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CONTEXT BASED-LEARNING

  • Context-based learning
  • Teaching method

    Context-based learning (CBL) refers to the use of real-life and fictitious examples in teaching environments in order to learn through the actual, practical

    Context-based learning

    Context-based_learning

  • Prompt engineering
  • Structuring text as input to generative artificial intelligence

    changes, in-context learning is temporary. Training models to perform in-context learning can be viewed as a form of meta-learning, or "learning to learn"

    Prompt engineering

    Prompt_engineering

  • Project-based learning
  • Learner centric pedagogy

    Project-based learning is a teaching method that involves a dynamic classroom approach in which it is believed that students acquire a deeper knowledge

    Project-based learning

    Project-based learning

    Project-based_learning

  • Task-based language teaching
  • Pedagogical approach

    paradigm. In "strong" task-based learning lessons, learners are responsible for selecting the appropriate language for any given context themselves. The instructors

    Task-based language teaching

    Task-based_language_teaching

  • Experiential learning
  • Theory and philosophy of learning

    education) – Theory of knowledge Context-based learning Contextual learning Cooperative education – Type of education Design-based learning – Learner centric pedagogy

    Experiential learning

    Experiential learning

    Experiential_learning

  • Inquiry-based learning
  • Form of active learning

    Inquiry-based learning (also spelled as enquiry-based learning in British English) is a form of active learning that starts by posing questions, problems

    Inquiry-based learning

    Inquiry-based_learning

  • Phenomenon-based learning
  • Learner centric pedagogy

    instead of in a subject-based approach. Phenomenon-based learning includes both topical learning (also known as topic-based learning or instruction), where

    Phenomenon-based learning

    Phenomenon-based_learning

  • Narrative-based learning
  • Narrative-based learning is a learning model grounded in the theory that humans define their experiences within the context of narratives – which serve

    Narrative-based learning

    Narrative-based_learning

  • Problem-based learning
  • Learner-centric pedagogy

    Problem-based learning (PBL) is a teaching method in which students aim to learn about a subject through the experience of solving an open-ended problem

    Problem-based learning

    Problem-based learning

    Problem-based_learning

  • Contextual learning
  • Learning outside the classroom

    Contextual learning is based on a constructivist theory of teaching and learning. Learning takes place when teachers are able to present information in

    Contextual learning

    Contextual_learning

  • Educational technology
  • Use of technology in education to enhance learning and teaching

    encompasses several domains, including learning theory, computer-based training, online learning, and mobile learning (m-learning). The Association for Educational

    Educational technology

    Educational technology

    Educational_technology

  • Educational game
  • Game genre

    problem solving. Game-based learning (GBL) is a type of game play that has defined learning outcomes. Generally, game-based learning is designed to balance

    Educational game

    Educational_game

  • Learning
  • Process of acquiring new knowledge

    of the context of the facts learned. Evidence-based learning is the use of evidence from well designed scientific studies to accelerate learning. Evidence-based

    Learning

    Learning

    Learning

  • Transformer (deep learning)
  • Algorithm for modelling sequential data

    In deep learning, the transformer is a family of artificial neural network architectures based on the multi-head attention mechanism, in which text is

    Transformer (deep learning)

    Transformer (deep learning)

    Transformer_(deep_learning)

  • Work-based learning
  • Educational strategy

    policies to secure learning that meets the need of the workplace. Work-based learning (WBL) is defined differently across contexts: System / policy strand:

    Work-based learning

    Work-based_learning

  • Model Context Protocol
  • Protocol for communicating between LLMs and applications

    The Model Context Protocol (MCP) is an open standard and open-source framework introduced by Anthropic in November 2024 to standardize the way artificial

    Model Context Protocol

    Model Context Protocol

    Model_Context_Protocol

  • Design-based learning
  • Learner centric pedagogy

    Design-based learning (DBL), also known as design-based instruction, is an inquiry-based form of learning, or pedagogy, that is based on integration of

    Design-based learning

    Design-based_learning

  • Diffusion model
  • Technique for the generative modeling of a continuous probability distribution

    In machine learning, diffusion models, also known as diffusion-based generative models or score-based generative models, are a class of latent variable

    Diffusion model

    Diffusion_model

  • Place-based education
  • Educational philosophy

    Place-based education, sometimes called pedagogy of place, place-based learning, experiential education, community-based education, environmental education

    Place-based education

    Place-based_education

  • Attention (machine learning)
  • Machine learning technique

    In machine learning, attention is a method that determines the importance of each component in a sequence relative to the other components in that sequence

    Attention (machine learning)

    Attention (machine learning)

    Attention_(machine_learning)

  • Machine learning
  • Subset of artificial intelligence

    performing either supervised learning, reinforcement learning, or unsupervised learning. They seek to identify a set of context-dependent rules that collectively

    Machine learning

    Machine_learning

  • Learning to rank
  • Use of machine learning to rank items

    Learning to rank (LTR) or machine-learned ranking (MLR) is the application of machine learning, often supervised, semi-supervised or reinforcement learning

    Learning to rank

    Learning_to_rank

  • Competency-based learning
  • Framework for teaching and assessment of learning

    type of education based on predetermined "competencies," which focuses on outcomes and real-world performance. Competency-based learning is sometimes presented

    Competency-based learning

    Competency-based_learning

  • Active learning (machine 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)

  • Transfer of learning
  • Educational psychology concept

    Transfer of learning occurs when people apply information, strategies, and skills they have learned to a new situation or context. Transfer is not a discrete

    Transfer of learning

    Transfer_of_learning

  • Situated learning
  • Theory of learning

    provide the proper context and facilitate learning. Situated learning was first proposed by Jean Lave and Etienne Wenger as a model of learning in a community

    Situated learning

    Situated_learning

  • High-context and low-context cultures
  • Social context in understanding culture

    high-context and low-context cultures are ends of a continuum of how explicit the messages exchanged in a culture are and how important the context is in

    High-context and low-context cultures

    High-context_and_low-context_cultures

  • Spaced repetition
  • Learning technique performed with flashcards

    increase the rate of learning. Although the principle is useful in many contexts, spaced repetition is commonly applied in contexts in which a learner must

    Spaced repetition

    Spaced repetition

    Spaced_repetition

  • Self-supervised learning
  • Machine learning paradigm

    than relying on externally-provided labels. In the context of neural networks, self-supervised learning aims to leverage inherent structures or relationships

    Self-supervised learning

    Self-supervised_learning

  • Rote learning
  • Memorization technique based on repetition

    Rote learning is a memorization technique based on repetition. The method rests on the premise that the recall of repeated material becomes faster the

    Rote learning

    Rote learning

    Rote_learning

  • Outline of machine learning
  • Overview of and topical guide to machine learning

    handling (GMDH) Inductive logic programming Instance-based learning Lazy learning Learning Automata Learning Vector Quantization Logistic Model Tree Minimum

    Outline of machine learning

    Outline_of_machine_learning

  • Motivation in second-language learning
  • the sites where L2 learning occurs: the formal site (i.e. the educational context), and the informal site (i.e. the cultural context). Gardner argued that

    Motivation in second-language learning

    Motivation_in_second-language_learning

  • Conditional random field
  • Class of statistical modeling methods

    statistical modeling methods often applied in pattern recognition and machine learning and used for structured prediction. Whereas a classifier predicts a label

    Conditional random field

    Conditional_random_field

  • Neural network (machine learning)
  • Computational model used in machine learning

    than relying on externally-provided labels. In the context of neural networks, self-supervised learning aims to leverage inherent structures or relationships

    Neural network (machine learning)

    Neural network (machine learning)

    Neural_network_(machine_learning)

  • Cognitive science of religion
  • Study of religious thought and behavior

    categories: the context-based model and content-based view of minimal counterintuitiveness. The context-based view emphasizes the role played by context in making

    Cognitive science of religion

    Cognitive_science_of_religion

  • Reinforcement learning
  • 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

    Reinforcement learning

    Reinforcement_learning

  • Reinforcement learning from human feedback
  • Machine learning technique

    In machine learning, reinforcement learning from human feedback (RLHF) is a technique to align an intelligent agent with human preferences. It involves

    Reinforcement learning from human feedback

    Reinforcement learning from human feedback

    Reinforcement_learning_from_human_feedback

  • Blended learning
  • Education practice

    professional development and training settings. Since blended learning is highly context-dependent, a universal conception of it is difficult. Some reports

    Blended learning

    Blended_learning

  • Fine-tuning (deep learning)
  • Machine learning technique

    Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning (PDF). Advances in Neural Information Processing Systems. Vol. 35.

    Fine-tuning (deep learning)

    Fine-tuning_(deep_learning)

  • Peer learning
  • Educational practice of interaction among students

    Boud describe peer learning as a way of moving beyond independent to interdependent or mutual learning among peers. In this context, it can be compared

    Peer learning

    Peer_learning

  • Mamba (deep learning architecture)
  • Deep learning architecture

    integrate the entire sequence context and apply the most relevant expert for each token. Language modeling Transformer (machine learning model) State-space model

    Mamba (deep learning architecture)

    Mamba_(deep_learning_architecture)

  • Deep learning
  • Branch of machine learning

    extended deep learning from TIMIT to large vocabulary speech recognition, by adopting large output layers of the DNN based on context-dependent HMM states

    Deep learning

    Deep learning

    Deep_learning

  • Desirable difficulty
  • Concept that some difficulty can assist learning

    is also described as a learning level achieved through a sequence of learning tasks and feedback that lead to enhanced learning and transfer. As the name

    Desirable difficulty

    Desirable_difficulty

  • Thematic learning
  • Highlighting a theme for teaching purposes

    place-based education, project-based education, and cooperative learning. When thematic instruction takes place along with cooperative learning, the advantages

    Thematic learning

    Thematic learning

    Thematic_learning

  • Learning through play
  • Concept in education and psychology

    Contemporary theories emphasize the role of social and cultural contexts in children's learning and development. Rousseau's work on children's rights and the

    Learning through play

    Learning_through_play

  • Context model
  • Software engineering concept

    contextually appropriate responses. In deep learning-based language models like GPT-4 or BERT, the context model is an inherent part of the architecture

    Context model

    Context_model

  • GPT-3
  • 2020 text-generating language model

    occupies 2 bytes. It has a context window size of 2,048 tokens, and has demonstrated strong "zero-shot" and "few-shot" learning abilities on many tasks.

    GPT-3

    GPT-3

  • Large language model
  • Type of machine learning model

    can typically generate, summarize, translate, and analyze text in many contexts, and are a foundational technology behind modern chatbots. Biased or inaccurate

    Large language model

    Large_language_model

  • Classical conditioning
  • Aspect of learning procedure

    classical conditioning from other forms of associative learning (e.g., instrumental learning and human associative memory); a number of observations

    Classical conditioning

    Classical conditioning

    Classical_conditioning

  • Dreyfus model of skill acquisition
  • Model of learning

    summary is based upon Rousse and Dreyfus, "Revisiting the Six Stages of Skill Acquisition." Stage 1: Novice Novices rely heavily on context-free rules

    Dreyfus model of skill acquisition

    Dreyfus_model_of_skill_acquisition

  • Learning management system
  • 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

    Learning_management_system

  • Pedagogy
  • Theory and practice of education

    skills are imparted in an educational context, and it considers the interactions that take place during learning. Both the theory and practice of pedagogy

    Pedagogy

    Pedagogy

    Pedagogy

  • Computational linguistics
  • Use of computational tools for the study of linguistics

    a limitation for the models at the time because the now available deep learning models were not available in late 1980s. It has been shown that languages

    Computational linguistics

    Computational_linguistics

  • Generative pre-trained transformer
  • Type of large language model

    used in generative artificial intelligence chatbots. GPTs are based on a deep learning architecture called the transformer. They are pre-trained on large

    Generative pre-trained transformer

    Generative pre-trained transformer

    Generative_pre-trained_transformer

  • Operant conditioning
  • Type of associative learning process for behavioral modification

    Operant conditioning, also called instrumental conditioning, is a learning process in which voluntary behaviors are modified by association with the addition

    Operant conditioning

    Operant_conditioning

  • Evidence-based education
  • Paradigm of the education field

    Evidence-based education is related to evidence-based teaching, evidence-based learning, and school effectiveness research. The evidence-based education

    Evidence-based education

    Evidence-based education

    Evidence-based_education

  • Service-learning
  • Pedagogy combining learning objectives with community service

    students of all grades and stages. Projects based in communities are designed to apply classroom learning to create positive change in the community and

    Service-learning

    Service-learning

    Service-learning

  • Life skills-based education
  • Education focused on developing personal skills

    central feature of LSBE pedagogy is its emphasis on experiential and context-based learning, in which educational activities are designed to reflect real-life

    Life skills-based education

    Life skills-based education

    Life_skills-based_education

  • Learning nugget
  • scope that learners undertake in a particular context in order to attain specific learning outcomes A learning nugget task will take a prescribed length of

    Learning nugget

    Learning_nugget

  • Traditional education
  • Long-established customs traditionally used in schools

    abandoned in favor of student centered and task-based approaches to learning. Depending on the context, the opposite of traditional education may be progressive

    Traditional education

    Traditional_education

  • Recognition of prior learning
  • Evaluating outside-classroom knowledge

    for the Recognition of Prior Learning that serve to guide and enhance the assessment of learning through RPL across contexts, contribute to organizational

    Recognition of prior learning

    Recognition_of_prior_learning

  • Feature learning
  • Set of learning techniques in machine learning

    used, and not the ordering or entire set of context words. More recent transformer-based representation learning approaches attempt to solve this with word

    Feature learning

    Feature learning

    Feature_learning

  • Outline of deep learning
  • Overview of and topical guide to deep learning

    and topical guide to, deep learning: Deep learning is a subfield of machine learning and artificial intelligence based on artificial neural networks

    Outline of deep learning

    Outline_of_deep_learning

  • Content-based instruction
  • Steps of using content based instruction for second language learners

    that the curriculum is based on a certain subject matter and communicative competence is acquired in the context of learning about certain topics in

    Content-based instruction

    Content-based_instruction

  • Social learning theory
  • Theory of learning and behaviour

    observing and imitating others. It states that learning is a cognitive process that occurs within a social context and can occur purely through observation

    Social learning theory

    Social_learning_theory

  • Kannu (learning management system)
  • Learning management system

    Kannu is a learning management system, purpose-built for creative education in music, arts, and design. It was released by California-based company Kadenze

    Kannu (learning management system)

    Kannu_(learning_management_system)

  • Active learning
  • Educational technique

    useful context in problem-based learning: Mark A Albanese, Laura C Dast (2013-10-22). Understanding Medical Education - Problem-based learning. doi:10

    Active learning

    Active_learning

  • Recurrent neural network
  • Class of artificial neural network

    forward and a learning rule is applied. The fixed back-connections save a copy of the previous values of the hidden units in the context units (since they

    Recurrent neural network

    Recurrent_neural_network

  • Attention Is All You Need
  • 2017 research paper by Google

    research paper in machine learning authored by eight scientists and engineers working at Google. The paper introduced a new deep learning architecture known

    Attention Is All You Need

    Attention Is All You Need

    Attention_Is_All_You_Need

  • Adversarial machine learning
  • Research field that lies at the intersection of machine learning and computer security

    automatically craft binaries to evade learning-based detectors while preserving malicious functionality. Optimization-based attacks such as GAMMA use genetic

    Adversarial machine learning

    Adversarial_machine_learning

  • Concept learning
  • 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

    Concept_learning

  • Grammar induction
  • Machine-learning process

    approach is based on distributional learning. Algorithms using these approaches have been applied to learning context-free grammars and mildly context-sensitive

    Grammar induction

    Grammar_induction

  • Whole language
  • Approach to teaching children to read

    It is based on the premise that learning to read English comes naturally to humans, especially young children, in the same way that learning to speak

    Whole language

    Whole_language

  • Prototype theory
  • Theory of categorization in psychology

    "Distinguishing prototype-based and exemplar-based processes in dot-pattern category learning", Journal of Experimental Psychology: Learning, Memory, and Cognition

    Prototype theory

    Prototype_theory

  • Learning theory (education)
  • Theory that describes how students receive, process, and retain knowledge during learning

    Geographical learning theory focuses on the ways that contexts and environments shape the learning process. Outside the realm of educational psychology

    Learning theory (education)

    Learning_theory_(education)

  • Gamification of learning
  • Educational approach aiming to promote learning by using video game design and elements

    Similarly, in learning contexts, the unique needs of each set of learners, along with the specific learning objectives relevant to that context must inform

    Gamification of learning

    Gamification of learning

    Gamification_of_learning

  • Semantic Web
  • Extension of the Web to facilitate data exchange

    A smart citation index that displays the context of citations and classifies their intent using deep learning". Quantitative Science Studies. 2 (3): 882–898

    Semantic Web

    Semantic Web

    Semantic_Web

  • Artificial intelligence
  • Intelligence of machines

    to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field

    Artificial intelligence

    Artificial_intelligence

  • LoRA (machine learning)
  • Parameter-efficient fine-tuning technique for large language models

    broadly to any dense layers in deep learning models, though it has been most extensively studied in the context of large language models. After training

    LoRA (machine learning)

    LoRA_(machine_learning)

  • Vector database
  • Type of database that uses vectors to represent other data

    from the raw data using machine learning methods such as feature extraction algorithms, word embeddings or deep learning networks. The goal is that semantically

    Vector database

    Vector_database

  • Dynamic decision-making
  • Broadbent's Sugar Production Factory task[clarification needed]. The Instance-Based Learning Theory (IBLT) is a theory of how humans make decisions in dynamic tasks

    Dynamic decision-making

    Dynamic_decision-making

  • Learning by teaching
  • Method of teaching in which students teach the subject to each other

    systematically developed the concept of having students teach other in the context of learning French as a foreign language, and he gave it a theoretical background

    Learning by teaching

    Learning_by_teaching

  • Situated cognition
  • Hypothesis that knowing is inseparable from doing

    bound to social, cultural and physical contexts. Situativity theorists suggest a model of knowledge and learning that requires thinking on the fly rather

    Situated cognition

    Situated_cognition

  • Learning environment
  • Term in education

    learning environment can refer to an educational approach, cultural context, or physical setting (the learning space) in which teaching and learning occur

    Learning environment

    Learning environment

    Learning_environment

  • Bloom's taxonomy
  • Classification system in education

    divides learning objectives into three broad domains: cognitive (knowledge-based), affective (emotion-based), and psychomotor (action-based), each with

    Bloom's taxonomy

    Bloom's_taxonomy

  • Word embedding
  • Method in natural language processing

    models" to reduce the high dimensionality of word representations in contexts by "learning a distributed representation for words". A study published in NeurIPS

    Word embedding

    Word embedding

    Word_embedding

  • Authentic learning
  • Educational approach

    authentic learning is an instructional approach that allows students to explore, discuss, and meaningfully construct concepts and relationships in contexts that

    Authentic learning

    Authentic_learning

  • Convolutional neural network
  • Type of feedforward neural network

    including text, images and audio. CNNs are the de-facto standard in deep learning-based approaches to computer vision and image processing, and have only recently

    Convolutional neural network

    Convolutional_neural_network

  • Context-dependent memory
  • Improved recall when the context of a situation is the same

    memory, state-dependent learning, cognitive context-dependent memory and mood-congruent memory. Research has also shown that context-dependence may play an

    Context-dependent memory

    Context-dependent_memory

  • Education
  • Transmission of knowledge and skills

    best available empirical evidence. It includes evidence-based teaching, evidence-based learning, and school effectiveness research. Autodidacticism, or

    Education

    Education

    Education

  • Westcott House, Cambridge
  • Anglican theological college in the United Kingdom

    the Diocese of Manchester, the college has pioneered patterns of context-based learning and innovative approaches to contextual theology for over twenty

    Westcott House, Cambridge

    Westcott House, Cambridge

    Westcott_House,_Cambridge

  • Error-driven learning
  • Reinforcement learning method

    In reinforcement learning, error-driven learning is a method for adjusting a model's (intelligent agent's) parameters based on the difference between its

    Error-driven learning

    Error-driven_learning

  • List of datasets for machine-learning research
  • 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

  • Context mixing
  • Type of data compression algorithm

    active area of research in machine learning.[citation needed] The PAQ series of data compression programs use context mixing to assign probabilities to

    Context mixing

    Context_mixing

  • Intelligent agent
  • Software agent which acts autonomously

    autonomously to achieve goals, and may improve its performance through machine learning or by acquiring knowledge.[citation needed] AI textbooks[which?] define

    Intelligent agent

    Intelligent agent

    Intelligent_agent

  • Microsoft Translator
  • Machine translation cloud service by Microsoft

    from one natural language to another. This system is based on four distinct areas of computer learning research seen below. The quality of Microsoft Translator's

    Microsoft Translator

    Microsoft_Translator

  • Artificial intelligence in India
  • 2010s with NLP based Chatbots from Haptik, Corover.ai, Niki.ai and then gaining prominence in the early 2020s based on reinforcement learning, marked by breakthroughs

    Artificial intelligence in India

    Artificial_intelligence_in_India

  • Natural language processing
  • Processing of natural language by a computer

    piece of text based on the information presented before and after the piece of text being analyzed, e.g., by means of a probabilistic context-free grammar

    Natural language processing

    Natural_language_processing

  • GPT-4
  • 2023 text-generating language model

    aligned by reinforcement learning from human feedback (RLHF), suggestions to assassinate people on a list were elicited from the base model by a red team investigator

    GPT-4

    GPT-4

  • Zone of proximal development
  • Concept in educational psychology

    where their minds are being pushed by other students. In the context of second language learning, the ZPD can be useful to many adult users. Prompted by this

    Zone of proximal development

    Zone of proximal development

    Zone_of_proximal_development

AI & ChatGPT searchs for online references containing CONTEXT BASED-LEARNING

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CONTEXT BASED-LEARNING

AI search in online dictionary sources & meanings containing CONTEXT BASED-LEARNING

CONTEXT BASED-LEARNING

  • Content
  • n.

    That which is contained; the thing or things held by a receptacle or included within specified limits; as, the contents of a cask or bale or of a room; the contents of a book.

  • Concent
  • n.

    Concert of voices; concord of sounds; harmony; as, a concent of notes.

  • Contents
  • pl.

    of Content

  • Convex
  • n.

    A convex body or surface.

  • Dispute
  • v. t.

    To strive or contend about; to contest.

  • Connex
  • v. t.

    To connect.

  • Content
  • n.

    Area or quantity of space or matter contained within certain limits; as, solid contents; superficial contents.

  • Based
  • a.

    Having a base, or having as a base; supported; as, broad-based.

  • Contents
  • n. pl.

    See Content, n.

  • Contex
  • v. t.

    To context.

  • Contempt
  • n.

    An act or expression denoting contempt.

  • Base
  • n.

    A rustic play; -- called also prisoner's base, prison base, or bars.

  • Based
  • imp. & p. p.

    of Base

  • Based
  • n.

    Wearing, or protected by, bases.

  • Convexo-convex
  • a.

    Convex on both sides; double convex. See under Convex, a.

  • Contend
  • v. t.

    To struggle for; to contest.

  • Contek
  • n.

    Quarrel; contention; contest.

  • Base
  • a.

    Alloyed with inferior metal; debased; as, base coin; base bullion.

  • Content
  • n.

    An expression of assent to a bill or motion; an affirmative vote; also, a member who votes "Content.".

  • Content
  • n.

    That which contents or satisfies; that which if attained would make one happy.