Aktivite 1
This is the space to describe the service and explain how customers or clients can benefit from it. It’s an opportunity to add a short description that includes relevant details, like pricing, duration, location and how to book the service.
Aktivite 2
This is the space to describe the service and explain how customers or clients can benefit from it. It’s an opportunity to add a short description that includes relevant details, like pricing, duration, location and how to book the service.
Aktivite 3
This is the space to describe the service and explain how customers or clients can benefit from it. It’s an opportunity to add a short description that includes relevant details, like pricing, duration, location and how to book the service.
Aktivite 4
This is the space to describe the service and explain how customers or clients can benefit from it. It’s an opportunity to add a short description that includes relevant details, like pricing, duration, location and how to book the service.
What personalisation looks like in practice
Most AI-supported personalisation happens in practice work. A pupil who answers several fraction questions correctly moves on to harder ones; a pupil who struggles receives an easier question, a hint or a short explanation. Khan Academy, for example, offers mastery-based practice where progress depends on answers given, and it has added an AI tutor called Khanmigo that guides pupils with questions rather than giving answers outright.
The tool handles pacing. The teacher still chooses the goals, spots misconceptions that a platform may miss, and decides when a pupil needs a conversation rather than another question.
Limits to keep in mind
Personalised practice can narrow what pupils see. If a platform keeps a child on easier material, they may never meet the reasoning tasks that build deeper understanding. Pupils also learn a great deal from each other, and too much time working alone on a screen removes that.
Parents often ask whether personalised means "less teaching". It should mean better-targeted teaching: the data from practice sessions shows the teacher who needs help, so small-group time goes where it matters.
School leaders should also look at what a platform reports. A dashboard that shows only time spent and questions answered says little about learning. Reports that show which skills a pupil has secured, and which errors recur, are far more useful for planning. Before renewing any subscription, ask teachers whether they actually used the reports and what they changed as a result. If the answer is rarely, the tool may be providing practice but not informing teaching, and a simpler option could do the same job.
A rotation lesson for a mixed-ability class
This model works well for Year 5 (ages 9 to 10) in a 50-minute maths lesson. Materials: devices for one third of the class, an adaptive practice platform set to the current topic, mini whiteboards and a set of hands-on fraction strips.
Split the class into three groups and rotate every 15 minutes, with 5 minutes to regroup.
Group A uses the adaptive platform on the current topic.
Group B works with the teacher on a misconception spotted in the last session's data.
Group C solves a paired problem using fraction strips and explains it on whiteboards.
After the lesson, check the platform report to plan tomorrow's teacher group.
Key points
Let AI handle pacing of practice while the teacher sets goals.
Use the practice data to decide who joins small-group teaching.
Balance screen practice with paired, hands-on and spoken work.
Check that pupils are still meeting challenging tasks, not only easier ones.
Photos: Vitaly Gariev, Taylor Flowe / Unsplash
AI for Personalized Learning
Personalised learning means giving each pupil work that fits what they already know and what they need next. Teachers have always done this with extension tasks and extra support. AI tools can help by adjusting practice question by question, which is hard to do by hand for thirty children at once.
Edutech
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AI for Personalized Learning
