Academic Integrity

Integrity in the Age of AI

Clear guidelines for ethical AI use, originality, and intellectual honesty. Not rigid rules—thoughtful principles for a new kind of learning.

Read Full Policy For Faculty
The Landscape

A New Kind of Integrity Challenge

Traditional academic integrity is straightforward: don't copy others' work, don't cheat on exams. But AI education introduces a paradox. We're teaching you to use AI effectively—which means the old rules don't quite fit.

The line between "using AI appropriately" and "letting AI do the work for you" isn't always clear. When does collaboration with AI become over-reliance? When does assistance become replacement?

Our approach centers on three things: transparency about how you use AI, judgment about when and how to use it, and genuine learning that builds your own capabilities.

Using AI Well
Misusing AI
Clear Intent Before Asking

You know what you need before prompting. AI assists your thinking, not replaces it.

Critical Evaluation

You question AI outputs, spot errors, and don't accept the first response blindly.

Iterative Refinement

You treat AI output as a starting point, refining through multiple exchanges.

Deep Understanding

You can explain why your prompt works and adapt it to new contexts.

Transparent Documentation

You openly share how AI contributed to your work and what you added.

Blind Acceptance

Taking the first AI response as final without review or critical thought.

No Comprehension

Unable to explain what you submitted or why your approach worked.

Shortcut Mentality

Using AI to avoid learning rather than accelerate it. Skipping the process.

Concealing AI Use

Hiding that you used AI or misrepresenting its role in your work.

Complete Dependency

Unable to complete work without AI. No skill transfer happening.

Guiding Principles

What We Stand For

These four principles guide every integrity decision at Bloom—from how we design assessments to how we handle concerns.

Transparency Over Concealment

We don't ask students to pretend they didn't use AI. We ask them to be clear about how they used it and what they learned in the process.

Understanding Over Output

We assess whether students understand what they're doing—not just whether they produced correct answers. A right answer you can't explain isn't learning.

Process Over Product

A well-reasoned approach that doesn't work perfectly is more valuable than a perfect output the student can't explain. We're building thinkers, not answer-finders.

Growth Over Punishment

Our first response to integrity concerns is education, not punishment. We want students to learn and grow, not fear and hide.

For Students

What We Expect From You

1

Disclose AI Use

If an assignment allows AI assistance, note how you used it. Be specific about what role AI played in your process.

"I used Claude to generate initial ideas, then refined and expanded them myself based on my industry experience."
2

Understand Your Work

Be prepared to explain any prompt you write and any output you submit. If you can't explain it, you haven't learned it.

3

Do Your Own Thinking

AI can assist, but the judgment and decisions must be yours. You're developing your capabilities, not outsourcing them.

"AI helped me explore options; I chose this approach because it best fits my organization's constraints."
4

Ask When Uncertain

If you're not sure whether something crosses a line, ask your instructor. Asking is always better than assuming.

5

Learn, Don't Just Complete

The goal is building competence, not checking boxes. Shortcuts undermine your own growth—and the value of your certificate.

Clear Examples
Using AI to brainstorm approaches, then selecting and refining ideas yourself
Testing multiple prompt approaches and analyzing which works better and why
Documenting your iteration process with explanations of your choices
Submitting AI-generated text as your own written reflection
Copying another student's prompt without understanding it
Using AI during assessments that prohibit AI assistance
Quick Reference
When in doubt, check here
Always Do
Disclose how you used AI
Be able to explain your work
Ask if you're uncertain
Document your process
Never Do
Submit without understanding
Copy others' work
Hide your AI usage
Assume—ask instead
Is This Okay?

Real Scenarios, Real Answers

Gray areas are hard. Here are common situations with clear guidance on where they fall.

Scenario 1 Okay
"I asked AI to check my prompt for spelling and grammar errors before submitting."
Why it's fine: Using AI as a proofreading tool doesn't undermine learning. The thinking, structure, and approach are still yours. This is similar to using spell-check.
Scenario 2 Caution
"I used AI to write my reflection, then edited it heavily to match my actual experience."
Why it's risky: Reflections should be your thoughts. Even heavy editing means the structure and initial framing came from AI. Better approach: write your reflection first, then use AI to help clarify.
Scenario 3 Okay
"I shared my general approach with a classmate who was stuck, without showing my actual prompt."
Why it's fine: Discussing strategies and mental models helps everyone learn. You didn't give them your work—you helped them develop their own thinking. That's peer learning.
Scenario 4 Not Okay
"I found a prompt template online that worked well, so I submitted it as my own approach."
Why it's problematic: Using others' work without attribution is plagiarism—even for prompts. You can learn from templates, but your submission must reflect your thinking and choices.
Scenario 5 Okay
"I tested 10 different prompt variations and documented why each one worked or didn't."
Why it's excellent: This is exactly what we want to see. Systematic experimentation, reflection on results, and documented learning. This demonstrates genuine understanding.
Scenario 6 Not Okay
"The AI gave me a great response, so I just submitted that without really understanding how the prompt worked."
Why it's problematic: Getting lucky isn't learning. If you can't explain why your prompt worked, you haven't developed the skill. You need understanding, not just results.
For Faculty

How to Handle Integrity Concerns

When You Suspect an Issue
1

Don't accuse—inquire. "Can you walk me through your thinking here?" opens dialogue without putting students on the defensive.

2

Focus on understanding, not catching. Your goal is to determine whether learning happened, not to "win" an interrogation.

3

Document the conversation. Note what you observed, what questions you asked, and how the student responded.

4

Escalate when appropriate. If a pattern continues or the issue is serious, bring it to the Academic Director.

Assessment Design Tips
Require explanation of choices, not just outputs—understanding matters more than answers
Use varied contexts that require application, not memorization or template-copying
Include reflection components that AI can't fake—personal experience, specific context
Value process documentation alongside final work—show your work matters
Helpful Conversation Starters
"Help me understand your approach to this prompt."
"What alternatives did you consider before settling on this?"
"If the AI gave you a different response, how would you adapt?"
The Details

Formal Policy

The complete policy framework. Click each section to expand.

  • Academic Dishonesty: Any attempt to gain unfair advantage through deception or unauthorized means
  • Plagiarism in AI Context: Presenting AI-generated content as your own original work without disclosure
  • Unauthorized Collaboration: Working with others when individual work is required
  • Misrepresentation: Falsely claiming capabilities, fabricating results, or misrepresenting AI outputs
  • Submitting AI output as original work without disclosure
  • Copying another student's prompts, work, or approaches
  • Using unauthorized tools or resources during assessments
  • Fabricating results or misrepresenting AI outputs
  • Sharing assessment content with future cohorts
  • First Offense: Educational conversation, possible assignment redo with guidance
  • Second Offense: Formal warning on record, required integrity module completion
  • Third Offense: Program dismissal consideration by Academic Director
  • Severe Cases: Immediate review—may bypass progressive steps for serious violations
  • Students have the right to appeal any integrity finding
  • Appeals must be submitted in writing within 7 days of notification
  • The Academic Director reviews all appeals with full documentation
  • Final decision communicated within 14 days of appeal submission
Common Questions

Integrity FAQ

Questions we hear often—with honest answers.

Accidents happen, especially when you're learning something new. Come to us proactively. Explain what happened and what you've learned. We strongly distinguish between honest mistakes and intentional deception. The former leads to conversation and education; the latter leads to consequences.
Absolutely—in fact, we encourage it. The more you practice with AI, the better you'll understand it. Our policies govern what you submit for assessment, not how you learn. Experiment freely. The learning you do outside class makes your in-class work stronger.
Be specific about what role AI played. Instead of just "I used AI," say something like: "I used Claude to brainstorm initial approaches, selected the most promising one, and then developed it further myself." Include which AI tool you used and what specific assistance it provided. Your instructor can give you more guidance on format if needed.
Can you explain why you made the choices you made? Can you predict how changes to your approach would affect results? Can you adapt your approach to a different context? If yes to these, you understand your work. If you're just hoping it works without knowing why, you don't—yet. That's what we're here to help you develop.
You're not obligated to report peers, but you can if you're concerned. Talk to your instructor or the Academic Director confidentially. We'll handle it appropriately without putting you in an uncomfortable position. Remember: integrity protects the value of everyone's certificate, including yours.
The specific examples may evolve, but the core principles won't. Transparency, understanding, and genuine learning matter regardless of what AI can do. We review our policies regularly and update them when needed. Any changes are communicated clearly and don't apply retroactively.
The Bigger Picture

Why Integrity Matters Here

This isn't just about following rules. We're preparing you to work with AI in your career—where the stakes are real and no one is grading you.

If you learn to cut corners here, you'll cut corners there. If you learn to depend on AI without understanding, you'll be vulnerable when AI behaves unexpectedly. Employers need people who understand AI, not people who've outsourced their thinking to it.

Our certificate means something because our standards mean something. Integrity protects its value—for you and for everyone who holds it.

Real-World Preparation

The habits you build here are the habits you'll carry into your career

Certificate Value

Standards protect the worth of your credential in the marketplace

Genuine Competence

Understanding beats dependence when AI behaves unexpectedly

Community Trust

Your integrity supports everyone in the Bloom community

The Bloom Integrity Commitment

"I commit to learning with honesty, using AI as a tool for growth rather than a shortcut around it. I will be transparent about my methods, genuine in my efforts, and accountable for my work."

Transparent in method Genuine in effort Accountable for work Committed to growth

Questions About Integrity?

Academic integrity can be nuanced. If you have questions or concerns, we want to hear them. That's how policies get better.

Contact Academic Director Faculty Resources