Abstract:

This presentation introduces a research-informed, design-based approach to integrating artificial intelligence (AI) in K–12 education through the intentional offloading of selected lower-level cognitive tasks. The approach is grounded in a synthesis of learning science research and design-based analyses of instructional practice, drawing on evidence from cognitive load theory, educational neuroscience, and classroom-based AI-supported learning environments. Across this body of work, findings consistently indicate that persistent emphasis on memorization and recall can overburden working memory and limit opportunities for higher-order thinking, transfer, and creative problem solving. These patterns have emerged across multiple instructional contexts, highlighting the need to articulate design principles that foreground cognitive offloading as a core consideration in contemporary learning design.

The session explores how instructional design can leverage AI to align with how the brain learns by managing cognitive load, supporting schema formation, and maintaining engagement through meaningful challenge. Drawing on a synthesis of research and practice, the presentation examines how long-standing instructional practices that prioritize recall and procedural accuracy often conflict with established principles of learning science, particularly under conditions of increased cognitive demand. Using practice-embedded examples, the session illustrates how AI can function as a cognitive partner that supports teacher decision-making and deepens student engagement, rather than replacing core learning processes. Design-based reasoning is used to surface emerging instructional design principles that clarify how purposeful task automation influences cognitive demand and instructional effectiveness.

Attendees will gain a design-oriented perspective on how AI enables more informed instructional planning, along with principles for identifying tasks appropriate for automation and developing cognitively balanced lessons that align learning design with contemporary learning science.

Keywords:

Artificial intelligence, cognitive learning, instructional design, critical thinking, professional development.