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Development of an AI-Powered Educational Math Support Application for Students
  1. case
  2. Development of an AI-Powered Educational Math Support Application for Students

Development of an AI-Powered Educational Math Support Application for Students

neurosys.com
Education

Educational Challenges in Math Comprehension among Students

Students often encounter difficulties in understanding and solving mathematical problems due to lack of detailed, step-by-step explanations and limited access to interactive learning resources, leading to poor comprehension and reduced engagement with math education.

About the Client

A mid-sized educational technology company seeking to enhance math learning experiences for primary and secondary school students through innovative software solutions.

Goals for Developing an AI-Enhanced Math Learning Platform

  • Create a mobile application for iOS and Android that enables students to easily find and understand solutions to math problems from textbooks.
  • Implement an OCR-based task recognition mechanism to allow quick digitization of textbook tasks via smartphone camera.
  • Develop an administrator web dashboard for managing textbooks, math tasks, and solutions.
  • Achieve high user engagement metrics, targeting over 150,000 downloads and registered users within the initial launch phase.
  • Facilitate effective learning by providing detailed, step-by-step solutions with explanations authored by qualified teachers.

Core Functional System Capabilities for Math Education Support

  • Mobile app for students to browse textbooks, scan ISBN codes, capture math tasks via camera, and view step-by-step solutions.
  • OCR module utilizing API integration to recognize handwritten or printed math problems from images.
  • Database management system to store textbooks, math tasks, solutions, and user data.
  • Web-based dashboard for administrators to upload and organize textbooks, add new math tasks, and manage solutions.
  • Ability to link solutions and multimedia explanations (e.g., mini-podcasts) to specific tasks.
  • User registration, login, and progress tracking functionalities.

Technological Frameworks and Architectural Preferences

Cross-platform mobile development frameworks (e.g., React Native or Next.js for web dashboards)
TypeScript for robust frontend and backend code
Nest.js as backend framework
Elasticsearch for efficient search and retrieval of tasks
Google OCR API for task recognition
MariaDB or equivalent relational database
Google Cloud Platform for deployment and scalable infrastructure

External System Integrations for Functionality Enhancement

  • Google OCR API for text/image recognition of math problems
  • Textbook ISBN database for quick textbook addition
  • Content management systems for storing multimedia explanations

Non-Functional System Performance and Security Criteria

  • System scalability to handle at least 200,000 users within the first year
  • High performance with fast OCR processing and responsive UI
  • Security measures to protect user data and prevent unauthorized access
  • High reliability with minimal downtime, aiming for 99.9% uptime
  • Compliance with relevant data privacy regulations

Projected Business and Educational Impact of the Platform

The development of this AI-powered math learning platform aims to significantly improve students' comprehension and problem-solving skills, targeting over 150,000 downloads and extensive engagement. By providing accessible, interactive, and detailed solutions, the platform is expected to enhance math literacy, increase user retention, and support scalable growth in the online education space.

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