Workshop Registration Details

Work samples are one of the most powerful and overlooked sources of learning data in special education. This session shows how AI can support, not replace, professional judgment when analyzing student writing, math, and classroom tasks. Participants will learn practical, research-informed procedures for identifying error patterns, task demands, skill gaps, and instructional mismatches using authentic student work. We will also address ethical use of AI, including privacy, bias, transparency, and maintaining evaluator responsibility in decision-making. Through guided examples, you will see how thoughtful work-sample analysis can move beyond surface-level mistakes to yield clearer, more defensible statements that connect student performance to standards, classroom expectations, and eligibility decisions. You will leave with practical tools you can use immediately in your evaluations.
Attendees will be able to participate in this webinar in their district via the Zoom link provided in the registration confirmation email and professional development records.

CPE

ARD / IEP
Artificial Intelligence (AI)
Assessment
Evaluation
Legal / Stat / Regulatory Req
Special Education

Diagnosticians
Related Services Personnel
SP (LSSP)
Special Ed Directors
Speech-Language Pathologists

Early Childhood
Headstart
Pre-Kinder
Kinder
1st
2nd
3rd
4th
5th
6th
7th
8th
9th
10th
11th
12th

*Region 7 Colleges /Universities (FREE)
*Region 7 Districts /Charters (FREE)
*Employees of Region 7 ESC (FREE)
IMPACT ETX (FREE)