Personalizing learning content to both the learner and the context is the best way to achieve optimal learning and performance outcomes.

L&D professionals have historically achieved personalization by making copies upon copies of learning assets and course materials, tweaking each copy to meet the differentiated needs of learners. This approach is labor-intensive and prone to inconsistencies and inaccuracies, including the risk of delivering incorrect or outdated information to learners. In contrast, reusable content can be updated in one place, ensuring consistency and accuracy—and improving content maintenance efficiency. All without sacrificing personalization and differentiated instruction.

This hands-on micro master class walks you through creating a reusable content model. Our model entails analyzing instructional content and logically chunking it into semantically meaningful components such that the smallest logical components are individually addressable with metadata—enabling a high level of personalization and relevance to the individual learner. 

We’ll also share examples of multi-channel publishing that reuse learning content in multiple contexts—without creating duplicate content. We will explore key concepts and best practices in reusable content, guide you in applying these concepts to creating a learning content model, and discuss the technical considerations and architecture necessary to leverage reusable learning content across contexts.