Atlanta, Georgia | February 24, 2026
By Joëlle Walls
Eunhye Grace Flavin, senior research scientist with the Center for Education Integrating Science, Mathematics, and Computing (CEISMC) in the College of Lifetime Learning, has been selected to receive the 2026 Early Career Publication Award of the Special Interest Group for Research in Mathematics Education (SIG-RME) within the American Educational Research Association (AERA). The award is for her publication, “‘Let's Ask the Robot!’: Epistemic Stance Between Teacher Candidates Toward AI in Mathematics Lesson Planning," published in the Journal of Teacher Education in 2025.
The award will be presented to Flavin at the SIG-RME Membership Meeting at the AERA Annual Conference in April. She will receive an honorarium of $500 at the reception during the conference.
To better understand the impact of her publication and the broader questions it raises about AI in teacher preparation, Flavin shared her perspective in a brief interview.
What does receiving this award represent for you and your work?
As an early-career scholar working across learning sciences, learning technologies, human–computer interaction, and mathematics education, this award deeply affirms my interdisciplinary path. It reassures me that boundary-crossing work truly matters. At a time when generative AI is rapidly reshaping education, this recognition highlights the importance of theory-driven research that examines how learning unfolds moment to moment in human–AI interaction, rather than focusing only on technological affordances or end-of-activity outcomes. It honors not only the quality of the work but also the commitment to studying AI as a sociotechnical partner in knowledge construction—not simply as a tool.
In what ways does this recognition support and shape your trajectory as an early-career scholar?
This award gives clarity and momentum to my research program. It highlights a distinctive focus: studying intelligent learning systems like AI through a sociotechnical and epistemic lens, with close attention to real-time interactions. It also amplifies the vision of my lab—to design learning environments that support critical, dialogic, and embodied reasoning and emotional engagement. The visibility helps attract students and collaborators who are committed to developing and studying intelligent systems through rigorous learning sciences approaches.
How does your research connect to or expand the idea of lifetime learning?
This study explores how learning emerges in AI-enhanced professional preparation, focusing on teacher candidates’ real-time knowledge construction with generative AI. Through a lifetime learning lens, it shows that learning continues well beyond K–12 and university settings, extending into professional practice and ongoing workforce development in AI-rich environments. As a learning scientist, examining how learning can be thoughtfully designed within intelligent systems—and unpacking how it unfolds—is deeply meaningful to me.
This emphasis on interdisciplinary impact aligns with what the award committee highlighted in their review. As they noted, “The committee was impressed with the quality of the research and writing, as well as the significant impact your manuscript can have on the field of mathematics education and across fields given the expansion of AI.” Their recognition underscores how the work contributes to both disciplinary knowledge and broader lifelong learning across domains.
