Determining keyboard accessibility with Intelligent Guided Tests
Sep 8, 2026 - Sep 8, 2026
1 credit
Full course description
Term: Fall 2026
Date: September 8th, 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 Keyboard Intelligent Guided Test (IGT), a feature of the axe DevTools Pro browser extension, and the keyboard accessibility problems it is designed to detect. These include missing or low-contrast focus indicators, mouse-only controls, focusable hidden content, unexpected changes of context on focus, controls that open new windows on focus, missing interactive roles, and keyboard traps.
During the workshop, the instructor will run the IGT on several focused demonstration pages. Participants will observe the auto-tabber, answer questions about skipped elements and alternative keyboard paths, and see how their answers generate findings. Participants may use the remaining time to begin the homework assignment: completing a full Keyboard IGT on the Enterprise Security & Infrastructure Dashboard practice page and submitting the saved review 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 page.
Course Objectives:
By the end of this workshop, participants will be able to:
1. Complete a Keyboard IGT, including the auto-tabbing process and questions about skipped elements, alternative keyboard paths, and interactive roles.
2. Distinguish accessible keyboard behavior from failures such as an invisible focus indicator, a keyboard-inaccessible control, a keyboard trap, or a change of context on focus.
3. Save and submit a Keyboard IGT review of the practice page, explore generative AI-assisted remediation of identified issues, and re-run the IGT on the updated page.
