{"schema_version":1,"assessment_id":"eoa_inverse_innovation_exp03_opportunity320_20260801","source_experiment_id":"eoa_inverse_innovation_exp03_full320_20260801","cell_id":"invariant_mode_decomposition_design__education_pedagogy","archetype_slug":"invariant_mode_decomposition_design","domain_slug":"education_pedagogy","title":"Modal targeting for hidden coupled skill failures","opportunity_summary":"Estimate coupled skill-propagation modes from routine low-stakes checkpoints and select supplemental task bundles intended to damp risky modes, comparing later independent mastery and efficiency with ordinary prerequisite remediation within a bounded course unit.","adopter_authorizer":"Classroom teacher and curriculum lead, jointly and subject to applicable school research, consent, data-protection, and student-protection procedures.","scores":{"meaningful_impact":{"score":3,"rationale":"Preventing delayed non-mastery while conserving instructional time and reducing subgroup disparities would be meaningful, but the frequency, severity, and preventability of coupled failures are unsupported in the sealed candidate."},"stakeholder_pull":{"score":2,"rationale":"Teachers and curriculum leads plausibly face remediation decisions, but the packet supplies no evidence that they recognize coupled propagation as a priority, want model-based targeting, or will accept its added workload."},"incremental_advantage":{"score":3,"rationale":"Targeting persistent or growing skill combinations could outperform remediation of the weakest ordered prerequisite, but no result establishes superior mastery, efficiency, or equity over that strong rival."},"distinctiveness_plausibility":{"score":3,"rationale":"The coupled-mode transition model and mode-selective task targeting form a concrete distinction from coordinate-wise remediation, but prior art is explicitly unsearched and world novelty is unmeasured."},"technical_implementability":{"score":3,"rationale":"Routine item-level checkpoints, a bounded unit, available task bundles, and a specified transition model make estimation conceivable, while small samples, noise, nonstationarity, nonlinear learning, weak spectral separation, and unstable conditioning may prevent a usable model."},"adoption_authority_feasibility":{"score":4,"rationale":"The teacher and curriculum lead are explicitly identified, required instruction is preserved, and high-stakes uses are excluded; feasibility remains conditional on school oversight, consent, data governance, and permission for blocked assignment."},"evidence_readiness":{"score":4,"rationale":"The candidate specifies a bounded unit, nearest-rival comparison, held-out outcomes, residual and drift gates, subgroup checks, falsifiers, and rollback criteria. Missing sample-size, measurement-quality, and task-selectivity evidence prevents the highest score."},"safety_net_benefit":{"score":3,"rationale":"The proposal could reveal prerequisite combinations missed by averages and separate subscores and includes equity and rollback safeguards, but noisy modes could create false alerts, stigma, narrowed instruction, or subgroup error."},"scalability":{"score":2,"rationale":"Routine assessments provide a possible common input, but the model is explicitly local to a unit and curriculum version and may require repeated estimation, specialist analysis, task mapping, drift monitoring, and subgroup validation for each new context."}},"score_confidence":"MODERATE","costs":{"first_evidence":{"band_2026_usd":"50K_TO_250K","scope":"One bounded-unit model-validation study followed, only if validity gates pass, by a short blocked comparison of modal targeting with ordinary prerequisite remediation using routine checkpoints and held-out mastery.","confidence":"LOW","assumptions":["A willing school partner and suitable routine item-level data already exist.","The study covers a limited number of classes or cohorts rather than a district-wide sample.","Costs include protocol design, approvals, data preparation, statistical modeling, task mapping, teacher coordination, subgroup analysis, and reporting.","No major new assessment platform or specialized equipment is required."]},"initial_deployment_startup":{"band_2026_usd":"250K_TO_1M","scope":"Production preparation for use across multiple classrooms in one school or small district after favorable evidence, including data integration, validated task-bundle mapping, decision support, training, governance, and monitoring design.","confidence":"LOW","assumptions":["Existing assessment and learning systems can export sufficiently granular data.","A production workflow requires engineering and analyst support beyond the research prototype.","Deployment remains restricted to validated units and curriculum versions.","Legal, privacy, accessibility, and school research requirements do not require unusually extensive remediation."]},"operational_launch":{"band_2026_usd":"250K_TO_1M","scope":"First supervised multi-classroom operational cycle, including teacher onboarding, model fitting, quality gates, supplemental-material coordination, help desk support, outcome evaluation, and rollback readiness.","confidence":"LOW","assumptions":["Launch is limited to one organization and selected course units.","Normal required instruction continues unchanged.","Human review remains part of assignment decisions.","The organization already has adequate devices, assessments, and secure student-data infrastructure."]},"annual_recurring":{"band_2026_usd":"250K_TO_1M","scope":"Annual operation in one small district or comparable organization, including data pipelines, model refitting, curriculum-version validation, drift and subgroup monitoring, task-library maintenance, training, support, and independent evaluation.","confidence":"LOW","assumptions":["Coverage is limited to selected subjects and units rather than all grades and curricula.","Curriculum and cohort changes require periodic revalidation.","Specialist statistical and data-engineering capacity remains necessary.","No exact staffing, licensing, enrollment, or compliance burden is provided."]}},"research_burden":"HIGH","earliest_credible_horizon":"3_TO_12_MONTHS","pipeline_gates":{"recognizable_externally_supportable_problem":{"status":"YES","reason":"The packet defines an observable and falsifiable problem: acceptable aggregates can coexist with coupled skill patterns that predict delayed non-mastery. Its prevalence and magnitude remain unverified, but the problem itself is externally testable."},"identifiable_adopter_or_authorizer":{"status":"YES","reason":"The classroom teacher and curriculum lead are named as joint authorizers under applicable school procedures, with participating students and affected teachers identified."},"distinct_testable_incremental_claim":{"status":"YES","reason":"The proposal claims that mode-targeted supplemental tasks can improve later independent mastery or efficiency over item-level weakest-prerequisite remediation, subject to explicit model-validity and subgroup constraints."},"bounded_next_evidence_step":{"status":"YES","reason":"A single-unit study using routine checkpoints, held-out validation, validity gates, and a short blocked comparison is bounded and includes both problem and intervention falsifiers."},"no_unresolved_safety_or_authority_stop":{"status":"YES","reason":"High-stakes decisions, fixed student labels, withholding required instruction, and out-of-scope deployment are prohibited; consent, oversight, workload, equity, and validity failures trigger stopping or rollback. Actual approvals are still prerequisites, not assumed facts."},"implementation_cost_scope_and_range":{"status":"UNCERTAIN","reason":"The candidate bounds the instructional and analytical scope but provides no sample size, staffing, system-integration requirements, data condition, task-development burden, or deployment scale from which a reliable resource range can be established."}},"blocking_evidence":["Held-out data must show a reproducible, sufficiently stable, well-conditioned, spectrally separated coupled transition rather than noise, structured residuals, or a single observable-skill explanation.","Available supplemental task bundles must measurably and selectively move the estimated risky mode without narrowing or displacing required instruction.","With validity gates satisfied, modal targeting must improve later independent mastery or instructional efficiency over prerequisite remediation.","Subgroup prediction and outcome errors must remain within preregistered margins, without stigmatizing labels or differential loss of support.","Teacher workload and coordination burden must be acceptable relative to any observed benefit.","Required school authorization, consent or waiver, privacy safeguards, and permission for blocked assignment must be secured before prospective comparison."],"next_evidence_step":"With one school partner, preregister a bounded single-unit study that first fits the transition model on routine checkpoints and tests mode stability, conditioning, spectral separation, residual structure, and held-out prediction against independent-skill and weakest-prerequisite models; proceed to a short blocked comparison of modal versus prerequisite task selection only if those gates pass, and reject the proposal if coupled propagation is not reproducible or if modal targeting fails to improve held-out mastery or efficiency within the subgroup-safety margin.","research_questions":["Do coupled modes remain stable across held-out weeks and cohorts after accounting for measurement error and assessment-induced behavior?","Does a coupled transition model predict delayed non-mastery better than a single-skill or independent-deficit model?","Can available task bundles selectively damp an estimated risky mode, and how is that selectivity verified?","Does modal targeting improve later independent mastery or instructional-time efficiency over weakest-prerequisite remediation?","How sensitive are assignments and outcomes to model specification, conditioning thresholds, missing data, and curriculum changes?","Are prediction errors, assignment rates, outcomes, and lost instructional opportunities acceptably distributed across student subgroups?","What teacher workload, analytic expertise, data integration, consent, and governance are required for sustained use?","What adjacent educational methods or prior art already use multivariate transition modes or comparable coupled-skill targeting?"] ,"recommendation":"PARTNERED_RESEARCH","uncertainty_constraints":["Closed-book assessment provides no external evidence of problem prevalence, stakeholder demand, educational effectiveness, novelty, market size, or realized impact.","The transition is only an approximate local linear model of adaptive, potentially nonlinear and nonstationary learners.","Small samples and noisy criterion-referenced estimates may manufacture or rotate modes.","A mathematical mode cannot be assumed to represent an independent cognitive mechanism or student type.","Cost bands are low-confidence resource-equivalent ranges because staffing, sample size, data condition, software, compliance, and organizational scale are unspecified.","Permission for random assignment, student-data use, and research participation is conditional on local procedures and has not been established."],"closed_book_prior_art_boundary":"The candidate is classified as UNSEARCHED and makes no novelty claim. This assessment can recognize the specified difference from its stated baseline and nearest rival, but cannot determine whether modal skill-transition analysis, multivariate mastery targeting, or equivalent interventions already exist, how prevalent they are, or whether they have demonstrated impact."}