Definitions & Examples

One of the challenges in implementing this content is understanding all the jargon.  Here are some of the terms mentioned in the progress outcomes, and some other related terms, ​with their definitions and some examples.
Programs: see here for definitions and examples related to programming.
​Downloadable Glossary of Terms from Technology Online
 Algorithmic thinking: ​ Solving a problem through the clear explanation (instructions) of the rules and/or steps needed.
​​Algorithm: A set of rules, steps or instructions to accomplish a task.
​Binary: Representing data through a  two symbol system. the most common binary system uses 1 and 0.
Bits: Binary digits (1 and 0)
Compression: Data compression reduces the amount of space needed to store files. Common forms of compression include JPEG (for photos), MP3 (for audio), MPEG (for videos) , and ZIP (for many kinds of data).  Image Compression  Unplugged video.  Unplugged Compression Activity.
Computational complexity: Classification of computer programs according to inherent difficulty. A problem is regarded as inherently difficult if its solution requires significant resources.
Data Representation: The methods used to represent information stored in a computer e.g. binary digits, ASCII and Unicode. 
Encryption: Used to keep data secret. In its simplest form, a file or data transmission is garbled so that only those with the secret "key" can unlock it. An encryption system often consists of two computer programs: one to encrypt the data (plaintext) into a form that looks like nonsense (ciphertext), and a second program that can decrypt the ciphertext back into plaintext form.
Error control: 
Input: Data or commands that are entered into a computer.
Input device: A device that feeds data to a computer e.g. a keyboard or mouse.
Output: Data generated by a computer. It could be physical e.g. a printed page or a software output as a result of a calculation e.g. the result of a mathematical operation on a calculator.
Sorting Algorithms: There are many types of algorithms that can be used for sorting, some are more efficient than others. Here are some examples.
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​​Computational Thinking: a process to solve problems or complete tasks. This can include the following elements:
  • Decomposition*: Breaking down data, processes, or problems into smaller parts.
  • Pattern Recognition*:  Looking for patterns, similarities  and trends in data.
  • Abstraction*: Focus on the important, relevant info. Take away or remove characteristics from something in order to reduce it to a set of essential characteristics.
  • Algorithmic design*: Developing the step by step instructions.
  • Data Representation:  How we represent information on a computer.
  • ​Logical thinking: Thinking in a disciplined manner based on observations, evidence and facts and the relationships between them.
  • Evaluation: Does our solution work? Is it effective in time and cost (in the broad sense)? 
  • Debugging: Finding mistakes in a program and correcting them.
* The four key techniques in computational thinking.