Mock Tests

This project aims to create an interactive mock test platform with the
following key features:
1. Formatives and Assessments Dropdown: Users can choose
between formative assessments and larger exams, limiting the
syllabus accordingly.
2. Mock Test Generation:
 Based on a blueprint (60% model questions, 40% AI-generated
questions).
 AI-generated questions adhere to the syllabus boundaries.
3. Post-Test Analysis:
 Display a leaderboard with performance rankings.
 Offer feedback on where the user went wrong and highlight
weak areas.
4. Retake or Revise:
 Option 1: Revise weak topics and their prerequisites.
 Option 2: Retake the test.
Key Modules
1. Frontend (React.js): Interactive UI for user experience.
2. Backend (AI): Question generation, performance tracking, and
recommendation system.
3. Database: Store questions, user performance, leaderboard data, etc.
Work Breakdown and Responsibilities
AI Team Responsibilities:
1. Syllabus Limitation Based on Dropdown Selection
 Task: AI model limits the syllabus based on formative or assessment
options selected by the user.
 Steps:
 Extract syllabus data.
 Create a system to dynamically limit topics.
 Integrate the syllabus filter with AI question generation.
2. AI Question Generation (40% New Questions)
 Task: Build an AI model to generate new questions that conform to
syllabus boundaries.
 Steps:
 Use NLP models to generate new questions.
 Ensure the new questions align with the difficulty level defined
in the blueprint.
 Validate generated questions for correctness.
3. Performance Analysis and Weak Area Detection
 Task: AI should evaluate answers and identify weak areas.
 Steps:
 Develop logic to analyze where users make mistakes.
 Calculate scores and detect trends in wrong answers.
 Generate personalized feedback and suggestions.
4. Prerequisite and Weak Topic Suggestions
 Task: Suggest topics for revision based on weak areas detected after
the test.
 Steps:
 Build a recommendation system that lists weak topics.
 Fetch relevant prerequisites and include them in the
recommendations.
 Display revision options based on weak topics and prerequisite
dependencies.
React.js Team Responsibilities:
1. User Interface for Dropdown Selection
 Task: Build an intuitive UI for users to select between formative
assessments or exams and adjust syllabus accordingly.
 Steps:
 Create dropdown menus for assessments.
 Trigger backend calls to limit syllabus when a selection is
made.
2. Blueprint-Based Mock Test Creation
 Task: Implement the frontend to display 60% model questions and
40% AI-generated questions.
 Steps:
 Design UI to display questions.
 Ensure the frontend communicates with the backend to pull
questions based on the blueprint.
3. Leaderboard and Performance Report UI
 Task: Display user performance via a leaderboard and provide
detailed reports on weak areas.
 Steps:
 Design a dynamic leaderboard.
 Create sections to show where users made mistakes and their
weak areas.
 Include options to retake the test or revise weak topics.
4. Retake and Revise Options Interface
 Task: Provide UI options to retake the test or focus on weak areas.
 Steps:
 Include buttons for "Revise Topics" or "Retake Test".
 Connect these options to backend functionality for test retake or
topic revision.
Development Sequence
Step 1:
 AI Team: Focus on syllabus limitation and the basic structure
for AI question generation.
 React.js Team: Begin developing the dropdown for formatives
and assessments, and blueprint-based test creation UI.
Step 2:
 AI Team: Develop the AI question generation model and
integrate it with the backend.
  React.js Team: Implement the leaderboard and post-test
feedback display.
Step 3:
 AI Team: Build performance analysis and topic
recommendations (prerequisites, weak areas).
 React.js Team: Add retake/revise functionality to the UI.
Step 4:
 AI Team: Fine-tune question generation and performance
analysis models.
 React.js Team: Ensure smooth integration of frontend with
backend services.
Step 5:
 Complete testing and debugging.
 Perform a project-wide review and polish the UI/UX.
 Prepare documentation and project deployment.
Additional Suggestions
1. AI Generation Checks: Set up quality controls to ensure AI-
generated questions are clear, on-topic, and challenging.
2. User Analytics: Track user interaction and performance trends over
time to improve future test recommendations.
3. Adaptive Mock Tests: Consider making the test adaptive, where the
difficulty changes based on user performance.