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

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

4.1.17 Identify examples of abstraction. Level: 2 4.1.18 Explain why abstraction is required in the derivation of computational solutions for a specified situation. Level: 3 4.1.19 Construct an abstraction from a specified situation. Level: 3 4.1.20 Distinguish between a real-world entity and its abstraction. Level: 2

Programming Design

4.2.1 Describe the characteristics of standard algorithms on linear arrays. Level: 2 4.2.2 Outline the standard operations of collections. Level: 2 4.2.3 Discuss an algorithm to solve a specific problem. Level: 3 4.2.4 Analyse an algorithm presented as a flow chart. Level: 3 4.2.5 Analyse an algorithm presented as pseudocode. Level: 3 4.2.6 Construct pseudocode to represent an algorithm. Level: 3 4.2.7 Suggest suitable algorithms to solve a specific problem. Level: 3 4.2.8 Deduce the efficiency of an algorithm in the context of its use. Level: 3 4.2.9 Determine the number of times a step in an algorithm will be performed for given input data. Level: 3

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.

Provide an answer from a number of possibilities. Recognize and state briefly a distinguishing fact or feature.

Give a detailed account including reasons or causes.

Develop information in a diagrammatic or logical form.

Make clear the differences between two or more concepts or items.

Produce a plan, simulation or model.

Give a detailed account or picture of a situation, event, pattern or process.

Give a brief account.

Offer a considered and balanced review that includes a range of arguments, factors or hypotheses. Opinions or conclusions should be presented clearly and supported by appropriate evidence.

Break down in order to bring out the essential elements or structure. To identify parts and relationships, and to interpret information to reach conclusions.

Propose a solution, hypothesis or other possible answer.

Reach a conclusion from the information given.

The circumstances that form the setting for an event, statement, or idea, and in terms of which it can be fully understood and assessed.

Obtain the only possible answer.

A unit of abstract mathematical system subject to the laws of arithmetic.

Apply knowledge or rules to put theory into practice.