Merge pull request #162 from AssetOverflow/docs/pedagogy-review-and-teaching-backlog

docs: pedagogy review + 2 deferred teaching-loop ADRs (0129 + 0130)
2026-05-23 07:05:22 -07:00 · 2026-05-23 07:05:22 -07:00 · f54c07d202
commit f54c07d202
parent 8851067982 f3c9436e66
3 changed files with 755 additions and 0 deletions
--- a/docs/decisions/ADR-0129-spaced-correction-replay-deferred.md
+++ b/docs/decisions/ADR-0129-spaced-correction-replay-deferred.md
@ -0,0 +1,198 @@
+# ADR-0129 — Spaced Reviewed-Correction Replay (Deferred Proposal)
+
+**Status:** Proposed — Deferred (backlog item; no implementation
+scheduled until the GSM8K-math substrate arc through ADR-0127 /
+ADR-0128 resolves Path-A vs Path-B)
+**Date:** 2026-05-23
+**Author:** CORE agents + reviewers
+**Depends on:** ADR-0040 (telemetry sink), ADR-0042 (audit tour),
+ADR-0043 (pack measurements phase 2), ADR-0059 (correction-pass
+telemetry), the entire `teaching/*` subsystem
+**Supersedes:** none
+
+---
+
+## Context
+
+A research review of *Beyond Traditional Pedagogy* (`/Users/kaizenpro/Downloads/...md`)
+plus follow-up literature confirmation surfaced two pedagogy
+findings with unusually strong empirical support and clean structural
+mapping onto CORE's existing teaching loop:
+
+1. **Retrieval practice for retention of practiced material** —
+   among the most robust findings in cognitive psychology
+   (Roediger & Karpicke 2006 and ~two decades of replications).
+2. **Spaced > massed practice** — Cepeda et al. 2006 meta-analysis;
+   not seriously contested in any subsequent literature.
+
+The combined "spaced retrieval" effect is consistently the single
+highest-effect-size pedagogy intervention in well-replicated
+literature. Far-transfer claims for retrieval are weaker (Pan &
+Rickard 2018, Glaser & Richter 2025) — but **transfer to other
+material is NOT the claim here**. The claim is *retention of
+already-corrected material across long time horizons*, which is
+precisely what retrieval-with-spacing addresses.
+
+The full research-and-review context lives at
+`docs/sessions/SESSION-2026-05-23-pedagogy-research-and-teaching-loop-pivot.md`.
+
+### What CORE already has
+
+`teaching/store.py` retains reviewed corrections. `teaching/review.py`
+and `teaching/correction.py` provide the reviewed-write path. When a
+correction is consulted (e.g., during a turn that touches the
+corrected case), CORE recalls it from the vault — exact, deterministic.
+
+### What CORE does NOT have
+
+No **deterministic schedule** that proactively re-runs CORE
+against past corrections at expanding intervals to verify the
+correction still produces the intended behavior under the
+*current* runtime state (which has since absorbed other
+corrections, pack updates, ratifications). Reviewed corrections
+sit in the store until something queries them; nothing pulls
+them back into circulation on a cadence.
+
+This is the gap "spaced retrieval" maps onto. In human pedagogy:
+re-quiz the learner on previously-learned material at 1-day,
+1-week, 1-month intervals to verify retention. In CORE: re-run
+the deterministic pipeline against the past correction's input
+on a fixed cadence and verify the output still matches the
+correction's expected outcome.
+
+---
+
+## Decision (proposed; deferred)
+
+Add a deterministic spaced-replay scheduler to the teaching
+subsystem that, on a fixed cadence, re-runs the pipeline against
+every retained reviewed-correction's input case and asserts the
+output still matches the correction's expected outcome. Failures
+become first-class "regression-against-prior-correction" events
+emitted to the telemetry sink and surfaced in the operator
+verdicts bundle.
+
+### Proposed shape (non-binding sketch — implementation defers)
+
+- **Cadence**: bounded, deterministic intervals. Initial proposal:
+  every reviewed correction is replayed at session counts `{5, 25,
+  125, 625}` past the original correction (geometric, mirroring
+  spaced-repetition literature). Cadence drift is forbidden —
+  same input session count → same replay event.
+- **Replay path**: pure read; the replay does NOT mutate any
+  state. It calls the standard pipeline against the correction's
+  recorded input, compares actual output to the correction's
+  expected output, emits an event.
+- **Event shape**:
+  ```json
+  {
+    "type": "spaced_correction_replay",
+    "correction_id": "...",
+    "original_session_count": N,
+    "replay_session_count": M,
+    "interval": M - N,
+    "passed": <bool>,
+    "actual_output_digest": "<sha256>",
+    "expected_output_digest": "<sha256>",
+    "trace_hash_delta": "<sha256-of-diff or empty>"
+  }
+  ```
+- **Failure handling**: a failed replay is NOT silently
+  re-corrected. It becomes an operator-visible event requiring
+  human review (preserves the "no unreviewed mutation" doctrine).
+  The original correction remains in the store; the new
+  divergence is logged as a separate event linked by
+  `correction_id`.
+- **Determinism**: same `(input_sequence, pack_versions,
+  correction_store_state)` → byte-equal replay event sequence.
+- **Cost ceiling**: per-session replay cost bounded — at session
+  count K, replays only fire for corrections whose
+  `(K - original) ∈ {5, 25, 125, 625}`. Most corrections fire
+  zero times per session; total replay cost is amortized.
+
+### Invariants
+
+| Invariant | Status |
+|-----------|--------|
+| `wrong == 0` | Preserved — replay is observational, not mutating |
+| Trace determinism | Preserved — replay path is the standard deterministic pipeline |
+| No unreviewed mutation | Preserved — replay failures emit events, do not auto-correct |
+| Reviewed teaching only | Preserved — the scheduler operates only on already-reviewed corrections |
+| `versor_condition(F) < 1e-6` | Untouched |
+
+### Why this is deferred, not accepted
+
+1. **Path-B uncertainty.** The GSM8K-math architectural arc
+   through ADR-0126 / 0127 / 0128 may resolve to a benchmark
+   re-targeting. If the math expert lane pivots, the
+   correction-store population characteristics change, and the
+   right cadence shape may differ.
+2. **No measured regression.** ADR-0042's audit-tour demo + ADR-0043's
+   pack measurements already prove replay-equality at the snapshot
+   level. There is no observed instance of a past correction
+   silently regressing under subsequent pack updates. Spaced
+   replay would *detect* such regressions if they occur — but
+   we don't currently have evidence they do.
+3. **Cost/benefit unmeasured.** The scheduler adds bounded but
+   nonzero per-session cost. Without an observed regression
+   incident, the lift is theoretical.
+4. **Pedagogy analog is suggestive, not proof.** The mapping
+   from human-learner spaced retrieval to deterministic-engine
+   correction replay is structurally clean but is not itself
+   empirically validated *for engines*. CORE's exact-recall
+   property may obviate the human-learner-style decay this
+   addresses.
+
+## Exit criteria for un-deferral
+
+This ADR becomes a candidate for acceptance if any of:
+
+1. A reviewed correction is observed to silently regress against
+   current state (the failure mode the scheduler would have
+   caught). One real incident promotes from "theoretical
+   defense" to "documented incident response."
+2. The teaching corpus grows past a threshold (~500 reviewed
+   corrections, current count is far below) where manual audit
+   is no longer feasible and proactive verification becomes
+   load-bearing for trust.
+3. The GSM8K-math arc resolves and produces a stable correction
+   population whose retention characteristics can be
+   characterized, removing the Path-B uncertainty.
+
+## Alternatives considered
+
+### A. Build the scheduler now as defensive infrastructure.
+Rejected per reason #2 above — no observed regression.
+
+### B. Run a single one-shot replay-all-corrections diagnostic.
+Considered as a smaller alternative. May be worth a short ADR
+of its own (`ADR-XXXX-correction-store-snapshot-audit`) if any
+of the un-deferral exit criteria fire. Not pursued now.
+
+### C. Make this a runtime-mode flag the operator can enable.
+Considered. The current operator surface (CLI lanes, telemetry
+sink, verdicts bundle) is already busy; adding another opt-in
+toggle increases surface area without a clear use case.
+
+## PR checklist (if/when proposed for acceptance)
+
+```
+What capability did this add?
+  → Deterministic spaced verification of past reviewed
+    corrections; defense against silent regression.
+What invariant proves the field remains valid?
+  → wrong == 0 (replay is observational); trace determinism
+    (standard pipeline); no unreviewed mutation (failures emit
+    events, do not auto-correct).
+Which CLI suite/eval proves the lane?
+  → New `core test --suite teaching-replay` lane runs replays
+    against a fixture correction store and asserts deterministic
+    event sequence; verdicts-bundle integration tested.
+Did this avoid hidden normalization, stochastic fallback,
+approximate recall, unreviewed mutation?
+  → Yes. Cadence is fixed-integer. Replay path is the standard
+    pipeline. Failures require human review.
+If it touches user input, what trust boundary was enforced?
+  → No user-input surface. Replays consume correction-store
+    records, which are already ratified.
+```
--- a/docs/decisions/ADR-0130-pre-articulation-calibration-deferred.md
+++ b/docs/decisions/ADR-0130-pre-articulation-calibration-deferred.md
@ -0,0 +1,221 @@
+# ADR-0130 — Pre-Articulation Calibration Logging (Deferred Proposal)
+
+**Status:** Proposed — Deferred (backlog item; no implementation
+scheduled until the GSM8K-math substrate arc through ADR-0127 /
+ADR-0128 resolves Path-A vs Path-B)
+**Date:** 2026-05-23
+**Author:** CORE agents + reviewers
+**Depends on:** ADR-0035 (turn-loop verdicts), ADR-0036 (safety
+refusal), ADR-0040 (telemetry sink), ADR-0043 (pack measurements
+phase 2), ADR-0059 (correction-pass telemetry)
+**Supersedes:** none
+
+---
+
+## Context
+
+The same research review that motivated ADR-0129
+(`docs/sessions/SESSION-2026-05-23-pedagogy-research-and-teaching-loop-pivot.md`)
+surfaced a second pedagogy finding with strong empirical support
+and a clean structural mapping: **metacognitive calibration via
+prediction-outcome comparison**.
+
+In human pedagogy: learners predict their performance before a
+task, compare prediction to outcome, and use the gap to recalibrate
+their judgments of learning. Repeated calibration cycles shrink the
+gap (Bjork, Dunlosky, Koriat, and successors). The mechanism is
+that *uncalibrated confidence* is the central failure mode of
+self-regulated learning — over-confidence leads to under-study;
+under-confidence to over-study; both waste capacity.
+
+CORE has analogs at the runtime layer:
+- `ADR-0035` end-of-turn safety + ethics verdicts
+- `ADR-0036` typed safety refusal
+- `ADR-0040` structured telemetry sink
+
+But CORE has **no analog at the teaching layer**. Before a
+reviewed correction lands, no event captures the answer CORE
+*would have produced* on the case-pre-correction; after correction,
+no event captures the gap.
+
+This is a genuine information loss. Unlike a human learner, CORE
+can do this without subjective bias: the pre-correction answer is
+deterministic and exactly recordable. The gap is a real
+measurement, not a self-report.
+
+---
+
+## Decision (proposed; deferred)
+
+Add a deterministic "pre-correction prediction" capture step to
+the teaching subsystem. When a correction is proposed (before
+review), record CORE's current pipeline output on the case as a
+prediction event. When the correction is accepted (review passes,
+correction lands in store), emit a paired calibration event
+recording the delta between prediction and the corrected outcome.
+
+### Proposed shape (non-binding sketch — implementation defers)
+
+- **Pre-correction prediction event** (emitted at correction
+  *proposal*):
+  ```json
+  {
+    "type": "pre_correction_prediction",
+    "correction_proposal_id": "...",
+    "input_digest": "<sha256-of-input>",
+    "predicted_output_digest": "<sha256>",
+    "predicted_trace_hash": "...",
+    "predicted_verdict": "correct | wrong | refused",
+    "current_runtime_state_digest": "<sha256-of-pack-versions+correction-store>"
+  }
+  ```
+- **Post-correction calibration event** (emitted at correction
+  *acceptance*):
+  ```json
+  {
+    "type": "post_correction_calibration",
+    "correction_id": "...",
+    "linked_prediction_id": "...",
+    "predicted_output_digest": "<sha256>",
+    "corrected_output_digest": "<sha256>",
+    "delta_class":
+      "no_change | answer_value | answer_unit | trace_only | refused_to_correct | correct_to_refused",
+    "pack_provenance_diff": [...]
+  }
+  ```
+- **Aggregation** (offline, periodic): a `calibration_report.json`
+  in the teaching subsystem's reports directory, summarizing:
+  - rate at which predictions matched corrections (no-change),
+  - distribution of delta classes,
+  - per-pack-version cohort comparisons (does calibration improve
+    after pack ratifications?).
+- **No runtime gating.** The prediction is observational. It does
+  NOT alter what the operator can or cannot do; it does NOT veto
+  any correction. It's measurement, not control.
+
+### Invariants
+
+| Invariant | Status |
+|-----------|--------|
+| `wrong == 0` | Preserved — prediction is observational |
+| Trace determinism | Preserved — prediction uses standard pipeline |
+| No unreviewed mutation | Preserved — prediction does not write to correction store |
+| Reviewed teaching only | Preserved — calibration emits only at proposal AND acceptance, both of which are operator-mediated |
+| Telemetry redaction defaults | Preserved — input digests, not raw input |
+| `versor_condition(F) < 1e-6` | Untouched |
+
+### What this enables that's not currently possible
+
+1. **Empirical answer to "is CORE actually getting better?"** Per-pack-
+   version calibration trends would show whether ratifications
+   improve pre-correction accuracy or just shift the surface.
+2. **Audit story strengthens.** Today operators see that
+   corrections happen; they don't see how often CORE was *already*
+   right before the correction. The calibration gap is exactly
+   that signal.
+3. **Misconfigured-pack detection.** A pack version that suddenly
+   spikes pre-correction error rate (vs the prior pack's rate)
+   is a flag worth surfacing automatically.
+4. **Honest framing of operator workload.** If the calibration
+   shows pre-correction prediction matches the eventual correction
+   95% of the time, the operator review can be lighter-touch on
+   that pack; if 5%, heavier-touch is warranted.
+
+### Why this is deferred, not accepted
+
+1. **Path-B uncertainty** (same as ADR-0129): the GSM8K-math arc
+   may produce a different correction-store population structure
+   that changes the right calibration cohorts.
+2. **No measured calibration problem.** We don't currently have
+   evidence that pre-correction accuracy is misaligned with
+   post-correction. The proposal is "measure to find out" — but
+   the cost of building the measurement infrastructure should
+   match the prior of finding something. We don't have a strong
+   prior.
+3. **Telemetry already substantial.** ADR-0040 / ADR-0042 /
+   ADR-0043 ship significant telemetry. Adding two new event
+   classes raises operator-noise floor; should only do so if the
+   signal proves worth it.
+4. **Operator workload concern.** Even though prediction is
+   observational, a calibration report is a thing the operator
+   has to read. More artifacts means more attention budget; only
+   worth it if the artifacts surface decisions.
+
+## Exit criteria for un-deferral
+
+This ADR becomes a candidate for acceptance if any of:
+
+1. An incident occurs where a correction was applied unnecessarily
+   (CORE was already producing the right answer on that input)
+   AND the wasted review effort would have been visible to a
+   calibration-event sequence.
+2. A pack ratification produces unexpected behavior whose
+   detection would have been faster via per-pack calibration
+   cohort comparison.
+3. The teaching corpus grows to where operator review bandwidth
+   becomes a bottleneck and routing reviews by calibration
+   confidence would help triage.
+4. The GSM8K-math arc resolves and ADR-0129 (spaced replay) is
+   un-deferred — at which point these two capabilities should
+   compose, since spaced replay events naturally produce
+   calibration evidence and they should share infrastructure.
+
+## Alternatives considered
+
+### A. Build calibration logging now, defer reporting.
+Considered. Logging without reporting still costs telemetry
+volume; without a report nobody reads the events; without reading
+the events the log is decoration. Rejected per CLAUDE.md "no
+decoration without integration."
+
+### B. Sample-based calibration (log a random 10% of proposals).
+Considered. Determinism doctrine pushes against sampling — same
+correction proposal should always produce same calibration event,
+or none at all. Could be acceptable if sampling is content-keyed
+(hash of input → bucket) so it's deterministic, but adds
+complexity. Defer for now.
+
+### C. Manual calibration audit on demand.
+The CLI could provide `core teaching calibration --window N` that
+re-runs the last N corrections through the prediction path
+*offline* and produces a one-shot calibration report. Lower
+implementation cost than continuous logging; could be a useful
+half-step. Worth its own short ADR if any of the exit criteria
+above fire.
+
+## Composition with ADR-0129
+
+If both ADRs are eventually un-deferred, they should share
+infrastructure:
+
+- Spaced-replay events (ADR-0129) naturally yield calibration
+  evidence: each replay produces a prediction against the original
+  correction's expected outcome. The two event streams should
+  merge into a single calibration report.
+- A correction whose spaced-replay events show repeated divergence
+  is a stronger signal than either system alone would catch.
+
+This composition is itself an argument for un-deferring both
+together if either is un-deferred.
+
+## PR checklist (if/when proposed for acceptance)
+
+```
+What capability did this add?
+  → Deterministic measurement of pre-correction prediction
+    accuracy; empirical signal for "is CORE getting better."
+What invariant proves the field remains valid?
+  → wrong == 0 (prediction is observational); trace determinism
+    (standard pipeline); no unreviewed mutation (calibration
+    writes events, not corrections).
+Which CLI suite/eval proves the lane?
+  → New `core test --suite teaching-calibration` lane; fixture
+    correction-proposal sequence asserts deterministic event
+    pairs and report aggregation.
+Did this avoid hidden normalization, stochastic fallback,
+approximate recall, unreviewed mutation?
+  → Yes. Pure observational, deterministic pipeline call.
+If it touches user input, what trust boundary was enforced?
+  → Telemetry emits input digests (SHA-256), not raw input,
+    consistent with ADR-0040's redact-by-default policy.
+```
--- a/docs/sessions/SESSION-2026-05-23-pedagogy-research-and-teaching-loop-pivot.md
+++ b/docs/sessions/SESSION-2026-05-23-pedagogy-research-and-teaching-loop-pivot.md
@ -0,0 +1,336 @@
+# SESSION 2026-05-23 — Pedagogy Research & Teaching-Loop Potential Pivot
+
+**Date:** 2026-05-23
+**Status:** Research note; load-bearing for ADR-0129 + ADR-0130
+**Trigger:** Operator-supplied review of *Beyond Traditional Pedagogy:
+Research-Based and Emergent Techniques for Deep, Durable Learning*
+(`/Users/kaizenpro/Downloads/Beyond Traditional Pedagogy ...md`,
+2026-05-23)
+**Branch:** `docs/pedagogy-review-and-teaching-backlog`
+
+---
+
+## Why this session exists
+
+CORE's mid-2026 work has concentrated on the GSM8K-math substrate arc
+(ADRs 0114a → 0119 → 0120 → 0121 → 0122 → 0123 / 0123a / 0123b → 0126
+candidate-graph topology → 0127 units pack → 0128 numerics pack). The
+last three substrate ADRs each produced **zero sealed-holdout lift**
+despite being correct work, leading to an architectural pivot (ADR-0126)
+and a substrate-substrate (ADR-0127 / 0128) reframing.
+
+That sequence has been **all about the truth-articulation path** —
+parse → graph → solve → verify → realize. The orthogonal axis — how
+CORE *learns* from reviewed corrections — has not received the same
+load-bearing attention since the ADR-0040-series teaching-substrate
+work. The operator surfaced a pedagogy literature review as a sanity
+check on whether the teaching loop, considered on its own merits,
+has structural gaps that the GSM8K-math focus has been deferring.
+
+This session is the result of that check: the literature review of
+the supplied document, follow-up confirmation research on contested
+claims, and the resulting two backlog ADRs (0129 and 0130).
+
+---
+
+## The reviewed document
+
+**Title:** *Beyond Traditional Pedagogy: Research-Based and Emergent
+Techniques for Deep, Durable Learning*
+
+**Structure:** Executive summary + ~10 themed sections + a
+synthesis table + 22 reference URLs. ~300 lines, well-cited within
+the established cognitive-psychology / learning-science canon
+(Bjork, Roediger & Karpicke, Kapur, Mayer, Collins / Brown / Newman,
+Freeman et al., etc.).
+
+**Headline claims:**
+
+1. Active learning > passive lecture (Freeman et al. 2014 PNAS
+   meta-analysis as exemplar).
+2. Retrieval practice (effortful recall) drives durable learning;
+   spacing + interleaving amplify.
+3. Productive failure (Kapur) produces larger conceptual gains than
+   instruction-first ("3x" rhetoric in some references).
+4. Embodied cognition: gesture, manipulation, handwriting matter for
+   acquisition.
+5. Multimedia learning (Mayer): coordinated verbal + visual channels
+   subject to cognitive-load management.
+6. Cognitive apprenticeship (Collins / Brown / Newman): modeling,
+   coaching, scaffolding, articulation, reflection, exploration.
+
+**Treatment quality:** sound at the survey level; weak on
+calibration of contested findings.
+
+---
+
+## Literature confirmation pass
+
+To avoid uncritical adoption, three areas with known replication
+or boundary concerns were searched against 2024–2025 literature:
+
+### 1. Productive failure — calibration of the "3x" rhetoric
+
+**Anchor:** Sinha & Kapur 2021 meta-analysis (166 experimental
+comparisons, ~12,000 participants), [SAGE](https://journals.sagepub.com/doi/full/10.3102/00346543211019105).
+
+| Claim | Reality |
+|-------|---------|
+| "3x conventional gains" | Headline from high-fidelity PF studies; meta-analysis average is **d = 0.36**, rising to **d = 0.58** at high design fidelity. Real but more modest. |
+| "Broadly applicable" | **Largely a STEM finding.** Non-STEM evidence scarce; domain-general skill transfer not supported. |
+| "Works for all learners" | Better effects for **older students** (secondary onwards); prior knowledge is a strong moderator (PMC 2023 study on prior math achievement). |
+
+**Verdict for CORE:** PF is the doc's most-overstated technique.
+The structural analog inside CORE (let-attempt-then-review)
+already exists in adversarial generation (ADR-0119.5), but with
+a different mechanism — adversarial generation is a wrong-answer
+*rejection* tool, not a learning-from-attempt tool. Adopting PF
+shape inside CORE would mean intentionally allowing the engine
+to attempt with knowingly-insufficient grounding and learning
+from the gap. **This is the deliberate inverse of CORE's
+`wrong==0` doctrine** and would require structural justification
+beyond "the literature supports it."
+
+### 2. Retrieval practice — transfer limits
+
+**Anchor:** Pan & Rickard 2018 transfer meta-analysis;
+Cognitive Research 2024 follow-up on far-transfer mechanisms,
+[Cognitive Research](https://cognitiveresearchjournal.springeropen.com/articles/10.1186/s41235-024-00598-y).
+
+| Claim | Reality |
+|-------|---------|
+| "Retrieval drives transfer" | **Near transfer: yes (d = 0.4). Far transfer: weak/null (Pan & Rickard d = 0.16, n.s.).** |
+| "Works for complex material" | Strongest for simple materials learned by rote; complex / educationally relevant materials show smaller, more contingent effects. |
+| "Universal mechanism" | Recent work (Cognitive Research 2024): far-transfer benefits appear specifically when **rule-based learning** is the underlying mechanism + after delay. |
+| "Lecture-hall ecological validity" | Glaser & Richter 2025 ([Teaching of Psychology](https://journals.sagepub.com/doi/10.1177/00986283231218943)): testing effect transfers poorly to studied-but-not-practiced content. |
+
+**Verdict for CORE:** Retrieval practice IS the most robust
+finding *for retention of practiced material*. CORE's vault recall
+already encodes the exact-recall ceiling of this technique. The
+*spaced-retrieval* extension (spacing across time) is the part
+not currently modeled in CORE's teaching loop — see ADR-0129.
+
+### 3. Embodied cognition — replication crisis
+
+**Anchor:** Machery 2024 chapter on the embodied-cognition
+replication crisis,
+[Routledge Handbook of Replication](https://www.taylorfrancis.com/chapters/edit/10.4324/9781003322511-50/replication-crisis-embodied-cognition-research-edouard-machery);
+Frontiers in Education 2026 STEM-learning integrative review,
+[Frontiers](https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2026.1811569/full).
+
+| Claim | Reality |
+|-------|---------|
+| Embodied learning effects | **Known replication crisis.** Foundational findings have failed independent replication. |
+| Handwriting > typing | Strongest for very early literacy acquisition; broader generalizations are contested. |
+| Universal benefit | "Embodiment sometimes facilitates learning and sometimes does not" — boundary conditions matter (Frontiers 2026). |
+
+**Verdict for CORE:** Not applicable directly (no body, no
+sensorimotor system). Structural analogs (e.g., the
+algebra/field/vault substrate as "grounding in a non-symbolic
+representation") exist but the analogy is too weak to load-bear
+design decisions.
+
+---
+
+## What the doc missed (frameworks worth knowing)
+
+These should be on the radar even though they weren't in the
+reviewed document:
+
+| Framework | Why it matters |
+|-----------|----------------|
+| **Worked-example effect** (Sweller, Paas, van Merriënboer) | Strong evidence for novice instruction; counter-evidence for experts (see expertise-reversal) |
+| **Expertise-reversal effect** | Techniques that help novices actively hurt experts and vice versa. Directly relevant to CORE's `apprentice → audit-passed → expert` promotion contract (ADR-0120) |
+| **Cognitive load theory** (Sweller) | Distinct intrinsic / extraneous / germane load distinction. Operationally useful for designing teaching corpora |
+| **Deliberate practice** (Ericsson) | Specific goals + immediate feedback + repetition at the edge of capability. Better lens than "active learning" for skill domains |
+| **Self-explanation effect** (Chi) | Narrow but strong evidence, particularly for science learning from worked examples |
+| **Bloom's 2-sigma problem** (1984) | Unsolved benchmark: 1:1 tutoring delivers ~2 SD gains over conventional instruction. Most "evidence-based" techniques are attempts to approach this asymptote without the staffing cost |
+| **Feedback science** (Hattie & Timperley 2007; Wisniewski et al. 2020) | Type / timing / specificity of feedback dominate effect sizes |
+| **Pre-testing effect** (Carpenter, Richland) | Testing *before* studying primes attention. Distinct from retrieval practice |
+
+---
+
+## Cross-walk to CORE architecture
+
+This is the load-bearing section: not "what does the literature
+say" but "what does the literature say that maps onto a structural
+move CORE could make."
+
+| Pedagogy concept | CORE analog | Status |
+|------------------|-------------|--------|
+| Retrieval practice | `teaching/correction.py` + vault recall | **Structurally aligned.** Every reviewed correction IS a retrieval+strengthen event. Exact-recall ceiling already met. |
+| Spaced retrieval | (none) | **Genuine gap.** No deterministic spaced re-verification of past corrections. → ADR-0129 |
+| Interleaving | Cross-pack chains (ADR-0064 / 0067) | **Aligned.** Cross-pack chains force discrimination across domains. |
+| Metacognition / calibration (prediction vs outcome) | (none at teaching layer; partial at runtime via ADR-0035) | **Genuine gap.** No prediction-vs-outcome capture in teaching loop. → ADR-0130 |
+| Cognitive apprenticeship | Ratified packs as articulated expert ontology | **Strong analog.** Packs ARE the encoded expert representation; ratification IS the "fade scaffolding" step. |
+| Worked examples → fading | Teaching corpora → unsupervised generation | **Partial.** Corpora encode correct answers; less so the reasoning chain that produced them. Could be more first-class. |
+| Productive failure | Adversarial generation (ADR-0119.5) | **Different mechanism.** Adversarial generation is rejection; PF would mean attempt-before-grounding. Inverse of `wrong==0`. Not recommended for direct port. |
+| Pre-testing | (none) | Genuine gap. CORE always grounds before articulating; never the reverse. Adopting would conflict with `wrong==0`; not recommended. |
+| Self-explanation | `SolutionTrace` provenance chain | **Structurally present.** Every answer has its derivation. Could be more first-class in teaching-store records. |
+| Cognitive load theory | Substrate hierarchy: algebra → field → vault → realizer | **Implicit alignment.** CORE's layering matches CLT separation of intrinsic structure from extraneous load. |
+| Expertise reversal | Pack-tier promotion (ADR-0120) | **Already encoded.** The `apprentice / audit-passed / expert` contract already knows that what helps an apprentice can ossify an expert. |
+| Desirable difficulties | `wrong == 0` discipline | **Inverse mapping.** CORE refuses *undesirable* difficulty (confabulation under uncertainty). A teaching-side concept of *desirable* difficulty (challenging-but-not-impossible curriculum sequencing) is not yet first-class. |
+| Feedback science | `teaching/review.py` | **Partially aligned.** Reviewed corrections ARE structured feedback. Timing / specificity dimensions could be more first-class. |
+
+---
+
+## The two structural gaps worth addressing
+
+Distilled from the cross-walk, two design moves are both
+*pedagogically supported by robust literature* AND *consistent
+with CORE's existing determinism + provenance discipline*:
+
+### Gap 1 — Spaced reviewed-correction replay
+**Mapped to:** retrieval-with-spacing literature (most robust
+finding).
+**ADR:** [ADR-0129](../decisions/ADR-0129-spaced-correction-replay-deferred.md)
+**Status:** Deferred.
+**Summary:** Periodic deterministic re-run of past reviewed
+corrections to verify they still produce intended outcomes
+under current state. Defense against silent regression as the
+correction store and pack set evolves.
+
+### Gap 2 — Pre-articulation calibration logging
+**Mapped to:** metacognitive calibration / prediction-outcome
+comparison literature.
+**ADR:** [ADR-0130](../decisions/ADR-0130-pre-articulation-calibration-deferred.md)
+**Status:** Deferred.
+**Summary:** When a correction is proposed, log CORE's
+pre-correction prediction; on acceptance, emit the gap.
+Provides empirical answer to "is CORE actually getting better"
+across pack-version cohorts; supports operator triage.
+
+---
+
+## What is NOT proposed (and why)
+
+| Considered | Rejected because |
+|------------|------------------|
+| Adopt productive-failure mechanism inside CORE | Inverse of `wrong==0`; would require structural justification beyond pedagogy literature. Adversarial generation (ADR-0119.5) covers the related "wrong-answer rejection" use case without the conceptual conflict. |
+| Adopt pre-testing in articulation | Same conflict with `wrong==0`. CORE grounds before articulating by design. |
+| Add embodied / sensorimotor layer | No body. The structural analogy (substrate as "grounding") is too weak to load-bear. |
+| Add peer-learning multi-agent loop | Out of scope. Multi-agent coordination is a separate architectural question; not driven by this pedagogy review. |
+| Adopt cognitive-load-theory load-balancing in realizer | Already implicit in the substrate hierarchy. Making it more explicit risks decoration without integration. |
+
+---
+
+## Why both ADRs are deferred, not accepted
+
+Both ADR-0129 and ADR-0130 are **proposed but deferred**, following
+the established ADR-0121 / ADR-0122-deferred pattern. The deferral
+reasons compose:
+
+1. **Path-B uncertainty.** The active GSM8K-math arc
+   (ADR-0126 / 0127 / 0128) may resolve to a benchmark
+   re-targeting. If so, the correction-store population
+   characteristics change, and the right cadence (ADR-0129) /
+   cohort structure (ADR-0130) may differ.
+2. **No observed incident.** Neither ADR has a triggering
+   incident. They're defensive infrastructure — useful if a
+   regression occurs (0129) or calibration drift develops (0130),
+   but speculative without that evidence.
+3. **Cost/benefit unmeasured.** Both add telemetry volume and
+   operator review surface. Worth it only if the signal proves
+   load-bearing.
+4. **Composition argument.** If either is un-deferred, the other
+   should be re-evaluated jointly — spaced-replay events
+   naturally yield calibration evidence; the two share
+   infrastructure. Deferring both together preserves that
+   composition.
+
+The exit criteria for un-deferral are documented in each ADR's
+"Exit criteria for un-deferral" section.
+
+---
+
+## Sequencing recommendation
+
+1. Land ADR-0126 (PR #161) — architecture.
+2. Land ADR-0127 (Gemini in flight) — units pack.
+3. Land ADR-0128 (Opus #2 in flight) — numerics pack.
+4. Re-run train sample with both packs mounted → real Path-A vs
+   Path-B verdict.
+5. If Path A: continue along the math expert promotion path.
+   ADR-0129 / 0130 remain deferred until an incident or
+   bandwidth pressure surfaces them.
+6. If Path B: benchmark re-targeting becomes the work; ADR-0129 /
+   0130 may become more relevant if the new benchmark's
+   correction-store characteristics are different enough to
+   warrant proactive verification.
+
+---
+
+## Reference list (additional to the original document)
+
+- Sinha, T. & Kapur, M. (2021). When Problem Solving Followed by
+  Instruction Works: Evidence for Productive Failure.
+  [SAGE](https://journals.sagepub.com/doi/full/10.3102/00346543211019105)
+- Pan, S. C. & Rickard, T. C. (2018). Transfer of test-enhanced
+  learning: meta-analytic review and synthesis. *Psychological Bulletin*.
+- Glaser, J. & Richter, T. (2025). The Testing Effect in the
+  Lecture Hall: Does it Transfer to Content Studied but Not
+  Practiced? [Teaching of Psychology](https://journals.sagepub.com/doi/10.1177/00986283231218943)
+- Cognitive Research: Principles and Implications (2024). Far
+  transfer of retrieval-practice benefits: rule-based learning
+  as the underlying mechanism.
+  [Springer](https://cognitiveresearchjournal.springeropen.com/articles/10.1186/s41235-024-00598-y)
+- Machery, E. (2024). The Replication Crisis in Embodied Cognition
+  Research. *Routledge Handbook of Replication*.
+  [Taylor & Francis](https://www.taylorfrancis.com/chapters/edit/10.4324/9781003322511-50/replication-crisis-embodied-cognition-research-edouard-machery)
+- Frontiers in Education (2026). Embodied cognition in STEM
+  learning: an integrative review.
+  [Frontiers](https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2026.1811569/full)
+- Sinha & Kapur (2023). Prior math achievement and inventive
+  production predict learning from productive failure.
+  [PMC](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10185511/)
+- Bloom, B. S. (1984). The 2 Sigma Problem.
+  *Educational Researcher 13(6)*.
+- Hattie, J. & Timperley, H. (2007). The Power of Feedback.
+  *Review of Educational Research 77(1)*.
+- Wisniewski, B., Zierer, K., Hattie, J. (2020). The Power of
+  Feedback Revisited: A Meta-Analysis.
+- Ericsson, K. A., et al. (1993). The Role of Deliberate Practice
+  in the Acquisition of Expert Performance.
+  *Psychological Review 100(3)*.
+- Sweller, J., van Merriënboer, J. J. G., Paas, F. G. W. C. (1998).
+  Cognitive Architecture and Instructional Design.
+
+---
+
+## Open questions surfaced (not resolved this session)
+
+These are noted for future sessions; not items I'm advocating
+for action:
+
+1. **Should teaching-corpus records carry "why" structure, not
+   just "what"?** Self-explanation literature suggests reasoning
+   chains in corpora may be more useful than answers alone.
+   `SolutionTrace` already exposes provenance; pushing this into
+   teaching corpora is a separate question.
+2. **Is there a deliberate-practice analog at the curriculum
+   level?** ADR-0120's promotion contract already encodes
+   "stretch-but-pass" structure (correct_rate ≥ 0.60 floor).
+   Whether sub-curricula should also encode this is open.
+3. **Could the pack-mutation-proposal pathway adopt a worked-
+   example pattern?** When a pack mutation is proposed, today
+   the operator sees the diff; could they also see a small
+   worked example showing the behavioral implication?
+   Speculative.
+4. **Is Bloom's 2-sigma a meaningful target for CORE?** A
+   deterministic engine with exact recall has structural
+   properties that may exceed 1:1 tutoring on some axes
+   (consistency, replay) while underperforming on others
+   (adaptation, social affordances). Whether to claim this
+   target is an architectural framing question, not a
+   technical one.
+
+---
+
+## End-of-session state
+
+- **ADRs added:** 0129 (deferred), 0130 (deferred).
+- **Session note:** this file.
+- **Branch:** `docs/pedagogy-review-and-teaching-backlog`.
+- **PR plan:** single docs-only PR for the three files; lands
+  independently of the in-flight ADR-0126 / 0127 / 0128 chain.
+- **No code changes.** No regression risk.