Skills for designing curriculum units and assessments that hold together — unit-level backwards design, knowledge-architecture mapping, differentiation that preserves the cognitive core of a task, project-based learning briefs, scope-and-sequence work, and routing curriculum content by knowledge type. Editorial note: this domain overlaps substantially with the Feedback domain (which already covers competency unpacking, rubric design, formative-assessment selection, gap analysis, learning progressions, and assessment validity) and with Curriculum Alignment (which covers KUD chart authoring, crosswalks, and band translation). We ship cards here that add a distinct lens — unit-level planning rather than item-level, knowledge-architecture rather than alignment-mechanics, and the two strongly evidenced design moves (differentiation, project-based learning) that don't fit cleanly into either neighbouring domain.
Avg. effect (d): 0.46 across the 2 cards with a d-valueStrongest: Project Brief Designer PBL (d=0.71, Chen & Yang 2019)EEF cross-ref: 0/6 cards — no Toolkit strand maps onto curriculum-assessment design workVerification profile: 2 verified-partial, 4 unverified — design moves and framework scholarshipLast reviewed: May 2026
How to read these numbers
"Months of progress" is a teacher-friendly shorthand from the EEF Toolkit. It is not directly comparable across studies — different meta-analyses use different baselines, age groups, and outcome measures. Treat it as a magnitude indicator, not a precise prediction.
Cohen's d is the standardised effect size used in the original meta-analyses. d ≈ 0.40 is Hattie's "hinge point" — the average effect of a year of schooling. Higher = larger relative effect, but context matters more than the number.
Effect sizes are averages. A skill that shows large average effects can still produce small or negative effects in a specific classroom. Use these as a starting point for professional judgment, not a substitute for it.
Sources are dated. Where multiple meta-analyses exist, we lead with the most recent quality study and cross-reference EEF where available.
Implementation cost (Low / Medium / High) is a practical signal — not an exact science — of what your school needs to invest in teacher time, training, and structural changes to actually run the intervention well. It is the editorial team's reading of what the intervention typically requires in practice. Use it to gauge whether something is straightforward to introduce or a larger undertaking — not as a budget figure.
Some interventions are also priced in £ (UK) by the EEF Toolkit. For monetary cost data, see the EEF Teaching & Learning Toolkit.
Colour bands signal calibration, not value. An intervention in the "below typical" band is not "bad" — it means the intervention's average effect is below the typical effect of a year of schooling. That can still be appropriate for specific contexts the average does not capture.
This domain ships a curated subset of Manning's curriculum-assessment skills. Seven of Manning's 13 skills in this domain are already published in our Feedback or Literacy & Critical Thinking domains and are not duplicated here. The cards on this page add a distinct lens (unit-level, knowledge-architecture, differentiation, PBL) on top of what those neighbouring domains already cover.
Curriculum & Assessment Design
Differentiation Adapter
Adapt a classroom task for specific learner needs while preserving the core learning objective intact — the central discipline of differentiated instruction. Built on Tomlinson's content/process/product framework and Universal Design for Learning principles. Honest evidence note: the differentiation literature shows wide disagreement. Deunk et al. 2018 in Educational Research Review — the most rigorous meta-analysis (21 primary studies, 78 effect sizes) — reported small to moderate positive effects, consistent with Hattie's Visible Learning database (d ≈ 0.13–0.20) and EEF Within-class attainment grouping (+1 month). Post-2020 broader meta-analyses in lower-tier journals report substantially larger effects (g = 1.02 in Magableh & Abdullah 2023; g = 1.11 in Sharma & Sharma 2024) but these include studies with weaker inclusion criteria and are less methodologically conservative. Bondie, Dahnke & Zusho's 2019 Review of Research in Education found large implementation gaps between researched differentiation and practised differentiation — which explains why high-effect lab studies don't replicate at classroom scale. The card anchors on the conservative reading: d=0.20.
no EEF strand
d = 0.20Deunk, Smale-Jacobse, de Boer, Doolaard & Bosker, Educational Research Review2018
MediumImplementation
Curriculum & Assessment Design
Project Brief Designer (PBL)
Design a project-based learning brief with a driving question, milestones, and assessment criteria — the spine that turns PBL from 'fun activity' into substantive learning. Anchored on Chen & Yang's 2019 meta-analysis in Educational Research Review (d=0.71 across 30 studies, medium-to-large positive effect on academic achievement compared to traditional instruction). Triangulated with Zhang & Ma's 2023 Frontiers in Psychology meta-analysis (66 studies, 190 effect sizes) which adds a crucial moderator finding: duration matters significantly. Projects of 9–18 weeks produce the strongest effects (SMD=0.673); shorter projects (1–8 weeks) drop to SMD=0.498; single-experiment 'project days' drop further to SMD=0.359; and projects running beyond 18 weeks decline to SMD=0.300 as students lose focus. Most effective in Asian contexts, high school settings, and groups of 4–5. The driving question is the structural element that distinguishes PBL from generic group work — without it, projects drift into activity rather than inquiry.
no EEF strand
d = 0.71Chen & Yang, Educational Research Review2019
HighImplementation
Curriculum & Assessment Design
Backwards Design Unit Planner
Plan a unit using Wiggins & McTighe's backwards design — Stage 1 identify desired results (enduring understandings, transfer goals, essential questions, knowledge and skills), Stage 2 determine acceptable evidence (performance tasks, other evidence), Stage 3 plan learning experiences and instruction. The discipline is structural: assessment evidence is designed before activities, so activities have a clear target rather than the more common pattern of teaching content and then writing a test on it. Use when starting a new unit or redesigning an existing one from standards. Same evidence anchor as the Curriculum Alignment domain's KUD Chart Author card — Wiggins & McTighe 1998/2005/2011 foundational scholarship and Yurtseven 2021 qualitative meta-synthesis — but operating at unit-level rather than objective-level. Verification status: unverified. UbD has a substantial qualitative research base finding positives for cognitive growth, engagement, and motivation, and documenting implementation gaps where teachers default to activity-based planning, but no quantitative meta-analysis with pooled Cohen's d on student outcomes exists.
no EEF strand
no independent meta-analysis found
HighImplementation
Curriculum & Assessment Design
Scope and Sequence Designer
Design a scope and sequence showing vertical and horizontal curriculum coherence across a programme or year. Vertical coherence = topics build on prior topics in a defensible order (Bruner's spiral curriculum at scale: revisit core concepts with increasing complexity). Horizontal coherence = topics across subjects at the same year level support each other rather than conflict (the maths the science class needs is taught before that science unit). Built on Bruner's 1960 Process of Education and 1966 Toward a Theory of Instruction, and the learning-progressions tradition (Heritage 2008, Corcoran, Mosher & Rogat 2009, National Academies Taking Science to School 2007). Sits at the architectural level above the Coverage Audit, Learning Progression Builder, and Developmental Band Translator cards — those operate on individual items, single progressions, and band-tagging respectively; this card designs the meta-structure that the others fill in. Verification status: unverified. Scope-and-sequence work has no isolated meta-analysis; the underlying scholarship is interpretive (Bruner) and methodological (learning-progressions tradition) rather than pooled-effect-size.
no EEF strand
no independent meta-analysis found
HighImplementation
Curriculum & Assessment Design
KUD Knowledge Type Mapper
Classify curriculum content into Wiggins & McTighe's Know / Understand / Do categories to align teaching and assessment approaches. Different from the KUD Chart Author skill in the Curriculum Alignment domain: that skill authors a fresh KUD chart for a target objective (forward design); this skill takes existing curriculum content — inherited from textbooks, prior teachers, national standards — and classifies each item into K/U/D buckets so the right assessment method can be selected for each (diagnostic and routing). Bernstein's distinction between hierarchical and horizontal knowledge structures (Bernstein 1999, 2000) shapes the mapping: mathematics and physics Knows often have to precede Understands; literature and sociology Understands can legitimately sit alongside many Knows. Verification status: unverified — same UbD framework as the chart-authoring card, no pooled Cohen's d on student outcomes; Bernstein's knowledge-structures theory is philosophical scholarship rather than meta-analytic.
no EEF strand
no independent meta-analysis found
MediumImplementation
Curriculum & Assessment Design
Curriculum Knowledge Architecture Designer
Map the epistemic structure of a subject to determine knowledge types and inform curriculum sequencing. Built on Basil Bernstein's distinction between hierarchical knowledge structures (vertical integration, each level depends on the last — maths, physics, formal logic) and horizontal knowledge structures (segmented knowledge with multiple legitimate entry points — literature, history, social sciences), extended by Karl Maton's Legitimation Code Theory (2014) which adds the expert / knower distinction (strong specialised codes in disciplinary STEM vs strong cultural-identity content in disciplinary humanities). The mapping informs how the curriculum should be sequenced and what kinds of assessment fit. Use when designing courses, restructuring programmes, or analysing a subject's knowledge architecture before scope-and-sequence work. Verification status: unverified — this is philosophical scholarship in the sociology of education rather than intervention research. Bernstein and Maton produce no pooled student-outcome effect sizes (that's not the kind of question their tradition answers); what they produce is a precise theoretical vocabulary for the architectural question that scope-and-sequence work then operationalises.
no EEF strand
no independent meta-analysis found
HighImplementation
Interrogate any educational claim
Heard a claim somewhere else? Type it here — we'll build a prompt you can paste into ChatGPT, Claude, or any chatbot. The prompt asks the model to cite real meta-analyses, separate strong from weak evidence, name boundary conditions, flag exaggerations, and discuss cost-effectiveness.
💡 For best results, enable your chatbot's reasoning / thinking mode before pasting — Claude's "Extended thinking", ChatGPT's "Think" mode, or Gemini's "Thinking" / 2.5 Pro reasoning. The prompt is more demanding than a typical Q&A and benefits from slower deliberation.