Understanding Our AI Leadership

Harnessing AI to Empower Teachers.

What Is AI in Special Education?

At Let’s Go Learn, our foundation has always been built on research-based, fully validated diagnostic assessments — created by experts, not algorithms. Our math and reading diagnostics, developed long before AI became mainstream, deliver the most granular and actionable data in the industry.

Now, AI is helping us take this trusted data even further. By empowering teachers, special education coordinators, and administrators to save time and drive targeted instruction, we’re turning great data into great outcomes.

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Classroom of the Future

Why Let’s Go Learn is Uniquely Positioned to Lead in AI for Education:

  • Research-Based Diagnostics: Built by educators and experts, not AI — and trusted for over two decades.
  • Incredible Depth: 44 math sub-tests and comprehensive reading diagnostics provide unparalleled insight.
  • Human Expertise First: Our assessments remain fully human-designed; AI simply helps to unlock their power.
  • AI Empowering Educators: Supports teachers, SPED coordinators, and administrators by saving time and reducing manual work.
  • Actionable Insights: AI translates rich data into clear next steps, draft PLAAFPs, Smart Goals, and more.
  • Customizable Outputs: We fine-tune AI outputs to match district-specific formats and preferences.

See Our AI Assistant in Action

With our AI Assistant, educators can:

  • Instantly generate draft PLAAFPs and supporting documentation
  • Quickly identify skill gaps and next instructional steps
  • Review student diagnostic data in an easy-to-digest format
  • Document system to store draft to final working files associated with each student
ADAM Diagnostic Assessment on Laptop Screen

Technical Excellence: Engineered for Precision

Before AI, we were already ahead — and we still are.

Our ecosystem was built with precision from day one, with native grade-equivalency scoring and data compatibility that others simply can’t match.

  • Seamless System Compatibility: Our quizzes and baseline assessments share a unified data structure.
  • Vertical Grade Alignment: Our scoring system clearly shows student progress across grades and subjects.
  • Supporting Today’s Standards: We support initiatives like Mastery Checkpoints Program (MCP) and Google’s A2A (Assessment-to-Assignment), helping schools stay aligned with evolving best practices.
  • Future-Proof Foundation: Our human-developed assessments ensure long-term reliability, while AI enhances usability.

Our Roadmap: The Future of Personalized AI Support

We’re not stopping here. We’re building a future where our trusted data continues to power increasingly intelligent AI assistance.

Here’s what’s coming next:

  • Customer-Specific Fine-Tuning: Using anonymized samples of customer PLAAFPs, Smart Goals, and Impact Statements, we refine AI outputs to match district-preferred formats.
  • Deeper Personalization: Custom outputs, starting from our trusted diagnostic data, ensure accuracy and familiarity.
  • Enhanced Smart Recommendations: AI-driven instructional suggestions aligned to district goals and learner needs.
  • Continuous Learning AI: As standards evolve, so will our AI models — always grounded in our original, human-developed data foundation.

Click the document to the right to see our most uptodate AI Roadmap document.

LGL AI Roadmap

Key Benefits for Special Education

Common Questions

How does LGL work with students who need accommodations?

Given the nature of Let’s Go Learn assessments, test accommodations will tend to have more flexibility based on the discretion of the resource teacher or the district policy. DORA, ADAM, and DOMA are diagnostic assessments, meaning that their data is generally not used for high-stakes accountability. As a result, if the student’s accommodation calls for the allowance of a calculator during a math assessment, Let’s Go Learn permits this accommodation to be made and does not have any strict policy against a teacher or administrator making this decision. Scores are not rolled up into a normalizing algorithm, which in the case of a high-stakes assessment might restrict scores with accommodations from being used.


Diagnostic 

Assessments


Personalized 

Instruction


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Areas of Focus