This presentation will explain findings from a two-phase study on generative AI disruption in higher education. Phase 1 maps evidence across 11 domains through a scoping review. Phase 2 introduces and norms the Emerging Technologies Disruption Framework, offering benchmarks institutions can use to guide adaptation, governance, and strategic decision-making

Generative Artificial Intelligence (GenAI) has rapidly emerged as one of the most disruptive forces in higher education. Since the launch of ChatGPT in late 2022, students have embraced these tools to complete assignments, enhance tutoring, and even translate across languages, while faculty and staff remain divided between viewing GenAI as a revolutionary opportunity or as a threat to academic integrity and cognitive development. This tension highlights a pressing need for systematic evidence to guide institutional decision-making.

This presentation will explain the findings of a two-phase study designed to map the scope of GenAI disruption in higher education and to introduce the Emerging Technologies Disruption Framework (ETDF). The first phase synthesizes the rapidly expanding but fragmented literature through a scoping review. The second phase develops, refines, and norms a validated framework that institutions can use to benchmark disruption, track changes over time, and inform governance strategies.

The purpose of the project is to clarify the scale and scope of GenAI-driven change and to provide a structured tool for measuring institutional readiness and response. Three questions guide the study: What evidence exists for disruption across key domains of higher education? How do patterns of disruption vary across institutional contexts? And what gaps in measurement or conceptualization remain that a framework could address?

The research is grounded in a multi-theoretical model that brings together perspectives from innovation diffusion, disruptive innovation, and technology adoption, alongside organizational change, socio-technical systems, and complex adaptive systems theories. These frameworks collectively capture adoption dynamics, institutional responsiveness, and systemic ripple effects. Pedagogical transformation is examined through TPACK and the Community of Inquiry model, while organizational and governance aspects are analyzed through Kotter’s Change Model, the Dynamic Capabilities Framework, and Actor–Network Theory. This integrated approach ensures that the project captures both micro-level teaching practices and macro-level policy and sector change.

Phase 1: Scoping Review

The scoping review follows PRISMA-ScR guidelines and uses the PRESS framework to ensure robust database search strategies. Sources include peer-reviewed literature and grey literature from 2023 onward, focusing on GenAI’s role in higher education. .

A coding framework assigns disruption intensity on a scale from zero (speculative mentions with no evidence of change) to four (systemic or transformative disruption). Data extraction captures bibliographic details, context, domain relevance, and disruption measures. The output of this phase will be domain-level evidence maps showing how GenAI is affecting pedagogical transformation, learning outcomes, equity, faculty and staff roles, administration, economics, research, policy, and broader sector dynamics.

Phase 2: Delphi and Framework Norming

Findings from the scoping review form the foundation of the Emerging Technologies Disruption Framework. Phase 2 involves multiple Delphi rounds with a purposive panel of 20–30 experts drawn from leadership, faculty, instructional design, IT, libraries, and policy roles across international higher education. Beginning with cognitive interviews to refine draft indicators, the Delphi process proceeds through iterative rounds of feedback and re-rating to achieve consensus on clarity, coverage, and weighting of domains.

Following consensus, the framework was piloted with approximately 100 participants from a range of institutional types. These participants apply the rubric to case examples, providing data for inter-rater reliability and the establishment of preliminary cut-bands such as Emergent, Developing, Established, and Transforming. This evidence-informed approach ensures that the framework is both theoretically grounded and practically validated.

The significance of this project lies in its dual contribution: clarifying what is currently known about GenAI disruption and creating a tool that enables institutions to respond strategically rather than reactively. Whereas existing studies are often narrow, discipline-specific, or speculative, this scoping review provides a comprehensive map across 11 domains of higher education. The subsequent framework offers benchmarks that institutions can apply to track readiness, identify risks, and allocate resources effectively.

Because this work addresses a rapidly evolving and contested topic, the presentation is designed to actively engage participants rather than simply deliver findings. The session will open with a live poll in which attendees indicate how they perceive GenAI’s disruption within their institutions across the 11 domains. The aggregated results will be displayed immediately and compared with patterns emerging from the scoping review, allowing participants to situate their experiences within the broader evidence landscape.

Participants will then engage in short, domain-based discussions. Attendees will be invited to cluster around themes most relevant to their roles, such as faculty development, student engagement, or ethical and policy pressures. Each group will identify whether their institutional experiences align with or diverge from the review findings, and share highlights back to the larger group. This exercise is intended to surface variation across institutional types while reinforcing the framework’s applicability to diverse contexts.

The session will also include an interactive case application of the ETDF. Participants will be presented with a hypothetical institutional scenario and asked to apply simplified disruption indicators to score the case. Results will be discussed collectively, providing a first-hand experience of how the framework functions. This mirrors the pilot norming process of the study and equips participants with a practical tool they can adapt within their own contexts.

The closing segment will combine structured Q&A with a futures-thinking activity. Participants will reflect on how GenAI might reshape their institutions five years from now and what strategies are necessary to prepare. These reflections will be collected and synthesized, and attendees will receive a summary resource after the conference to extend the learning and dialogue.

This project makes contributions at several levels. Empirically, it offers the first systematic mapping of GenAI disruption across multiple domains of higher education. Methodologically, it demonstrates the value of combining scoping review approaches with Delphi consensus to develop practical frameworks. Practically, it provides the ETDF as a validated tool that institutions can adopt for benchmarking and strategy development. And pedagogically, the interactive presentation format engages participants in applying the framework, ensuring that they leave with concrete strategies for navigating GenAI disruption.

Generative AI is simultaneously an opportunity and a challenge for higher education. Without systematic evidence and clear frameworks, institutions risk reactive approaches that exacerbate inequities or miss opportunities for innovation. This study provides both clarity and tools: a scoping review that synthesizes what is known, and a validated framework that enables institutions to benchmark, strategize, and govern effectively.

This presentation will explain the findings of both phases, demonstrate how the framework can be applied, and engage participants in activities that connect the evidence to their own institutional realities. By the end of the session, attendees will not only understand the scope of GenAI disruption but will also have tested a practical tool for guiding adaptation, governance, and innovation in online and blended learning environments.

Dr. Carrie Lewis Miller

Senior Researcher at Online Learning Consortium, Inc.

As senior researcher at OLC, Carrie designs, conducts and manages the portfolio of research projects that align with the mission, vision, and goals of the Online Learning Consortium. She brings with her over 15 years of experience as an online educator and instructional designer with a passion for research. In the early part of her career, Carrie helped open the branch campus of Benedictine University at Mesa, where students were invited to attend a lecture-free, technology-enhanced campus that used problem-based and flipped learning strategies to engage learners. In addition to providing instructional design and technology support, Carrie designed Benedictine at Mesa’s first online MBA program using problem-based learning and conducted a full curriculum evaluation at the end of the first semester. As an instructional designer at Minnesota State University, Carrie expanded her expertise in game-based learning, online pedagogy, assessment, and research while sharing those skills with faculty in professional development workshops. Carrie also received two grants during her time at MNSU that allowed her to expand professional development offerings around Open Educational Resources and save students almost $1 million in textbook costs. She has peer-reviewed publications covering a variety of topics such as open educational resources, online course best practices, and game-based learning. In addition to a strong background in higher education teaching and instructional design, Carrie brings with her extensive experience in customer service and small business management. She holds a PhD in Educational Technology from Arizona State University, an MS in French from Minnesota State University, and BA in French from Arizona State University.