How Algorithms Determine What You See Online

~60 min · 15 stations

How Algorithms Determine What You See Online is a self-paced learning path in Mathematics & Logic, free to read, written at General Public / 9th Grade reading level. Across 15 structured stations, you will work through the core ideas step by step, each with a short quiz to check your understanding. By the end you will be able to identify the basic function of online filtering systems; explain how platforms collect individual user data; trace the evolution of early recommendation systems.

Conductor

The Conductor

Welcome aboard this express line through the hidden logic of your feed. We will navigate the math that builds your digital reality, so keep your eyes on the tracks ahead.

What you will learn

Complete each station to unlock the next.

FOUNDATION

Establishes the core vocabulary and essential context you need before going further.

• Identify the basic function of online filtering systems

Station 01: Defining The Digital Filter▶

• Explain how platforms collect individual user data

Station 02: Data Points And User Profiles▶

• Trace the evolution of early recommendation systems

Station 03: The History Of Sorting Logic▶

CORE CONCEPTS

Unpacks the ideas and principles that the subject is built on.

• Describe how group behavior influences personal suggestions

Station 04: Collaborative Filtering Logic▶

• Define how item features drive feed rankings

Station 05: Content-Based Filtering Methods▶

• Differentiate between active and passive user signals

Station 06: Implicit Versus Explicit Feedback▶

• Analyze how time spent impacts visibility

Station 07: The Role Of Engagement Metrics▶

MECHANICS

Examines how things actually work — the processes, rules, and systems in action.

• Apply weights to different user interaction types

Station 08: Weighting Variables In Equations▶

• Solve for new user content delivery challenges

Station 09: The Cold Start Problem▶

• Forecast future user interests via patterns

Station 10: Predictive Modeling Techniques▶

APPLICATION

Puts knowledge to use through real-world scenarios and practical problems.

• Examine how isolation occurs within feeds

Station 11: Filter Bubble Effects▶

• Evaluate fairness in automated ranking systems

Station 12: Algorithmic Bias And Fairness▶

• Advocate for clearer user control settings

Station 13: Transparency In Design▶

SYNTHESIS

Connects everything together and explores broader implications and open questions.

• Apply strategies to curate personal feeds

Station 14: Optimizing Your Digital Feed▶

• Predict trends in next-generation sorting

Station 15: Future Of Intelligent Curation▶

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General Public / 9th GradeAI Generated · gemini-3.1-flash-lite