Pedagogical Assessment Prover MCP Connector for Claude
A+A curriculum listed 12 learning objectives. Every one used 'understand' — an unmeasurable verb. Pedagogical Assessment Prover forces Bloom's-aligned objectives, explicit rubrics, scaffolded instruction, and actionable feedback.
AI agents generate lesson plans and assessments that look professional but violate fundamental principles of learning science. They write learning objectives using 'understand' — a verb that cannot be observed or measured. They assess at Level 1 (recall) while claiming to teach Level 4 (analysis). They provide feedback that is empty praise rather than actionable guidance.
The Problem It Solves
AI-generated pedagogical reasoning fails for five specific reasons:
- Taxonomy misalignment — The learning objective says 'analyze' but the assessment tests 'remember.' This misalignment means you're measuring the wrong cognitive level.
- Rubric absence — Evaluation without explicit, observable, measurable criteria. 'Grade based on quality' is subjective judgment, not assessment.
- Scaffolding gap — Instruction that assumes prerequisites without diagnosing or building them. Teaching above the Zone of Proximal Development causes frustration, below it causes boredom.
- Feedback vacuum — 'Good job' and 'needs improvement' are value judgments, not feedback. Hattie's research (d = 0.70) shows feedback is among the most powerful influences on learning — but ONLY when task-specific and forward-looking.
- Bias blindness — Assessment that disadvantages learners based on cultural background, language proficiency, or neurological differences without systematic review.
Key Benefits
- Enforces Bloom's alignment — Every learning objective must use observable verbs at the same cognitive level as the assessment task. No more 'students will understand.'
- Demands explicit rubrics — Observable criteria, distinct performance levels, behaviorally anchored descriptors, shared with learners before assessment.
- Requires scaffolded instruction — Prior knowledge diagnosis, prerequisite mapping, graduated release (I do → We do → You do), and UDL-compliant representations.
- Forces actionable feedback — Feed Up (where am I going?), Feed Back (how am I doing?), Feed Forward (where to next?) per Hattie & Timperley's model.
- Audits for bias — Cultural relevance, linguistic accessibility, UDL Principle II compliance, accessibility, and differential item functioning.
Pedagogical Framework Coverage
- Bloom's Taxonomy — Anderson & Krathwohl (2001) revision
- Webb's Depth of Knowledge — DOK levels 1-4
- Understanding by Design — Wiggins & McTighe backward design
- Zone of Proximal Development — Vygotsky's scaffolding theory
- Visible Learning — Hattie's effect size research
- Universal Design for Learning — CAST framework, 3 principles
- Assessment FOR Learning — Stiggins formative assessment
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