Overview
AI tools can provide individualized, timely feedback, helping students refine their work and deepen their understanding of key concepts, skills, and areas for improvement. However, receiving feedback from AI, teachers, or peers is only one part of the learning process. Students need the skills and structures to interpret, evaluate, and apply feedback effectively to truly benefit.
Without intentional support, students may accept AI-generated suggestions uncritically or ignore them altogether, missing opportunities for meaningful learning. By integrating structured reflection, goal-setting, and revision strategies, educators can help students develop metacognitive skills that allow them to engage with feedback thoughtfully and take ownership of their learning.
Building these skills ensures that AI-generated feedback becomes more than just a list of corrections — it becomes a tool for deeper thinking, meaningful revision, and long-term growth.
Example From the School Teams AI Collaborative
To help students develop the skills needed to process and apply AI-generated feedback effectively, educators at The Eliot School participating in the School Teams AI Collaborative designed a structured approach that integrates reflection, discussion, and revision. ELA teachers in grades 5-8 integrated AI-generated feedback into writing instruction, ensuring students actively processed and applied insights rather than treating AI as an automatic correction tool. Their approach combined co-developed AI prompts, structured reflection, and teacher-led goal-setting conferences to support metacognitive skill-building. This process follows four structured steps:
Generating Targeted AI Feedback: Teachers collaboratively designed and refined AI prompts to ensure Claude’s feedback was clear, student-friendly, and aligned with instructional goals. Standardizing these prompts ensured that AI-generated feedback remained consistent across classrooms. Before sharing, teachers reviewed and refined the AI feedback to ensure its accuracy and developmental appropriateness.
Engaging in Structured Reflection: Students used the Literary Essay Revision Checklist, a co-developed tool that guides them through identifying strengths, areas for growth, and next steps before engaging in revisions. This standardized reflection process ensured all students had a structured approach to processing AI feedback before making changes.
Facilitating Teacher-Led Feedback Conferences: Teachers followed a shared conferencing structure, ensuring all students could ask questions, clarify misunderstandings, and refine their revision plans. By aligning conference protocols, educators ensured students received consistent support across classrooms.
Applying Feedback in Revisions: After reflecting independently and engaging in a structured conference, students applied their feedback and revised their writing. Teachers monitored student progress using conferring logs and student reflections, making adjustments as needed.
This structured, collaborative approach ensured that AI feedback was not just a tool for individual teachers but an integrated school-wide practice that supported metacognitive skill development and deeper student engagement with feedback.
Apply This Strategy in Your Context
Educators looking to help students process and apply AI-generated feedback effectively can take the following steps:
Structure Opportunities for Reflection: Provide structured reflection tools to help students critically engage with AI-generated feedback rather than passively accept it. A revision checklist or targeted prompts — such as What does this feedback tell me? or What specific changes should I make? — can guide students in identifying strengths and areas for growth. Teachers can model how to analyze and prioritize AI feedback, ensuring students develop the metacognitive skills needed to make thoughtful revisions.
Align AI Feedback Expectations and Practices Across Classrooms: For AI-generated feedback to be meaningful, educators should establish clear guidelines for how students engage with AI tools. Standardizing AI-generated feedback prompts helps ensure that feedback is consistent, actionable, and developmentally appropriate. Using structured approaches like the AI stoplight protocol can clarify when and how students should incorporate AI insights. Collaborating with colleagues to align how AI is introduced, used, and processed across classrooms ensures that students develop a coherent and scaffolded approach to self-revision.
Support Application of Feedback Through Targeted Instruction and Conferences: AI feedback should be a starting point for deeper learning, not a shortcut to correctness. Provide students with structured opportunities to discuss and refine revisions through teacher-led feedback conferences, small group coaching, or peer review. During these discussions, students can ask questions, examine the reasoning behind AI-generated feedback, and decide how to apply or challenge AI suggestions.
Ensure Students Apply Feedback and Reflect on Growth: Encourage students to track and reflect on how they use AI feedback in their revisions over time. Using a conferring log, digital tracker, or portfolio, students can document what feedback they received, how they responded, and what changes they made. This process helps students recognize their progress and strengthens transferable skills in self-assessment, revision, and independent learning.
By implementing these strategies, educators ensure that AI-generated feedback becomes a tool for active student learning rather than a passive correction mechanism. With structured opportunities to reflect, discuss, and apply feedback, students take ownership of their learning, develop confidence in evaluating feedback critically, and build lifelong skills for self-directed improvement.
This AI-enabled strategy was developed by a member of the School Teams AI Collaborative — a partnership between Leading Educators and The Learning Accelerator (TLA). The Collaborative was developed to bring together innovative educators from schools across the country to share ideas and discover effective ways to use AI in the classroom.
Strategy Resources
The Eliot School’s Student-Facing AI Feedback Conferring Log (Paper)
Student-facing conference log designed by the Eliot School to support student processing of AI-generated feedback. Learn More
The Eliot School’s Generative AI Student Feedback Shared Prompt Framework
Shared Claude student writing feedback prompting framework developed by The Eliot School’s ELA department. Learn More
The Eliot School’s Literary Essay Feedback Reflection Checklist
Essay revision checklist designed by the Eliot School’s ELA department to support students in processing... Learn More
The Eliot School: AI-Generated Feedback - Student Work Sample 1
Sixth-grade student work sample demonstrating the application of AI-generated feedback. Learn More
The Eliot School: AI-Generated Feedback - Student Work Sample 2
Sixth-grade student work sample demonstrating the application of AI-generated feedback. Learn More
The mission of the Eliot K-8 Innovation School is to provide a fully inclusive, joyful, rigorous learning journey that prepares every student to achieve their highest potential by embracing their identities, developing interdisciplinary 21st-century skills, and applying an antiracist mindset empowered by knowledge to participate actively in a complex and constantly changing, culturally diverse world.
