Call for Chapters: Advanced AI-Assisted Methodologies in Ethical Research Design, Data Collection, and Analysis

Editors

John Branch, University of Michigan, United States
Bryan Christiansen, Southern New Hampshire University, United States

Call for Chapters

Proposals Submission Deadline: July 16, 2026
Full Chapters Due: October 29, 2026
Submission Date: October 29, 2026

Introduction

Artificial Intelligence (AI) is rapidly transforming the global research ecosystem across the social sciences, business, education, healthcare, engineering, humanities, and interdisciplinary domains. From automated literature reviews and AI-assisted coding to predictive analytics, synthetic data generation, and generative AI-supported scholarly writing, researchers are increasingly integrating intelligent systems into every stage of the research lifecycle. Despite widespread adoption, there remains a substantial gap in methodological guidance regarding the responsible, rigorous, and discipline-sensitive integration of AI into scholarly inquiry. Existing books tend to focus narrowly on technical AI applications or generalized discussions of digital transformation without offering comprehensive methodological frameworks applicable across disciplines. This publication addresses this gap by presenting a comprehensive, interdisciplinary reference work examining how AI technologies are reshaping research design, data collection, analysis, interpretation, validation, ethics, reproducibility, and dissemination.

Objective

The primary objective of this publication is to provide a comprehensive scholarly reference on the integration of artificial intelligence into contemporary research methodologies across academic disciplines. Specific objectives include the following: 1) Examining how AI tools reshape research design and methodological decision-making; 2) Exploring AI-assisted approaches to qualitative, quantitative, mixed, and computational research; 3) Identifying ethical, epistemological, and governance implications of AI-supported research; 4) Providing discipline-specific applications and methodological frameworks; 5) Addressing reproducibility, transparency, and bias in AI-assisted scholarly practices; 6) Establishing best practices for responsible AI integration in academic research workflows; and 7) Supporting graduate education and doctoral research training in emerging AI-enabled methodologies.

Target Audience

Primary audiences include Researchers, Faculty members, Doctoral students, Postdoctoral scholars, Methodologists, Research administrators, and Data scientists. Secondary audiences include Academic libraries, Policy researchers, Business intelligence researchers, and Computational social scientists.

Recommended Topics

Section I — Foundations of AI-Assisted Research Chapter 1: Introduction to AI-Assisted Research Methodologies Chapter 2: The Evolution of Artificial Intelligence in Scholarly Research Chapter 3: Epistemological Implications of AI-Enhanced Knowledge Production Chapter 4: Human-AI Collaboration in Research Design Chapter 5: AI Literacy and Research Competencies in Higher Education

Section II — AI in Research Design and Literature Review Chapter 6: Generative AI for Research Problem Identification Chapter 7: AI-Assisted Systematic Literature Reviews Chapter 8: Automated Knowledge Mapping and Bibliometric Analysis Chapter 9: AI Tools for Hypothesis Development Chapter 10: Prompt Engineering for Scholarly Research Applications

Section III — AI-Assisted Qualitative Research Chapter 11: AI-Supported Interview Analysis Chapter 12: Natural Language Processing in Qualitative Research Chapter 13: Automated Thematic Coding and Interpretation Chapter 14: AI in Digital Ethnography and Online Community Research Chapter 15: Trustworthiness and Bias in AI-Assisted Qualitative Inquiry

Section IV — AI-Assisted Quantitative and Computational Methods Chapter 16: Machine Learning Applications in Quantitative Research Chapter 17: Predictive Analytics in Social and Behavioral Sciences Chapter 18: Synthetic Data Generation and Research Simulation Chapter 19: AI-Enhanced Survey Design and Sampling Chapter 20: Big Data and Computational Social Science Methodologies

Section V — Mixed Methods and Interdisciplinary Applications Chapter 21: AI-Integrated Mixed Methods Frameworks Chapter 22: Cross-Disciplinary Research Using AI Systems Chapter 23: AI-Assisted Educational Research Chapter 24: AI Applications in Healthcare and Public Health Research Chapter 25: AI in Business, Organizational, and Market Research

Section VI — Ethics, Governance, and Research Integrity Chapter 26: Ethical Frameworks for AI-Assisted Research Chapter 27: Algorithmic Bias and Fairness in Research Systems Chapter 28: Transparency, Reproducibility, and Open Science Chapter 29: Research Integrity and AI-Generated Scholarship Chapter 30: Institutional Policy and Governance for AI in Research

Section VII — Future Directions Chapter 31: Emerging Trends in Autonomous Research Systems Chapter 32: AI and the Future of Doctoral Education Chapter 33: The Future of Peer Review and Scholarly Publishing Chapter 34: Global Perspectives on AI-Assisted Research Chapter 35: Toward Responsible and Sustainable AI-Enabled Scholarship

Submission Procedure

Researchers and practitioners are invited to submit on or before July 16, 2026, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by July 30, 2026 about the status of their proposals and sent chapter guidelines.Full chapters of a minimum of 10,000 words (word count includes references and related readings) are expected to be submitted by October 29, 2026, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ prior to submission. All submitted chapters will be reviewed on a double-anonymized review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Advanced AI-Assisted Methodologies in Ethical Research Design, Data Collection, and Analysis. All manuscripts are accepted based on a double-anonymized peer review editorial process.

All proposals should be submitted through the eEditorial Discovery® online submission manager.

Publisher

This book is scheduled to be published by IGI Global Scientific Publishing, an international academic publisher of the "Information Science Reference", "Medical Information Science Reference", "Business Science Reference", and "Engineering Science Reference" imprints. IGI Global Scientific Publishing specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com. This publication is anticipated to be released in 2027.

Indexing Information for Prospective Authors

IGI Global Scientific Publishing meets the criteria for inclusion in major indexing services such as Scopus; however, it is important to note that all indexing decisions are made independently by these services. IGI Global Scientific Publishing books are selectively indexed by the indexing organization after publication. Indexing cannot be guaranteed for any book prior to publication, and the indexing organization has complete control over the final selection and timeline.

Important Dates

July 16, 2026: Proposal Submission Deadline
July 30, 2026: Notification of Acceptance
October 29, 2026: Full Chapter Submission
December 31, 2026: Review Results Returned
February 11, 2027: Final Acceptance Notification
February 25, 2027: Final Chapter Submission

Inquiries

John Branch, PhD
University of Michigan
jdbranch@umich.edu

Bryan Christiansen, MBA, MS**
Southern New Hampshire University
b.christiansen@snhu.edu

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