📖 Lorebound
Lorebound Turn your study material into an after class adventure. Your knowledge is your weapon.
👤 Team Information
| Field | Details |
|---|---|
| Name | Naif Ali Bin Dair |
| Country | Saudi Arabia |
| Track | Productivity |
Project Description
Overview
Lorebound is an AI-powered web application that transforms students' study material into an interactive role-playing game experience. Instead of passively re-reading notes or grinding through flashcards after class, students upload their study PDF, name a character, choose a world, and are immediately dropped into a living narrative — where every question they answer correctly advances their story, and every wrong answer costs them a life and earns them an explanation.
The application is designed for after-class, single-session studying — a focused 15–30 minute experience that reinforces what was just learned through active recall wrapped in engaging storytelling.
The Problem
After-class studying is one of the most important and most neglected stages of learning. Students know they should review their material, but conventional methods — re-reading notes, Quizlet sets, or static practice tests — offer no motivation, no engagement, and no consequence for wrong answers. The result is passive skimming rather than genuine recall.
The gap Lorebound fills is simple: students don't avoid studying because the material is hard — they avoid it because it's boring.
The Solution
Lorebound solves this by combining three proven learning techniques with generative AI:
1. Active Recall — Instead of reading, students are challenged with questions directly generated from their own material, forcing genuine memory retrieval.
2. Consequence-Based Learning — The Hearts system means wrong answers have a cost. Stakes — even fictional ones — increase engagement and focus.
3. Immediate Corrective Feedback — When a student answers incorrectly, the AI doesn't just mark it wrong and move on. It pauses the story, explains the concept clearly, and then continues. The mistake becomes a teaching moment embedded in the narrative.
These three elements are wrapped inside a Gemini-powered generative narrative that is unique to every student's character name, chosen world, and study material — making every session feel personal and immersive.
How It Works
Student uploads PDF + sets character name & world
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Gemini reads the PDF and builds a narrative world from the content
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Story begins — the character enters a world themed around the student's input
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At key story beats, the AI generates a multiple-choice question from the PDF
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Correct answer → story advances, hearts maintained
Wrong answer → heart lost + AI explains the concept → story continues
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Session ends when hearts reach 0 or the material is covered
Core Features
🎭 Generative Narrator
Google Gemini acts as a live storyteller. It reads the uploaded PDF and generates a unique narrative world based on the student's character name and world description. No two sessions produce the same story — the AI adapts the setting, tone, and characters to match the student's input.
📄 PDF-to-Quest Integration
The student's study material is the source of truth. Gemini extracts key concepts, definitions, and facts from the uploaded PDF and converts them into multiple-choice challenges that appear organically within the story. There are no pre-written question banks — every question is generated live from the student's actual material.
❤️ Hearts & Consequence System
Students begin with a set number of hearts — their health within the story. Correct answers keep the narrative moving forward. Wrong answers cost a heart and trigger a narrative setback (the character faces a challenge, loses ground, or encounters an obstacle). When all hearts are lost, the adventure ends. This system creates low-stakes but real consequences that keep students alert and engaged.
💬 Real-Time Corrective Explanations
This is the most educationally significant feature. When a student answers incorrectly, the AI does not simply reveal the right answer. It pauses the story and delivers a clear, contextual explanation of why the correct answer is right and what the student misunderstood — using language grounded in the student's own study material. Learning happens at the point of failure.
⚡ Streaming Responses
Gemini's responses are delivered word-by-word in real time, giving the session the feeling of a live storytelling experience rather than a static quiz. This pacing is intentional — it maintains immersion and gives students time to absorb the narrative before each challenge.
Technologies Used
| Layer | Technology |
|---|---|
| AI / LLM | Google Gemini API |
| PDF Processing | Gemini Document Understanding (native PDF input) |
| Streaming | Gemini streaming API |
| Frontend | HTML, CSS, JavaScript, React, Vite |
| Hosting | Netlify |
| Language | Arabic / English bilingual support |
Hackathon Theme Alignment
Primary Theme: Education Technology
Lorebound directly addresses one of the most persistent challenges in education — student engagement during self-directed study. It does not replace the classroom or the teacher. It specifically targets the after-class window, the period where retention is most at risk and motivation is lowest.
The project demonstrates:
- A meaningful, real-world problem with a clear target user (students at any level)
- An original application of generative AI beyond chatbot use cases
- A functional, working prototype with end-to-end flow
- Accessibility considerations (bilingual support, simple onboarding)
- Scalability potential across subjects, languages, and education levels
Impact
| Metric | Impact |
|---|---|
| Target Users | Students at secondary and university level |
| Use Case | After-class review sessions (15–30 min) |
| Subject Coverage | Any subject with a PDF — fully universal |
| Language Reach | English and Arabic |
| Learning Outcome | Active recall, corrective feedback, engagement |
Every student, regardless of subject or level, has study material in PDF format. Study RPG requires no integration with institutional systems, no teacher setup, and no prior configuration. A student can go from uploading a PDF to answering questions inside their personalized story in under two minutes.
Future Roadmap
While the current version is scoped as a single-session, after-class tool, the architecture supports meaningful expansion:
- Session summary — A post-game report showing which questions were missed and which concepts need review
- Voice narration — Text-to-speech for the story segments to deepen immersion
- Multiplayer study mode — Competing with classmates using the same PDF
- LMS integration — Connecting with platforms like Google Classroom or Moodle for direct material import
Screenshots
See attached UI previews
| Screen | Description |
|---|---|
| Landing Page | Introduction to Study RPG with feature overview and Start Adventure CTA |
| Character Setup | Form to enter character name, world description, hearts count, and PDF upload |
| Game Screen | Live narrative with character stats, story text, and A/B/C/D answer buttons |
GitHub Repository
https://github.com/naif-bin-dair/Lorebound
Demo Link
Built With
- css
- gemini
- html
- javascript
- netlify
- react
- vite
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