AI for BLV Educators

How to leverage AI to reclaim time on high-stakes writing tasks, particularly FVAs LMAs, by shifting from handwritten notes to voice-captured observations and structured prompting, while navigating student privacy and district policies.

JJ shared her comprehensive FVA/LMA workflow, which included:

Using voice-to-text (iPhone Notes or AI recorders) to capture real-time observations and parent interviews, eliminating downtime and allowing more human connection during assessments rather than distracted note-taking.

Creating a reusable "Master Prompt" that pre-loads district templates, rubrics, and evidence-based clinical sources (ACVREP, CVI research) to ensure consistent, non-deficit-based language and professional tone.

Treating AI as a processing tool rather than storage: redacting all Personally Identifiable Information before uploading, never using student photos or signatures, and verifying outputs with professional judgment before finalizing reports.

Generating narrative sections from raw data (distance chart results, parent transcripts) and drafting parent-friendly definitions of ocular conditions.

Resources:
JJ's slide deck: AI as Accessibility for TSVIs
FVA/LMA Master Prompt and How-To Guide
AI Empowered EDU 2026 conference at University of Portland

Start simple, one task or prompt and leveraging the microphone feature for "rambling voicemail" style input that AI synthesizes into structured text.

Student-facing: JJ discussed using ChatGPT or Gemini as a "backup book" for math problem-solving, where students check work and explore alternative solution methods rather than simply retrieving answers. Participants stressed teaching critical thinking and digital citizenship, particularly regarding accessibility (prompting AI to remove emojis and use screen-reader-friendly formatting).