How Algorithms Recommend Content: Algorithms and Your Digital World

This six-page student resource introduces how recommendation algorithms use likes, skips, watch time, and browsing history to personalize digital feeds.

$5USD · Digital download

This six-page student resource introduces how recommendation algorithms use likes, skips, watch time, and browsing history to personalize digital feeds. Students explore filter bubbles, analyze their own recommendations, compare platforms, and reflect on privacy and algorithmic bias.

6 pagesof ready-to-use material · PDF

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Single-classroom licence

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Preview

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What you’ll teach

Clear goals. Useful learning.

Students will explain how recommendation algorithms use personal data and user behavior.
Students will define key terms including algorithm, data point, personalization, and filter bubble.
Students will identify how likes, skips, and watch time influence recommendations.
Students will reflect on algorithmic mistakes, privacy, and the impact of personalized feeds.

How Algorithms Recommend Content: Algorithms and Your Digital World

See exactly what you’ll get

Clear goals. Useful learning.

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