Computational thinking has four subsets: decomposition, pattern recognition, algorithms, and abstraction. Together, these valuable areas form the benefits of computational thinking.

Excellence and Expertise Miami, ODHE partnership helps K-12 teachers provide pattern recognition and abstract thinking skills to students Computational thinking modules will allow education prep ...

Boost student engagement through the core concepts of computational thinking: decomposition, pattern recognition, abstraction, and algorithmic thinking. In this session, you’ll learn how to ...

[It’s] pattern recognition, which is like book awareness.” Her Ready, Set, Think! program introduces families to CT skills through everyday activities that can be broken down into steps, such as tying ...

The main principles of computational thinking include decomposition (breaking problems down into smaller parts), pattern recognition (finding similarities between pieces), abstraction (generalizing ...

We suggest that computational thinking — which applies concepts from computer science — provides a framework for pre-K-12 educators to integrate and apply computational methods to solve ...

Pattern recognition in relation to Artificial Intelligence (AI) refers to the ability of a machine or algorithm to identify and classify patterns from data, such as images, sounds, or other inputs.

This video discusses a lesson on Computational Thinking, designed to show you how to take a big difficult problem and turn it into several simpler problems.

Computational thinking is one of the biggest buzzwords in education—it’s even been called the ‘5th C’ of 21st century skills. While it got its start as a way to help computer scientists think more ...

The scientist taught computers to read handwriting and advanced the fields of pattern recognition, computational forensics and machine learning.