Computer Science LearnITWithMrC ⛯ Year 7 Year 8 Year 9 GCSE
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### Learning Objectives

IDSkill_nameRAG
3.3Fundamentals of data representation
3.3.1Number bases
R36 I can understand decimal (base 10)
R36 I can understand binary (base 2)
R43 I can understand hexadecimal (base 16).
R36 I can understand that computers use binary to represent all data and instructions.
R43 I can explain why hexadecimal is often used in computer science.
3.3.2Converting between number bases
R36 I can understand how binary can be used to represent whole numbers.
R43 I can understand how hexadecimal can be used to represent whole numbers.
R37 I can convert from binary to decimal.
R38 I can convert from decimal to binary.
R43 I can convert in both directions between binary and hexadecimal.
R41 I can convert from hexadecimal to decimal.
R42 I can convert from decimal to hexadecimal.
3.3.3Units of information
R45 I can explain that that quantities of bytes can be described using prefixes.
R45 I can explain that kilo, 1 KB is 1,000 bytes.
R45 I can explain that mega, 1 MB is 1,000 kilobytes
R45 I can explain that giga, 1 GB is 1,000 Megabytes
R45 I can explain that tera, 1 TB is 1,000 Gigabytes.
R45 I can compare quantities of bytes using the prefixes above
3.3.4Binary arithmetic
R39 I can add together two binary numbers.
R40 I can add together up to three binary numbers.
R44 I can apply a binary shift to a binary number.
R44 I can describe situations where binary shifts can be used.
3.3.5Character encoding
R46 I can understand what a character set is.
R46 I can describe the ASCII amd Unicode character encoding methods:
R46 I can convert characters to character codes
R46 I can convert character codes to characters.
R46 I can understand that character codes are commonly grouped and run in sequence within encoding tables.
R47 I can describe the purpose of Unicode and the advantages of Unicode over ASCII.
R47 I can describe how Unicode uses the same codes as ASCII up to 127.
3.3.6Representing images
R48 I can explain what a pixel is and how pixels relate to an image and the way images are displayed.
R48 I can describe for bitmaps the image size in pixels.
R48 I can describe for bitmaps the colour depth.
R49 I can describe how the size of a bitmap image is measured in pixels (width x height)
R49 I can describe how a bitmap represents an image using pixels and colour depth.
R49 I can explain how the number of pixels and colour depth can affect the file size of a bitmap image.
R49 I can calculate bitmap image file sizes based on the number of pixels and colour depth.
R49 Convert binary data into a bitmap image.
R49 I can convert a black and white image into binary data.
3.3.7Representing sound
R50 I can understand that sound is analogue and that it must be converted to a digital form for storage and processing in a computer.
R50 I can understand that analogue signals are sampled to create the digital version of sound.
R50 I can describe the digital representation of sound in terms of sampling rate.
R50 I can describe the digital representation of sound in terms of sample resolution.
R50 I can calculate sound file sizes based on the sampling rate and the sample resolution.
3.3.8Data compression
R51 I can explain what data compression is.
R51 I can understand why data may be compressed and that there are different ways to compress data.
R53 I can explain how data can be compressed using Huffman coding.
R53 I can interpret�Huffman trees.
R53 I can calculate the number of bits required to store a piece of data compressed using Huffman coding.
R53 I can calculate the number of bits required to store a piece of uncompressed data in ASCII.
R52 I can explain how data can be compressed using run length encoding (RLE).
R52 I can represent data in RLE frequency/data pairs.

### Assessment Scores

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