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In this comprehensive tutorial, we demonstrate how to use the Gemini AI Handwriting Grader within the Firebase Studio workspace to automate the grading of handwritten assignments. This tool leverages Google's Gemini AI to recognize handwriting, compare it against a marking scheme, provide detailed feedback, and even automate the reporting and emailing process. 🕒 Timestamps: 00:00 - Introduction to Firebase Studio 00:24 - Importing the GitHub Repository 01:04 - Environment Setup & Extension Installation 03:12 - Configuration: API Keys & SMTP (Email) Settings 05:06 - Step 1: Generating Personalized Answer Sheets (Mail Merge) 10:22 - Step 2: Extracting the Marking Scheme to Excel 13:36 - Step 3: Auto-detecting Answer Areas (Bounding Boxes) & Manual Review 17:45 - Step 4: OCR & AI Scoring Preprocessing 18:41 - Step 5: Post-Scoring Data Validation 19:45 - Step 6: Packaging Results & AI-Generated Class Analysis 21:16 - Final Step: Automatically Emailing Feedback to Students 🚀 Key Features: Automated OCR: Effortlessly convert handwritten text into digital data. AI-Driven Grading: Uses Gemini to score answers based on your specific marking rubrics. Personalized Feedback: Generates strengths, weaknesses, and study suggestions for every student. Firebase Studio Integration: Runs entirely in a cloud-based IDE—no complex local setup required. End-to-End Workflow: From generating the test paper to emailing the final grade. 🛠️ Prerequisites: A Google Account (for Firebase Studio and Gemini API). A Gemini API Key (available via Google AI Studio). A Gmail App Password (if you wish to use the automated emailing feature). GitHub Repo: https://github.com/wongcyrus/gemini-h... #GeminiAI #FirebaseStudio #EdTech #AIinEducation #AutomatedGrading #Python #HandwritingRecognition #GoogleGemini