Lingua.ly
Immersion-based language learning through real-world web content and context-aware SRS.
The world's first math program that marks every step of a student's working.
Mathspace is a sophisticated adaptive learning platform designed for the K-12 mathematics sector, distinguished by its proprietary evaluation engine that analyzes every step of a student's mathematical reasoning. Unlike traditional EdTech platforms that only validate final answers, Mathspace utilizes a generative feedback loop to identify specific misconceptions in real-time. The 2026 architecture leverages advanced handwriting recognition (Digital Ink) and Large Language Models (LLMs) to provide contextual hints and video tutorials tailored to the individual's current hurdle. Its market position is solidified by its 'Waypoints' diagnostic tool, which provides a continuous map of student proficiency against curriculum standards (CCSS, NSW, etc.) without the need for high-stakes testing. By 2026, Mathspace has evolved into a comprehensive digital ecosystem that integrates seamlessly with major Learning Management Systems, offering data-driven insights for educators to facilitate differentiated instruction. The technical backbone is optimized for low-latency processing of mathematical expressions, supporting both symbolic and numerical inputs across a wide range of devices, ensuring equitable access in diverse educational environments.
A proprietary symbolic logic engine that evaluates intermediate mathematical steps, providing feedback on the process, not just the product.
Immersion-based language learning through real-world web content and context-aware SRS.
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Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Continuous, non-intrusive assessment algorithm that maps student knowledge against a global skill graph.
Machine learning algorithms that adjust the difficulty and sequence of questions based on a student's real-time accuracy and speed.
Neural network-based handwriting recognition optimized for complex mathematical symbols and fractions.
Dynamic scaffolding that breaks down complex multi-part problems into digestible sub-tasks if the student struggles.
Real-time data visualization of classroom performance, highlighting common misconceptions across the group.
Contextual hints delivered based on the specific error type (e.g., sign error vs. conceptual error).
Teachers struggle to assign homework that challenges top students without overwhelming those who are behind.
Registry Updated:2/7/2026
The system adjusts difficulty level after every three questions.
Teacher monitors the 'Mastery' heat map to see who reached the goal.
Traditional diagnostic tests are time-consuming and only provide a snapshot in time.
Typing math is cumbersome and slows down the learning process.