Intelligent adaptive learning is the modern version of personalized learning whose first traces date back to the 19th century. Powered by artificial intelligence, this customized learning can tailor training to a learner’s particular profile, needs and interests. Above all, it can generate in real-time the learning path that is most likely to enable the learner to achieve his or her objectives. Here’s how the various functions of an intelligent adaptive learning system are deployed.
It covers these 3 phases of the learning process:
- Knowledge Assimilation
- Knowledge Consolidation
- Knowledge Translation
It includes 5 processes:
- Identification of the learner’s profile
- Adaptation of training according to performance
- Progressive profile refinement
- Recurring assessments
- Status of skills acquired
It can adapt the training to 3 levels:
- Presentation
- Navigation
- Content
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Author:
Catherine Meilleur
Creative Content Writer @KnowledgeOne. Questioner of questions. Hyperflexible stubborn. Contemplative yogi.
Catherine Meilleur has over 15 years of experience in research and writing. Having worked as a journalist and educational designer, she is interested in everything related to learning: from educational psychology to neuroscience, and the latest innovations that can serve learners, such as virtual and augmented reality. She is also passionate about issues related to the future of education at a time when a real revolution is taking place, propelled by digital technology and artificial intelligence.
