Machine Learning Unplugged
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Provided by: LabXchange|Published on: May 8, 2026
Lesson Plans
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This resource has been reviewed by SubjectToClimate's climate scientists and verified for scientific accuracy and up-to-date information. Learn about our review process →
Synopsis
- This lesson plan introduces students to the concept of machine learning through hands-on activities that require no computer access, helping learners understand how algorithms are trained using data.
- Students engage in sorting, classifying, and pattern-recognition activities that mirror how machine learning models work, building foundational computer science and data literacy skills.

Subjects: Science, Computer Science
Authors: The Tech Interactive
Region: Global
Languages: English
Teaching Materials
Preparation:
- Print and cut one set of the Data Set Cards for each group, planning for groups of 3-4 students.
Prerequisites:
- Provide students with a grade-level-appropriate definition for the terms artificial intelligence and algorithm.
Climate Change Connections:
- Have students consider why it is necessary to track animals. Discuss the impacts of climate change on biodiversity, habitats, and migration.
- Have students brainstorm other uses for AI and data processing that can contribute to mitigation or adaptation strategies in the face of climate change.
- For a balanced discussion about AI, discuss some of the environmental and climate change-related concerns associated with the use of these technologies. Have students consider how people weigh the benefits and the costs. Consider using this video as an introduction to the topic.
Differentiation:
- Refer to the sections titled "Beginning Programmers" and "Advanced Programmers" in the Lesson Directions for ways to differentiate for young learners and extensions for older learners, respectively.
- Differentiate for advanced learners by asking them to design their own simple classification algorithm for a real-world environmental problem.
This resource guides students through a clear machine learning (ML) scenario that illustrates how artificial intelligence is trained. All key terms are clearly defined in the text with a complete glossary included. Climate change is not directly mentioned, but ML is a powerful tool used by climate scientists to track global change. This resource is recommended for teaching.
Teaching Tips
Standards
Resource Type and Format
About the Partner Provider
LabXchange
Harvard University’s LabXchange is a free online platform for science education, created with support from the Amgen Foundation. It makes learning science online flexible and fun, with interactives, lab simulations, and more.
Scientist Reviewed
This resource has been reviewed by SubjectToClimate's climate scientists and verified for scientific accuracy and up-to-date information. Our review process ensures that every resource in our library reflects the current state of climate science.
Learn about our review process →

