Instructional Frameworks

We share rubrics and frameworks that help educators:

Evaluate AI-supported instructional practices

Assess student AI literacy and responsible use

Reflect on instructional quality, not just tool usage

Support consistent expectations across classrooms and schools

These tools are designed for reflection, not compliance, and can be adapted for different grade levels and content areas.

AI Implementation Guidance

The Design, Define, Demonstrate Framework is Washington Leadership Academy’s instructional framework for using AI in ways that strengthen learning rather than replace student thinking. Grounded in backwards design, the framework asks teachers to begin with a clear learning goal and then determine how AI can meaningfully support that outcome. At WLA, this means starting with a Human → AI → Human approach from AI for Equity: students first generate their own ideas, use AI as a thinking partner for feedback or iteration, and then return to independent revision and judgment. This keeps human thinking at the center while making room for purposeful innovation.

The framework also emphasizes clarity and modeling. Teachers must explicitly define what level of AI use is permitted for each assignment, using a bounded, guided approach rather than unrestricted access. Just as importantly, they must demonstrate how AI should be used in that specific context, showing students how to prompt effectively, evaluate outputs critically, and reflect on what the tool improved and what still required their own reasoning. Together, the Design, Define, Demonstrate Framework provides a practical, human-centered model for responsible AI integration that builds student agency, supports strong instruction, and helps schools move beyond tool use toward real learning.

AI Classroom Usage Guidance by Adam Browning

AI Coaching @ WLA

The AI Coaching at WLA framework outlines a comprehensive, yearlong approach to building educator and student capacity in the responsible, meaningful use of artificial intelligence. Designed as a coaching model rather than a one-time initiative, the framework supports sustained growth through monthly professional learning, classroom-based coaching, and student-centered experiences.

The framework is organized around three interconnected strands: effective implementation of AI and educational technology tools by teachers; development of AI literacy for both educators and students; and opportunities for students to use and create with AI in authentic, creative, and problem-solving contexts. Together, these strands ensure that AI integration is aligned to instructional goals, ethical considerations, and long-term student outcomes.

Through a structured progression, from listening and piloting to scaling, cross-curricular integration, and sustainability, the AI Coaching framework emphasizes trust-building, reflective practice, and continuous improvement. A tiered rubric supports clarity and consistency by defining what growth looks like for educators and students over time. This model serves as a replicable example of how schools can move from experimentation to intentional, equity-driven AI integration.

Levels of Classroom AI Use

The Levels of Classroom AI Use document offers a practical framework for defining how artificial intelligence may be used in classroom learning and assessment. It outlines a clear progression—from no AI use, to planning support, collaboration, full use, and creative exploration—helping educators make expectations explicit and intentional.

By distinguishing different levels of AI engagement, the framework supports transparency, academic integrity, and instructional alignment. It encourages students to demonstrate core skills while also developing the ability to critically evaluate, refine, and responsibly collaborate with AI tools. Schools can use this framework to clarify norms, support consistent practice across classrooms, and communicate clearly with students and families about appropriate AI use in learning environments

Want to Contribute or Request a Resource?

We welcome collaboration and feedback. Let us know if you:

Have a resource you’d like to share

Want guidance on adapting a tool

Are looking for a specific framework or rubric