Data types — AQA GCSE Computer Science

Data types form the foundation of data representation and algorithmic problem solving in AQA GCSE Computer Science. Every variable, constant, and data structure must hold an explicit or inferred type, which dictates how bits are stored in RAM and what operations are valid.

Understanding data types ensures programs run efficiently, prevent runtime type errors, and maintain data integrity. It links theoretical concepts of binary representation directly to practical programming and software design.

• →Integer: Whole numbers (positive, negative, or zero) without fractional components, used for counting and arithmetic.
• →Real / Float: Numbers containing fractional or decimal components, stored using floating-point representation.
• →Boolean: A logical data type that can take only one of two values: True or False.
• →Character and String: A character is a single alphanumeric or control symbol; a string is a sequence of zero or more characters.
• →Type Casting: The explicit conversion of data from one type to another (e.g. converting a string representation of digits into an integer).

• Identifies each listed data type and the kind of value it stores, such as integer for whole numbers and Boolean for true/false.
• Selects an appropriate data type for a given value or scenario rather than an unsuitable one.
• Explains why a chosen type is appropriate, referring to the nature of the value and valid operations.
• Recognises that using an inappropriate type can cause errors or incorrect results.

• 💡Identify what the value represents before selecting a type.
• 💡Reject options that cannot store the value correctly, such as a Boolean for a price.
• 💡If asked why, link the type to the value's nature and the operations needed.
• 💡Use AQA-approved terminology: refer to numbers with decimal points as 'Real' or 'Float' rather than 'decimal' or 'fraction'.
• 💡When explaining why a field is a string, always mention two features: preventing loss of leading zeros and not requiring mathematical operations.
• 💡Check trace tables carefully when casting occurs; ensure you update variable values to match their new data type (e.g. writing '5.0' for Real instead of '5').

• Choosing a string for a value that will be used in arithmetic; correction: select a numeric type so calculations are valid.
• Treating a character and a string as interchangeable; correction: a character holds a single symbol while a string holds text of any length.
• Ignoring the purpose of the value and picking any type; correction: match the type to how the value will be stored and used.
• Believing any variable containing digits must be an integer: non-arithmetic identifiers like phone numbers, bar codes, and national insurance numbers must be strings to retain formatting and leading zeros.
• Assuming integer division returns a real number: in many languages and pseudo-code constructs, dividing integers truncates or requires explicit conversion (DIV vs /).
• Confusing single-quote characters with strings: AQA expects students to know a character is exactly one byte/symbol, whereas strings are composite collections of characters.

1. 1Day 1-2: Memorise the 5 primitive data types and their definitions, noting differences between Character and String.
2. 2Day 3-4: Practice identifying data types for real-world scenarios (e.g. flight booking systems, supermarket checkouts).
3. 3Day 5-6: Master explicit type casting functions across Python and AQA pseudo-code (e.g. INT, REAL, STRING, CHAR).
4. 4Day 7: Complete past paper questions focusing on 1-mark and 2-mark data type identification and justification.

• 📋Table Completion: Given a list of variables and example values, state the most appropriate data type for each.
• 📋Justification Questions: Explain why a specific data type must be chosen over another (e.g. String vs Integer).
• 📋Code and Trace Table Analysis: Identify errors where incompatible data types are combined without casting.