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Website: https://equaled.v0.build/
Project Description:
EqualEd is an innovative educational platform designed to democratise access to college readiness resources for underserved high school students. By leveraging generative AI, EqualEd provides personalised support across crucial areas like college application guidance, financial aid resources, and standardised test preparation. This platform seeks to address the systemic challenges faced by low-income and underrepresented students who often lack access to the support systems essential for navigating the complex journey to higher education.
The initial focus of EqualEd is an AI-driven chatbot, designed to deliver tailored assistance based on each student’s unique needs. Starting with a chatbot allows me to introduce core functionalities incrementally, enabling deeper insights through user interactions and iterative refinement. This approach has underscored the importance of understanding student and counselor needs, crafting an inclusive onboarding experience, and inspiring student agency in their educational journey.
Through the process of designing and refining EqualEd, I have gained significant insights into learning design, particularly in balancing technology’s capabilities with the human element in education. This journey has shown me the value of incorporating user feedback, and the need for adaptable, iterative development when addressing real-world issues in educational equity. EqualEd ultimately aims to bridge gaps in access, empower students, and make the college application process more accessible and transparent.
Learning Reflections and Next Steps:
Reflecting on the design process, I’ve learned that effective educational tools require a deep understanding of user needs and flexibility in approach. This project has taught me the importance of prioritising the initial user experience and focusing on key pain points early on. If I were to start a new project, I’d incorporate more structured frameworks for gathering user insights from the outset and lean more into community participation to ensure the solution resonates broadly.
Moving forward, I aim to continue developing EqualEd’s prototype into a more comprehensive platform, incorporating feedback from counselors and students. My goal is to refine the AI model with college-specific resources, engage students and educators in the development process, and expand EqualEd’s capabilities while maintaining a focus on accessibility, inclusiveness, and empowerment.
Technical Details and Implementation Plan:
EqualEd is in its early stages, with a clear vision for building a dynamic, AI-driven platform to deliver personalised college readiness support to underserved students. Leveraging OpenAI’s API, the platform will use conversational AI trained on college readiness resources to provide tailored guidance on college applications, financial aid, and standardised test preparation. The goal is for EqualEd to adapt dynamically to each student’s needs, delivering highly personalised and relevant answers.
Key Technical Elements :
- OpenAI’s API: The backbone of the AI-powered chatbot. This API enables adaptive, conversational college readiness support tailored to each student’s unique needs.
- Stack AI: Stack AI will be utilised to training the AI chatbot specifically on curated college readiness content, materials and resources, ensuring high relevance in responses.
- Prototype Website Development with V0: The current prototype, built using V0 by Vercel, provides a basic web interface where students can interact with the AI chatbot and see core features. This MVP allows for early feedback from students and counselors, and serves as a foundation for further iterative development.
Future Enhancements (Long-Term Vision):
- Dynamic Learning Model: The AI model will adapt and refine its responses based on user interactions and feedback over time.
- Recommendation Engine: This will offer personalised resources, such as articles, practice tests, and financial aid links, based on each student’s engagement and progress.
- Sentiment Analysis: Understanding user sentiment and emotions will allow the AI to respond empathetically, especially for students feeling overwhelmed or anxious by the college application process.
- Counselor-Facing Dashboard: This will enable counselors to monitor trends in student engagement and identify where support is needed the most, while still respecting privacy.
This phased development approach allows for flexibility, enabling EqualEd to start with a simple prototype and grow based on user needs and feedback. By combining all these technologies and having a roadmap of feature development, EqualEd will become a robust personalised college readiness tool that addresses critical gaps in higher ed access and support.
