Which concept facilitates personalized education by adjusting content?

The concept that facilitates personalized education by adjusting content is adaptive learning. Adaptive learning systems use algorithms and data analytics to tailor educational experiences to individual learners' needs, preferences, and progress. This approach allows the system to modify the difficulty level, types of content, and pace of learning to optimize the educational experience for each student.

By continuously assessing a learner's understanding and skills, adaptive learning technologies can provide immediate feedback and adapt the instructional pathways accordingly. This personalized approach helps to engage students more effectively, enhances their learning outcomes, and addresses diverse learning styles and paces.

In contrast, while narrow AI is a subset of artificial intelligence focused on specific tasks and capabilities, it does not inherently encompass the personalization aspect found in adaptive learning systems. Artificial intelligence, in broader terms, refers to the simulation of human intelligence processes by machines but is not limited to educational contexts. Active learning, on the other hand, is an instructional strategy that involves engaging students actively in the learning process, which may not specifically relate to adjusting content based on individual needs. Thus, adaptive learning stands out as the most appropriate concept for personalized education tailored to individual learners.