A field of computer science focused on creating systems that can perform tasks typically requiring human intelligence, such as learning and problem-solving.

A subset of AI that enables systems to learn from data and improve their performance over time without being explicitly programmed.

An educational approach that tailors learning experiences to individual student needs, preferences, and interests.

The protection of personal data and information from unauthorized access and misuse, especially in educational technologies.

A design principle that allows a system to handle increasing amounts of work or user traffic without compromising performance.

The practice of ensuring that AI systems are designed and implemented in a manner that is fair, transparent, and respects user rights.

An approach that prioritizes the needs, preferences, and behaviors of end users in the design process.

The ability of an AI system to adapt and improve its performance based on new data and user interactions over time.

A phenomenon where an algorithm produces unfair or prejudiced outcomes due to biased training data or design.

A process in which the output of a system is used as input for future iterations, enhancing learning and adaptation.

A technique used to evaluate a system's performance under expected conditions, ensuring it can handle user demand.

The process of creating a preliminary model of a product to test concepts and gather user feedback.

A method of comparing two versions of a product to determine which performs better based on user interactions.

The steps taken to clean and organize raw data before it is used for training machine learning models.

Fictional characters created based on user research to represent different user types and their needs.

Techniques used to create visual representations of a user interface, allowing for exploration of design ideas.

The process of defining the structure, components, and relationships of a software system.

A method of evaluating a product by testing it with real users to identify any usability issues.

The practice of improving the efficiency and speed of a system to enhance user experience.

A set of principles designed to guide the ethical development and use of AI technologies.

The process of involving all parties affected by a project in its planning and implementation.

A phase in software testing where individual components are combined and tested as a group.

Comprehensive guides and manuals that outline how to deploy and use a software system effectively.

Mathematical representations of real-world processes used to make predictions based on input data.

Collections of related data used for training and testing machine learning algorithms.