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How is student strength calculated?
How is student strength calculated?

How we use Artificial Intelligence to predict how students retain content over time.

Tom O'Donahoo avatar
Written by Tom O'Donahoo
Updated over a week ago


Unfortunately, human memory is far from perfect. When you learn something new without enough repetition spaced out over time, that new knowledge can quickly fade away. Scientists have studied this for generations, and their research suggests it’s super important to revise content regularly to commit it to your long term memory. Doing so saves you from having to re-learn something all over again down the track.

For most students, there’s often a very long time between when you learn some content and when you might be asked to recall it in an assessment or exam. When you combine this with the sheer volume of material you’re expected to learn, it’s a big task to keep all that information fresh in your brain. 

Here at Atomi, we’ve worked hard to make this process easier. 

When you complete an Atomi quiz or practice, we track how you went and compare it to millions of other data points from Atomi users. This helps us understand where you’re strong and weak and how well you’re doing in each topic relative to other users. Using all this data, we’ve built an Artificial Intelligence Engine that can predict how you’ll remember content over time. 

We use this system to predict your current strength for each item, which is a relative measure of how much content you’ve retained.

If you recently did very well in a quiz or practise, your strength will be High. However, after time, if you haven’t revised, your strength will begin to drop. So the more times you do a quiz or practice, and the better your scores, the longer your strength will take to decay.

If you see your strength is slipping on a particular piece of content, we recommend you jump in and revise to build your strength back up.

P.S. We also use your predicted strength to make data-driven personalised recommendations on what you should revise next. You’ll find these recommendations at the top of your course!

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