Recommendation Algorithms: A Middle School Computer Science Lesson

For educators teaching middle-school technology, one of the biggest challenges is making abstract concepts like machine learning feel concrete and relevant. Students are surrounded by recommendation engines, yet they rarely see them as the complex data-processing tools they are. This worksheet provides a ready-to-use lesson plan for computer science or technology courses, helping you transition from surface-level screen use to fundamental algorithmic literacy.

Making Data Science Accessible

Computer science at the middle-school level should bridge theory and experience. This printable worksheet allows students to examine the 'black box' of algorithms like YouTube's and TikTok's through inquiry-based activities. It focuses on the mechanics of collaborative filtering and the ethics of personalization, ensuring students grasp why these systems behave the way they do.

Worksheet Activities for the Lab

This resource is broken down into structured exercises that can be integrated into a single class period or spread across two.

1. Data Mapping: The Input Layer

Students map their own digital interactions to understand what data platforms collect. They categorize actions like skips, likes, and shares, and predict how these feed into the platform's profile database.

2. Simulating Filtering: Content vs. Collaborative

Using scenarios provided in the worksheet, students work in small groups to simulate how an algorithm makes recommendations. They act as the 'engine,' making decisions based on limited datasets. This hands-on simulation demonstrates the difference between content-based filtering and collaborative approaches.

3. Case Studies: Analyzing the Echo Chamber

Students analyze a provided case study about echo chambers, debating how engagement-focused algorithms affect public discourse and individual choices. This encourages critical thinking about the societal impacts of tech design.

Classroom Implementation Tips

This material is perfect for a 50-minute technology session. Start with a brief 10-minute hook discussing the 'For You' feed, then dedicate 30 minutes to individual worksheet work, followed by a 10-minute class-wide debrief. Encouraging students to discuss their findings in small groups helps them realize that different data inputs lead to vastly different digital experiences.

This worksheet is not meant to be a full-semester curriculum but an essential, modular tool for any unit on data privacy or computer science. It demystifies the software that defines our students' digital experiences and provides the scaffolding you need to move them from consumers to skeptical, informed designers.