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From Conversation to Coherence: How ERA-NOVA Is Shaping the Future of AI in Education
May 11, 2026
By Christy Hudson
As artificial intelligence becomes increasingly embedded in teaching and learning, educators and institutions have a critical opportunity to shape how it is understood and used in schools. This spring, educators, researchers, and school division leaders convened at George Mason University through the College of Education and Human Development’s Educational Research Alliance of Northern Virginia to advance a shared vision for AI literacy and to strengthen the connection between research, preparation, and practice across the region.
What emerged from that work was not a single framework or set of recommendations, but a clearer picture of a field in transition and a growing alignment around what matters most.
Across Northern Virginia’s school systems, AI is already shaping how teachers plan, instruct, and respond to student needs. In some classrooms, it is being used to design lessons, differentiate instruction, and support more responsive teaching. In others, its use is still developing, shaped by questions of ethics, accuracy, and appropriate application. Rather than signaling fragmentation, this variation reflects a system actively working to define effective practice in real time.
Within that landscape, a consistent pattern is beginning to take hold. The educators who are using AI most effectively are not those with the most advanced tools, but those with the strongest instructional foundation. They approach AI as a thought partner, using it to extend their thinking, refine their plans, and respond more precisely to students. Their work remains anchored in pedagogy, with AI serving to enhance rather than replace professional judgment.
That distinction is shaping how participants across ERA-NOVA are defining AI literacy. Increasingly, it is understood not as a discrete technical skill, but as a broader capacity that integrates critical thinking, ethical reasoning, and content expertise. As one participant noted in post-convening reflections, the goal is not to treat AI as “an additional tool,” but to position it as a function of strong teaching practice.
This reframing carries important implications for teacher preparation.
Participants emphasized that AI literacy must be embedded throughout preparation programs, not isolated in standalone experiences. Suggestions ranged from integrating AI into methods courses and clinical experiences to creating opportunities for candidates to engage in simulations where they use AI to solve real instructional challenges. Others pointed to the importance of modeling how AI is used in the workforce, ensuring that future teachers can connect classroom practice to broader professional contexts.
At the same time, the conversations surfaced a critical mindset shift. “It’s not the future—it’s right now,” one participant wrote, underscoring the need to move beyond conceptual discussions and into applied practice. This immediacy is shaping expectations for both pre-service and in-service educators, who are seeking clearer guidance, more consistent training, and opportunities to build confidence through use.
The human dimension of this work remained central throughout. Educators raised questions about how to preserve teacher voice, maintain rigor, and ensure that students continue to develop critical and creative thinking skills in an AI-enabled environment. The emphasis on human agency was consistent across responses, with participants highlighting the importance of keeping “human review at the forefront” and ensuring that AI supports, rather than diminishes, the intellectual work of teaching and learning.
“These conversations reflect exactly why research practice partnerships matter,” said CEHD Dean Ingrid Guerra-López. “AI is not something that sits outside of teaching and learning. It is becoming part of the broader educational ecosystem, which means we must think intentionally about how teacher preparation, research, professional learning, and school systems evolve together. Through ERA-NOVA, we are bringing together educators, researchers, and systems leaders into a sustained collaboration so we can move beyond isolated innovation and build more coherent, evidence-informed approaches that truly support students and teachers in this rapidly changing landscape.”
These priorities extend beyond classrooms. Participants pointed to the importance of engaging families and communities, where perceptions of AI are still evolving. They also emphasized the need for shared expectations around ethical use, data privacy, and student readiness. Taken together, these insights reinforce that AI literacy is not only an instructional concern, but a system-level responsibility.
That responsibility is shaping the work of the CEHD, which leads ERA-NOVA as part of its broader commitment to research practice partnerships.
Through ERA-NOVA, CEHD has established a model for sustained collaboration between higher education and PK-12 systems, where research and practice are developed in tandem. The convening reflects a broader strategy: aligning teacher preparation, professional learning, and applied research so that educators are supported across every stage of their development.
“AI is accelerating changes that were already underway in education,” said Audra Parker, Director of the Office for Teacher Preparation at George Mason’s CEHD. “Our role is to ensure that educators are not just introduced to these tools, but are prepared to use them with intention, with strong pedagogy, and with a clear understanding of their impact on students and communities.”
The need for that alignment was evident throughout the discussions. Pre-service teachers are looking for clearer signals about what AI literacy looks like in practice. In-service teachers need job-embedded learning opportunities, time to experiment, and access to exemplars. School and division leaders are seeking frameworks that are both adaptable and grounded in shared principles.
CEHD’s response is increasingly focused on coherence. Efforts to embed AI into coursework, expand credentialing opportunities, and develop tools to assess teacher readiness reflect a commitment to building a connected system rather than a collection of initiatives. Participants also pointed to emerging ideas, such as AI “tinkering labs” and regional sandbox models that would allow educators to explore tools collaboratively in low-stakes environments.
Just as important is the emphasis on partnership. Across responses, participants highlighted the value of continued collaboration between Mason and regional school divisions, including shared resources, aligned professional learning, and ongoing opportunities to learn from one another. ERA-NOVA provides the structure for that work to evolve over time, ensuring that insights are not only generated, but acted upon.
The significance of this spring’s convening lies in that forward momentum. It reflects a shift from exploration to coordination, from isolated innovation to shared direction. It also signals a broader commitment to ensuring that AI in education is shaped intentionally, with attention to both opportunity and responsibility.
In a rapidly evolving landscape, that kind of alignment will be essential.
CEHD’s work through ERA-NOVA demonstrates how institutions can move beyond conversation to build the structures, partnerships, and shared understanding needed to support educators—and ultimately students—in an AI-enabled future.