learning-progression-builder

これはレビュー時に保存された抜粋です。完全で最新の内容は外部ソースを確認してください。

---
# AGENT SKILLS STANDARD FIELDS (v2)
name: learning-progression-builder
description: "Build a learning progression showing prerequisite-to-mastery steps for a target skill or understanding. Use when sequencing content, designing diagnostics, or mapping prerequisite gaps."
disable-model-invocation: false
user-invocable: true
effort: medium

# EXISTING FIELDS

skill_id: "curriculum-assessment/learning-progression-builder"
skill_name: "Learning Progression Builder"
domain: "curriculum-assessment"
version: "1.0"
evidence_strength: "moderate"
evidence_sources:
  - "Heritage (2008) — Learning progressions: supporting instruction and formative assessment"
  - "Popham (2007) — The lowdown on learning progressions"
  - "Daro et al. (2011) — Learning trajectories in mathematics: a foundation for standards, curriculum, assessment, and instruction"
  - "Wilson & Bertenthal (2005) — Systems for state science assessment"
  - "Hattie & Donoghue (2016) — Learning strategies: a synthesis and conceptual model"
input_schema:
  required:
    - field: "target_skill"
      type: "string"
      description: "The skill or understanding at the end of the progression — what students should be able to do"
    - field: "student_level"
      type: "string"
      description: "Age/year group range the progression covers"
  optional:
    - field: "subject_area"
      type: "string"
      description: "The curriculum subject"
    - field: "starting_point"
      type: "string"
      description: "Where students typically begin — their existing knowledge"
    - field: "student_profiles"
      type: "array"
      description: "From context engine: class data showing where different students currently sit on the progression"
    - field: "curriculum_framework"
      type: "string"
      description: "From context engine: relevant curriculum standards or progression documents"
output_schema:
  type: "object"
  fields:
    - field: "progression_map"
      type: "array"
      description: "Ordered sequence of stages from novice to target, with observable indicators at each stage"
    - field: "prerequisite_relationships"
      type: "object"
      description: "Which stages depend on which — the prerequisite structure"
    - field: "common_stuck_points"
      type: "array"
      description: "Where students commonly stall and why"
    - field: "diagnostic_tasks"
      type: "array"
      description: "Quick tasks that reveal which stage a student is at"
chains_well_with:
  - "competency-unpacker"
  - "formative-assessment-technique-selector"
  - "practice-problem-sequence-designer"
  - "backwards-design-unit-planner"
  - "curriculum-knowledge-architecture-designer"
  - "scope-and-sequence-designer"
teacher_time: "4 minutes"
tags: ["learning-progressions", "trajectories", "prerequisites", "diagnostic", "curriculum-mapping"]
---

# Learning Progression Builder

## What This Skill Does

Maps the learning progression from novice to target proficiency for a specific skill domain, identifying the sequential stages of understanding, the prerequisite relationships between them (what must come before what), common stuck points (where students typically stall and why), and diagnostic tasks that reveal which stage a student is currently at. The output is a progression map that teachers can use for three purposes: planning instruction (teaching in the right sequence), formative assessment (diagnosing where a student is), and differentiation (providing the right support for each student's current stage). AI is specifically valuable here because constructing a valid learning progression requires both deep content knowledge (understanding the logical structure of the domain) and pedagogical knowledge (knowing where students actually get stuck, which is not always where the content logic would predict).

## Evidence Foundation

Heritage (2008) defined learning progressions as "descriptions of the successively more sophisticated ways of thinking about a topic that can follow one