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Let's create continuous conversations about climate change education: Spreading the Sediment of Science!
AI for Oceans
Provided by: Code.org |Published on: April 27, 2021
Videos
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Synopsis
- This interactive lesson teaches students about artificial intelligence, machine learning, and bias.
- Using video game-like modules, students will train a virtual robot to clean up the ocean with machine learning techniques.
Subjects: Science, Computer Science
Authors: Code.org
Region: Global
Languages: English, Spanish, French, Russian, Arabic, Chinese, German, Dutch, Bulgarian, Italian, Polish, Portuguese, Japanese, Vietnamese, Indonesian, Persian, Norwegian, Basque, Croatian, Danish, Estonian, Greek, Hebrew, Hungarian, Kazakh, Korean, Lithuanian, Mongolian, Serbian, Slovak, Thai, Albanian, Azerbaijani, Catalan, Georgian, Hindi, Icelandic, Telugu, Uzbek, Czech, Finnish, Latvian, Marathi, Romanian, Slovenian, Swedish, Tamil, Maori, Armenian, Irish, Sinhala, Khmer, Filipino
Teaching Materials
Positives
- Students will enjoy this fun and highly engaging resource.
- Facts about ocean pollution pop up intermittently as students train the robot.
Additional Prerequisites
- This resource is available in many different languages. Users can change the language at the bottom left-hand corner of the screen.
- The lesson plan for this resource includes objectives, advice on lesson preparation, and a teaching guide.
Differentiation
- Philosophy, ethics, and design classes could use this resource to discuss the way that human bias can influence machine learning.
- Computer and technology classes could make a list of ways that artificial intelligence could be used to combat climate change.
- Other resources on this topic include this video on the effect of plastic pollution in the ocean, this video on the hidden reservoirs of plastic in the ocean, and this podcast episode on environmental problems within the commercial fishing industry.
Scientist Notes
Teaching Tips
Standards
Resource Type and Format
All resources can be used for your educational purposes with proper attribution to the content provider.
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