Knowledge Rich Mathematics: Neurocognitive Science, Scaffolding, and the Case for Explicit Instruction
Distinguished Professor of Engineering, Oakland University
How do students actually learn mathematics—and what kinds of teaching best support that learning? This session explores findings from neuroscience and cognitive psychology about how mathematical knowledge is stored and retrieved in the brain. We'll examine scaffolding, declarative and procedural memory, the limitations of working memory, and why explicit, well-sequenced instruction is critical. Building on the approaches of mathematician John Mighton, founder of JUMP Math, we'll explore a concrete example of teaching division, consider why minimally guided instruction may widen achievement gaps, and how retrieval practice, direct modeling, and visual supports can create more equitable and effective mathematics learning environments.
