As generative AI increasingly automates the "final product," higher education faces a crisis of cognitive atrophy. When AI provides solutions instantly, it skips the "earned struggle" essential for long-term retention. This session introduces Somagraphic Learning™: a human-first visual cognitive framework designed to bridge the Clarity Gap between AI data volume and human sense-making capacity.

Moving beyond traditional "AI-first" workflows, this interactive presentation demonstrates how to reposition AI as a "Follower" rather than a "Leader". Participants will engage with the Shape-Emotion Grammar™, a pre-verbal language that uses perceptual cues like circles for safety, boxes for structure, and arrows for movement to anchor understanding before a single prompt is typed.

We will workshop a virtual "Attempt → Map → Refine" process, where learners externalize ideas through hand-drawn motion (on paper or digital whiteboards) before utilizing AI for optimization. By the end of this session, educators will possess a replicable strategy to protect the "Human Edge", ensure academic integrity through somatic principles, and foster a "soul-made" environment where technology supports, rather than replaces, the human mind.

By the end of this session, participants will be able to: Diagnose the "Clarity Gap" in current digital curricula, identifying where AI-generated output prematurely terminates student sense-making. Apply Shape-Emotion Grammar™ to translate abstract academic concepts into pre-verbal visual anchors (circles, boxes, arrows), reducing early cognitive load. Facilitate the virtual "Attempt → Map → Refine" workflow, successfully repositioning AI as a "Follower" that optimizes student-led inputs. Implement "Somatic Mirroring" principles to create verifiable proof of human effort and intention, enhancing academic integrity in virtual, AI-integrated assignments.

This online session utilizes the Attempt → Map → Refine workflow to drive active participation. We begin with a "Silent Sketch" exercise where participants use either a digital whiteboard or physical paper to map a complex concept using Shape-Emotion Grammar™, activating embodied cognition before digital logic. I will then lead a "Virtual Somatic Mirroring" demo, showing how to "read" the time, energy, and intention behind these strokes to generate specific AI feedback. Finally, attendees will engage in a "Clarity Gap" Peer Review, using basic shapes to critique each other's maps, fostering social interaction and real-world problem-solving.

● Event: Conference (TEACHx 2026, Northwestern University)
● Mode: 45 min Online Interactive Presentation
● Audience: Instructors, students, learning designers, and technology specialists from higher education institutions interested in showcasing innovative experiments and collaborations in teaching and learning with technology.