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Study: Kids’ lack of focus does not mean lack of learning

Us adults excel at filtering out irrelevant information and focusing on key facts.

So, understandably, it drives us crazy when our kids jump on the couch, daydream, talk, or doodle while we’re trying to give instructions or explain the schedule for the day.

But new research published in Psychological Science found that kids may absorb information just as well if they’re told to focus on it as if they’re not.

Actually, it’s pretty incredible.

Instructors told participants in an initial study to pay attention to a series of drawings, then perform an activity identifying them. Adults outperformed kids.

In a second study, instructors told participants to pay attention to shapes laid over drawings. In the follow-up activity, adults outperformed kids in identifying the shapes. But when asked to identify the drawings underneath, children performed just as well as adults.

What does this mean? While the adult brain learns better when directed to focus on something specific, children learn just as well either way.

“These results suggest that a sponge may be a good metaphor for learning during childhood: Children appear to take things in regardless of whether they are trying to or not,” the authors wrote.

The skill of selective attention, or capacity to filter out distractions in favor of focusing on relevant information, is well known to develop quite slowly well into early adulthood, the authors wrote.

So next time you start to get frustrated because your kids don’t seem to be paying attention, take a deep breath and remember: They’re probably absorbing it all.

Pariva Health has helped more than 25,000 families of neurodivergent children and 
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Cited study: Directing Attention Shapes Learning in Adults but Not Children, by Marlie C. Tandoc, Bharat Nadendla, Theresa Pham, Amy S. Finn. https://journals.sagepub.com/doi/epub/10.1177/09567976241263347

Prithvi Singh

Seasoned Technical Product Manager, focusing on product strategy, roadmap development, and data-driven decision-making. Hands-on experience in implementing and optimizing machine learning algorithms in various projects