docs(*): Add further information to the readme

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Josh Creek
2025-04-24 19:32:04 +01:00
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> An intelligent, agentic AI system designed to significantly reduce teachers' workloads by providing instant assessment and personalized differentiated feedback and follow-on activities for student assignments.
## Who is this for?
This project is designed for:
- **Teachers** who want to save time on grading and provide more consistent, individualized feedback to students.
- **Schools and educational institutions** seeking to improve the quality and efficiency of assessment and feedback workflows.
## ⚡ Workflow At a Glance
- Upload an assignment and student response (file or text)
- Instantly receive detailed, actionable feedback and differentiated individualized follow-on tasks and a grade
@@ -48,6 +54,79 @@ This project was developed for the [Microsoft Hack Together: AI Agents Hackathon
- Allows teachers more time to focus on direct student interaction and lesson planning.
## 🛠️ Responsible AI
I am committed to responsible and ethical use of AI in education. This project:
- Uses Azure OpenAI and Cognitive Services, which comply with Microsoft's responsible AI principles.
- Does not retain or share student data beyond local processing in the browser (history is stored in localStorage only).
- Clearly communicates to users when they are interacting with AI-generated feedback.
- Is designed to minimize bias by providing transparent, explainable feedback and allowing teachers to review/edit results.
- Does not use student data for model training or any secondary purpose.
## ♿ Accessibility
Accessibility is a core priority:
- The interface is screen reader-friendly, with proper semantic HTML and ARIA labels.
- All features are keyboard accessible (tab navigation, focus indicators).
- Color contrast meets WCAG AA standards for readability.
- Error messages and progress indicators are accessible to assistive technologies.
- The site has been tested with browser accessibility tools and screen readers.
## 🗺️ Architecture Diagram
```mermaid
flowchart TD
%% User
Teacher["Teacher (User)"]
%% Frontend
Upload["Upload Page"]
Results["Results/History Page"]
AgenticProgress["AgenticProgress Component"]
LocalStorage["localStorage (Browser)"]
%% API
APIEndpoint["API: /api/grade (Netlify serverless function)"]
APINote["API endpoints are Netlify serverless functions (SvelteKit endpoints)"]
APIEndpoint -.-> APINote
%% PartyKit
EventStream["PartyKit WebSocket (Real-time Agent Progress)"]
PartyKitNote["PartyKit provides WebSocket-based real-time updates on agent progress/tools."]
EventStream -.-> PartyKitNote
%% Azure
OpenAI["Azure OpenAI (NLP, Grading, Feedback)"]
%% Data Flow
Teacher -->|Uploads assignment & student work| Upload
Upload -->|Calls| APIEndpoint
APIEndpoint -->|Sends data & assignment description| OpenAI
APIEndpoint -->|Streams grading progress| EventStream
EventStream -->|Updates progress| AgenticProgress
APIEndpoint -->|Returns feedback & grade| Results
Results -->|Planned: Teacher reviews/edits feedback| Results
Results -->|Saves assessment| LocalStorage
Results -->|Displays feedback, history| Teacher
PrivacyNote["Assessment history is stored only in the users browser (localStorage), not sent to any backend."]
LocalStorage --> PrivacyNote
class Teacher user;
class Upload,Results,AgenticProgress,LocalStorage frontend;
class APIEndpoint api;
class EventStream partykit;
class OpenAI azure;
```
## 👥 Teacher Workflow Example
Here's an example of how a teacher might use the Automated Assessment and Feedback Agent:
1. The teacher uploads an assignment and a student response, and uploads them to the platform.
2. The platform generates instant, individualized feedback and a grade using Azure OpenAI.
3. The feedback is stored locally in the browser.
4. The teacher reviews the feedback and grade, and can edit or modify them as needed.
## 🔮 Future Enhancements
- Integration with major Learning Management Systems (LMS) for streamlined workflow.