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A Personalize E-Learning System

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# EduSmart: Panaversity Personalized Learning Platform

## EduSmart Mini Projects

### Task 1: GQL Schema via Phrases
Build a GQL schema via phrases which stores Program and Course Content, Interactions, Student Profile, Tracks Students, etc.

Technology Used: GQL Editor

Team: Junaid, Osman, Wania

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### Task 2: Dummy Neo4j AuraDB
Develop a Python UV Console Project that creates a dummy Neo4j AuraDB based on Schema created in Tast 1 which teams will use to develop there code until the real DB is up and running.

Technology: Neo4j AuraDB, Neo4j Python SDK, Python UV

Team: Suhail, Raheela

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### Task 3: Student Chatbot (Artifact/Canvas)
This will be a student chatbot which will interact with the 
student and help him in his learning jounery. Intially it will
create a student profile. It will also show the student the 
content (in markdown) which will be taught in the next class and 
the timing and detials of each class. After each class it will 
interact with the student to identify his understanding and help 
him/her with personalized content. It will also take the midterm
and final evalution exams. The Claude Artifact type chatbot is a
perfect fit for students. We will be developing chatbot with
bidirectional Q&A interface where both the AI and student can ask
questions, similar to how human conversations naturally flow.

3a. Create Student Profile by Interacting with him/her covering Python, Maths, English, and IQ

3b. Show the Text Topics in markdown to students before the class (may be personalized).

3b. Create interactions which students will take after attending the class and lab. The explaination of answers will be personalized.

4b. Take the mid term and final quizzes.

Technology: Next.js, [Open Canvas](https://github.com/langchain-ai/open-canvas), LangGraph, LangChain, Neo4j AuraDB

Team: Junaid, Wania, Ahmed

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### Task 4: Teacher Chatbot (Artifact/Canvas)
This will be a teacher chatbot which will generate content 
(Textbook and Interaction) and keep the teacher in the loop. 
It will also help the teacher track student progress.
The OpenAI Canvas type chatbot is a perfect fit for the teachers.
We will be developing chatbot with bidirectional Q&A interface 
where both the AI and teacher can ask questions, similar to
how human conversations naturally flow.

4a. Generate Text Book Table of Content and Content in AuraDB

4b. Generate Interactions (Questions) in AuraDB

4c. Track students and generate Student Analysis Reports

Technology: Next.js, [Open Canvas](https://github.com/langchain-ai/open-canvas), LangGraph, LangChain, Neo4j AuraDB

Team: Rehan,

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### Task 5: Github Textbook Repository Creator and Updater (Optional)
5a. This project part will take the content (Textbook) stored in Neo4j AuraDB and create a GitHub Repository. The Python script will push the content in the repository. In each repository file it will also store the metadata in [front matter](https://www.npmjs.com/package/front-matter)

5b. This project part will syncronize the GitHub to the Neo4j AuraDB using the GitHub Actions.

Technology: Neo4j AuraDB, Neo4j Python SDK, GitHub, GitHub Actions, Python UV

Team:

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