Data Ethics: Privacy, Use, and Responsible Linkage

Apply ethical questions to data collection and use, with attention to privacy, context, and linkage risks.

Looking for step-by-step tutorials for individual AI tools?

Course overview

A practical introduction to ethical reasoning throughout a data lifecycle. Learners identify affected people and purposes, consider responsible use and privacy in learning analytics, then examine how combining datasets can create new risks even when individual sources seem harmless. The course provides a review framework—not legal advice—and ends with a concrete data-use decision record.

Identify affected people, intended purposes, and possible harms before using a dataset. Apply data-minimization, transparency, and access questions to a proposed use. Explain how combining datasets can increase identifiability or reveal unexpected information. Record a decision, safeguards, and unresolved questions for a responsible data-use review.

No technical or legal background is needed. Use a hypothetical or public example; do not submit personal or confidential information.

Beginners who want a clear, guided introduction without unnecessary jargon

People who learn best through examples, guided lessons, and hands-on practice

Professionals, creators, and independent builders looking for a repeatable workflow

Lesson 1 is free

4 lessons · Beginner · Full course.

Open-license course content · CC BY licensed · license verified

This course uses CC BY licensed material attributed to its content provider or uploader. Lesson playback is available only through authenticated access after publication and licensing checks pass.