New articles in this journal are licensed under a Creative Commons Attribution 4.0 United States License. This journal is published by the University Library System of the University of Pittsburgh as part of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 1 This journal is supported by the Carnegie Project on the Education Doctorate: A Knowledge Forum on the EdD (CPED) cpedinitiative.org impactinged.pitt.edu ISSN 2472-5889 (online) Vol.10 No.1 (2025) DOI 10.5195/ie.2025.529 New articles in this journal are licensed under a Creative Commons Attribution 4.0 United States License. This journal is published by Pitt Open Library Publishing. Introduction to the AI Special Edition Themed Issue The Role of Generative Artificial Intelligence (AI) in Doctoral Research and Writing James Dunnigan Arizona State University james.dunnigan@asu.edu Michael Kozak Drexel University michael.g.kozak@drexel.edu Nicole Pearce Texas A&M University-Commerce nicole.pearce@tamuc.edu Harriette Thurber Rasmussen Drexel University htr25@drexel.edu ABSTRACT This special AI-themed issue of the Impacting Education Journal examines the integration of generative artificial intelligence into EdD programs following the release of ChatGPT in 2022. This collection of articles explores three main themes: student use of AI in dissertation writing and research, faculty perspectives on AI integration, and institutional perspectives on AI's future impact on EdD programs. The articles investigate how students utilize generative AI tools for research assistance, how faculty develop frameworks for responsible AI implementation, and how institutions navigate the broader implications of generative AI use, including academic integrity and epistemic shifts. This very relevant and timely set of articles provides practitioners with guidance on current issues related to adapting to the use of generative AI in doctoral education. KEYWORDS Artificial Intelligence, ChatGPT, generative AI, EdD, scholar-practitioner With the release of ChatGPT in November 2022, generative artificial intelligence (AI) sparked unprecedented disruption across the educational landscape. Since that time, EdD programs have struggled to incorporate these new generative AI tools into their curricula and programs. In this special edition of the Impacting Education Journal, practitioners will find research, guidance, and practical considerations on how to reshape the doctoral journey with generative AI. Three themes emerged from the articles in this issue: Student Use of Generative AI in Dissertation Writing and Research, Faculty Perspectives and Frameworks for Integrating Generative AI into EdD Programs, and Institutional Perspectives on How Generative AI will Impact EdD Programs in the Future. In exploring the promises and challenges of integrating generative AI into EdD programs, we hope these articles will provide valuable insights to faculty, students, and program directors. STUDENT USE OF GENERATIVE AI IN DISSERTATION WRITING AND RESEARCH One of the earliest uses of generative AI in EdD programs related to dissertation writing and research. This set of articles documents the role, potential, and impact of generative AI as a support system for students and faculty. In addition, the articles examine how faculty are guiding students in using these tools in an academically responsible manner. The tension between ensuring academic integrity and embracing new technologies are explored in the articles, presenting perspectives of both students and faculty. In the essay, “Can AI Facilitate a Human-Centric Approach to Writing a Problem of Practice Dissertation? Insights from Doctoral Students,” Kell et al. explore the transformative potential of using generative AI to support students throughout their dissertation journey. Through narrative inquiry, it shares the experiences of two doctoral students writing dissertations in practice about AI, while simultaneously negotiating the use of it in their research and writing. The study, “An Examination of the Use of AI (Artificial Intelligence) Technology as Experienced by Scholarly Practitioners in an Educational Doctorate Program,” Harris et al. examined the applications and perceptions of AI tools in doctoral studies, focusing on their efficacy in enhancing research effectiveness. They found the most indicated uses of AI to be proofreading, researching scholarly articles for literature reviews, and the organization and structure of research. http://www.library.pitt.edu/ http://www.pitt.edu/ http://www.library.pitt.edu/articles/digpubtype/index.html http://www.library.pitt.edu/articles/digpubtype/index.html http://upress.pitt.edu/ http://creativecommons.org/licenses/by-nc-nd/3.0/us/ http://cpedinitiative.org/ https://library.pitt.edu/e-journals http://creativecommons.org/licenses/by-nc-nd/3.0/us/ https://orcid.org/0009-0007-6331-2975 https://orcid.org/0000-0002-9878-2471 https://orcid.org/0000-0002-2599-0691 Dunnigan et al. Impacting Education: Journal on Transforming Professional Practice impactinged.pitt.edu Vol. 10 No. 1 (2025) DOI 10.5195/ie.2025.529 2 Wilder and Calderone examine broader implications for scholarly practice in “Empowering Educational Leadership Research with Generative: Insights and Innovations from a Qualitative EdD Dissertation,”, focusing on the experiences between a doctoral student and supervisor when generative AI is used in the dissertation process. The article highlights the potential of generative AI to streamline data analysis and foster greater reflexivity and critical thinking in the research process, prompting researchers to consider their positionality and potential biases more thoroughly. In the article, “Navigating New Frontiers: AI's Transformation of Dissertation Research and Writing in an Educational Leadership Doctoral Program,” Khan addresses the imperativeness of providing students with guidance on leveraging AI advances and maintaining academic integrity across writing, teaching, and research. In their article, “Dissertation 2.0: An Action Research Study on Adapting with AI,” Grichko et al. engage both faculty and students in testing generative AI tools to make recommendations for guidelines on AI use for dissertation writing. Results showed AI use needed to be made clear and transparent alongside adopting a flexible approach to AI incorporation, given factors such as differing journal requirements. In their article, “Generative AI Use in an EdD Program: Informal, Independent Student Use and Formalized, Instructor-directed Use,” Buss et al. explored two ways AI has been used by students in their EdD program—informally and independently and in a more formalized, guided manner. Results suggested students were more confident to try out and utilize generative AI when instructors introduced it and students found the tools to be extremely helpful. FACULTY PERSPECTIVES AND FRAMEWORKS FOR INTEGRATING GENERATIVE AI INTO EDD PROGRAMS As generative AI continues to grow in importance in education, faculty members are struggling with how to best implement this technology in EdD programs. These articles provide valuable insights into the current landscape of generative AI use among EdD faculty, along with frameworks and critical questions for integrating generative AI into curricula and policies in ethical and effective ways. The authors explore faculty perceptions and usage of generative AI, the ways in which it can be used to support student learning in research methods, and how to implement generative AI responsibly. In the study, “Unlocking the Future: How are EdD Faculty Using Generative AI in Doctoral Research,” Black and Betts investigated faculty’s perceptions and use of generative AI and the ways they have leveraged the technology to support EdD students. In “Framework for Generative AI in Research Methods and Statistical Analysis Preparation,” Eith and Zawada propose a framework for integrating generative artificial intelligence (AI) tools into statistical training for Doctor of Education (EdD) students. They explore how generative AI can serve as a scaffold for learning, potentially mitigating statistics anxiety and enhancing students' ability to focus on core statistical concepts rather than software intricacies. In their article, “REPAC: Critical Questions to Inform EdD Programs in an Era of Generative Artificial Intelligence,” Langran et al. present a framework of critical questions designed to guide EdD program leaders and faculty in integrating generative artificial intelligence (GenAI) into their curricula and policies. The REPAC framework aids in reflecting, reenvisioning, and redesigning educational practices to better incorporate GenAI, focusing on how candidates learn with and about AI tools. INSTITUTIONAL PERSPECTIVES ON HOW GENERATIVE AI WILL IMPACT EDD PROGRAMS IN THE FUTURE While many articles in this special issue focus on the direct impact of generative AI on faculty and student work in dissertation writing, this set of articles explores the broader implications of generative AI integration in doctoral programs. They examine the evolving landscape of academic integrity, ethical considerations, and practical challenges that arise when generative AI tools become part of the educational experience. Topics range from institutional policies to anxieties surrounding academic dishonesty. These articles examine the issues that educators and students must navigate in the age of generative AI. In their essay, “The Education Doctorate in the Context of Gen AI: Epistemic Shifts and Challenges to Practical Wisdom,” Henriksen et al. examine the role of practitioner knowledge, specifically practical wisdom, in the context of GenAI–rooted in the Aristotelian notion of phronesis. They explore how GenAI, as an epistemic technology, might influence the nature of knowledge in education, proposing that EdD curricula must adapt to include digital criticality and humanistic awareness to navigate the ethical and practical challenges posed by AI. Azevedo and Valadez investigate the critical gaps in current governance frameworks regarding AI meeting assistant in “If Ferris Bueller had a bot: AI meeting assistant policy landscape of CPED member institutions” –They reveal a need to consider ethical, legal, and pedagogical implications of AI meeting assistants in EdD programs. In their article, “Nothing New under the Sun: Generative AI and Educator Anxiety over Academic Dishonesty,” Werse and Smith– using an historical context, argue that while there are valid worries about students using GAI in ways the displace student work, these anxieties are not new and have been observed with previous disruptive technologies such as the Internet. By recontextualizing this anxiety within a broader historical perspective, educators can develop strategies to mitigate academic dishonesty while leveraging the benefits of GAI integration in education. And finally, in his article, “GPT and Me: An Honest Reevaluation: The Dawn of Co-active Emergence,” Sanders explores the transformative concept of co-active emergence in education, where human and machine intelligence synergize to enhance learning experiences. Without question, generative AI is evolving almost more rapidly than can be documented. These articles, however, provide a foundation for thinking about the potentiality of generative AI to scaffold programs, support students, and help faculty navigate this new and exciting landscape, while framing the caveats and areas that warrant further investigation. We extend our gratitude to all the authors for their innovative research and thoughtful analyses, and hope that this collection will inspire further dialogue and development in the intersection of generative AI and educational leadership. James Dunnigan Arizona State University Michael Kozak Drexel University Nicole Pearce Texas A&M University-Commerce Harriette Thurber Rasmussen Drexel University Student Use of Generative AI in Dissertation Writing and Research Faculty Perspectives and Frameworks for Integrating Generative AI into EdD Programs Institutional Perspectives on How Generative AI Will Impact EdD Programs in the Future