AI Engagement Research Tool

How Do You
Really Use AI?

Paste any AI conversation and get an instant analysis of your engagement patterns across 8 research-backed modes. Find out whether you're passively consuming AI output, partnering with it, or exercising genuine intellectual agency.

Built by Dr. Mark Keith, Professor of Information Systems at BYU

Launch offer: 50 free analyses per month through June 2026

Create a free account to get started. No credit card required.

The 8 Engagement Modes

Passivity
OracleProduction Assistant
Partnership
TutorCollaborative Problem-Solver
Agency
Verification AgentCreative ExpanderCritical ChallengerProblem Setter
PASSIVE → ACTIVE

Your Engagement Plan

Not just analysis. A personalized plan to improve.

01

Paste

Copy any AI conversation from ChatGPT, Claude, Gemini, or any other tool and paste it into the analyzer.

02

Analyze

Our AI classifies every message across 8 engagement modes and 3 tiers of intellectual agency.

03

Grow

Get a personalized engagement plan with benchmarks, archetype, growth predictions, and targeted exercises.

Peer Benchmarks

See how your engagement compares to other users across every mode.

Your Archetype

Discover whether you are a Delegator, Partner, Challenger, Explorer, Specialist, or Learner.

Custom Exercises

Get targeted exercises to break through plateaus and develop new engagement modes.

Sample Results

See what you get

Every analysis includes an overall score, tier breakdown, mode distribution, personalized feedback, and growth recommendations.

aimodes.ai/apps/ai-engagement/results/...
42out of 100

Tier Breakdown

Passivity55%
Partnership25%
Agency20%

Mode Distribution: Actual vs. Target

Oracle
35%
Production Asst.
20%
Tutor
15%
Collaborative
10%
Verification
8%
Creative
5%
Critical
5%
Problem Setter
2%
ActualTarget

Feedback

Your conversation was heavily Oracle-dependent. You asked broad questions and accepted answers without verification. Try breaking problems into smaller steps and asking the AI to explain its reasoning before accepting its output.

Strengths

  • • Good use of follow-up questions
  • • Provided context about your task

Growth Areas

  • • Verify AI claims before accepting
  • • Challenge assumptions in responses
  • • Try setting the problem yourself first

This is a sample result showing heavy Oracle usage. Your results will reflect your actual conversation patterns.

Try It With Your Conversation

Pricing

Start free. Grow with a plan.

Every plan includes the full engagement analysis, peer benchmarks, archetype discovery, growth predictions, and personalized exercises. Students whose instructors use our textbooks get free access automatically.

Try It

Free

No account needed

  • 1 analysis ever
  • Full 8-mode breakdown
  • Personalized feedback
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Free Account

Free

Sign up in 30 seconds

  • 1 analysis per month
  • Full 8-mode breakdown
  • Personalized feedback
  • Submission history
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Individual Pro

$5/month

For regular AI users

  • 50 analyses per month
  • Full 8-mode breakdown
  • Personalized feedback
  • Submission history
  • Growth tracking over time
  • Cancel anytime
Subscribe

Semester Pass

$5/semester

For students in a course

  • 50 analyses per semester
  • Full 8-mode breakdown
  • Personalized feedback
  • Submission history
  • Course-specific assignments
  • Instructor feedback view
Get Started

Need more analyses? Add a Top-Up Pack (50 extra) for $5 anytime. Top-up credits carry over month to month.

Mark Keith

About the Researcher

Mark Keith, PhD

Professor of Information Systems, Brigham Young University

The AI Engagement Modes framework grew out of years of research into how students interact with technology. Over the past two years, that work has focused specifically on AI, resulting in a model that classifies every AI interaction into one of 8 modes across 3 tiers of intellectual agency, from passive consumption to active critical thinking.

Dr. Keith has taught advanced machine learning, data analytics, and AI courses at five universities. He has authored 6 textbooks on analytics, Python, and machine learning, and is currently writing 3 AI-focused books designed to teach these methods to all types of college students. His research spans information privacy, AI in education, and predictive modeling.

This tool is backed by ongoing research with real student data, validated survey instruments, and a growing ML prediction pipeline. It is not a toy demo. It is an active research instrument designed to help students, instructors, and researchers understand AI engagement at a deeper level.