Research basis for the 2016 ISTE Standards for Students: Computational thinking
Being able to think and solve problems in the way that a computer is designed to solve problems is a vital skill in today’s digital age. Computational thinking (CT) is a problem-solving process that includes but also exceeds coding. It is fundamental to solving problems via computer applications but its methods can be used in a variety of situations and approaches. CT combines logic and deep knowledge of the fundamentals of how computers “think.” Thus it is an important, contemporary literacy for all students, not just those who are likely to become software engineers. Even if students do not pursue computing in their careers, they will need to be familiar with the vocabulary and processes to effectively communicate with colleagues on technical issues and to be knowledgeable themselves about how computing works and affects their lives.
Empowering students to take ownership of their learning emerged as a major theme during the refresh.
Being able to think and solve problems in the way that a computer is designed to solve problems is a vital skill in today’s digital age. Computational thinking (CT) is a problem-solving process that includes but also exceeds coding. It is fundamental to solving problems via computer applications but its methods can be used in a variety of situations and approaches. CT combines logic and deep knowledge of the fundamentals of how computers “think.” Thus it is an important, contemporary literacy for all students, not just those who are likely to become software engineers. Even if students do not pursue computing in their careers, they will need to be familiar with the vocabulary and processes to effectively communicate with colleagues on technical issues and to be knowledgeable themselves about how computing works and affects their lives.
Empowering students to take ownership of their learning emerged as a major theme during the refresh.
Computational Thinking (CT) is a problem solving process that includes a number of characteristics and dispositions. CT is essential to the development of computer applications, but it can also be used to support problem solving across all disciplines, including the humanities, math, and science. Students who learn CT across the curriculum can begin to see a relationship between academic subjects, as well as between life inside and outside of the classroom.
- Decomposition: Breaking down data, processes, or problems into smaller, manageable parts
- Pattern Recognition: Observing patterns, trends, and regularities in data
- Abstraction: Identifying the general principles that generate these patterns
- Algorithm Design: Developing the step by step instructions for solving this and similar problems