As learning becomes increasingly self-directed, buzzwords like “adaptive” and “personalized” are attached to more and more eLearning platforms. These two trends are overturning eLearning conventions like requiring all learners to complete the same training content.
It’s worth examining what each of these terms means, how they differ—and where they overlap.
Personalization is static
Personalizing learning accommodates a learner’s preferred approach to learning, offering choice of what to learn, when and where, and in what format. This could mean offering multimodal content that covers the same topic. It can also underscore the self-directed aspect of modern learning, allowing learners to choose when to consume content.
Personalization can take a bigger-picture role, too. Individual employees, often in coordination with their managers, can plan personal learning paths, selecting courses and content that meet their immediate and anticipated job needs and goals. A manager can personalize a learning plan to address an individual’s skills gap or areas where performance is weak. A personal learning path can guide an employee toward a desired promotion.
The mix of learning courses, documents, videos, etc. is tailored to the person’s immediate needs. But the actual content of each item is static; that is, each learner whose mix includes Course A or Video B gets the same Course A or Video B.
Big picture or small, personalization addresses a current situation and meets the needs of an individual, now.
Adaptive learning evolves
In an adaptive learning paradigm, each learner gets different content, even when they’re studying the same topic. Adaptive learning respects an individual learner’s prior knowledge and experience; it is the antithesis of one-size-fits-all training.
A new employee will get the fundamentals, while a more experienced professional can skip the introductory content and go right to advanced topics or tougher problems and application questions. Someone who’s learned a topic before but needs a refresher can get that—without having to start over at the beginning and plod through the basic material.
Some adaptive programs use a pretest to determine which content to deliver, but artificial intelligence (AI) is rapidly changing the adaptive learning landscape. AI-based eLearning uses algorithms to keep track of what learners know and their performance on activities and quizzes. These adaptive platforms dynamically deliver content in learners’ weak areas and avoid boring learners with content they know well.
The specific content mix delivered to each learner is fluid, adapting in real time to learners’ progress. Some adaptive microlearning platforms take this to a very granular level, choosing a unique set of questions, activities, or information cards to deliver to each learner during each session.
Where personalization and adaptive learning overlap
It’s understandable that many people confuse adaptive and personalized learning; there’s overlap in key areas:
- Similar goals: Both aim to deliver the content an individual learner needs at a particular moment.
- Focus on individual learning needs: Personalization and adaptive learning both abandon the convention of forcing all learners in a group or company to complete the same courses in favor of looking at each learner’s learning goals and knowledge gaps—to a certain extent. Adaptive platforms take that idea much farther than personalization, though.
- Fit modern learners: Adaptive and personalized learning emphasize individual needs and choices and are a good fit with self-directed modern learners. Whether offering multiple modes of instruction or determining content on the fly, the end result is respecting learners’ time and learning preferences.
Learners resent having to cover material they know already or that is irrelevant to their job roles, so moving toward adaptive and personalized learning is a way to re-engage learners and improve training results. Organizations can implement personalization and adaptive learning at various levels, depending on their corporate and learning culture.
Explore adaptive and personalized learning at DevLearn
Several sessions at DevLearn 2019 Conference & Expo dig into adaptive learning, personalization, AI in eLearning, and other topics that help L&D professionals design and develop the eLearning their organizations need to excel. These include:
- "Using AI for Matching Emerging Skills with Adaptive Learning"
- "Learning Buzzword Bingo: Making Sense of the Hype"
- "Getting Started with Adaptive Learning"