This panel brings together leading scholars to explore the transformative potential of generative artificial intelligence (genAI) in digital learning environments. Drawing from recent scholars (Picciano & Moskal, in press), our distinguished panel will examine both the opportunities and challenges that GenAI presents to contemporary education.

The Current AI Educational Landscape

Artificial intelligence burst onto the public educational scene in late 2022 with the introduction of ChatGPT by OpenAI, though AI's educational roots extend back to the 1950s. As Suleyman (2023), co-founder of DeepMind, defines it, AI represents the science of teaching machines to learn humanlike capabilities. Today's generative AI platforms—called generative because they create information in text, image, video, and audio formats based on user prompts—represent deep learning models capable of collecting vast quantities of data from across the Internet.

Faculty members, administrators, and policymakers across educational institutions are actively exploring generative AI's potential as a pedagogically appropriate, administratively sound, and beneficial vehicle for educational advancement. While scholarship on generative AI is rapidly developing, significant research, study, and knowledge-seeking remain to be accomplished. We stand at the nascent stage of AI evolution, which will dominate how we live, work, and educate in the coming decades.

Key Research Perspectives:

Empowering Doctoral Student Success Through AI

Research by Shelton & Brown (in press) addresses a critical educational challenge: doctoral student attrition rates consistently reaching 50% across institutions (Mensah, 2025). This alarming statistic has prompted programs to seek innovative solutions to improve retention and completion rates. The emergence of AI as a research and academic writing support tool presents unprecedented opportunities to address this crisis.

The research identifies that doctoral students experience heightened vulnerability during the dissertation phase, when traditional educational support structures diminish and students must function as independent researchers (Ali & Kohun, 2007; Rockinson-Szapkiw et al., 2014). This transition often triggers imposter syndrome, particularly regarding academic writing (Chapman, 2015), creating additional barriers to completion. Competition among peers replaces the collaborative support systems present during coursework phases.

Generative AI offers a potential solution by providing an additional layer of support and confidence-building in academic writing when used ethically. The technology can serve as a sophisticated writing assistant, helping students overcome the isolation and self-doubt that contribute to high attrition rates. However, implementation must maintain academic rigor and ethical standards while empowering students throughout the dissertation writing process.

AI's Fundamental Impact on Digital Learning Architecture

Campbell, Dziuban, Howlin, & Smith (in press) provide a comprehensive analysis of AI's relationship to digital learning, examining the underlying technological infrastructure that powers these transformative tools. Their work explores transformer architecture, embedding, and tokenization processes that create language symbolism within AI systems, providing educators with essential understanding of how these tools function.

The research introduces critical concepts including transformed search capabilities and scale-free networks with power law distributions. These networks create information ecosystems dominated by AI hubs that dynamically couple and decouple digital learning resources, fundamentally altering how educational content is accessed, processed, and delivered.

A significant concern raised is AI's potential to eliminate entry-level positions traditionally filled by new graduates, removing foundational career development opportunities. This shift, termed the "answer machine" phenomenon, will impact graduates, industry, and educational institutions, creating urgent needs to mitigate risks while leveraging AI's opportunities.

The research also addresses potential consequences for human creativity and inquiry in an AI-driven world, warning of the danger of losing "the ability to think about thinking." While AI promises remarkable improvements to digital educational culture, its immediate and long-term impacts remain largely undefined and require careful consideration.

Implications for Educational Practice

Addressing Institutional Challenges

The panel will explore how institutions can implement AI tools to address specific challenges such as doctoral student attrition while maintaining academic integrity. Discussion will focus on developing frameworks for ethical AI use that support rather than replace critical thinking and original scholarship.

Technological Infrastructure Considerations

Understanding AI's underlying architecture becomes crucial for educational leaders making implementation decisions. The panel will discuss how transformer-based systems, embedding processes, and tokenization affect educational content delivery and student learning experiences.

Workforce Development Implications

The potential elimination of entry-level positions poses significant challenges for career development pathways. Educational institutions must consider how to prepare graduates for an AI-transformed workforce while ensuring human creativity and critical inquiry remain central to educational missions.

Panel Discussion Framework

Supporting Student Success

Panelists will examine specific strategies for using AI to support struggling students, particularly at the doctoral level, while maintaining academic rigor. Discussion will include practical implementation approaches, ethical guidelines, and assessment strategies that leverage AI's capabilities without compromising educational quality.

Navigating Technological Transformation

The panel will address how educational institutions can adapt to AI's scale-free network structures and power law distributions that reshape information access. Considerations include infrastructure requirements, faculty development needs, and policy implications for institutional planning.

Preserving Human Elements in Education

Critical discussion will focus on maintaining human creativity, critical thinking, and the "art of inquiry" within AI-enhanced educational environments. Panelists will explore strategies for leveraging AI's capabilities while preserving essential human elements of learning and discovery.

Future Research Directions

Given that we remain in AI's nascent stage, the panel will identify priority areas for future research, including longitudinal studies of AI's impact on student outcomes, effectiveness of various implementation approaches, and strategies for mitigating identified risks while maximizing educational benefits.

Conclusion

This panel addresses timely and critical questions facing educational institutions as they navigate AI integration. By examining both the promise of AI in supporting student success and the challenges it presents to traditional educational structures, participants will gain valuable insights for implementing AI tools effectively and ethically. The discussion will provide practical guidance for educational leaders while identifying areas requiring continued research and development.

The convergence of expertise represented by our panelists—spanning digital learning research, AI implementation, educational policy, and student success—ensures comprehensive coverage of these complex issues. Attendees will leave with actionable insights for leveraging AI's potential while preserving the human elements essential to meaningful education.

As we stand at this transformative moment in educational technology, understanding both opportunities and challenges becomes crucial for institutional success. This panel provides essential perspectives for navigating AI's integration into digital learning environments while maintaining focus on student success and educational excellence.

References

Ali, A., & Kohun, F. (2007). Dealing with social isolation to minimize doctoral attrition -- A four stage framework. International Journal of Doctoral Studies, 2, 33-49.

Campbell, G., Dziuban, C., Howlin, C., Smith, M. (in press). Artificial Intelligence and Digital Learning: Architecture, Hallucinations, Information, Findability, the First Rung and the Art of Inquiry. In Picciano, A. G., & Moskal, P. D. (Eds.).Trends in the use of generative artificial intelligence for digital learning [Special issue]. Education Sciences. MDPI. https://www.mdpi.com/journal/education/special_issues/6UHTBIOT14

Chapman, A. (2015). Using the assessment process to overcome Imposter Syndrome in mature students. Journal of Further and Higher Education, 41(2), 112-119. https://doi.org/10.1080/0309877X.2015.1062851

Mensah, F. (2025). The 50% tipping point: Addressing doctoral student attrition through institutional innovation. Journal of College Academic Support Programs, 7(1), 50-54. https://doi.org/10.58997/7.1pp1

Picciano, A. G., & Moskal, P. D. (Eds.). (2025). Trends in the use of generative artificial intelligence for digital learning [Special issue]. Education Sciences. MDPI. https://www.mdpi.com/journal/education/special_issues/6UHTBIOT14

Rockinson-Szapkiw, A. J., Spaulding, L. S., & Bade, B. (2014). Completion of educational doctorates: How universities can foster persistence. International Journal of Doctoral Studies, 9, 293-308. https://doi.org/10.28945/2072

Roble, J, Shelton, K., & Brown, K. (in press). K-12 Teachers and Artificial Intelligence in Picciano, A. G., & Moskal, P. D. (Eds.).Trends in the use of generative artificial intelligence for digital learning [Special issue]. Education Sciences. MDPI. https://www.mdpi.com/journal/education/special_issues/6UHTBIOT14

Shelton, K., & Brown, K. (in press). Empowering Doctoral Student Research with Artificial Intelligence in Picciano, A. G., & Moskal, P. D. (Eds.).Trends in the use of generative artificial intelligence for digital learning [Special issue]. Education Sciences. MDPI. https://www.mdpi.com/journal/education/special_issues/6UHTBIOT14

Suleyman, M. (2023). The coming wave: Technology, power, and the twenty-first century's greatest dilemma. Crown Publishers.

Patsy Moskal

Director, Research Initiative for Teaching Effectiveness at University of Central Florida

Anthony Picciano

Professor at CUNY Hunter College

Charles Dziuban

Director of RITE at University of Central Florida

Kelvin Thompson

Vice Provost, Online Strategy and Teaching Innovation at University of Louisville

Dr. Kelvin Thompson works to make online and blended learning even better a little bit every day while serving at the University of Louisville as Vice Provost for Online Strategy and Teaching Innovation. Kelvin writes, speaks, and consults within the US higher education community. During his 24+ years at UCF he created a number of resources for use by the broader online community (e.g., the Teaching Online Pedagogical Repository; the Faculty Seminars in Online Teaching; and the BlendKit Course). He also co-hosts the popular “TOPcast: The Teaching Online Podcast,” is co-editor of the SAGE Handbook of Online Higher Education, and publishes The Lift newsletter monthly. Dr. Thompson has held leadership roles within the work of the Online Learning Consortium, EDUCAUSE, and WCET. In 2020, Kelvin was selected as a Fellow of the Online Learning Consortium.

Paige McDonald

Vice Chair & Assoc. Prof. of Clinical Research & Ldrshp. at George Washington University