1. Introduction
This proposal outlines the plan to integrate AI Studio functionalities seamlessly into the Staff-Dashboard MFE. The goal is to enhance the user experience with a dynamic, AI-driven interface that adapts based on user inputs, providing intelligent navigation, smart recommendations, and automation.
2. Objectives
- Create a minimalist, user-friendly AI Studio starting screen.
- Implement AI-assisted navigation and dynamic UI updates.
- Provide smart course creation tools with AI enhancements.
- Introduce AI-powered analytics and reporting.
- Ensure scalability and maintainability for future enhancements.
3. Key Features
3.1 AI Studio Main Page (Existing)
- Clean, simple UI with two primary actions:
- “Create New Course” → Opens course creation tools.
- “Generate Reports” → Opens analytics & insights.
- AI Chat Assistant to process user commands for navigation.
- Sidebar navigation for quick access to platform modules.
3.2 AI-Driven Navigation Assistance
- AI listens to user inputs (clicks, commands) and updates UI accordingly.
- Voice and text-based navigation: Users can ask AI to take them to different sections.
- Smart recommendations for frequently used sections.
- Quick search input to locate features instantly.
3.3 Organization Settings Management
- AI-powered command input:
- “Change branding color to blue.”
- “Enable dark mode.”
- AI suggestions based on usage trends.
- Toggle switches for quick settings updates.
3.4 AI-Generated Reports & Insights
- Dropdown selector for report generation:
- Courses, Learners, Instructors, Engagement.
- AI Summary Cards highlighting learner progress trends.
- Downloadable PDF/CSV reports with AI-generated insights.
3.5 Course Enhancement with AI
- AI analyzes course content for improvements.
- Automated quiz generation based on uploaded material.
- Auto-summarization of lengthy course content for better comprehension.
3.6 Learner Risk Analysis & Notifications
- AI-driven risk assessment to identify at-risk learners.
- Automated interventions such as reminder emails.
- Personalized learning paths suggested by AI.
3.7 Smart Assistance for Staff
- AI Chatbot for real-time assistance:
- “Enroll a learner in XYZ course.”
- “Show me today’s schedule.”
- Voice input support for hands-free interaction.
- AI-suggested workflow optimizations based on historical data.
4. Core Components
| Component | Description |
|---|---|
HomeScreen.jsx |
Displays initial dashboard options. |
CourseCreation.jsx |
AI-powered course creation workspace. |
AIReports.jsx |
AI-generated analytics and insights. |
AIChatAssistant.jsx |
Processes user input for navigation. |
DynamicCanvas.jsx |
Flexible workspace that updates dynamically. |
5. Technical Implementation
- React + Context API/Redux for state management.
- Lazy loading for performance optimization.
- Integration with AI/NLP models for smart assistance.
- REST API & WebSockets for real-time updates.
6. Expected Outcomes
- A seamless AI-driven experience for staff users.
- Faster and smarter navigation across dashboard features.
- Improved workflow efficiency with AI-enhanced tools.
- Data-driven decision-making with AI-powered reports.
7. Next Steps
- Wireframe Finalization – Adjust based on stakeholder feedback.
- Prototype Development – Create a React-based functional UI.
- AI Integration & Testing – Implement AI-driven components.
- User Testing & Iteration – Optimize based on feedback.
- Deployment & Monitoring – Ensure performance and scalability.
8. Conclusion
This proposal presents a roadmap for AI-driven UI/UX enhancements in AI Studio, ensuring a user-friendly, intelligent, and scalable dashboard experience. By leveraging AI, we aim to streamline workflows, enhance usability, and provide valuable insights for staff users.