Lingua.ly
Immersion-based language learning through real-world web content and context-aware SRS.

Code.org is a non-profit organization and leading EdTech platform that has evolved from basic block-coding into a comprehensive technical ecosystem for Computer Science and Artificial Intelligence. By 2026, the platform has integrated advanced generative AI modules within its 'App Lab' and 'AI Lab' environments, allowing students to train classification models and integrate them into JavaScript-based applications. Technically, the platform utilizes a proprietary transpiler that converts Google Blockly visual blocks into executable JavaScript, providing a bridge between logical abstraction and syntax-based programming. Its infrastructure is designed for extreme scale, supporting millions of concurrent sandbox environments that execute in the browser via client-side rendering, ensuring privacy and low latency without heavy server-side execution. As a market leader, Code.org acts as the primary pipeline for the next generation of software engineers, emphasizing ethical AI deployment, data bias awareness, and the 'human-in-the-loop' paradigm. Its 2026 roadmap focuses heavily on LLM (Large Language Model) literacy, teaching students how to architect prompts and manage context windows in a safe, sandboxed environment.
A browser-based environment where students can train, test, and export machine learning classification models.
Immersion-based language learning through real-world web content and context-aware SRS.
Hybrid language mastery through pedagogical technology and expert human oversight.
Master vocabulary 10x faster with AI-driven spaced repetition and big-data linguistics.
Accelerate Spanish and English mastery through Lingu, an adaptive AI tutor that personalizes every lesson.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Real-time conversion of visual logic blocks into industry-standard JavaScript code.
A rapid prototyping tool using HTML, CSS, and JS with a library of pre-built UI components.
A controlled LLM interface that allows students to learn prompt engineering within pedagogical guardrails.
Cross-curricular modules linking computer science to math, science, and history datasets.
Interactive data visualization engine supporting large CSV uploads for trend analysis.
A virtual network simulation showing packet switching, IP addressing, and protocol hierarchies.
Students need to understand how computers categorize plastic waste.
Registry Updated:2/7/2026
Discuss ethical bias in the initial training set labels.
Enabling students to build mobile-ready tools without mobile SDKs.
Teaching students to interact with LLMs effectively and safely.