Instructional Design Mentor
Overview
Title: Custom GPT: AI-Powered Instructional Design Mentor
Audience: Aspiring Instructional Designers, especially career changers from teaching, corporate training, or higher ed
Role: Instructional Designer, AI Prompt Engineer, Learning Experience Designer
Tools Used: ChatGPT (Custom GPT builder), Canva (branding), Miro (flow mapping), Google Docs (content design)
Categories: Scenario-Based Learning, Simulation, Microlearning
Purpose & Rationale
Many new instructional designers—especially those transitioning from K–12 or ESL teaching—are introduced to a wide range of theories and models but struggle to understand how they connect to real-world ID work. Resources are often either overly academic or too surface-level, with little guidance on how to translate theory into design decisions, portfolio projects, or job interview answers.
I designed a Custom GPT that serves as a theory-to-practice bridge. The AI acts as a personal learning coach, helping users:
- Understand key ID theories (e.g., Cognitive Load Theory, Constructivism, Gagné’s Nine Events, Adult Learning Theory)
- Learn how models like ADDIE, SAM, and Backward Design are applied in real projects
- Get examples of how to apply theory in practice (e.g., “How would I apply cognitive load theory in an eLearning course?”)
- Reflect on their own teaching or training experience and how it connects to ID principles
- Prepare for interviews with theory-informed answers and examples
- Download templates and prompts for practice and reflection
Design Process
I began by identifying common pain points for new IDs: difficulty internalizing theory, confusion about terminology, and a lack of practical context. Then I:
- Mapped key theories and models to their use cases in ID practice (e.g., course design, eLearning, needs analysis)
- Scripted AI prompt logic to support clear explanations, Socratic questioning, and non-judgmental feedback
- Tested early versions with transitioning teachers and new IDs to refine tone, clarity, and usefulness
- Designed a guided experience so users can explore theory in flexible yet focused ways—by topic, question, or scenario
- Added reflection tools to encourage metacognition and document growth over time
Results & Reflections
- Testers reported feeling more confident in using theory during interviews and project planning
- The GPT became a launchpad for deeper learning, giving users the language and examples they needed to move forward
- Helped bridge the gap between academic theory and day-to-day ID work, especially for portfolio projects and resume writing
- Sparked deeper reflection on how existing teaching skills already align with evidence-based instructional strategies
This project solidified my belief that theory-informed design doesn’t need to be intimidating—and that AI can be a valuable tool in supporting adult learners through self-paced, supportive coaching.
© 2025 Flavia Bernardes