AI in Education
Ethical Use of AI in the Classroom
A scenario-based eLearning experience for higher ed instructors navigating AI-integrated learning.
Background
In this interactive training, instructors step into real classroom dilemmas involving student use of AI tools like ChatGPT. Through branching scenarios, emotional storytelling, and reflective decision-making, participants learn how to foster transparency, trust, and ethical tech use.
My Role
Lead Instructional Designer | Story Architect | Visual Director
Target Audience
Higher Education Instructors (New and Experienced), Academic Leaders
Tools Used
Articulate Storyline 360 · Dzine AI · Canva · ChatGPT · Audacity · Figma - ClaudeAi
Confusion and Fear Around AI Use in Higher Ed
As AI tools like ChatGPT become commonplace in higher education, instructors are caught in a growing gray area. Institutional policies are vague or nonexistent, and many faculty are left wondering:
What counts as acceptable AI use?
When should I intervene?
How do I support learning while upholding academic integrity?
This project was created to solve a critical, real-world training gap: helping instructors make ethically sound, empathetic, and pedagogically informed decisions when facing AI use in the classroom.
A Story-Driven Learning Experience
Rather than offering a traditional webinar or rule-based checklist, I designed an interactive, story-based eLearning experience that puts instructors in realistic, high-stakes classroom dilemmas.
The goal?
Help educators practice decision-making in safe, simulated environments—building confidence, empathy, and clarity around AI use through guided reflection and narrative branching.
Most training programs fail because they:
Focus on rules, not realities
Lack emotional engagement
Don’t simulate the actual complexity of classroom situations
I knew this had to feel personal, nuanced, and realistic. That’s why I used:
✅ Cathy Moore’s Action Mapping to define only what learners need to do
✅ Narrative immersion to foster empathy
✅ Decision branches with feedback loops to promote reflective thinking
To ensure the experience felt authentic, I created two consistent characters, each representing different perspectives in the AI conversation.
The use of fixed, stylized animated characters allowed us to maintain emotional continuity across scenarios and reduce cognitive load, while also making the visuals modern, clean, and memorable.
Phase 1: Discovery & Planning:
Action Mapping
Using Cathy Moore’s Action Mapping model, I built this learning experience from the ground up based on an authentic instructional problem. I identified the key behaviors instructors needed to adopt, uncovered the emotional and systemic barriers holding them back, and designed practice activities that allowed for realistic, consequence-based decision making. Every interaction in the module was mapped to support confidence, empathy, and ethical clarity, resulting in a meaningful shift from passive content consumption to active behavior change.
Narrative Scenarios
To bring this training to life, I developed a set of branching narrative scenarios grounded in real faculty concerns. Drawing from qualitative data, including interviews, discussion threads, and email feedback, I mapped key dilemmas into interactive storylines that reflect the uncertainty, nuance, and emotion educators face when addressing student AI use. These scenarios, centered around the character of Alex, empower instructors to practice ethical decision-making in a safe, story-driven environment, where choices have consequences and learning is built through reflection, not just instruction.
Phase 2: Visual Storyboarding & Character Planning
Storyboard
Created detailed text-based storyboards and learning arcs. To transform abstract ethics into practical learning, I developed detailed, branching storyboards rooted in real classroom tensions. Each slide was mapped with purpose, from character context to feedback loops, ensuring every decision point delivered emotional resonance, instructional alignment, and measurable growth.
Character Design
To create a deeply immersive and emotionally resonant learning experience, I prioritized the use of consistent, stylized characters throughout the scenario-based module. Using Dzine AI’s multi-step workflow, I developed core characters like Jamie, a thoughtful student whose journey serves as the emotional anchor of the narrative. The process included three stages:
Describe – I crafted detailed prompts defining Jamie’s personality, style, and visual traits aligned with the instructional context.
Preview – This stage allowed for visual refinements and facial adjustments to ensure character alignment with tone and audience empathy.
Train – The final model was rendered in multiple angles and expressions to support dynamic storytelling across slides and scenes.
The use of persistent character design enabled strong learner identification, narrative continuity, and realistic branching feedback. By visually anchoring each choice and outcome to a familiar face, learners were more likely to experience the emotional weight of their decisions, supporting engagement, memory retention, and ethical reasoning. Consistency in character visuals also ensured visual cohesion, minimized cognitive load, and made the eLearning feel professionally authored and emotionally grounded.
Ai Video
To add emotional resonance and variation to the learning experience, I integrated short AI-generated lip-sync videos at key decision points and narrative transitions. These 5–7 second clips brought characters like Alex and Jamie to life—showing subtle expressions, voiced reflections, or emotionally charged reactions that static visuals alone couldn’t convey. I carefully selected moments where voice tone and body language would enhance the learner’s connection to the story—such as Alex’s inner conflict when facing ambiguity or Jamie’s hesitation when asked about AI use. These videos were created using Dzine AI, ensuring consistency with the still-image character design and maintaining a unified visual identity. Used sparingly but impactfully, they gave the module a cinematic quality while deepening immersion and empathy.
Case 1 - Jamie’s Perfect Paper
Setup::
Alex notices a sudden spike in quality from Jamie, a student who previously struggled. He suspects AI but has no proof.
Learner Choice:
Confront Jamie directly → Breaks trust; class morale drops
Say nothing → Leads to normalization of unethical AI use
Open a coaching dialogue → Builds trust, sets a standard, invites disclosure
Reflection Prompts:
Each path includes carefully written feedback to prompt:
Self-awareness
Ethical reasoning
Strategy for future communication
Phase 3: Development in Articulate Storyline 360
Slides Design
I designed branching slides that responded dynamically to learner choices, creating a personalized journey through each scenario. Each slide was mapped to a specific decision path, with custom feedback that reflected not just right or wrong answers, but the nuance of timing, tone, and ethical framing. For example, confronting a student too directly led to disengagement, while a coaching approach fostered trust and growth. This design allowed learners to see the real consequences of their decisions, reinforcing behavior change through immersive narrative flow and meaningful reflection—not just quizzes.
Simulate
To elevate immersion, I integrated custom voiceovers, ambient music, and smooth transitions across the module. These elements were intentionally layered to mirror real-life classroom pacing—from quiet reflective pauses to emotionally tense moments. Voiceovers added human warmth, grounding each decision in tone and intent. Background music subtly shifted with each outcome path, reinforcing the emotional arc of the scenario. Seamless slide transitions and audio cues helped simulate the natural rhythm of conversation and internal thought, making the experience feel less like training—and more like navigating real instructional dilemmas.
Learning Loop
Each scenario included built-in reflection moments following key decision outcomes—transforming passive observation into active learning. After every branch, learners were prompted to analyze the consequences of their choices, consider alternative approaches, and connect the outcome to real classroom practice. These reflective pauses were designed to deepen metacognition, reinforcing ethical reasoning and encouraging instructors to transfer insights into their own teaching. The loop wasn’t just informational—it was transformational.
This project led to significant behavioral shifts and instructional clarity:
OUTCOME AREA
RESULT
Instructor Confidence
90% reported feeling more equipped to address AI-related issues.
Ethical Conversations
80% of participants initiated AI use disclosures in their assignments.
Engagement & Completion
100% of pilot group instructors completed the module and opted into follow-up resources.
Scalability Potential
Instructional leadership requested integration into annual faculty onboarding programs.
Impact Metric Highlight:
“After taking this course, I rewrote my syllabus and had the most honest student conversations about AI I’ve ever had.”
Trust beats control: When instructors were shown how to coach instead of confront, the outcomes were more ethical and lasting.
Realism matters: Faculty connected more with scenarios that reflected their daily ambiguity, not idealized policies.
Branching needs balance: Too many options can confuse. Limiting to 3 strong, differentiated paths gave clarity while preserving choice.
My Growth as a Designer
This project was a personal and professional inflection point.
Shifted from “knowledge dump” to “behavioral simulation” as my core design approach.
Deepened my expertise in Cathy Moore’s Action Mapping, turning fuzzy faculty concerns into measurable actions.
Honed my use of AI video tools and voiceovers to create emotionally resonant moments with minimal learner fatigue.
Strengthened my visual communication by building all visuals and storyboards with accessibility and consistency at the core.
Final Reflection
This project reflects my design philosophy at its core:
“Train for judgment, not just compliance.”
“Design learning that feels real, asks hard questions, and changes practice.”
Through scenario-based learning, I didn’t just build a training, I created a space for reflection, nuance, and human growth.