Educator's Guide - .md

# Building Permit Pipeline - Educator's Guide

## Course Overview

**Duration:** 8-12 weeks (1-2 class periods per week)

**Level:** High school (grades 9-12)

**Prerequisites:** Basic computer skills, optional: intro to Python

**Class Size:** Works for 5-30 students

## Learning Objectives

By completing this project, students will:

1. Understand their city's development approval process

2. Collect and analyze real civic data

3. Create public-facing data visualizations

4. Present findings to community stakeholders

## Week-by-Week Plan

### Week 1: Introduction to Civic Data

**Topics:** What are building permits? Why do they matter?

**Activities:**

- Visit city planning website

- Identify local development projects

- Discuss housing issues in your community

**Notebook:** `lesson_01_permits_basics.ipynb`

**Homework:** Find 3 construction projects in your neighborhood

### Week 2: Data Collection

**Topics:** Open data, APIs, CSV files

**Activities:**

- Access city's open data portal

- Download permit data

- Inspect data structure

**Notebook:** `lesson_02_data_import.ipynb`

**Homework:** Document your data source

### Week 3: Data Cleaning

**Topics:** Missing data, inconsistent formats, address standardization

**Activities:**

- Clean address fields

- Handle missing values

- Filter for housing projects

**Notebook:** `lesson_03_cleaning.ipynb`

**Homework:** Write data quality report

### Week 4: Geocoding

**Topics:** Latitude/longitude, mapping, APIs

**Activities:**

- Geocode addresses

- Validate coordinates

- Handle failed matches

**Notebook:** `lesson_04_geocoding.ipynb`

**Homework:** Research geocoding services

### Week 5: Databases

**Topics:** SQLite, database design, queries

**Activities:**

- Create database schema

- Import data

- Write basic queries

**Notebook:** `lesson_05_database.ipynb`

**Homework:** Design 3 SQL queries

### Week 6: Analysis

**Topics:** SQL aggregation, statistics, trends

**Activities:**

- Calculate total units

- Analyze by neighborhood

- Track timeline

**Notebook:** `lesson_06_analysis.ipynb`

**Homework:** Find 3 insights in the data

### Week 7: Visualization

**Topics:** Charts, maps, dashboards

**Activities:**

- Create interactive maps

- Build time-series charts

- Design dashboard layout

**Notebook:** `lesson_07_visualization.ipynb`

**Homework:** Sketch dashboard design

### Week 8: Deployment & Presentation

**Topics:** GitHub Pages, public communication

**Activities:**

- Deploy website

- Create presentation

- Invite community stakeholders

**Notebook:** `lesson_08_website.ipynb`

**Final Project:** Public presentation

## Differentiation Strategies

### For Advanced Students:

- Connect to live APIs for auto-updates

- Build predictive models

- Compare multiple cities

- Create mobile apps

### For Struggling Students:

- Use pre-cleaned sample data

- Focus on visualization over coding

- Pair programming

- Provide more structured templates

## Assessment Rubric

| Criteria | Points | Description |

|----------|--------|-------------|

| Data Collection | 20 | Successfully gathered city permit data |

| Data Quality | 20 | Cleaned and geocoded addresses |

| Analysis | 20 | Generated meaningful insights |

| Visualization | 20 | Created clear, accurate visualizations |

| Communication | 20 | Presented findings effectively |

## Community Partnership Opportunities

1. **City Planning Department**

   - Guest speakers

   - Data access assistance

   - Feedback on findings

2. **Local News Organizations**

   - Data journalism mentorship

   - Publish student work

   - Career connections

3. **Housing Advocacy Groups**

   - Context on housing issues

   - Use student data for advocacy

   - Service learning hours

4. **Tech Companies**

   - Mentor volunteers

   - Code review

   - Internship opportunities

## Common Challenges & Solutions

### Challenge: City data is hard to access

**Solution:** Start with `data_sources_by_state.md`, contact city directly, use FOIA requests

### Challenge: Students have varying Python skills

**Solution:** Use pair programming, provide scaffolded notebooks, offer office hours

### Challenge: Geocoding fails for many addresses

**Solution:** Use address normalization scripts, manual lookup for key projects, accept imperfection

### Challenge: Project feels too big

**Solution:** Start small (just one neighborhood), iterate and expand, celebrate small wins

## Extensions & Next Steps

After completing the basic project:

- **Track progress over time** (monthly updates)

- **Add inspection data** (construction progress)

- **Compare proposals vs completions** (accountability)

- **Build predictive models** (forecast housing production)

- **Analyze demographic impacts** (who benefits?)

- **Create policy recommendations** (present to city council)

## Resources

- [Video Tutorial Series](#)

- [Teacher Discord Community](#)

- [Sample Lesson Plans](#)

- [Grant Opportunities](#)

## Support

Questions? Email: education@buildingpermitpipeline.org

Slack: #educators-channel

Office Hours: Fridays 3-4pm PT

Getting Started Checklist for Teachers .md

## Week 1: Setup

- [ ] Clone GitHub repository

- [ ] Review all lesson notebooks

- [ ] Test on your computer

- [ ] Identify your city's data source

- [ ] Customize city configuration

## Week 2: Preparation

- [ ] Print STUDENT_GUIDE for class

- [ ] Set up class GitHub organization

- [ ] Contact city planning department

- [ ] Create assessment rubric

- [ ] Recruit guest speakers

## Week 3: Launch

- [ ] Introduce project to students

- [ ] Form teams (optional)

- [ ] Complete Lesson 01 together

- [ ] Assign homework

- [ ] Set up office hours