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Term in educational psychology
Concept learning, also known as category learning, concept attainment, and concept formation, is defined by Bruner, Goodnow, & Austin (1956) as "the search
Concept_learning
Fundamental unit of cognition
debate whether concepts are mental representations or abstract objects that exist independently of individual minds. Concept learning is the process of
Concept
Educational software application
programs, materials, or learning and development programs. The learning management system concept emerged directly from e-Learning. Learning management systems
Learning_management_system
Diagram showing relationships among concepts
Gowin, their approach to concept mapping is based on a "learning theory that focuses on concept and propositional learning as the basis on which individuals
Concept_map
Process of acquiring new knowledge
repeatedly processed. Rote learning is used in diverse areas, from mathematics to music to religion. Meaningful learning is the concept that learned knowledge
Learning
Theory and philosophy of learning
learner and the learning context. Experiences "stick out" in the mind and assist with information retention. The general concept of learning through experience
Experiential_learning
Overview of and topical guide to machine learning
learning theory AlphaGo AlphaGo Zero Alternating decision tree Apprenticeship learning Causal Markov condition Competitive learning Concept learning Decision
Outline_of_machine_learning
Change of statistical properties over time
In predictive analytics, data science, machine learning and related fields, concept drift or drift is an evolution of data that invalidates the data model
Concept_drift
Subset of artificial intelligence
machine learning approaches include learning classifier systems, association rule learning, and artificial immune systems. Based on the concept of strong
Machine_learning
Concept in psychology
points denote objects, and regions denote concepts. The theory of conceptual spaces is a theory about concept learning first proposed by Peter Gärdenfors. It
Conceptual_space
Book by Marvin Minsky and Seymour Papert
the XOR function is difficult for humans to acquire as well during concept learning experiments. When Papert arrived at MIT in 1963, Minsky and Papert
Perceptrons_(book)
Concept in education
to have been lost. Despite this, NTL's learning pyramid model became a central representation of this concept with a large number of models drawing from
Learning_pyramid
Version space learning is a logical approach to machine learning, specifically binary classification. Version space learning algorithms search a predefined
Version_space_learning
One's internal beliefs about oneself
in a big pond: Contrast and assimilation effects on academic self-concept". Learning and Individual Differences. 20 (5): 522–531. doi:10.1016/j.lindif
Self-concept
Model of algorithmic learning
of a concept c in concept class 𝒞 can be expressed by the length size(c) of the shortest bit string that can represent c in 𝒞. Occam learning connects
Occam_learning
Type of company
management, a learning organization is a company that facilitates the learning of its members and continuously transforms itself. The concept was coined
Learning_organization
Psychological categorization proposal
exemplar theory have led to a simplification of thought concerning concept learning, because they suggest that people use already-encountered memories
Exemplar_theory
Use of technology in education to enhance learning and teaching
concept or principle. For example, m-learning emphasizes mobility, which allows for altered timing, location, accessibility, and context of learning;
Educational_technology
Method of deriving an ontology
in the 1930s. Formal concept analysis finds practical application in fields including data mining, text mining, machine learning, knowledge management
Formal_concept_analysis
Support given to a student by an instructor
student-centered learning, which tends to facilitate more efficient learning than teacher-centered learning.[page needed] This learning process promotes
Instructional_scaffolding
Field of machine learning
Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised learning. While supervised learning and
Reinforcement_learning
Machine learning strategy
active learning, hybrid active learning and active learning in a single-pass (on-line) context, combining concepts from the field of machine learning (e.g
Active learning (machine learning)
Active_learning_(machine_learning)
Learning methodology
Meaningful learning refers to the act of higher order thinking and development through intellectual engagement that uses pattern recognition and concept association
Meaningful_learning
Pattern recognition puzzle
Anandkumar, Anima (2020). "Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning". Advances in Neural Information Processing Systems.
Bongard_problem
American psychologist
Bloomington, Indiana. His research interests include concept learning and representation, perceptual learning, collective behavior, and computational modeling
Robert_Goldstone
American psychologist
Study of Concepts". Notre Dame Philosophical Reviews. Retrieved 15 December 2022. Beck, Jacob (2017). "Can bootstrapping explain concept learning?" (PDF)
Susan_Carey
Approach to training in machine learning
In machine learning, one-class classification (OCC), also known as unary classification or class-modelling, is an approach to the training of binary classifiers
One-class_classification
Educational learning method using computer algorithms and AI
Adaptive learning, also known as adaptive teaching, is an educational method which uses computer algorithms as well as artificial intelligence to orchestrate
Adaptive_learning
or the characteristics of the data change over time. Online learning Data streams Concept drift Data which can be modeled well using a hierarchical model
Incremental_decision_tree
Theory of knowledge
constructivist learning has significantly influenced learning theories and teaching methods in education. It serves as a foundational concept in education
Constructivism (philosophy of education)
Constructivism_(philosophy_of_education)
Branch of machine learning
interpretation derives from the field of machine learning. It features inference, as well as the optimization concepts of training and testing, related to fitting
Deep_learning
Theories that aim to account for differences in individuals' learning
categorized and assessed. A common concept is that individuals differ in how they learn. The idea of individualized learning styles became popular in the 1970s
Learning_styles
Ongoing, voluntary, and self-motivated pursuit of knowledge
Lifelong Learning, which caters to the needs of the disadvantaged and marginalized learners. Lifelong learning is distinguished from the concept of continuing
Lifelong_learning
Learner centric pedagogy
Phenomenon-based learning is a constructivist form of learning or pedagogy, where students study a topic or concept in a holistic approach instead of in
Phenomenon-based_learning
Framework for mathematical analysis of machine learning
framework is the introduction of computational complexity theory concepts to machine learning. In particular, the learner is expected to find efficient functions
Probably approximately correct learning
Probably_approximately_correct_learning
Type of supervised learning in machine learning
In machine learning, multiple-instance learning (MIL) is a type of supervised learning. Instead of receiving a set of instances which are individually
Multiple_instance_learning
How people learn from experience
A learning cycle is a concept of how people learn from experience. A learning cycle will have a number of stages or phases, the last of which can be followed
Learning_cycle
Acquisition of knowledge, skills, and competencies as a result of teaching or practice
and social psychology concept Learning – Process of acquiring new knowledge Microtraining – Support method for informal learning processes in organisations
Training
Educational technique
Active learning is "a method of learning in which students are actively or experientially involved in the learning process and where there are different
Active_learning
Learner centric pedagogy
design concepts are developed Problem-based learning – Learner-centric pedagogy Project-based learning – Learner centric pedagogy Organizational learning STEM
Design-based_learning
Interactive learning is a pedagogical approach that incorporates social networking and urban computing into course design. In interactive learning, people
Interactive_Learning
Norwegian online educational quiz game
Kahoot! is a Norwegian online game-based learning platform. It has learning games, also known as "kahoots", which are user-generated multiple-choice quizzes
Kahoot!
Subfield of machine learning
Meta-learning is a subfield of machine learning where automatic learning algorithms are applied to metadata about machine learning experiments. As of
Meta-learning (computer science)
Meta-learning_(computer_science)
Professor Emeritus of computer science and engineering (born 1965)
engineering at the University of Washington. He is a researcher in machine learning known for Markov logic network enabling uncertain inference. Domingos received
Pedro_Domingos
(2010). "Concept learning in nonprimate mammals: In search of evidence". In Mareschal D, Quinn PC, Lea SE (eds.). The Making of Human Concepts. Oxford
Animal_cognition
machine learning (ML) research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning. Major
List of datasets for machine-learning research
List_of_datasets_for_machine-learning_research
Interdisciplinary research area
Quantum machine learning (QML) is the study of quantum algorithms for machine learning. It often refers to quantum algorithms for machine learning tasks which
Quantum_machine_learning
Concept in machine learning
In statistics and machine learning, leakage (also known as data leakage or target leakage) refers to the use of information during model training that
Leakage_(machine_learning)
Machine learning paradigm
including self-improvement through autonomous learning. Founded in representation learning, LeCun included the concept of a “world model” in JEPA which aims to
Self-supervised_learning
Decentralized machine learning
Federated learning (also known as collaborative learning) is a machine learning technique in a setting where multiple entities (often called clients)
Federated_learning
Branch of analytics
certain courses of action. Another approach for defining Learning Analytics is based on the concept of Analytics interpreted as the process of developing
Learning_analytics
Learning logic programs from data
both given the background knowledge B. In Muggleton's setting of concept learning, "completeness" is referred to as "sufficiency", and "consistency"
Inductive_logic_programming
Educational psychology concept
to new concepts. Some methods for bridging include brainstorming, developing analogies, and metacognition. In machine learning, transfer learning is an
Transfer_of_learning
Intelligence in machines
to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is also
Artificial_intelligence
Learning theory predicated on making connections across curricula
This higher education concept is distinct from the elementary and high school "integrated curriculum" movement. Integrative Learning comes in many varieties:
Integrative_learning
Italian computer scientist
scientist whose research topics in artificial intelligence include concept learning and abstraction. She is a professor emeritus of computer science at
Lorenza_Saitta
Diagram to visually organize information
Romance, Nancy R.; Vitale, Michael R. (Spring 1999). "Concept mapping as a tool for learning: broadening the framework for student-centered instruction"
Mind_map
Memorization technique based on repetition
alternatives to rote learning include meaningful learning, associative learning, spaced repetition and active learning. Rote learning is widely used in the
Rote_learning
6th President of Latvia
1965 with a dissertation supervised by Dr. Virginia Douglas, entitled Concept Learning in Normal and Hyperactive Children. From 1965 to 1998, Vīķe-Freiberga
Vaira_Vīķe-Freiberga
Machine learning paradigm
clustering is closely related to formal concept analysis, decision tree learning, and mixture model learning. Conceptual clustering is obviously closely
Conceptual_clustering
Machine learning technique
on transfer learning in neural networks, 1976". Informatica 44: 291–302. S. Bozinovski (1981). "Teaching space: A representation concept for adaptive
Transfer_learning
Ancient Greek word for being in love
other males. The ancient Greek philosopher Plato developed an idealistic concept of eros which would prove to be very influential in modern times. In general
Eros_(concept)
Attempt to convey information to a sleeping person
has concluded that sleep-learning is not possible. Once a concept explored in the early history of psychology, sleep-learning appears frequently in fiction
Sleep-learning
Paradigm in machine learning
Weak supervision (also known as semi-supervised learning) is a paradigm in machine learning, the relevance and notability of which increased with the
Weak_supervision
Assumptions for inference in machine learning
machine learning", Machine Learning, 20 (1–2): 5–22, doi:10.1007/BF00993472 Utgoff, P. E. (1984), Shift of bias for inductive concept learning, New Brunswick
Inductive_bias
Range of neurodevelopmental conditions
the following definition: Concept of LD: Strong converging evidence supports the validity of the concept of specific learning disabilities (SLD). This
Learning_disability
Concept on humans' and animals' use of past learning in present situations
Generalization is the concept that humans, other animals, and artificial neural networks use past learning in present situations of learning if the conditions
Generalization_(learning)
Professor of computer science
Dana Angluin (1988). Queries and concept learning. Machine Learning. 2 (4): 319–342. Dana Angluin (1987). "Learning Regular Sets from Queries and Counter-Examples"
Dana_Angluin
computational learning theory, sample exclusion dimensions arise in the study of exact concept learning with queries. In algorithmic learning theory, a concept over
Sample_exclusion_dimension
Concept in educational psychology
thereby encouraging and advancing their individual learning skills and strategies. The concept of the zone of proximal development was originally developed
Zone_of_proximal_development
Learning by physical activities
Kinesthetic learning (American English), kinaesthetic learning (British English), or tactile learning is learning that involves physical activity. As
Kinesthetic_learning
Mental representation of the external world
major role in cognition, reasoning and decision-making. The term for this concept was coined in 1943 by Kenneth Craik, who suggested that the mind constructs
Mental_model
Computational model used in machine learning
In machine learning, a neural network (NN) or artificial neural network (ANN) is a computational model inspired by the structure and functions of biological
Neural network (machine learning)
Neural_network_(machine_learning)
Computational learning theory
computational learning theory in mathematics, a concept over a domain X is a total Boolean function over X. A concept class is a class of concepts. Concept classes
Concept_class
American cognitive scientist
learn and generalize new concepts, models, theories and tasks from very few examples, a concept known as "one-shot learning." "Eulogy". December 8, 2020
Joshua_Tenenbaum
Study of psychological theories of learning
the 1950s, psychological learning theory varied across countries. In Germany, gestalt psychology viewed psychological concepts holistically, such as the
Psychology_of_learning
Problem setup in machine learning
their class. The name is a play on words based on the earlier concept of one-shot learning in computer vision, in which classification can be learned from
Zero-shot_learning
Learning through egalitarian dialogue
arguments based on validity claims and not on power claims. The concept of dialogic learning is not a new one. Within the Western tradition, it is frequently
Dialogic_learning
Educational concept
Out-of-school learning is an educational concept first proposed by Lauren Resnick in her 1987 AERA presidential address, which consists of curricular and
Out-of-school_learning
Representation learning technique
In machine learning, embedding is a representation learning technique that maps complex, high-dimensional data into a lower-dimensional vector space of
Embedding_(machine_learning)
Approach to neurological rehabilitation
children with cerebral palsy). The goal of applying the Bobath concept is to promote motor learning for efficient motor control in various environments, thereby
Bobath_concept
Learning through practice, self-perfection and minor innovations
Learning-by-doing is a concept in economic theory by which productivity is achieved through practice, self-perfection and minor innovations. An example
Learning-by-doing_(economics)
Text editor providing intelligent, computer-generated suggestions
by the user, during a process known as selection guessing, based on concept learning. This ability occurs via, and is an instance of, programming by example
Lapis_(text_editor)
Community
The concept was first proposed by cognitive anthropologist Jean Lave and educational theorist Etienne Wenger in their 1991 book Situated Learning. Wenger
Community_of_practice
American computer scientist and professor (born 1948)
toward furthering the concept and using it as the basis for artificial intelligence. This concept became known as reinforcement learning and went on to becoming
Andrew_Barto
Analysis of continuous, rapid data
stream. Machine learning techniques can be used to learn this prediction task from labeled examples in an automated fashion. Often, concepts from the field
Data_stream_mining
Model for music education
musical differences. The theory takes into account the concepts of discrimination and inference learning in terms of tonal, rhythmic, and harmonic patterns
Gordon_music_learning_theory
Automatic creation of ontologies
ontology learning system. During the domain terminology extraction step, domain-specific terms are extracted, which are used in the following step (concept discovery)
Ontology_learning
Machine learning algorithm
Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or
Decision_tree_learning
Process of learning better perception skills
Perceptual learning is the learning of perception skills, such as differentiating two musical tones from one another or categorizations of spatial and
Perceptual_learning
Method in education
assessment for learning, including diagnostic testing, is a range of formal and informal assessment procedures conducted by teachers during the learning process
Formative_assessment
Concept describing the stages of learning
Shuhari (Japanese: 守破離) is a Japanese concept that describes the stages of learning to mastery. Shuhari is usually translated as "follow the rules, break
Shuhari
Type of learning style
Harold Pashler; Mark McDaniel; Doug Rohrer; Robert Bjork (2009). "Learning Styles: Concepts and Evidence". Psychological Science in the Public Interest. 9
Auditory_learning
Learning that occurs through observing the behaviour of others
Observational learning is learning that occurs through observing the behavior of others. It is a form of social learning which takes various forms, based
Observational_learning
Principle in teaching
alignment is the underpinning concept behind the current requirements for programme specification, declarations of learning outcomes (LOs) and assessment
Constructive_alignment
People feel better about themselves when they are more obviously superior
changes in academic self concept development: On the long-term persistence of big-fish-little-pond effects" (PDF). Learning and Instruction. 45: 31–39
Big-fish–little-pond_effect
Topics referred to by the same term
computational learning theory, a subset of the instance space; see Concept class Concepts (C++), an extension to C++'s template system Concept virus (disambiguation)
Concept_(disambiguation)
Technique in machine learning
with the simplest concepts and then building on them. The authors also note that the application of this technique in machine learning has its roots in
Curriculum_learning
Method of teaching in which students teach the subject to each other
Jean-Pol Martin systematically developed the concept of having students teach other in the context of learning French as a foreign language. He gave it a
Learning_by_teaching
Concept that some difficulty can assist learning
Bjork in 1994. The UCLA psychologist introduced the concept as an experience that makes learning more difficult, allowing students to form stronger connections
Desirable_difficulty
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