ReadBuddy 

readbuddy.ai

Newark's low literacy rates among K-12 students are a big challenge that needs fresh, innovative solutions since the old ways haven't really worked. To tackle this challenge, I, Jhamar Youngblood, candidate for councilman of Newark’s Central Ward, am excited to introduce ReadBuddy—an AI-powered learning companion that helps students improve their literacy skills through interactive reading exercises, real-time pronunciation feedback, and personalized comprehension assessments. Unlike other literacy tools, ReadBuddy offers a unique combination of AI-driven pronunciation analysis and in-depth comprehension evaluation, creating a comprehensive and engaging learning experience tailored to each student’s needs. By focusing on a localized approach that takes into account regional accents and the specific needs of diverse communities, such as Newark’s, ReadBuddy aims to provide a pathway to success for every student in our city. 

This initiative showcases my dedication to education and serves as a key part of my campaign to introduce innovative, tailored solutions to Newark—moving away from the outdated frameworks and ideas that other politicians often rely on.

Overview of the Software

The goal of this software is to help K-12 students in Newark improve their literacy skills by leveraging AI technologies. 

The software will focus on two primary functions:

  • Pronunciation Analysis: The software will use speech recognition and natural language processing (NLP) to analyze students' pronunciation and provide instant feedback to help them improve.

  • Reading Comprehension: The software will assess students' understanding of texts by analyzing their responses to questions and providing personalized recommendations for improvement.

Core Features and Functionality

User Interface (UI):

  • Kid-friendly, intuitive interface with visual aids for younger children.

  • Interactive elements like quizzes, games, and flashcards.

  • Progress tracking dashboard for students, teachers, and parents.

Speech Recognition and Pronunciation Analysis:

  • Use pre-trained models for speech recognition (e.g., Google's Speech-to-Text API or open-source alternatives like Mozilla DeepSpeech).

  • Incorporate NLP models to detect pronunciation errors and provide feedback.

  • Develop a feature to record and analyze student readings, highlighting mispronunciations and offering suggestions for correction.

Reading Comprehension Assessment:

  • Implement NLP models (e.g., BERT, GPT) to evaluate the complexity of texts.

  • Generate quizzes and comprehension questions dynamically based on the content.

  • Analyze students' responses to assess comprehension and provide personalized feedback.

Personalized Learning Paths:

  • AI-driven recommendation engine to suggest reading materials and exercises tailored to the student's current skill level.

  • Adaptive learning algorithms to modify difficulty based on ongoing performance.

Data Privacy and Security:

  • Implement end-to-end encryption for all data transactions.

  • Ensure compliance with COPPA (Children’s Online Privacy Protection Act) and FERPA (Family Educational Rights and Privacy Act).

  • Secure storage solutions for audio recordings and analysis results.

Technical Architecture

Frontend:

  • Technologies: React Native (for cross-platform mobile app development).

  • Features: Real-time interaction capabilities, audio recording, and playback

Backend:

  • Technologies: Node.js for server-side logic, Python for AI/ML model integration.

  • Services: AWS, Google Cloud, or Azure for cloud services, including AI model hosting and data storage.

  • Database: NoSQL database (e.g., MongoDB) for handling dynamic data related to student profiles, progress, and feedback.

AI/ML Models:

  • Speech Recognition: Custom model trained with local accents and pronunciation patterns or use existing APIs with fine-tuning.

  • NLP Models: Pre-trained language models like BERT or GPT, fine-tuned on educational datasets.

  • Reinforcement Learning: For personalized learning paths and adaptive difficulty adjustments.

Development Roadmap

Research and Planning:

  • Identify specific literacy challenges faced by K-12 students in Newark.

  • Collaborate with educators to define requirements and desired outcomes.

  • Conduct a feasibility study to choose the right technologies and platforms.

Partnership with NJIT:

  • Approach NJIT’s computer science and education departments to form a collaborative team.

  • Define roles and responsibilities for NJIT faculty and students.

  • Secure funding and resources from NJIT, local grants, or educational foundations.

Prototype Development:

  • Develop a basic version of the app with core functionalities: audio recording, speech analysis, and comprehension assessment.

  • Use NJIT resources for initial development and testing.

  • Conduct usability testing with a small group of students and teachers in Newark

Iterative Development and Testing:

  • Incorporate feedback from initial testing to improve UI/UX and core functionalities.

  • Expand AI model capabilities and fine-tune them based on local dialects and accents.

  • Conduct security audits and ensure compliance with privacy laws.

Pilot Program:

  • Launch a pilot program in a select number of schools in Newark’s Central Ward.

  • Gather data on usage, effectiveness, and user satisfaction.

  • Refine the software based on pilot feedback.

Full Deployment and Scaling:

  • Deploy the software to all interested schools in Newark.

  • Establish ongoing support and training for teachers and students.

  • Develop a long-term maintenance and update plan.

Partnership Plan with NJIT/Rutgers

Formal Agreement:

  • Draft a memorandum of understanding (MoU) outlining the partnership's objectives, contributions, and benefits.

  • Establish a joint steering committee to oversee the project.

Resource Allocation:

  • Utilize NJIT’s/Rutgers expertise in AI, machine learning, and software development.

  • Involve NJIT/Rutgers students in development as part of their coursework or internships.

  • Leverage NJIT’s/Rutgers computing resources for initial AI model training and testing.

Research and Development:

  • Collaborate on research papers and publications based on the project outcomes.

  • Use this project as a case study for NJIT’s/Rutgers educational technology courses.

Community Engagement:

  • Host workshops and seminars for teachers in Newark, led by NJIT faculty.

  • Create opportunities for NJIT students to mentor Newark K-12 students.

Help Needed

Budget:

  • Estimate total costs, including development, testing, deployment, and maintenance.

  • Identify potential funding sources: local government grants, educational foundations, corporate sponsorships.

Technology Stack:

  • Ensure the technology stack mentioned above is scalable and maintainable.

  • Find the available open-source tools to reduce costs.

Impact Assessment:

  • Establish key performance indicators (KPIs) to measure the software's effectiveness in improving literacy.

  • Plan for periodic reviews and updates based on performance data.

Closing

Let’s work together to boost literacy in Newark! If you’re excited about making a difference and believe in fresh, innovative solutions, I’d love for you to join me in this effort. Whether you’re a parent, teacher, techie, donor, or just someone who cares about our community, there’s a place for you in this project with ReadBuddy. We need all kinds of skills and support to help our kids succeed. So, if you’re ready to roll up your sleeves and get involved, reach out today and let’s make a real impact for Newark’s future!