The Physics of Learning: How Race-Architecture Constraints Explain What We Know About Teaching, Communication, and Understanding

Paper 16 in the Friction Theory paper-series. A didactic translation of Friction Theory mechanics to human learning, teaching, and communication for audiences in education research, instructional design, and organisational psychology. Abstract. Three traditions of learning science — cognitive load theory and multimedia learning (Sweller, Mayer); desirable difficulties and retrieval practice (Bjork, Roediger, Karpicke); psychological safety and need-prepotency (Maslow, Edmondson) — are each empirically excellent and mechanically thin. They terminate at cognitive-architecture-as-given, representational-properties-as-given, and behavioural-information-flow-as-given. This paper proposes that the three are local consequences of the same substrate-universal physical constraints: bounded-capacity race-architecture, friction as the cost of unresolved competing routes, hysteresis as encoding-through-loading, and the Net Friction Rule as integrated-friction optimisation. The substrate-level account is empirically anchored by LLM substrates where the mechanism is mechanically visible (Paper 4, Paper 13), and the same constraints derive, rather than postulate, working-memory limits, the testing effect, the spacing effect, expertise reversal, and prepotency of safety-field activity over substantive-content processing. Implications for curriculum design, moment-by-moment classroom diagnosis, technical and organisational communication, and change management are developed. Four falsification conditions are specified. Three central commitments: Substrate-mechanical account of established didactics (§2-§6). Race-architecture (R1-R3), friction as competing-route cost, hysteresis as encoding-through-loading, and the Net Friction Rule are developed for a non-AI / non-FT-kyndig audience. The substrate-level account derives — rather than postulates — working-memory limits (capacity is a structural consequence of bounded compute over race-architecture, not a brute empirical fact); the testing effect (encoding happens through loading, not from passive exposure); spacing and interleaving effects (commit-against-decay vs commit-against-confusion friction-profiles); expertise reversal (prior commitments raise the matched-friction window upward); prepotency (safety-field activity competes for race-allocation regardless of substantive-content needs). LLM substrates as mechanical mirror (§3). Per-token competing-routes signature, capacity-titration threshold-collapse, volume-asymmetry between dense and dilute content, and substrate-graded expertise reversal observed on LLM substrates make the substrate-mechanical constraints empirically visible. The LLM evidence is positioned as mechanical mirror, not load-bearing — Paper 1 (substrate theory) and Paper 4B (substrates encode experience) carry the load as Zenodo-live empirical anchors; Paper 4 (LLM calibration) and Paper 13 (Operational Friction Theory) provide preliminary mechanistic support. Three classroom failure modes from one mechanism (§5, §8). Dump (raw quantity exceeds race-arbitration capacity), dilute (correct information at insufficient race-opening density), and ambiguity-without-commit (multiple strategies sustained throughout without commit-pressure release) are three distinct failure modes of the same substrate-mechanical constraint. The matched-friction principle (Paper 6) specifies the don't-over-explain corollary as upper-boundary matched-friction violation. Diagnostic protocols and intervention recipes are mode-specific. Methodological commitments. The substrate-level account is presented as a programmatic hypothesis, not a closed theory. Section 2.7 positions Friction Theory relative to predictive-processing (Friston, Clark), ACT-R (Anderson), and Bayesian cognitive science (Chater, Oaksford); commit-pressure under bounded race-architecture is identified as the load-bearing structural assumption that distinguishes the substrate-level account from these alternatives. Section 8 implications include curiosity gaps as engineered matched-friction on race-opening (sustain-pressure mechanism); pre-flag bargain as reactance-bypass via voluntary commit; meaning-field mis-diagnosis as dominant organisational learning failure; the formal-education abstraction-mismatch as structural feature of context-independent curriculum. Four falsification conditions are specified at §9: substrate-mechanical signature on biological measurements; matched-friction window measurability; capacity-titration threshold-collapse; per-token competing-routes signature on biological substrates. Companion papers in the Friction Theory series: Paper 0 (Behavioural Friction Theory): 10.5281/zenodo.19462499 Paper 1 (Friction Theory substrate): 10.5281/zenodo.20012654 Paper 4 (LLM calibration; same content wider track): 10.5281/zenodo.20059860 Paper 4B (Substrates encode experience): 10.5281/zenodo.20059861 Paper 6 (Matched friction under hysteresis): 10.5281/zenodo.20059863 Paper 13 (Operational Friction Theory): 10.5281/zenodo.20367725 Pre-submission review. Pre-mortem pass + two rounds of hostile peer-review simulation (ChatGPT and Gemini, both targeting Educational Psychologist as initial venue; both reject) applied; convergent attack-vectors C1-C5 addressed at Tier 1 + Tier 2 level. Tomas's 2025 practitioner book Superlæring 1: Læringens DNA read in full to identify integration-points; book is cross-cited as evidence-of-prior-articulation that the four building-blocks (attention/engagement/understanding/memory) were named before the framework was complete. Three research notes integrated (curiosity gaps, social-proof as mirror-friction, free-will substrate-mechanical). Scite-verification pass run on ~93 bibliography entries; pre-flight scan run for horizontal-rules, H3-alphabet dividers, AI-tool mentions, and discovery-narratives. Target venue: Educational Psychologist (primary) / Learning and Instruction (secondary) for journal submission after preprint feedback.