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Vijay Janapa Reddi 11c689ef58 Add comprehensive NBGrader documentation for instructors

- Create complete instructor guide with user journey from setup to course completion
- Cover all phases: setup, course prep, assignment management, grading workflow
- Include weekly routines, troubleshooting, and student guidance
- Add quick reference card for daily commands
- Update Jupyter Book TOC to include instructor documentation
- Update classroom-use guide to reference comprehensive documentation

Features documented:
- 30-minute initial setup process
- Weekly assignment workflow (generate -> release -> grade -> feedback)
- Batch operations for efficiency
- System monitoring and analytics
- End-to-semester procedures
- Student support guidelines
- Common troubleshooting scenarios

Provides complete user journey for instructors and TAs using NBGrader + TinyTorch.

2025-09-16 02:45:02 -04:00

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📋 NBGrader Quick Reference Card

TinyTorch + NBGrader Essential Commands for Instructors

🚀 One-Time Setup

# 1. Setup environment
python3 -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt

# 2. Initialize NBGrader
./bin/tito nbgrader init

# 3. Verify setup
./bin/tito system doctor

📝 Weekly Assignment Workflow

Monday: Release New Assignment

# Generate assignment from TinyTorch module
./bin/tito nbgrader generate 03_activations

# Create student version
./bin/tito nbgrader release 03_activations

# Upload assignments/release/03_activations/03_activations.ipynb to LMS

Friday: Grade Submissions

# After downloading student submissions to assignments/submitted/
./bin/tito nbgrader autograde 03_activations
./bin/tito nbgrader feedback 03_activations

# Return assignments/feedback/ files to students

🔧 Essential Commands

Status & Monitoring

./bin/tito module status --comprehensive    # System health
./bin/tito nbgrader status                  # Assignment status
./bin/tito nbgrader analytics MODULE_NAME   # Student progress

Batch Operations

./bin/tito nbgrader generate --all          # All assignments
./bin/tito nbgrader generate --range 01-04  # Module range
./bin/tito nbgrader autograde --all         # Grade everything
./bin/tito nbgrader feedback --all          # Generate all feedback

Export & Cleanup

./bin/tito nbgrader report --format csv     # Export gradebook
./bin/tito clean                            # Clean temp files

📁 Directory Structure

assignments/
├── source/        # Generated assignments (git tracked)
├── release/       # Student versions (git tracked)
├── submitted/     # Student submissions (git ignored)
├── autograded/    # Graded submissions (git ignored)
└── feedback/      # Student feedback (git ignored)

🆘 Quick Troubleshooting

# Environment issues
source .venv/bin/activate
./bin/tito system doctor

# Module not found
ls modules/source/                          # Check available modules
./bin/tito nbgrader generate 02_tensor      # Use exact name

# Validation failures (normal for student notebooks)
# Students have unimplemented functions = expected behavior

📚 Course Planning

17 TinyTorch Modules:

00-02: Foundation (intro, setup, tensors)
03-07: Building Blocks (activations, layers, dense, spatial, attention)
08-11: Training (dataloader, autograd, optimizers, training)
12-16: Production (compression, kernels, benchmarking, mlops, capstone)

Recommended Pacing: 1 module per week = 16-week semester

📖 For complete details: See Instructor Guide

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