI applications in research, the methodologies for effectively leveraging AI technologies, and the critical ethical dimensions of AI work. The importance of interdisciplinary collaboration in expanding the use of AI in research is covered in this book by drawing on expert insights to provide a rich, multifaceted understanding of the potential of AI in academia. The combination of topics in this book can empower PGR students to navigate the complexities of AI in their research. The book is a much-needed compilation prepared by leading scholars in the field of digital technology to help PGRs, as well as decision-makers, determine the best ways to integrate and use AI tools in research.
List of contents
Part 1: The Role of AI in Advancing Research in Higher Education.- Chapter 1. Introduction to AI in Research.- Chapter 2: Understanding GenAI's Perception in Higher Education.- Chapter 3: AI Tools and Technologies for Academic Research.- Part 2: Practical Applications and Excellence in AI-Driven Research.- Chapter 4: AI in Literature Reviews.- Chapter 5: AI in Data Analysis.- Chapter 6: Interpreting Research Outcomes with AI.- Chapter 7: AI-Assisted Writing and Editing.- Part 3: Ethical Considerations in AI-Enabled Research.- Chapter 8: Ethical Implications and Governance of AI in Research.- Chapter 9: Data Integrity and AI Ethics.- Part 4: Policy Perspectives and Future Directions in AI and Higher Education.- Chapter 10: AI Policy in Academic Institutions.- Chapter 11: The Horizon of AI in Academic Research.
About the author
Professor Xue Zhou is a Professor in AI in Business Education at the University of Leicester and a Principal Fellow of the Higher Education Academy (PFHEA). Her research explores digital literacy, the integration of AI in education, digital technology adoption, and cross-cultural adjustment. She is particularly focused on embedding AI meaningfully and ethically into business education to enhance student learning, drive inclusive innovation, and promote future-ready skills. Professor Zhou has been recognised with numerous awards, including the British Academy of Management Education Practice Award (Highly Commended) and the President and Principal’s Education Excellence Award for her pioneering AI Literacy Training initiative. She has led transformative work on AI-enhanced assessment, equipping students to critically evaluate, interpret, and co-create with AI tools in data-driven environments. She has delivered keynotes at national and international conferences on AI in education, digital transformation, and pedagogical innovation, and was shortlisted in the AI in Education category at the QS Reimagine Education Awards. Professor Zhou also serves as an Associate Editor and as a judge for prestigious educational awards, contributing to the global dialogue on responsible and impactful AI adoption in higher education.
Dr Hosam Al-Samarraie is an Associate Professor in Digital Innovation Design at the University of Leeds, UK. His research lies at the intersection of human–computer interaction, higher education, and machine learning. His work on digital innovations involves the development of new ideas and concepts aimed at maximising the performance of online learning systems that are tailored to specific student needs, behaviours, cultures, and intentions, rather than being based on assumed or generalised models. He has led several projects on the design and development of adaptive interfaces across various settings. These include the utilisation of EEG and eye-movement data to inform the design of enhanced learning experiences. He has also contributed to the development of numerous online learning scenarios, including virtual learning environments that support learners’ understanding of complex concepts. His work has received media attention for its methodological contributions and advancement of knowledge in the field. With over 100 peer-reviewed journal publications, his research output has gained international recognition, culminating in his inclusion in Stanford University's prestigious list of the "World's Top 2%" scientists in his field. In 2020, he was awarded the Silver Medal by the Market Research Society in London for his research on understanding social behaviour on microblogs. He currently serves on the editorial board of the HCI section of PLOS One and has acted as a guest editor for other key academic journals
Summary
This book provides a comprehensive exploration of the integration of artificial intelligence (AI) into academic research, specifically tailored for higher education institutions and postgraduate research (PGR) students. It addresses the unique challenges and opportunities that these institutions and students encounter when incorporating AI into research. The work emphasises practical case studies, step-by-step guides on AI tools and techniques, ethical considerations in AI usage, and features contributions from experts across various disciplines. Following the introduction, the book delves into the specifics of how AI can enhance academic research such as literature review, data analysis and interpretation, and assistance in academic writing across different disciplines. The wide range of topics introduced in this book is supported by practical examples and guidance. This book also explores the landscape of current AI applications in research, the methodologies for effectively leveraging AI technologies, and the critical ethical dimensions of AI work. The importance of interdisciplinary collaboration in expanding the use of AI in research is covered in this book by drawing on expert insights to provide a rich, multifaceted understanding of the potential of AI in academia. The combination of topics in this book can empower PGR students to navigate the complexities of AI in their research. The book is a much-needed compilation prepared by leading scholars in the field of digital technology to help PGRs, as well as decision-makers, determine the best ways to integrate and use AI tools in research.
