Synopsis
What makes research credible, rigorous, and relevant in today's rapidly evolving scientific landscape? Research Methodology: Integrating Generative AI in Contemporary Research Practices offers a comprehensive yet accessible guide for students, researchers, and professionals seeking clarity and confidence in conducting research.Spanning foundational theories to emerging trends such as generative AI, open science, and citizen-led research, this book walks readers through every stage of the research process-from identifying meaningful problems and designing robust studies to analysing data and communicating findings ethically. It also explores research in the digital age, addressing algorithmic experimentation, dataset ethics, and responsible innovation.Designed with undergraduate learners in mind and aligned with the National Education Policy (NEP) 2020, the book follows a pedagogical approach that encourages critical thinking and inquiry-based learning. Clear learning objectives, examples, and reflective exercises help readers connect theory with practice, while a "How to Navigate This Book" roadmap guides learners through its structure.
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About the Authors
Dr Geetika Vashishta is an Assistant Professor in the Department of Computer Science at the College of Vocational Studies, University of Delhi. She holds a Ph.D. in Data Science and has a strong academic and professional background that bridges industry and higher education. Prior to joining academia, she worked as a software engineer with leading organizations including Aricent Technologies Limited and Samsung Engineering Labs. Motivated by a long-standing passion for teaching, she transitioned to academic life after qualifying the National Eligibility Test (NET) and has been serving as an Assistant Professor at the University of Delhi since 2013.
Dr Om Pal is an Associate Professor in the Department of Computer Science at the University of Delhi, India. He holds a B.E. in Computer Science and Engineering from Dr B. R. Ambedkar University, Agra; an MBA in Operations and Management from IGNOU; an M.S. (Research) in Cryptography from IIT Bombay; a postgraduate diploma in Cyber Law, Cyber Crime Investigation and Digital Forensics from the National Law Institute University, Bhopal; and a PhD in Information Security from Jamia Millia Islamia, New Delhi. He has over 20 years of academic and research experience in diverse areas of Computer Science.
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Hardcover. Condition: new. Hardcover. What makes research credible, rigorous, and relevant in today's rapidly evolving scientific landscape? Research Methodology: Integrating Generative AI in Contemporary Research Practices offers a comprehensive yet accessible guide for students, researchers, and professionals seeking clarity and confidence in conducting research.Spanning foundational theories to emerging trends such as generative AI, open science, and citizen-led research, this book walks readers through every stage of the research process-from identifying meaningful problems and designing robust studies to analysing data and communicating findings ethically. It also explores research in the digital age, addressing algorithmic experimentation, dataset ethics, and responsible innovation.Designed with undergraduate learners in mind and aligned with the National Education Policy (NEP) 2020, the book follows a pedagogical approach that encourages critical thinking and inquiry-based learning. Clear learning objectives, examples, and reflective exercises help readers connect theory with practice, while a "How to Navigate This Book" roadmap guides learners through its structure. Practical guide to using generative AI across the research workflow, from framing research questions to data analysis and academic writing, with a clear focus on dataset ethics, transparency and responsible innovation. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9789349919679
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Hardcover. Condition: new. Hardcover. What makes research credible, rigorous, and relevant in today's rapidly evolving scientific landscape? Research Methodology: Integrating Generative AI in Contemporary Research Practices offers a comprehensive yet accessible guide for students, researchers, and professionals seeking clarity and confidence in conducting research.Spanning foundational theories to emerging trends such as generative AI, open science, and citizen-led research, this book walks readers through every stage of the research process-from identifying meaningful problems and designing robust studies to analysing data and communicating findings ethically. It also explores research in the digital age, addressing algorithmic experimentation, dataset ethics, and responsible innovation.Designed with undergraduate learners in mind and aligned with the National Education Policy (NEP) 2020, the book follows a pedagogical approach that encourages critical thinking and inquiry-based learning. Clear learning objectives, examples, and reflective exercises help readers connect theory with practice, while a "How to Navigate This Book" roadmap guides learners through its structure. Practical guide to using generative AI across the research workflow, from framing research questions to data analysis and academic writing, with a clear focus on dataset ethics, transparency and responsible innovation. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9789349919679
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Hardcover. Condition: new. Hardcover. What makes research credible, rigorous, and relevant in today's rapidly evolving scientific landscape? Research Methodology: Integrating Generative AI in Contemporary Research Practices offers a comprehensive yet accessible guide for students, researchers, and professionals seeking clarity and confidence in conducting research.Spanning foundational theories to emerging trends such as generative AI, open science, and citizen-led research, this book walks readers through every stage of the research process-from identifying meaningful problems and designing robust studies to analysing data and communicating findings ethically. It also explores research in the digital age, addressing algorithmic experimentation, dataset ethics, and responsible innovation.Designed with undergraduate learners in mind and aligned with the National Education Policy (NEP) 2020, the book follows a pedagogical approach that encourages critical thinking and inquiry-based learning. Clear learning objectives, examples, and reflective exercises help readers connect theory with practice, while a "How to Navigate This Book" roadmap guides learners through its structure. Practical guide to using generative AI across the research workflow, from framing research questions to data analysis and academic writing, with a clear focus on dataset ethics, transparency and responsible innovation. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9789349919679