• C1 = Get it (find the right AI content).
• C2 = Fit it (make it work for your students).
• C3 = Prove it (check, improve, and finalize it for accuracy and effectiveness).
  
  

  Dimension	C1. Content Retrieval	C2. Instructional Adaptation	C3. Critical Inspection
  Primary Focus	Finding and obtaining relevant instructional materials, insights, or data from AI that align with educational goals.	Reshaping AI-generated content so it fits the classroom context, student needs, and institutional expectations.	Evaluating the accuracy, usefulness, and relevance of AI content, then refining it through further AI use and professional judgment.
  Core Skill	Search & selection – prompting effectively to get aligned, useful materials.	Modification & contextualization – tailoring content for differentiation, modality, tone, and cultural fit.	Quality assurance & improvement – fact-checking, assessing instructional fit, and iteratively improving the content.
  When It Happens	First stage – during idea generation and initial resource gathering.	Second stage – after retrieval, before lesson delivery.	Continuous stage – after adaptation and even during delivery, ensuring final quality.
  Teacher’s Role	Curator – chooses the most relevant AI outputs.	Designer – modifies AI outputs into classroom-ready resources.	Reviewer & editor – rigorously inspects and perfects AI outputs for accuracy and effectiveness.
  Indicators of Success	Retrieved content is relevant to objectives.	Adapted content is accessible, engaging, and matches student profiles and educational settings.	Final content is error-free, instructionally strong, and aligned to both curriculum and context.
  End Product	Raw, relevant AI-generated material.	Customized, useful classroom-ready instructional resources.	Fully vetted and polished materials suitable for direct use or sharing.

   

   

To achieve C1. Content Retrieval, educators need to develop the ability to efficiently pull AI-generated resources that are directly relevant to their curriculum goals, while ensuring the content is relevant to their objectives.

1. Define Clear Retrieval Goals

• Identify curriculum alignment: Know the relevant standards, learning objectives, and skill targets before prompting AI.
• Specify instructional purpose: Clarify whether the content is for lesson planning, student activities, assessment, or professional development.

2. Identify Specific Context

• Provide detailed context: Include subject, grade level, standards, desired difficulty, and any special considerations (ELL, IEP, cultural context).
• Request specific formats: Ask AI for the output type you need, e.g., lesson outlines, reading passages, problem sets, discussion questions, charts, tables.
  

3. Interactive Refinement

• Clear and specific prompts: Provide AI with precise requests that clearly articulate goals and context.
• Iterate for refinement: Iteratively improve output relevance by actively identifying and adding missing contextual information.

To achieve C2. Instructional Adaptation, educators must be able to take existing or AI-generated content and rework it so it truly fits their students, instructional context, and institutional expectations, turning generic outputs into classroom-ready materials.

1. Analyze the AI Output

• Check for alignment: Ensure the content supports the intended learning objectives and standards.
• Identify gaps or excesses: Look for missing scaffolds, overly simple or complex sections, or content that exceeds what students’ prior knowledge or current educational settings.
• Evaluate appropriateness: Confirm that examples, language, and references are culturally responsive and age-appropriate.

2. Adapt for Student Needs

• Adjust difficulty and complexity: Adjusting language and content for emerging learners or enrich for advanced learners.
• Integrate differentiation: Create alternative versions for ELL students, IEP/504 accommodations, and varied learning needs.
• Provide scaffolds: Add guiding questions, vocabulary lists, visual aids, or graphic organizers.

3. Modify Format and Modality

• Change delivery mode: Turn text explanations into visuals, slides, podcasts, simulations, or interactive activities.
• Shift activity type: Convert a reading passage into a discussion prompt, a hands-on task, or a project-based challenge.
• Balance teacher- vs. student-led use: Adjust content based on pedagogical strategies, for example, turn the content into an explicit teaching resource or a student exploration tool.

4. Refine Tone and Style

• Match classroom culture: Adapt tone for formal instruction, playful exploration, or inquiry-based learning to foster a positive learning enironment.
• Localize examples: Replace generic references with locally relevant, culturally familiar, or personally meaningful examples.
• Embed values and norms: Ensure the content reflects your institution’s mission, community values, and professional principles.

5. Integrate into Lesson Flow

• Align with existing materials: Blend the adapted content with your existing lesson sequence, resources, and assessments.
• Ensure coherence: Transition smoothly between adapted AI materials, teacher-created content, and institution-adopted curriculum.
• Pilot and adjust: Test the adapted resource in class, observe student response, and refine for future use.

To achieve C3. Critical Inspection, educators need to develop the ability to critically evaluate AI-generated outputs for quality and appropriateness, and then use AI itself (alongside professional expertise) to improve those outputs until they meet instructional standards.

1. Accuracy Verification

• Fact-check content: Compare AI-generated information against trusted academic, curriculum, or subject-specific sources.
• Identify conceptual errors: Flag inaccuracies, logical inconsistencies, or misleading explanations.
• Check citations and data: Verify that references (if provided) are legitimate and match the claims.

2. Usefulness Evaluation

• Assess instructional fit: Determine whether the content helps achieve the stated learning objectives.
• Consider cognitive load: Judge whether the content’s complexity is appropriate for your students’ readiness level.
• Prioritize engagement: Evaluate whether examples, formats, or scenarios will capture and sustain student interest.

3. Relevance Assessment

• Check alignment with curriculum: Ensure the content meets your district’s or institution’s scope and sequence.
• Ensure contextual appropriateness: Review for cultural responsiveness, policy initiatives, and community norms.
• Match to learning environment: Confirm that the content’s format and tone fit the intended audience and delivery mode (e.g., in-person, online, hybrid).

4. Operating AI for Refinement

• Iterative prompting: Feed back specific revision requests to the AI (e.g., “simplify language,” “add local context related to […],” “provide three examples for visual learners”).
• Selective integration: Strategically selecting to integrate and implement high-quality elements of the output.
• Multi-pass improvement: Use multiple approaches or tools to verify accuracy and factuality.

5. Professional Judgment

• Balance AI suggestions with expertise: Maintain the teacher’s voice and instructional intent over AI default patterns.
• Document reasoning: Note why changes were made for transparency and future reference.
• Share vetted content: Utilize or share only fully reviewed and refined materials.