Objective

To develop a platform that generates personalized learning paths and syllabi for students based on their academic history, performance, and learning preferences using AI and Machine Learning techniques.

Key Features

Student Panel:

• Input academic history and subject preferences

• Receive personalized syllabus tailored to strengths and weaknesses

• Adaptive learning path with recommended topics and difficulty levels

• Option to prioritize topics for exam preparation

• Track progress along the suggested syllabus

Teacher Panel:

• Upload course curriculum and topics

• Review AI-generated personalized syllabi for students

• Provide additional suggestions or adjustments

• Monitor student performance on recommended syllabus

 Admin Panel:

• Manage users (students & teachers)

• Configure AI model settings (recommendation algorithms, difficulty weighting)

• View analytics of overall student progress and syllabus effectiveness

Tech Stack

Workflow (Step-by-Step)

1. Student Profile Input

• Student logs in and enters academic history:

  • Grades, completed courses, interests, weak areas

2. Data Analysis

• AI engine analyzes:

  • Past performance

  • Learning speed and style

  • Weak and strong topics

3. Syllabus Generation

• AI generates personalized syllabus:

  • Selects topics in recommended order

  • Suggests difficulty levels for each topic

  • Provides estimated completion time for each module

4. Review & Adjustments

• Students or teachers can modify suggested syllabus

• Add/remove topics or adjust difficulty

5. Progress Tracking

• Track completion of topics and modules

• Suggest updates in syllabus based on ongoing performance