Impacting Education: Journal on Transforming Professional Practice
https://impactinged.pitt.edu/ojs/ImpactingEd
<p>"<em>When you do your work and you innovate and examine it, make it public; Invite others to critique it; and Pass it on</em>." <br>- Dr. Lee Shulman, President Emeritus, Carnegie Foundation for the Advancement of Teaching.</p>University Library System, University of Pittsburghen-USImpacting Education: Journal on Transforming Professional Practice2472-5889<p>Authors who publish with this journal agree to the following terms:</p><ol><li>The Author retains copyright in the Work, where the term “Work” shall include all digital objects that may result in subsequent electronic publication or distribution.</li><li>Upon acceptance of the Work, the author shall grant to the Publisher the right of first publication of the Work.</li><li>The Author shall grant to the Publisher and its agents the nonexclusive perpetual right and license to publish, archive, and make accessible the Work in whole or in part in all forms of media now or hereafter known under a <a title="CC-BY" href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a> or its equivalent, which, for the avoidance of doubt, allows others to copy, distribute, and transmit the Work under the following conditions:<ol type="a"><li>Attribution—other users must attribute the Work in the manner specified by the author as indicated on the journal Web site;</li></ol>with the understanding that the above condition can be waived with permission from the Author and that where the Work or any of its elements is in the public domain under applicable law, that status is in no way affected by the license.</li><li>The Author is able to enter into separate, additional contractual arrangements for the nonexclusive distribution of the journal's published version of the Work (e.g., post it to an institutional repository or publish it in a book), as long as there is provided in the document an acknowledgement of its initial publication in this journal.</li><li>Authors are permitted and encouraged to post online a prepublication manuscript (but not the Publisher’s final formatted PDF version of the Work) in institutional repositories or on their Websites prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work. Any such posting made before acceptance and publication of the Work shall be updated upon publication to include a reference to the Publisher-assigned DOI (Digital Object Identifier) and a link to the online abstract for the final published Work in the Journal.</li><li>Upon Publisher’s request, the Author agrees to furnish promptly to Publisher, at the Author’s own expense, written evidence of the permissions, licenses, and consents for use of third-party material included within the Work, except as determined by Publisher to be covered by the principles of Fair Use.</li><li>The Author represents and warrants that:<ol type="a"><li>the Work is the Author’s original work;</li><li>the Author has not transferred, and will not transfer, exclusive rights in the Work to any third party;</li><li>the Work is not pending review or under consideration by another publisher;</li><li>the Work has not previously been published;</li><li>the Work contains no misrepresentation or infringement of the Work or property of other authors or third parties; and</li><li>the Work contains no libel, invasion of privacy, or other unlawful matter.</li></ol></li><li>The Author agrees to indemnify and hold Publisher harmless from Author’s breach of the representations and warranties contained in Paragraph 6 above, as well as any claim or proceeding relating to Publisher’s use and publication of any content contained in the Work, including third-party content.</li></ol><p><span style="font-size: 75%;">Revised 7/16/2018. Revision Description: Removed outdated link. </span></p>Introduction to the AI Special Edition Themed Issue
https://impactinged.pitt.edu/ojs/ImpactingEd/article/view/529
<p>This special AI-themed issue of the <em>Impacting Education Journal</em> 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.</p>James DunniganMichael KozakNicole PearceHarriette Thurber Rasmussen
Copyright (c) 2025 James Dunnigan, Michael Kozak, Nicole Pearce, Harriette Thurber Rasmussen
https://creativecommons.org/licenses/by/4.0
2025-02-072025-02-071011–21–210.5195/ie.2025.529Can AI Facilitate a Human-Centric Approach to Writing a Problem of Practice Dissertation?
https://impactinged.pitt.edu/ojs/ImpactingEd/article/view/482
<p class="AbstractParagraph" style="text-indent: 0in;">This essay explores the evolving role of generative AI within EdD programs, highlighting its transformative potential 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 essay centers around AI and the CPED framework, in particular, concepts of the problem of practice, inquiry as practice, and mentoring. By documenting these experiences, this essay offers valuable insights for students, faculty, and program directors navigating the integration of AI in doctoral education.</p>Carrie KellBrian KraeerWilliam Cain
Copyright (c) 2025 Carrie Kell, Brian Kraeer, William Cain
https://creativecommons.org/licenses/by/4.0
2025-02-072025-02-071013710.5195/ie.2025.482An Examination of the Use of AI (Artificial Intelligence) Technology as Experienced by Scholarly Practitioners in an Educational Doctorate Program
https://impactinged.pitt.edu/ojs/ImpactingEd/article/view/472
<p class="AbstractParagraph" style="text-indent: 0in;">This study examined the applications and perceptions of AI tools in doctoral studies, focusing on their efficacy in enhancing research effectiveness. A survey found that most participants used AI tools in their doctoral studies (63%), with the majority of those users reporting some positive impact from their usage. The most indicated uses of AI were proofreading, researching scholarly articles for literature reviews, and the organization and structure of research. Future research may include a larger sample size and examine instruments for alignment with the program practices and curriculum to best capture responses that indicate participants' program-specific use of AI tools. The study concluded that AI tools have not yet been integrated into research within doctoral studies, and 47% of participants did not find them conducive to effectively communicating research findings in their doctoral work.</p>Michelle HarrisNicole E. SorianoNicole Ralston
Copyright (c) 2025 Michelle Harris, Nicole Soriano, Nicole Ralston
https://creativecommons.org/licenses/by/4.0
2025-02-072025-02-0710181710.5195/ie.2025.472Empowering Educational Leadership Research with Generative AI
https://impactinged.pitt.edu/ojs/ImpactingEd/article/view/489
<p class="AbstractParagraph" style="text-indent: 0in;">This study explores the integration of generative artificial intelligence (AI) into qualitative research within a higher education context. Through a collaborative self-study, a doctoral candidate and their dissertation supervisor examined the application of Google’s Gemini 1.5 to analyze interview data from a dissertation of practice (DiP) focused on interinstitutional partnerships. The findings demonstrate that AI can enhance the depth and efficiency of qualitative analysis, revealing hidden complexities and patterns while augmenting the researcher's analytical skills and fostering reflexivity. However, challenges related to data integrity, potential biases, and the need for careful human oversight are also discussed. This research offers insights into the transformative potential of AI in qualitative research, particularly within doctoral education, while raising important ethical considerations and prompting a re-evaluation of traditional dissertation practices in the context of emerging technologies.</p> <p class="KeywordsTitle"><span style="text-decoration: none;"> </span></p>Corrie WilderShannon Calderone
Copyright (c) 2025 Corrie Wilder, Shannon Calderone
https://creativecommons.org/licenses/by/4.0
2025-02-072025-02-07101182610.5195/ie.2025.489Navigating New Frontier
https://impactinged.pitt.edu/ojs/ImpactingEd/article/view/477
<p class="AbstractParagraph" style="text-indent: 0in;">The landscape of generative AI in Education Doctorate (EdD) programs is multifaceted and rapidly evolving, demonstrating a significant impact on educational methodologies and student engagement. In the Molloy University EdD program, AI is leveraged extensively for a range of purposes, from assessment tools like Perusall to advanced platforms like Roshi.ai. These technologies not only streamline the assessment process but also offer a personalized learning experience. Furthermore, AI's role in assisting student research is pivotal, providing sophisticated data analysis, trend prediction, and comprehensive literature review capabilities. The use of AI for writing assistance further exemplifies its utility in enhancing academic rigor and student productivity. This integration of AI tools within the EdD curriculum represents a forward-thinking approach, preparing educators and leaders to harness the power of AI in their future professional practices.</p>Mubina Khan Schroeder Joanna Alcruz
Copyright (c) 2025 Mubina Khan Schroeder , Joanna Alcruz
https://creativecommons.org/licenses/by/4.0
2025-02-072025-02-07101273210.5195/ie.2025.477Dissertation 2.0
https://impactinged.pitt.edu/ojs/ImpactingEd/article/view/468
<p>Universal guidelines for AI’s use in the context of higher education remains unestablished. Despite this, doctoral students utilized AI to help in forming research ideas and with editing manuscripts. Thereby, the socialization of doctoral students into ethical AI use became imperative. This action research study had faculty and EdD students test AI tools to then 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. Furthermore, as doctoral students constituted novice researchers, they needed to realize that they would be responsible for AI’s output. Keeping the doctoral identity at the forefront was core to advising doctoral students into the new era of responsible research. </p>Vassa GrichkoBetsy SchamberShanice HallKari TermansenDavid SwankDavid BarkerErin Lehmann
Copyright (c) 2025 Vassa Grichko, Betsy Schamber, Shanice Hall, Kari Termansen, David Swank, David Barker, Erin Lehmann
https://creativecommons.org/licenses/by/4.0
2025-02-072025-02-07101334110.5195/ie.2025.468Generative AI Use in an EdD Program
https://impactinged.pitt.edu/ojs/ImpactingEd/article/view/476
<p>Generative AI has emerged as a tool to assist doctoral students as they conduct academic research and writing. In this study, we explored two ways AI has been used by students in our EdD program—informally and independently and in a more formalized, guided manner. First, we found students have been engaged in self-directed, informal, independent use of AI tools like Grammarly and Wordtune to aid them with writing. Other students used AI to summarize information from research studies and locate research articles. To be competitive, they believed that they needed to learn more about AI and its use. Second, we obtained data for students’ use of AI as they searched for theories to inform their research efforts. They were more confident to try out and utilize AI when instructors introduced it. Results indicated students found this use to be extremely helpful and a necessary tool for students in EdD programs. </p>Ray BussAmy MarkosJosephine Marsh
Copyright (c) 2025 Ray Buss, Amy Markos, Josephine Marsh
https://creativecommons.org/licenses/by/4.0
2025-02-072025-02-07101424810.5195/ie.2025.476Unlocking the Future
https://impactinged.pitt.edu/ojs/ImpactingEd/article/view/475
<p>This convergent mixed methods research study investigated how a small, non-representative sample of Educational Doctorate (EdD) faculty perceive and use generative AI and how they have leveraged the technology to support EdD students. A cross-sectional survey was used to gather data from 27 EdD faculty members to assess their generative AI perceptions and use as of April 2024. Findings revealed widespread generative AI use among participants, with 89% utilizing the technology for a variety of tasks related to supporting EdD students, including brainstorming, lesson planning, building students’ generative AI knowledge, and supporting dissertation research and writing. Generative AI use did not differ significantly based on demographic or background factors, but perceptions varied between users and nonusers, with users holding much more favorable attitudes about the technology. Both groups perceived it to pose a relatively low threat to their career, but nonusers perceived an even lower threat. This study illustrates diverse generative AI use among participants, underscores the need for ongoing exploration into how perceptions about generative AI shape faculty’s adoption and use of the technology, and calls for future research into generative AI integration and its impact on faculty and student learning and satisfaction. </p>Ellana BlackKristen Betts
Copyright (c) 2025 Ellana Black, Kristen Betts
https://creativecommons.org/licenses/by/4.0
2025-02-072025-02-07101495610.5195/ie.2025.475Framework for Integrating Generative AI Into Statistical Training in Doctor of Education Programs
https://impactinged.pitt.edu/ojs/ImpactingEd/article/view/518
<p class="AbstractParagraph" style="text-indent: 0in;">This paper proposes a framework for integrating generative artificial intelligence (AI) tools into statistical training for Doctor of Education (EdD) students. The rigorous demands of doctoral education, coupled with the challenges of learning complex statistical software and coding language, often lead to anxiety and frustration among students, particularly those in part-time or online programs. This article explores how generative AI can serve as a scaffold for learning, potentially mitigating statistics anxiety and enhancing students’ abilities to focus on core statistical concepts rather than software intricacies. The proposed framework, grounded in constructivist learning theory, outlines a process for faculty to facilitate dialogues using generative AI tools that support students in developing research questions, selecting appropriate statistical tests, checking assumptions, and conducting statistical analyses. By leveraging AI as a dialogic partner, students can engage in self-regulated learning and enhance critical thinking skills essential for practitioner-scholars. This approach has the potential to improve statistical training in EdD programs, producing more competent translators of research who can effectively apply and interpret statistical methods in their professional practice. The article concludes by discussing implications for EdD programs and suggestions for improving the curriculum that includes statistical training.</p>Christine EithDenise Zawada
Copyright (c) 2025 Christine Eith, Denise Zawada
https://creativecommons.org/licenses/by/4.0
2025-02-072025-02-07101576510.5195/ie.2025.518REPAC
https://impactinged.pitt.edu/ojs/ImpactingEd/article/view/469
<p class="AbstractParagraph" style="text-indent: 0in;">This essay presents 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. These questions ensure that program transformations are evaluated through equity, ethics, and justice lenses. Moreover, they provide a foundation for revising policies and practices, developing new guidelines, and promoting innovative AI use while upholding academic integrity. Authored by faculty from three institutions, this framework includes scenarios that illustrate the educational potential and impact of GenAI, scaffolding the decision-making process and fostering an understanding of AI tools in EdD programs.</p>Elizabeth LangranPaula Cristina R. AzevedoOliver DreonStephanie Smith BudhaiClara Hauth
Copyright (c) 2025 Elizabeth Langran, Paula Cristina R. Azevedo, Oliver Dreon, Stephanie Smith Budhai, Clara Hauth
https://creativecommons.org/licenses/by/4.0
2025-02-072025-02-07101667210.5195/ie.2025.469The Education Doctorate in the Context of Generative Artificial Intelligence
https://impactinged.pitt.edu/ojs/ImpactingEd/article/view/485
<p>The emergence of generative artificial intelligence (GenAI) fundamentally shifts how educational knowledge is created, shared, and validated. Through the lens of epistemic technologies—tools that transform knowledge creation and dissemination—we analyze how GenAI challenges traditional notions of practical wisdom in education doctorate (EdD) programs. Drawing on parallels with previous epistemic shifts like written language, print, and digital media, we explore how GenAI, as a generative, dialogic, multimodal, and sometimes unpredictable technology, transforms practitioner knowledge and decision-making. We discuss implications for EdD programs, emphasizing the need to balance AI integration with the preservation of human judgment and ethical decision-making to maintain practical wisdom for scholarly practice.</p>Danah HenriksenPunya MishraLauren WooNicole Oster
Copyright (c) 2025 Danah Henriksen, Punya Mishra, Lauren Woo, Nicole Oster
https://creativecommons.org/licenses/by/4.0
2025-02-072025-02-07101737910.5195/ie.2025.485If Ferris Bueller Had a Bot
https://impactinged.pitt.edu/ojs/ImpactingEd/article/view/471
<p class="AbstractParagraph" style="text-indent: 0in;">Artificial Intelligence (AI) has seen a significant rise in public use since the release of ChatGPT in November of 2022. Higher education institutions (HEI) have struggled to negotiate how best to manage AI technologies within their academic communities, acknowledging both positive and negative impacts of AI on education. Focused primarily on large language model (LLM) technologies, such as ChatGPT, HEIs are working to build policies and guidelines to regulate their use. However, within these policies, few HEIs have considered AI meeting assistants, even though these applications bring their own set of benefits and risks. This article examines the public websites of 135 CPED universities, eight of which mention AI meeting assistants in their policies. The article analyzes the risks, benefits, and use guidance provided by these policies and suggests next steps for HEIs to address the ethical, legal, and pedagogical implications of AI meeting assistants.</p>Paula Cristina R. AzevedoChristine B. Valadez
Copyright (c) 2025 Paula Cristina R. Azevedo, Christine B. Valadez
https://creativecommons.org/licenses/by/4.0
2025-02-072025-02-07101808910.5195/ie.2025.471Nothing New Under the Sun
https://impactinged.pitt.edu/ojs/ImpactingEd/article/view/484
<p class="AbstractParagraph" style="text-indent: 0in;">In this article, the authors explore the concerns surrounding academic dishonesty related to generative artificial intelligence (GAI). The authors 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. Drawing upon lessons learned from addressing plagiarism caused by paper mill usage, the authors suggest incorporating multimodal assessments as an effective strategy for ensuring authentic representation of student learning outcomes at all levels of academia but particularly at doctoral level dissertations where oral defenses play a crucial role in evaluating expertise.</p>Nicholas WerseJoshua Smith
Copyright (c) 2025 Nicholas R. Werse, Joshua Caleb Smith
https://creativecommons.org/licenses/by/4.0
2025-02-072025-02-07101909510.5195/ie.2025.484GPT and Me, An Honest Reevaluation
https://impactinged.pitt.edu/ojs/ImpactingEd/article/view/479
<p class="AbstractParagraph" style="text-indent: 0in;">This essay explores the transformative concept of co-active emergence in education, where human and machine intelligence synergize to enhance learning experiences. It discusses the integration of AI in doctoral research, emphasizing collaborative efforts between humans and AI to push academic boundaries. It also addresses the challenges and ethical considerations of AI, advocating for a balanced approach that leverages AI's capabilities without compromising educational integrity, ultimately proposing a dynamic, interactive academic environment enriched by technology.</p>Bryan P. Sanders
Copyright (c) 2025 Bryan Sanders
https://creativecommons.org/licenses/by/4.0
2025-02-072025-02-071019610010.5195/ie.2025.479