Reflection on Two Research Studies in Mathematics Education through the Lens of Relational Teaching in the Age of AI

Author/ Authors/ Presenter/ Presenters/ Panelists:

Valentina Postelnicu, Governors State UniversityFollow
Xiaobo She, Governors State University
Andrius Tamulis, Governors State UniversityFollow
J. Christopher Tweddle, Governors State UniversityFollow

Type of Presentation

Panel

Location

D34170

Start Date

4-9-2026 3:15 PM

End Date

4-9-2026 4:00 PM

Description of Program

This panel brings together findings from two research studies to reflect on how relational teaching can be supported through digital, physical, and computational tools in higher education contexts. The first study examined future early childhood and elementary teachers' understanding of geometric rotation through a comparison of a digital tool (GeoGebra) and a physical tool (tracing paper) using a quasi-experimental pretest-posttest design. Both groups demonstrated improvement, with no significant differences between interventions. Each tool supported complementary aspects of conceptual understanding. The second study investigated the integration of computational thinking (CT) into undergraduate statistics projects across two course contexts- an introductory statistics course addressed to students from various majors and a mathematics content course addressed to future early childhood and elementary teachers. Student work was analyzed across core CT components: decomposition, pattern recognition, abstraction, and algorithm design. While both groups showed strong performance in decomposition, higher levels of abstraction and algorithmic reasoning appeared in the context that included more extensive and deeper instruction. We discuss and reflect on the findings of these studies through the lens of relational teaching in the age of AI. Student understanding and performance depend not on replacing traditional practices with advanced technologies, but on fostering connections among concepts, representations, and students' ways of thinking. Our instructional approaches across the courses in these studies highlight the importance of designing learning environments and assignments where ways of thinking, tools, and technologies support meaningful human interaction.