Date: Wednesday, July 15, 2026
Time: 3:00pm - 4:00pm ET
Pricing: Free for RESNA Members | $45 for Non-Members
Speaker(s): Sharvari Dixit, OTR/L, ATP, Empower AT Services
Lcation: Zoom via RESNA Learn
Webinar Series: Building a Streamlined AT Assessment System in K-12 Schools
Part 3: Feature Matching and AT Trials
Abstract:
Gathering assessment data is only the beginning of the AT process. The real clinical work happens in what comes next: translating functional data into defensible tool recommendations through systematic feature matching and structured trials. This session focuses on the decision-making engine of AT practice — how practitioners move from a documented access barrier to a trialed, evidence-supported recommendation. Participants will learn to apply a hypothesis-driven feature matching framework. They will also learn to design and document AT trials that produce defensible data, and to interpret trial results — including negative outcomes — as meaningful clinical information. Using a running case study, the session walks through feature matching and tool walkthroughs for reading access, written output, and writing
organization. This work culminates in a complete feature-based recommendation statement that is ready to be translated into IEP language in Part 4. The tools referenced throughout this session — including Read&Write, OrbitNote, and Mindomo — are examples drawn from the presenter's direct clinical experience in K–12 settings. They are used to illustrate specific AT features in practice and do not constitute endorsement or promotion of any product.
Currently under review for IACET credit approval.
Learning Outcomes:
By the end of this session, participants will be able to:
- Define feature matching and explain why it begins with the access barrier rather than the
tool
2. Design a structured AT trial — including task selection, the feature being tested,
conditions, and data to be collected — that produces defensible, documentable evidence
3. Interpret both positive and negative trial results as clinical evidence
4. Apply a hypothesis-driven framework to match specific tool features to documented
student barriers
5. Construct a feature-based recommendation statement that connects assessment data to
expected functional outcomes
Currently under review for IACET credit approval.
Target Audience: Assistive Technology specialists, occupational therapists, special education teachers, speech-language pathologists, and related service providers working in K–12 settings.
Completion of this webinar and all required components earns 0.1 IACET CEU.
Click "Register' in the upper right corner to register today.