EdTech Platform: Accessible Learning for 2M+ Students

Testing and optimizing an AI-driven learning platform for WCAG 2.1 AA compliance and seamless performance across low-bandwidth regions.

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January 20, 2023 Education

Client

A leading EdTech company serving K-12 and higher education

The Challenge

The platform served 2M+ students across diverse regions including rural areas with limited internet. Accessibility was a legal requirement for public school contracts. The AI-driven adaptive learning engine needed validation for pedagogical accuracy and fairness across demographics.

Our Solution

We conducted comprehensive accessibility testing against WCAG 2.1 AA standards, performance optimization for low-bandwidth environments, AI fairness testing across demographic groups, and cross-platform testing covering Chromebooks, tablets, and smartphones used in classrooms.

Education technology has the power to democratize learning, but only if it works for every student regardless of their abilities, devices, or internet connectivity.

Our accessibility testing program went beyond automated scanning. We conducted testing with screen readers (JAWS, NVDA, VoiceOver), keyboard-only navigation, and switch device access. We also partnered with students with disabilities for usability feedback.

Low-bandwidth optimization required creative approaches including progressive content loading, offline-capable assessments, and adaptive media quality. We tested across simulated network conditions from 3G to satellite internet.

AI fairness testing was particularly important — we validated that the adaptive learning algorithm provided equally effective recommendations regardless of student demographics, catching and helping resolve two algorithmic biases.

Key Results

1

WCAG 2.1 AA compliance achieved across all platform features

2

Platform usable on connections as slow as 256kbps

3

AI learning path recommendations validated for demographic fairness

4

Won 12 new public school district contracts post-certification

5

Student engagement metrics improved 40% with optimized performance

Technologies Used

ReactNode.jsTensorFlow.jsLighthouseAxeBrowserStack

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