Week 2: Policy Development

Building policies that work

Today’s Session

Starting with educational philosophy
Creating acceptable use frameworks
Redefining academic integrity for AI era
Age-appropriate approaches across grades

The Core Question

Before writing policy, answer this: Why do we assign this work?

Different Purposes

Demonstrating mastery: AI must be prohibited
Learning through practice: AI might accelerate growth
Producing quality output: AI collaboration may reflect reality

Values Before Rules

Effective policies begin with articulated values, not restrictions.

What Matters Most

Honest representation of one’s own work
Genuine skill development for future learning
Fair treatment and equal opportunity
Preparation for college and career environments

The Three-Zone Framework

Zone 1: Prohibited AI use
Zone 2: Allowed with full disclosure
Zone 3: Encouraged AI collaboration

Zone 1: Prohibited

Formal assessments measuring individual mastery
Work designed to build foundational skills
Assignments where the struggle is the learning
Preparing for AI-restricted environments

Zone 2: Conditional Use

Research and information gathering with verification
Brainstorming and idea generation
Getting explanations of difficult concepts
Draft review and editing suggestions

Zone 3: Encouraged

Complex research projects where AI aids synthesis
Professional writing where AI helps structure
Data analysis where AI accelerates computation
Creative projects where AI serves as tool

Assignment-Specific Guidance

Teachers must specify for every assignment.

Clear Communication

Explicit statement whether AI use is allowed
If allowed, exactly how AI may be used
What must be disclosed and how
Examples of acceptable and unacceptable use

Disclosure Requirements

Students should specify when using AI.

Required Documentation

Which AI tool was used
Exactly what prompts were given
What output the AI provided
How student evaluated or modified output

Rethinking Academic Integrity

Traditional definitions assumed work without technological assistance.

Historical Perspective

1970s: Calculators in math considered cheating
1990s: Spell-check prohibited in English classes
2000s: Wikipedia banned as untrustworthy
2010s: Grammar checkers seen as avoiding learning

New Integrity Standards

Honesty: Accurately representing work source
Learning: Ensuring required skills are developed
Fairness: Equal access to resources

Consequences That Educate

Match severity to the violation
Focus on learning and restoration
Apply consistently across students
Include opportunities to rebuild trust

Elementary School Approach

All AI interaction must be supervised
Focus on basic literacy without AI
Use AI only in teacher-directed activities
Protect from inappropriate content

Middle School Approach

Introduce AI with explicit instruction
Require teacher permission before use
Teach how to verify AI output
Begin discussing AI limitations and ethics

High School Approach

Develop mature understanding of when to use AI
Practice professional AI use cases
Require strong critical evaluation
Prepare for AI-rich college and workplace

Why Detection Fails

Detection tools have 30-40% false positive rates
False accusations harm student-teacher relationships
Students develop workarounds faster than tools detect
The technological arms race cannot be won

Alternatives to Detection

Design assignments that make AI assistance visible
Require process documentation showing thinking
Include in-class components verifying understanding
Build culture where honesty is valued

Building Integrity Culture

Consistent, clear expectations communicated repeatedly
Fair consequences applied equitably
Recognition that most students want to do right
Trust-building through transparent policies

Communicating to Students

Explain why policies exist, not just what they prohibit
Provide clear examples of permitted use
Create opportunities for questions
Revisit and reinforce expectations regularly

Communicating to Parents

Explain educational reasoning behind approach
Describe how students will learn to use AI
Provide guidance for supporting use at home
Address concerns about cheating and skills

Communicating to Faculty

Provide clear frameworks with professional judgment
Offer concrete examples for different subjects
Give teachers authority for assignment-specific decisions
Create channels for ongoing support

Board Communication

Connect policy to educational mission
Address legal compliance and risk management
Explain resource requirements
Outline metrics for evaluating effectiveness

Building in Adaptability

Schedule mandatory annual policy reviews
Create process for addressing emerging issues
Grant teachers flexibility for professional judgment
Document lessons learned and adjustments

Common Policy Mistakes

Blanket prohibition of all AI use
No written policy at all
Detection-dependent enforcement
One-size-fits-all rules across grades

Legal Requirements

FERPA protects student education records
COPPA restricts data collection under 13
Many AI tools incompatible with K-12 use
Parental consent may be required

The Equity Imperative

Provide school-supported AI access
Teach AI literacy explicitly
Consider how enforcement affects different groups
Recognize that access gaps compound inequalities

Workshop Activity

Draft initial policy language for your school.

Drafting Steps

Articulate core values guiding decisions
Define three zones with specific examples
Create disclosure requirements for Zone 2
Outline consequences for violation types

This Week’s Takeaway

Policy focused on learning objectives and transparency outlasts tool prohibition.

The Question

What are we trying to assess? Does this assignment design measure it effectively in an AI-enabled world?

Looking Ahead

Week 3 addresses faculty enablement.

Teachers Need

Understanding of what AI can and cannot do
Confidence in using AI themselves
Skills to guide students effectively
Support in redesigning assignments