Standard #: SC.35.CS-CS.2.4 (Discontinued after 2024-2025)


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Solve real-world problems in science and engineering using computational thinking skills.


General Information

Subject Area: Science
Grade: 35
Body of Knowledge: Computer Science - Communication Systems and Computing (Discontinued after 2024-2025)
Date Adopted or Revised: 05/16
Status: State Board Approved

Related Courses

Course Number1111 Course Title222
5002020: Introduction to Computer Science 2 (Specifically in versions: 2016 - 2022, 2022 - 2024, 2024 - 2025 (course terminated))


Related Resources

Lesson Plans

Name Description
Ultimate Building Miami

Students will explore how climate change impacts Miami by examining issues such as sea level rise, intensified hurricanes, and extreme heat. Students will be given a scenario directing them to design a building in Miami that can withstand an issue exacerbated by climate change. They will then work together as a class to create the ultimate building in Miami, one that can withstand multiple impacts of climate change.

How Generative AI like ChatGPT Works

Students will explore Artificial Intelligence (AI) and how generative AI models use Large Language Models (LLMs) and Natural Language Processing NLP to generate outputs. This grades 4-5 lesson is an integrated Computer Science, ELA and Math lesson designed for application of math and ELA content knowledge while exploring and using computational thinking to understand how generative AI works, making cross-curricular connections to understand emerging technologies.

How does Generative AI work?

Students will explore Artificial Intelligence (AI) and the basics on how generative AI models use Large Language Models (LLMs) and Natural Language Processing NLP to generate outputs. This K-3 lesson is an integrated Computer Science, ELA and Math lesson designed for application of math and ELA content knowledge while exploring and using computational thinking to understand how generative AI works, making cross-curricular connections to understand emerging technologies.

Using Machine Learning and Computational Thinking to Train an AI Model

Students will explore Artificial Intelligence (AI) and use computational thinking and Machine Learning (ML) to pretrain a model to recognize and identify objects, including geometric shapes and aircraft. They will used unplugged activities to mimic sorting and classification of the objects using their prior knowledge and then make connections to human learning and Machine Learning. Students will then problem solve and propose solutions using computational thinking to improve the ML model to better recognize the objects. This lesson is an integrated Computer Science, Science and Math lesson designed for students in grades 3-5 to apply math and science content knowledge while exploring and using computational thinking as they think like Computer Engineers and reflect on potential career paths.

Original Student Tutorials

Name Description
Build a Car with Computational Thinking: Part 1

Use computational thinking strategies to build a wind powered car using decomposition, pattern recognition, abstraction, and algorithm design. This is part 1 of a 2 part series on computational thinking.

Test a Car with Computational Thinking: Part 2

Use computational thinking strategies to test a wind powered car using decomposition, pattern recognition, abstraction, and algorithm design. This is part 2 of a 2 part series on computational thinking.

Student Resources

Original Student Tutorials

Name Description
Build a Car with Computational Thinking: Part 1:

Use computational thinking strategies to build a wind powered car using decomposition, pattern recognition, abstraction, and algorithm design. This is part 1 of a 2 part series on computational thinking.

Test a Car with Computational Thinking: Part 2:

Use computational thinking strategies to test a wind powered car using decomposition, pattern recognition, abstraction, and algorithm design. This is part 2 of a 2 part series on computational thinking.



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