The Epiphany Instructional Design Framework is a structured, evidence-based approach to instructional design that ensures learning is engaging, effective, and transferable.
Rooted in decades of cognitive science, learning theory, and instructional design research, this framework serves as the pedagogical foundation for AI-powered learning design.
With the rapid growth of AI-assisted education, instructional designers must leverage research-backed strategies to optimize motivation, ensure deep learning, and foster real-world knowledge application.
Epiphany, as an AI-powered copilot for instructional design, ensures that all learning experiences are scientifically optimised through its Motivate – Practice – Transfer framework.
Motivation is the foundation of learning. Learners are most likely to persist and succeed when the learning experience aligns with their needs, interests, and professional goals. This phase ensures that instructional design fosters curiosity, belonging, autonomy, and clear relevance—while leveraging data to understand what truly drives each learner.
Epiphany helps identify actual performance gaps using AI to analyse learner data, role requirements, and business KPIs. It surfaces insights into what learners care about, how they prefer to learn, and what motivates them—allowing for the design of highly relevant, personalised learning experiences.