Research & Resources

We are building an evidence-informed organization that learns in public, protects participants, and shares practical resources with educators and communities.

Questions that matter for students, educators, and schools.

• When and how does AI-supported practice strengthen middle school academic learning?

• What educator knowledge and support are needed for responsible implementation?

• How do access, infrastructure, language, disability, and bias shape outcomes?

• Which forms of human oversight best support learning quality and student safety?

• How should schools evaluate tools, pilots, and long-term adoption decisions?

• What models can expand opportunity without widening existing gaps?

Measure what matters—and be honest about what the evidence can support.

Academic evidence

Skill growth, work quality, reasoning, explanation, and progress toward the partner’s defined learning goals.

Experience evidence

Educator usefulness, student engagement, workload, usability, accessibility, and implementation conditions.

Responsibility evidence

Privacy, safety, bias, transparency, human review, academic integrity, and unintended consequences.

Practical materials for responsible implementation.

Resources will be published as they are developed and reviewed. The live site can link to Google Drive files, PDFs, videos, and external publications.

Responsible AI Classroom Readiness Checklist

A pre-pilot checklist for goals, roles, privacy, safety, educator preparation, and student communication.

Educator AI Implementation Toolkit

Planning templates, sample guardrails, task-design guidance, reflection tools, and evaluation prompts.

Middle School AI Literacy Framework

Developmentally appropriate competencies for asking, evaluating, revising, explaining, and using AI responsibly.

Pilot Learning Briefs

Clear summaries of partner context, approach, findings, limitations, and next steps.

Research quality begins with respect for people.

Any research involving students, educators, or identifiable data should use appropriate consent, permissions, privacy protections, data minimization, security, and—when applicable—institutional review or independent ethics oversight.

Collaborate on research or resource development.

We welcome conversations with universities, researchers, educators, evaluators, and mission-aligned funders.