Computational thinking, problem-solving and programming

This is one of the most important ideas you can take with you:

Decompose a problem into smaller parts, model a problem with flowcharts. Learn to think sequentially

Computational thinking, problem-solving and programming

Wing (2006, 2011) defined computational thinking as the thought processes involved in formulating problems and their solutions so that the solutions are represented in a form that can be effectively carried out by a computer.

Computational Thinking (CT) is a process that generalizes a solution to open-ended problems. Open-ended problems encourage full, meaningful answers based on multiple variables, which require using decomposition, data representation, generalization, modeling, and algorithms found in Computational Thinking. Computational Thinking requires the decomposition of the entire decision making process, the variables involved, and all possible solutions, ensuring that the right decision is made based on the corresponding parameters and limitations of the problem. The term computational thinking was first used by Seymour Papert in 1980[1] and again in 1996.[2] Computational thinking can be used to algorithmically solve complicated problems of scale, and is often used to realize large improvements in efficiency

The big ideas in computational thinking

Thinking procedurally

• Procedural thinking
• Evaluating process
• Sub-process

Thinking logically

• Logical decisions
• Conditions and decisions
• Logical rules

Thinking ahead

• Inputs and outputs
• Pre-conditions
• Exceptions and pre-conditions

Thinking concurrently

• Concurrency

Thinking abstractly

• Abstraction
• Applied abstraction

Programming design

• Linear arrays
• Collections
• Pseudocode
• Algorithms
• Applied algorithmic thinking

Introduction to programming

• Fundamental operations
• Compound operations
• What is a programming language?
• High level languages
• Low level languages
• Translating high-level code to low-level code

Use of programming languages

• Variables (See also: data types and primitive data types)
• Constants (See also: data types and primitive data types)
• Objects (See also: data types and primitive data types)
• Operators
• Algorithms
• Collections
• Functions

Separate into simpler constituents.

Separate into simpler constituents.

Produce a plan, simulation or model.

Apply knowledge or rules to put theory into practice.