learning-objectives

To write measurable learning objectives aligned with Bloom's taxonomy, define eval-first success criteria and map each statement to concrete assessment methods. This ensures objectives are specific, testable, and progressively complex across proficiency levels.

Eval-first design for curriculum planning is the process of defining concrete success criteria and assessment methods before writing the actual learning objectives. This approach ensures statements remain specific, actionable, and testable throughout course design.

Mapping CEFR proficiency levels to course learning objectives involves attaching specific CEFR scales to generated objective blocks. This ensures progressive complexity in language learning contexts and aligns outcomes with standardized accreditation requirements.

Yes, you can generate YAML-ready objective blocks for curriculum validation. The process outputs structured data fields including id, statement, blooms_level, context, prerequisites, assessment_method, and success_criteria for direct deployment.

Yes, this approach supports AI co-learning integration for lesson design through a Three-Role framework where AI acts as teacher, student, and coworker. This fosters collaborative generation of measurable learning outcomes.

Yes, you need YAML to structure learning objectives and assessment methods. The system requires YAML to output portable objective blocks containing fields like prerequisites and success criteria for validation and curriculum deployment.