Computational thinking

From Wikipedia, the free encyclopedia
Jump to: navigation, search
Three stage process describing Computational Thinking

Computational Thinking (CT) is the thought processes involved in formulating a problem and expressing its solution(s) in such a way that a computer—human or machine—can effectively carry out.[1] Computational Thinking is an iterative process based on three stages: 1) Problem Formulation (abstraction), 2) Solution Expression (automation), and 3) Solution Execution & Evaluation (analyses) captured by the figure to the right. The term computational thinking was first used by Seymour Papert in 1980[2] and again in 1996.[3] Computational thinking can be used to algorithmically solve complicated problems of scale, and is often used to realize large improvements in efficiency.[4]


The characteristics that define computational thinking are decomposition, pattern recognition / data representation, generalization/abstraction, and algorithms.[5][6] By decomposing a problem, identifying the variables involved using data representation, and creating algorithms, a generic solution results. The generic solution is a generalization or abstraction that can be used to solve a multitude of variations of the initial problem.

The phrase computational thinking was brought to the forefront of the computer science community as a result of an ACM Communications article on the subject by Jeannette Wing. The article suggested that thinking computationally was a fundamental skill for everyone, not just computer scientists, and argued for the importance of integrating computational ideas into other disciplines.[7]

Characteristics of Computational Thinking[edit]

Computational Thinking is a problem-solving process that includes (but is not limited to) the following characteristics:[8]

  • Formulating problems in a way that enables us to use a computer and other tools to help solve them;
  • Logically organizing and analyzing data;
  • Representing data through abstractions such as models and simulations;
  • Automating solutions through algorithmic thinking (a series of ordered steps);
  • Identifying, analyzing, and implementing possible solutions with the goal of achieving the most efficient and effective combination of steps and resources;
  • Generalizing and transferring this problem solving process to a wide variety of problems.

Center for Computational Thinking[edit]

Carnegie Mellon University in Pittsburgh has a Center for Computational Thinking. The Center's major activity is conducting PROBEs or PROBlem-oriented Explorations. These PROBEs are experiments that apply novel computing concepts to problems to show the value of computational thinking. A PROBE experiment is generally a collaboration between a computer scientist and an expert in the field to be studied. The experiment typically runs for a year. In general, a PROBE will seek to find a solution for a broadly applicable problem and avoid narrowly focused issues. Some examples of PROBE experiments are optimal kidney transplant logistics and how to create drugs that do not breed drug resistant viruses. [9]

Computational Thinking (CT) for Pre-College levels[edit]

While Computational Thinking is mostly practiced in college level education, it has gained its ground in K-12 levels in STEM education. You may find a small handful of online institutions which provides curriculum, and other related resources to build and strengthen pre-college students with Computational Thinking, Analysis and Problems Solving. One prominent one is the Carnegie Mellon Robotics Academy. It offers training sessions for both pre-college students, as well as teachers. CMU's programs exercise instructional scaffolding methods via engineering process. There is also another online site named[10] offering similar resources.

As far as a physical facility, in Central New Jersey, there is a small institution, named Storming Robots, offers technology programs to Grade 4 to 12 with focus on Algorithmic and Computational Thinking via robotics projects throughout the school year. Students may follow its road map [11] starting from Grade 4 until they graduate to college.

Computational Thinking (CT) for Secondary STEM Education[edit]

Problem-based learning is an important element of Science, Technology, Engineering, and Mathematics, also known as STEM, education in particular . The connection Computational Thinking makes in the context of problem solving processes is present in STEM focused classes. Characteristics of Computational Thinking reformulate problems by decomposing them into smaller and more manageable segments. These strategies enable students to transform complex problems into multiple step procedures that is not only easier to navigate through, but also provides an efficient way of thinking (Wing, 2006). In STEM education Computational Thinking is defined as a set of cognitive skills that let K-12 educators identify patterns, break apart complex problems into smaller steps , organize and create a series of steps to provide solutions, and build a representation of interacting data through simulations. Teachers in STEM focused classrooms that include Computational Thinking, allow students to practice problem-solving skills such as trial and error (Barr, et al, 2011).[12]


  1. ^ Wing, Jeannette (2014). "Computational Thinking Benefits Society". 40th Anniversary Blog of Social Issues in Computing. 
  2. ^ Papert, Seymour. Mindstorms: Children, computers, and powerful ideas. Basic Books, Inc., 1980.
  3. ^ Papert, Seymour (1996). "An exploration in the space of mathematics educations". International Journal of Computers for Mathematical Learning. 1. doi:10.1007/BF00191473. 
  4. ^ Computational thinking:
  5. ^ "Introduction to computational thinking". BBC Bitesize. Retrieved 25 November 2015. 
  6. ^ "Exploring Computational Thinking". Google for Education. Retrieved 25 November 2015. 
  7. ^ Wing, Jeanette M. (2006). "Computational thinking" (PDF). Communications of the ACM. 49 (3): 33. doi:10.1145/1118178.1118215. 
  8. ^ Stephenson, Chris; Valerie Barr (May 2011). "Defining Computational Thinking for K-12". CSTA Voice. 7 (2): 3–4. ISSN 1555-2128. CT is a problem solving process... 
  9. ^ PROBE Experiments
  10. ^ "LEGO Engineering". Retrieved 30 Dec 2013. 
  11. ^ "Roadmap for learning path". Retrieved 30 Dec 2013. 
  12. ^ Barr, David; Harrison, John; Leslie, Conery (2011-03-01). "Computational Thinking: A Digital Age Skill for Everyone". Learning & Leading with Technology. 38 (6): 20–23. ISSN 0278-9175. 

External links[edit]