A theory that suggests people learn behaviors, skills, and attitudes through observing and imitating others, as well as through direct experiences. Crucial for understanding how users acquire new behaviors and designing educational or training programs.
An ongoing process of learning about user needs and validating assumptions through continuous research and experimentation. Crucial for staying responsive to user needs and improving products iteratively.
An ongoing process of learning and development that enables individuals and organizations to adapt to changing environments and requirements. Crucial for staying current with industry trends and improving skills and knowledge.
The belief that abilities and intelligence can be developed through dedication and hard work. Important for fostering a culture of continuous learning and improvement.
The process of self-examination and adaptation in AI systems, where models evaluate and improve their own outputs or behaviors based on feedback. Crucial for enhancing the performance and reliability of AI-driven design solutions by fostering continuous learning and improvement.
Zone of Proximal Development (ZPD) is a concept in educational psychology that describes the difference between what a learner can do independently and what they can achieve with guidance and support. Crucial for designing effective educational experiences and scaffolding that promote optimal learning and skill development.
An agile methodology that separates product discovery and product delivery into parallel tracks to ensure continuous learning and delivery. Essential for balancing innovation and execution in agile product development.
A meeting held at the end of a project or development cycle, also known as a "post-mortem," to review what went well, what didn't, and how processes can be improved in the future. Crucial for continuous improvement and learning from past experiences to enhance future projects.
A learning method that involves teaching a concept to a novice to identify gaps in understanding and reinforce knowledge. Important for enhancing comprehension and retention of complex subjects.
A broader, more informal community of interest that spans across the entire organization, focusing on shared topics such as agile practices or UX design. Valuable for cross-functional learning, knowledge sharing, and promoting a unified approach to common challenges.
An AI model that has been pre-trained on a large dataset and can be fine-tuned for specific tasks. Essential for developing state-of-the-art NLP applications.
The study of how people acquire knowledge, skills, and behaviors through experience, practice, and instruction. Useful for creating educational content and interactive tutorials that enhance user learning.
The integration and application of knowledge and skills from multiple disciplines to enhance understanding and innovation. Crucial for fostering a holistic approach to problem-solving and design.
A schedule of reinforcement where a desired behavior is reinforced every time it occurs, promoting quick learning and behavior maintenance. Important for designing systems that encourage consistent user behavior.
The theory that all behaviors are acquired through conditioning, often used to understand and influence behavior change. Important for designing interventions that promote positive behavior change.
A learning phenomenon where information is better retained when study sessions are spaced out over time rather than crammed in a short period. Crucial for designing educational tools and content that optimize long-term retention.
A cognitive architecture model that explains how humans can learn and adapt to new tasks. Useful for understanding user learning and behavior adaptation, informing better user experience design.
The phenomenon where taking a test on material improves long-term retention of that material more than additional study sessions. Crucial for designing educational tools and methods that enhance learning and retention.
A cognitive approach that involves meaningful analysis of information, leading to better understanding and retention. Crucial for designing educational and informational content that promotes deep engagement and learning.
A structured routine for continuous improvement based on a scientific approach to problem-solving and process optimization. Crucial for fostering a culture of continuous improvement and innovation within product design teams.
Build-Measure-Learn (BML) is a feedback loop used in Lean Startup methodology where a product is built, its performance is measured, and learnings are used to make improvements. Essential for iterating quickly and efficiently to create products that better meet user needs and market demands.
A phenomenon where learning is improved when study sessions are spaced out over time rather than crammed together. Crucial for designing educational and training programs that enhance long-term retention.
A phenomenon where people are more likely to remember information when they are in the same state of consciousness as when they learned it. Important for understanding how context affects memory recall and designing experiences that facilitate better retention.
ModelOps (Model Operations) is a set of practices for deploying, monitoring, and maintaining machine learning models in production environments. Crucial for ensuring the reliability, scalability, and performance of AI systems throughout their lifecycle, bridging the gap between model development and operational implementation.
The ability to use learned knowledge and experience, often increasing with age and accumulated learning. Important for understanding how expertise and knowledge accumulation impact design and decision-making.
A group of people who share a common interest or profession and engage in collective learning through regular interactions, sharing knowledge, and developing expertise together. Essential for fostering collaboration, continuous learning, and the dissemination of best practices within a specific field or discipline.
A tool used in education to help learners organize and structure new information before learning it in detail. Useful for designing educational content and onboarding materials that facilitate better learning and retention.
A machine learning-based search engine algorithm used by Google to help process search queries and provide more relevant results. Important for understanding modern SEO practices and how search engines interpret and rank web content.
A theory suggesting that information processed at a deeper, more meaningful level is better remembered than information processed at a shallow level. Crucial for designing educational and informational content that enhances retention and understanding.
A phenomenon where information is better remembered if it is generated from one's own mind rather than simply read. Useful for designing educational and interactive content that enhances memory retention.
Artificially generated data that mimics real data, used for training machine learning models. Crucial for training models when real data is scarce or sensitive.
The ability to perform actions or behaviors automatically due to learning, repetition, and practice. Important for understanding user habits and designing intuitive user interfaces.
A phenomenon where new information interferes with the ability to recall previously learned information, affecting memory retention. Crucial for understanding memory dynamics and designing educational or training programs.
Plan-Do-Check-Act (PDCA) is an iterative four-step management method used for continuous improvement of processes and products. Essential for quality control and operational efficiency.
A theory that suggests the depth of processing (shallow to deep) affects how well information is remembered. Important for designing educational content and user interfaces that enhance memory retention.
Adaptive Software Development (ASD) is a software development methodology that focuses on continuous adaptation to changing requirements and environments. Essential for managing changing requirements and ensuring agile project delivery.
A set of practices that combines software development (Dev) and IT operations (Ops) to shorten the development lifecycle and deliver high-quality software continuously. Crucial for improving the speed, efficiency, and quality of software development and deployment.
A type of artificial intelligence capable of generating new content, such as text, images, and music, by learning from existing data. Important for automating creative processes and generating novel outputs.
A memory aid that helps individuals recall information through associations, patterns, or acronyms. Important for designing educational content and interfaces that enhance memory retention.
A method of splitting a dataset into two subsets: one for training a model and another for testing its performance. Fundamental for developing and evaluating machine learning models in digital product design.
Total Quality Management (TQM) is a comprehensive management approach focused on continuous improvement in all aspects of an organization. Essential for ensuring high-quality products and services and achieving customer satisfaction.
The use of data, algorithms, and machine learning to recommend actions that can achieve desired outcomes. Essential for optimizing decision-making and implementing effective strategies.
A type of long-term memory involving information that can be consciously recalled, such as facts and events. Important for understanding how users retain and recall information in design.
Information provided by users about their experience with a product, used to inform improvements and adjustments. Crucial for continuous improvement and user-centered design.
A cognitive approach where information is processed at a surface level, focusing on basic features rather than deeper meaning, often leading to poorer memory retention. Important for designing educational and informational content that encourages deeper processing and understanding.
AI systems that can dynamically adjust their behavior based on new data or changes in the environment. Important for developing systems that can respond to real-time changes and improve over time.
In AI and machine learning, a prompt that specifies what should be avoided or excluded in the generated output, guiding the system to produce more accurate and relevant results. Crucial for refining AI-generated content by providing clear instructions on undesired elements, improving output quality and relevance.
A time-boxed period during which specific work must be completed and made ready for review, used in Agile project management. Crucial for managing workload and ensuring continuous delivery and improvement in Agile projects.
The process of training an AI model on a large dataset before fine-tuning it for a specific task. Crucial for building robust AI models that perform well on various tasks.
A time-boxed period in which Agile teams deliver incremental value in the form of working, tested software and systems. Essential for aligning teams, managing dependencies, and ensuring continuous delivery.
Case-Based Reasoning (CBR) is an AI method that solves new problems based on the solutions of similar past problems. This approach is essential for developing intelligent systems that learn from past experiences to improve problem-solving capabilities.
Generative Pre-trained Transformer (GPT) is a type of AI model that uses deep learning to generate human-like text based on given input. This technology is essential for automating content creation and enhancing interactive experiences.
The use of algorithms to generate new data samples that resemble a training dataset, often used in AI for creating realistic outputs. Important for developing creative and innovative solutions in digital product design, such as content generation and simulation.
A tree-like model of decisions and their possible consequences, used in data mining and machine learning for both classification and regression tasks. Valuable for creating interpretable models in digital product design and user behavior analysis.
The systematic process of capturing, evaluating, and implementing ideas to drive innovation, reflecting a collective commitment to continuous improvement and product excellence. Essential for harnessing team creativity and maintaining the entrepreneurial spirit that characterizes successful product development.
A set of algorithms, modeled loosely after the human brain, designed to recognize patterns and perform complex tasks. Essential for developing advanced AI applications in various fields.
A component in neural networks that allows the model to focus on specific parts of the input, improving performance. Essential for developing advanced AI models, particularly in natural language processing.
Agile Release Train (ART) is a long-lived team of Agile teams that, along with other stakeholders, incrementally develops, delivers, and operates one or more solutions in a value stream. Important for coordinating Agile development and delivery at scale.
Application Release Automation (ARA) is the process of automating the release of applications, ensuring consistency and reducing errors. Crucial for accelerating the delivery of software updates and maintaining high-quality digital products.
A practice of performing testing activities in the production environment to monitor and validate the behavior and performance of software in real-world conditions. Crucial for ensuring the stability, reliability, and user satisfaction of digital products in a live environment.