What is an example of adaptive learning?

An online math platform that adjusts difficulty based on your answers is a good example. If the students solve a problem quickly, it moves them to more complex questions. If they are struggling, it provides hints or simpler problems. This real-time adjustment helps learners progress at their own pace. Contact us to learn more about adaptive learning platforms.

What are the types of adaptive learning?

Adaptive learning comes in a few forms: Rule-based systems – Adjust content based on preset conditions (e.g., getting three wrong answers triggers a review lesson). AI-powered platforms – Use machine learning to personalise lessons based on behaviour and performance. Competency-based learning – Moves students forward only when they demonstrate mastery rather than sticking to a fixed schedule. Data-driven feedback – Uses analytics to provide customised insights to both learners and instructors.

What is an adaptive classroom?

An adaptive classroom adjusts teaching methods, materials, and pacing based on students’ needs. This could mean using technology that tracks student progress or simply a teacher who modifies lessons in real time to help students grasp concepts better. It’s about flexibility—ensuring no one is left behind or held back. Contact us to build your own adaptive solution.

What is adaptive vs personalised learning?

Both adjust to a student's needs, but there’s a key difference: Adaptive learning relies on technology to analyse performance and adjust content in real-time. Personalised learning is broader—it can include teacher-driven strategies, student choice, and custom learning plans, not just automated adjustments. Think of adaptive learning as a smart GPS that changes routes as you drive, while personalised learning is more like planning your own road trip based on preferences.

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