Students often lack emotionally intelligent, accessible academic help. Traditional tools are either too generic or lack personalized feedback. This product gives students AI-powered learning support with sentiment-aware, tailored content to improve engagement and outcomes.
English-speaking students globally, especially in the U.S., with particular value for under-resourced school districts and remote learners.
Python-based CLI prototype integrating OpenAI GPT-3.5-turbo and VADER for sentiment analysis. Designed for future expansion into a web app (React/Flask or Streamlit).
Mission is to improve equitable access to personalized education and AI-powered learning tools.
Helps students feel heard, supported, and confident. Uses sentiment data to adjust tone and content delivery.
| Persona | Psychographic (Values & Motivation) | Behavioral (Patterns & Usage) | Need-Based (Pain Points & Desired Outcome) |
|---|---|---|---|
| Anika (11th grader, anxious overachiever) | High-achieving, perfectionist. Values academic success and validation. Gets overwhelmed by ambiguity or failure. | Uses multiple study apps, studies late, searches for precise answers. Reacts emotionally to feedback or unclear explanations. | Needs clear, accurate, emotionally sensitive support. Wants fast help to feel reassured and stay ahead. |
| Jake (10th grader, underserved learner) | Curious and motivated to improve but lacks structure and resources. Values simplicity, accessibility, and independence. | Inconsistent study habits, uses public/shared devices, prefers examples over theory. | Needs low-friction, relatable help that’s easy to digest. Struggles with organization and confidence. |
| Priya (College student, volunteer tutor) | Service-driven, values educational impact. Balances many responsibilities, seeks efficiency and quality. | Manages multiple students at once, struggling too curate personalized lesson plans for each. | Needs pre-curated content to better support students/ |