VCAA GLOSSARY

The definitions of terms in the glossary are examinable IF they also appear in the relevant Key Knowledge (KK) dotpoint after the word "including".

Terms like 'stacks' that appear in the glossary but do not appear in a KK are only examples, and are not examinable.

(I have this information personally from the Curriculum Manager, Digital Technologies at VCAA in 2023.)

You are unlikely to be asked to define a term in an exam (but it is possible). More likely, these terms will be used in questions and you will be expected to interpret and respond to them correctly.

If your personal definition of a term does not agree with VCAA's, suck it down and don't argue. You won't win. Use VCAA's definition.

For years I waged a campaign to have 'ease of use' removed from the definition of 'efficiency'. Eventually, I won, but in the meantime I had to suck it down and answer questions using VCAA's wonky definition.

Any emphases below are mine.

TERM

VCAA DEFINITION

The process of recognising aspects of computation in the world and being able to think logically, algorithmically, recursively and inferentially.

It typically involves inferential thinking, defining problems through decomposition, documenting steps and decisions through algorithms, the use of programming languages and software, and evaluating the resulting solutions.

General or formal agreements to ensure consistency and clarity when working with digital systems. Program names and file names are examples of conventions to be used during software development.

Conventions can be mandatory, such as when passwords must have specific characters, and recommended, such as including a subject line in emails.

The way data is stored to enable efficient algorithms to be used to optimise program execution time and memory usage.

Types of data structures include:

• arrays,
• associative arrays,
• classes,
• fields,
• files,
• hash tables,
• linked lists,
• queues,
• records
• stacks.

The forms that an item of data can take, including

• binary (as represented in images and sound),
• Boolean,
• character and
• numeric

characterised by the kind of operations that can be performed on it. Depending on the software being used, these data types can be divided into more specific data types, for example integer and floating point, which are numeric types. More sophisticated types can be derived from them, for example a string of characters or a data type, and their names may vary, such as text data type versus string data type.

Design principles are accepted characteristics that contribute to the functionality, usability and appearance of solutions. In this study the principles related to usability include

• ease of use,
• flexibility and robustness, and
• accessibility, including navigation and error tolerance.

Design principles related to appearance are

• alignment,
• balance,
• contrast,
• image use,
• space, and
• text and table formatting.

A measure of how well a solution, information management strategy or a network functions and whether each achieves its intended results. Measures of effectiveness in a solution include

• accessibility,
• accuracy,
• attractiveness,
• clarity,
• communication of message,
• completeness,
• readability,
• relevance,
• timeliness, and
• usability.

Measures of effectiveness of an information management strategy include

• currency of files,
• ease of retrieval,
• integrity of data and
• security.

Measures of effective networks include

• maintainability,
• reliability and
• the security of data during storage and transmission.

A measure of how much

• time,
• cost and
• effort

is applied to achieve intended results.

Measures of efficiency in a solution could include the cost of file manipulation, its functionality and the speed of processing.

Measures of efficiency in a network include its productivity, processing time, operational costs and level of automation.

The physical appearance in which data and information can be presented. These include

• images,
• graphs,
• tables,
• text and
• web pages.

Formats specify characteristics such as presentation style or arrangement, shape and size.

Graphical representations of complex data or information. They rely upon visual elements to quickly and clearly communicate patterns or trends in data or information. These include

• complementary colour schemes,
• easy-to-read fonts,
• graphs,
• simple charts and
• statistics.

The combination of

• digital hardware,
• software and network components (digital systems),
• data,
• processes and
• people

that interact to create, control and communicate ideas and data in digital solutions.

Individuals and organisations are expected to comply with legal requirements, with respect to the ownership and privacy of information, and freedom of expression. For the purposes of this study, the key provisions of the following acts are relevant:

• Charter of Human Rights and Responsibilities Act 2006 (Vic) (sections 13, 14 and 15),
• Copyright Act 1968,
• Health Records Act 2001,
• Privacy Act 1988, including
  • Privacy Amendment (Enhancing Privacy Protection) Act 2012
  • Privacy Amendment (Notifiable Data Breaches) Act 2017,
• Privacy and Data Protection Act 2014
• Spam Act 2003 (Part 1.3, Simplified outline).

File management includes the naming, storing and handling of files.

Strategies to manage files should have a consistent and descriptive naming convention and a clear directory structure.

Files should be easily identified and accessed.

File management also includes procedures for backing up, archiving and deleting files.

A set of guidelines for providing consistency in the naming of entities in software development and data management. These include

• program names,
• function names,
• variable names,
• table names,
• file names, and
• document names.

Naming conventions can minimise the effort needed to read and understand source code.

The equipment and procedures used to assist in the protection of information systems and the files created, communicated and stored by individuals and organisations. Equipment controls include

• zoned security strategies,
• barrier techniques and
• biometrics.

Physical procedures include

• backing up,
• shredding confidential documents and
• checking authorisation credentials.

Also see Software security controls.

The distinctive or characteristic parts of a programming language. These include

• classes,
• control structures,
• functions,
• instructions and
• methods.

The practice of applying techniques, processes, tools, knowledge and skills to deliver a solution.

Features of project management include

• identification of tasks,
• sequencing,
• time allocation,
• dependencies,
• milestones and
• critical path.

A series of English-like statements used to represent an algorithm that will solve a problem. Though there is no standard to pseudocode, there are a number of conventions. These include the use of

• START/BEGIN and FINISH/END to indicate the beginning and end of a program,
• IF…ELSE and SELECT to represent decisions, and
• REPEAT…UNTIL/WHILE…DO for loops.

The actions, devices and events that threaten the integrity and security of data and information stored within, and communicated between, information systems.

The threats can be

• accidental, such as losing a portable storage device containing files;
• deliberate, such as malware, phishing; and
• events-based such as a power surge.

The intended purpose and environment of a software solution. It documents the key activities associated with the analysis stage of the problem-solving methodology. Features of an SRS should include

• a description of the functional and non-functional requirements,
• system and technical requirements,
• constraints,
• scope and
• assumptions.

The software and procedures used to assist in the protection of information systems and the files created, communicated and stored by individuals and organisations. These include

• usernames and passwords,
• access logs and audit trails,
• access restrictions,
• encryption,
• firewalls and system protection, and
• security protocols such as Transport Layer Security (TLS).

The method of creating required digital output through the application of digital systems and processes that transforms data into information.

The output of a solution may take the form of an information product, such as a website, instructions to control a game, an abstract piece of art or a soundscape.

Solutions can be interactive or non-interactive, online (internet connected) or not, multimodal or not.

Techniques to ensure that a solution is operating as intended.

Test data should include data types and values that rigorously test software functions.

Testing tables can be used to record the outcomes of tests.

Types of data are general categories of data, including

• image (still and moving),
• number and
• text.

A visual modelling language that describes the interfaces between solutions, users and networks.

An example of this is a use case diagram (UCD) that models the requirements of an information system.

The checking of data for its reasonableness and completeness.

Validation of data includes:

• existence or presence checking, which verifies that a required field has a value entered and is not empty or blank;
• range checking, which involves ensuring that data entered falls within a certain range; and
• type checking, which confirms that data entered is of a particular type.

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This page was created on 2022-01-20
Last modified on Thursday 2 November, 2023 11:29