Course

Determining the accessibility of tables with Intelligent Guided Tests

Ended Sep 3, 2026
1 credit

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Full course description

Term: Fall 2026

Date: September 3rd, 2026

Time: 2:00 to 3:00 p.m.

Location: Online Only

Instructors: Robert Fentress & Sunayana Mishra

Presented By: Technology-enhanced Learning and Online Strategies (TLOS)

 

Description:

This workshop introduces the Table Intelligent Guided Test (IGT), a feature of the axe DevTools Pro browser extension, which evaluates table structure and header markup. Participants will learn to classify tables as having one header row, one header column, both row and column headers, irregular headers, multilevel headers, or a layout-only purpose, and to identify visual headers that are not programmatically marked as headers. 

During the workshop, the instructor will use several focused examples to demonstrate each classification, including a data table with its semantics removed and a layout table that incorrectly exposes table roles to assistive technologies. Participants may use the remaining time to begin the homework assignment: running the Table IGT on every table on the SaaS Executive Performance Dashboard practice page and submitting the saved reviews within one week. 

An optional brownbag lunch will be offered during the following week for questions and additional support. The answer key will be shared after the submission deadline. The workshop concludes with an exploration of how generative AI tools can help remediate issues identified during the IGT review, followed by re-testing the updated tables. 

 

Course Objectives:

By the end of this workshop, participants will be able to: 

    Classify a table in the Table IGT and complete the missing-header evaluation appropriate to that classification. 

    Distinguish data tables from layout tables and identify missing or overridden header markup that prevents assistive technologies from conveying row and column context. 

    Save and submit Table IGT reviews of the practice page, explore generative AI-assisted remediation of identified issues, and re-test the updated tables.