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Data-driven learning (DDL) is an approach to foreign language learning. Whereas most language learning is guided by teachers and textbooks, data-driven
Data-driven_learning
Unit of information
journalism Data-driven testing Data-driven learning Data-driven science Data-driven control system Data-driven marketing Digital privacy Environmental data rescue
Data
Class of computational model
Data-driven models are a class of computational models that primarily rely on historical data collected throughout a system's or process' lifetime to
Data-driven_model
Field of study to extract knowledge from data
Dehmer, Matthias (2018). "Defining data science by a data-driven quantification of the community". Machine Learning and Knowledge Extraction. 1: 235–251
Data_science
Subset of artificial intelligence
learn from data and generalize to unseen data, and thus perform tasks without being explicitly programmed. Advances in the field of deep learning have allowed
Machine_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
Error-driven_learning
Data-driven instruction is an educational approach that relies on information to inform teaching and learning. The idea refers to a method teachers use
Data-driven_instruction
Overview of and topical guide to machine learning
Supervised learning, where the model is trained on labeled data Unsupervised learning, where the model tries to identify patterns in unlabeled data Reinforcement
Outline_of_machine_learning
Choosing based on factual information
process is referred to as data-driven decision-making, "which is defined similarly as making decisions based on hard data as opposed to intuition, observation
Data-informed_decision-making
Domain driven data mining is a data mining methodology for discovering actionable knowledge and deliver actionable insights from complex data and behaviors
Domain_driven_data_mining
Academic journal
research on machine learning, knowledge extraction and related areas of data-driven artificial intelligence. It is published by MDPI and was launched in
Machine Learning and Knowledge Extraction
Machine_Learning_and_Knowledge_Extraction
intelligence to create learning environments. Considerations in the field include data-driven decision-making, AI ethics, data privacy and AI literacy
Artificial intelligence in education
Artificial_intelligence_in_education
Tasks in machine learning
function by making data-driven predictions or decisions, through building a mathematical model from input data. These input data used to build the model
Training, validation, and test data sets
Training,_validation,_and_test_data_sets
Computer program that constructs concordances from text corpora
corpora. Tim Johns at the University of Birmingham coined the term data-driven learning (DDL) around 1990 to describe a pedagogical approach in which language
Concordancer
Dynamic Data Driven Applications Systems (DDDAS) is a paradigm whereby the computation and instrumentation aspects of an application system are dynamically
Dynamic Data Driven Applications Systems
Dynamic_Data_Driven_Applications_Systems
Process of analyzing large data sets
Data mining is the process of extracting and finding patterns in massive data sets involving methods at the intersection of machine learning, statistics
Data_mining
Machine learning paradigm
Self-supervised learning (SSL) is a paradigm in machine learning where a model is trained on a task using the data itself to generate supervisory signals
Self-supervised_learning
Javascript library for data visualization
js (also known as D3, short for Data-Driven Documents) is a JavaScript library for producing dynamic, interactive data visualizations in web browsers.
D3.js
Topics referred to by the same term
League, a Dutch offshoot of the English Defence League Data-driven learning, an approach to learning foreign languages Den Danske Landinspektørforening,
DDL
semi-supervised machine-learning algorithms are usually difficult and expensive to produce because of the large amount of time needed to label the data. Although they
List of datasets for machine-learning research
List_of_datasets_for_machine-learning_research
Field of machine learning
and unsupervised learning algorithms respectively attempt to discover patterns in labeled and unlabeled data, reinforcement learning involves training
Reinforcement_learning
Branch of machine learning
Fundamentally, deep learning refers to a class of machine learning algorithms in which a hierarchy of layers is used to transform input data into a progressively
Deep_learning
Learning technique
use of concordancers in the language classroom with his concept of Data-driven learning (DDL). DDL encourages learners to work out their own rules about
Computer-assisted language learning
Computer-assisted_language_learning
Text corpus of British English
language leaner and is referred to as “data-driven learning” by Tim Johns. The corpus data used for data-driven learning is relatively smaller, and consequently
British_National_Corpus
Group of samples that have been tagged with one or more labels
unlabeled data. Algorithmic decision-making is subject to programmer-driven bias as well as data-driven bias. Training data that relies on bias labeled data will
Labeled_data
Open source platform
large-scale data analysis and model deployment. H2O is primarily used by data scientists and developers for statistical modeling and data-driven decision-making
H2O_(software)
Software engineering approach to designing and developing information systems
and data science, which often involves machine learning. Making the data usable usually involves substantial computing and storage, as well as data processing
Data_engineering
Journalistic process
Data journalism or data-driven journalism (DDJ) is journalism based on the filtering and analysis of large data sets for the purpose of creating or elevating
Data_journalism
American mechanical engineer
Professor of AI & Data-Driven Engineering at the University of Washington, where his research focuses on applying machine learning to dynamical systems
Steven_L._Brunton
Software development process
"Comparing Domain-Driven Design with Model-Driven Engineering". Modeling Languages. Retrieved 2021-08-05. Learning Domain-Driven Design: Aligning Software
Domain-driven_design
Interdisciplinary field of study
astronomy, data science, machine learning, informatics, and information/communications technologies. The field is closely related to astrostatistics. Data-driven
Astroinformatics
Technique to solve partial differential equations
laws that govern a given data-set in the learning process, and can be described by partial differential equations (PDEs). Low data availability for some
Physics-informed neural networks
Physics-informed_neural_networks
Family of control systems
Data-driven control systems are a broad family of control systems, in which the identification of the process model and/or the design of the controller
Data-driven_control_system
Process of acquiring new knowledge
interacts with the e-learning environment, it is called augmented learning. By adapting to the needs of individuals, the context-driven instruction can be
Learning
Branch of analytics
Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and
Learning_analytics
Mechanism for enabling artificial agents to exhibit curiosity
Empirical data from psychology were computationally simulated and accounted for using this model. Intrinsically motivated (or curiosity-driven) learning is an
Intrinsic motivation (artificial intelligence)
Intrinsic_motivation_(artificial_intelligence)
strongly associated with the origins and development of data-driven learning (DDL), an approach to learning foreign languages which has learners use the output
Tim_Johns
Process supporting machine learning
bounding boxes, semantic segmentation, and keypoint annotation. Data annotation is used in AI-driven fields, including healthcare, autonomous vehicles, retail
Data_annotation
Process of linking data objects in distinct models
purchase orders and invoices. Modern data mapping processes increasingly use artificial intelligence (AI) and machine learning (ML) techniques to automate and
Data_mapping
Facility used to house computer servers
the global financial system, cloud services, machine learning, and artificial intelligence (AI). Data centers vary widely in terms of size, power and water
Data_center
Measurable property or characteristic
In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a data set. Choosing informative, discriminating
Feature_(machine_learning)
Algorithmically generated data that have a similar distribution as sampled data
mathematical models and to train machine learning models. Data generated by a computer simulation can be seen as synthetic data. This encompasses most applications
Synthetic_data
Computational model used in machine learning
NNs in the 1960s and 1970s. The first working deep learning algorithm was the group method of data handling, a method to train arbitrarily deep neural
Neural network (machine learning)
Neural_network_(machine_learning)
Specialized data centers designed for artificial intelligence
inference for artificial intelligence (AI) and machine learning models. Unlike general-purpose data centers, they are optimized for the parallel processing
AI_data_center
Use of artificial intelligence in the automation of electronic design
design cycles. AI Driven Design Automation uses several methods, including machine learning, expert systems, and reinforcement learning. These are used
AI-driven_design_automation
Investment fund using mathematical methods
that relies on systematic, data-driven methods, such as mathematical models, statistical techniques, AI, and machine learning, to make investment decisions
Quantitative_fund
Change of statistical properties over time
predictive analytics, data science, machine learning and related fields, concept drift or drift is an evolution of data that invalidates the data model. It happens
Concept_drift
Artificial intelligence in IT operations
the use of artificial intelligence, machine learning, and big data analytics to automate and enhance data center management. It helps organizations manage
AIOps
American neuroscientist
initiative established under his tenure is the BrainHealth Databank, a data-driven learning health system integrating AI and computational models with mental
Sean_Hill_(scientist)
Software creating a unified customer database accessible to other systems
the recency of their engagement. Predictive and AI-driven segmentation, which uses machine learning models to identify high-value customers, assess churn
Customer_data_platform
Automated recognition of patterns and regularities in data
statistical data analysis, signal processing, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Pattern
Pattern_recognition
English academic and writer
communication. Evidence-based Health Communication (2006) — Advocates for data-driven learning in health communication. Madness in Post-1945 British and American
Paul_Crawford_(academic)
is a timeline of machine learning. Major discoveries, achievements, milestones, and other major events in machine learning are included. History of artificial
Timeline_of_machine_learning
Form of advertising
Targeted advertising or data-driven marketing is a form of advertising, including online advertising, that is directed towards an audience with certain
Targeted_advertising
Machine learning that combines deep learning and reinforcement learning
Deep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the problem
Deep_reinforcement_learning
building up machine learning models based on data collected from numerical simulations or physical experiments. The machine learning models for fitness
Fitness_approximation
Title given to a small number of open-source software development leaders
language [citation needed] Ritchie Vink Polars Data analysis framework William Falcon PyTorch Lightning Deep learning framework Lars Hvam abapGit Git client for
Benevolent_dictator_for_life
Organization of research institutions
from ICSPR data using an instructor-predefined subset of variables Data Driven Learning Guides – enhance teaching of core concepts in the social sciences
Inter-university Consortium for Political and Social Research
Inter-university_Consortium_for_Political_and_Social_Research
Online project collecting example sentences
Tatoeba Corpus are not all authentic, they are sometimes used to build data-driven learning applications. BES (Basic English Sentence) Search is a non-commercial
Tatoeba
Cloud-based service and infrastructure
series of modular cloud services including computing, data storage, data analytics, and machine learning, alongside a set of management tools. It runs on the
Google_Cloud_Platform
Use of technology in education to enhance learning and teaching
addition to the need for promoting learning on a larger scale. Over the years, a combination of cognitive science and data-driven techniques have enhanced the
Educational_technology
American multinational technology company
company to reach a US$1 trillion valuation. In 2025, driven by soaring global demand for AI data center hardware in the midst of the AI boom, Nvidia became
Nvidia
Software engineering role
involving data-driven systems, cloud computing, and advanced software platforms, including areas such as data analysis and machine learning. Recent industry
Forward_Deployed_Engineer
Relationship between proficiency and experience
a learning curve Proficiency (test score)Experience (hours spent)01234503691215Proficiency (test score)Example of a steep learning curve A learning curve
Learning_curve
Disciplines of managing data as a resource
from data. Data mining is the process of extracting and finding patterns in massive data sets involving methods at the intersection of machine learning, statistics
Data_management
Educational technique
utilizing learning strategies that can include small-group work, role-play and simulations, data collection and analysis, active learning is purported
Active_learning
multidisciplinary field that studies history through machine learning and other data-driven, computational approaches. International Society for Computational
Computational_history
deep learning models for edge devices TensorRT-LLM — Nvidia toolkit for optimizing and deploying large language models on GPUs EDLUT – event-driven neural
Lists of open-source artificial intelligence software
Lists_of_open-source_artificial_intelligence_software
Type of air data system
air data when sensor fusion and real-time computing are required. Other non-conventional methods such as data-driven learning or machine learning based
Synthetic_air_data_system
Extremely large or complex datasets
collection, big data has low cost per data point, applies analysis techniques via machine learning and data mining, and includes diverse and new data sources
Big_data
Visual representation of data
data, explore the structures and features of data, and assess outputs of data-driven models. Data and information visualization can be part of data storytelling
Data and information visualization
Data_and_information_visualization
Centralized storage of knowledge
Unlike data warehouses, data lakes stores data is structured, semi-structured and unstructured format that makes them usable for machine learning and big
Data_warehouse
AI-driven satellite data analysis, passive acoustics or remote sensing and other applications of environmental monitoring make use of machine learning.
Applications of artificial intelligence
Applications_of_artificial_intelligence
and machine learning 2020 Hou, Zhongsheng For contributions to data-driven learning and control with applications in transportation systems 2020 Huang
List of fellows of IEEE Computational Intelligence Society
List_of_fellows_of_IEEE_Computational_Intelligence_Society
Subfield of artificial intelligence
computational models of learning from data. At the same time, it seeks to address deep learning’s main limitations: lack of reliability, data and energy efficiency
Neuro-symbolic_AI
AI that generates content
autonomous spacecraft. Machine learning uses both discriminative models and generative models to predict or generate data. Beginning in the late 2000s and
Generative_AI
Cloud computing platform by Microsoft
is a fully managed cloud data warehouse. Azure Data Factory is a data integration service that allows creation of data-driven workflows in the cloud for
Microsoft_Azure
Class of artificial neural network
probability of the data. Given a lot of learnable predictability in the incoming data sequence, the highest level RNN can use supervised learning to easily classify
Recurrent_neural_network
Type of machine learning model
Tošić, Aleksandar (5 March 2025). "Is Open Source the Future of AI? A Data-Driven Approach". Applied Sciences. 15 (5): 2790. doi:10.3390/app15052790. ISSN 2076-3417
Large_language_model
Hardware acceleration unit for artificial intelligence tasks
applications include algorithms for robotics, Internet of things, and data-intensive or sensor-driven tasks. They are often manycore or spatial designs and focus
Neural_processing_unit
Software for understanding biological data
prediction, this proved difficult. Machine learning techniques such as deep learning can learn features of data sets rather than requiring the programmer
Machine learning in bioinformatics
Machine_learning_in_bioinformatics
Open-source software library developed by Yandex
best machine learning tools". InfoWorld. "State of Data Science and Machine Learning 2020". "State of Data Science and Machine Learning 2021". "PyPI Stats
CatBoost
Projection of data onto lower-dimensional manifolds
(NLDR), also known as manifold learning, is any of various related techniques that aim to project high-dimensional data, potentially existing across non-linear
Nonlinear dimensionality reduction
Nonlinear_dimensionality_reduction
Capability that enables an organization to ensure high data quality
Model, and DAMA-DMBOK. While data governance initiatives can be driven by a desire to improve data quality, they are often driven by C-level leaders responding
Data_governance
Structured data and method for its publication
In computing, linked data is structured data which is associated with ("linked" to) other data. Interlinking makes the data more useful through semantic
Linked_data
AI whose outputs can be understood by humans
Transactions on Machine Learning Research. arXiv:2211.08425. Retrieved 2025-11-13. Martens, David; Provost, Foster (2014). "Explaining data-driven document classifications"
Explainable artificial intelligence
Explainable_artificial_intelligence
Data analysis techniques for fraud detection
these methods include knowledge discovery in databases (KDD), data mining, machine learning and statistics. They offer applicable and successful solutions
Data analysis for fraud detection
Data_analysis_for_fraud_detection
American private school network
2014. The network uses a proprietary instructional model called 2 Hour Learning, which replaces traditional teachers with "guides" and relies on software‑based
Alpha_School
Business intelligence Data presentation architecture Exploratory data analysis List of datasets for machine-learning research List of data science software
Data_analysis
British autonomous vehicle technology company
3D maps and hand-coded rules, in favour of a self-learning "AI driver" that learns from camera data and driving experience. The London-headquartered startup
Wayve
E-learning platform
open-source learning management system written in PHP and distributed under the GNU General Public License. Moodle is used for blended learning, distance
Moodle
Engineering applied to artificial intelligence
language. The process begins with text preprocessing to prepare data for machine learning models. Recent advancements, particularly transformer-based models
Artificial intelligence engineering
Artificial_intelligence_engineering
machine learning, and deep learning to revolutionize the agricultural industry. By using big data analytics and genomic research to support data-driven agriculture
Artificial intelligence in India
Artificial_intelligence_in_India
Type of economy
of valuable data, is referred to as partial data barter. The human-driven data economy is a fair and functioning data economy in which data is controlled
Data_economy
Data-driven algorithm
identification of nonlinear dynamics (SINDy) is a data-driven algorithm for obtaining dynamical systems from data. Given a series of snapshots of a dynamical
Sparse identification of non-linear dynamics
Sparse_identification_of_non-linear_dynamics
Method for discovering interesting relations between variables in databases
Association rule learning is a rule-based machine learning method for discovering interesting relations between variables in large databases. It is intended
Association_rule_learning
Machine learning method
Logic Learning Machine. Also, an LLM version devoted to regression problems was developed. Like other machine learning methods, LLM uses data to build
Logic_learning_machine
Educational philosophy and pedagogy
self-guided curriculum that uses self-directed, experiential learning in relationship-driven environments. The programme is based on the principles of respect
Reggio_Emilia_approach
Type of artificial neural network
Scientific computing: scientific machine learning (SciML) recently emerged as the combination of physics-based and data-driven models, to numerically solve differential
Neural_field
Educational approach
their learning. Learning is student driven, with tutors, peers, teachers, parents, and outside experts all assisting and coaching in the learning process
Authentic_learning
DATA DRIVEN-LEARNING
DATA DRIVEN-LEARNING
Male
French
French name derived from Latin Adrianus, ADRIEN means "from Hadria."
Female
Hungarian
 Short form of Hungarian Katalin, KATA means "pure." Compare with other forms of Kata.
Male
Iranian/Persian
 Short form of Persian Dârayavahush, DARA means "possesses a lot, wealthy." Compare with other forms of Dara.
Female
Polish
Short form of Polish Edyta, DYTA means "rich battle."
Female
Hebrew
(×“Ö¼Ö¸× Ö¸×”) Feminine form of Hebrew Dan, DANA means "judge." Compare with other forms of Dana.
Female
Russian
 Short form of Russian Yekaterina, KATA means "pure." Compare with other forms of Kata.
Female
Finnish
 Short form of Finnish Katariina, KATA means "pure." Compare with other forms of Kata.
Surname or Lastname
English
English : occupational name for a driver of horses or oxen attached to a cart or plow, or of loose cattle, from a Middle English agent derivative of Old English drīfan ‘to drive’.
Male
Irish
 From Irish Gaelic Mac Dara, DARA means "son of oak." Compare with other forms of Dara.
Male
English
English surname transferred to unisex forename use, possibly DANA means "from Denmark."
Female
English
 English surname transferred to unisex forename use, possibly DANA means "from Denmark." Compare with other forms of Dana.
Female
Hebrew
(דִּיתָה) Pet form of Hebrew Yehuwdiyth, DITA means "Jewess" or "praised." Compare with another form of Dita.
Female
English
 Middle English name DARA means "brave, daring." Compare with another form of Dara.
Female
Slavic
 Short form of Slavic Bogdana, DANA means "gift from God." Compare with other forms of Dana.
Male
Hebrew
Variant spelling of Hebrew Dathan, DATAN means "belonging to a fountain."
Female
Finnish
Variant form of Finnish Aada, AATA means "noble."
Male
Turkish
Turkish name ATA means "ancestor."
Female
Hindi/Indian
(लता) Hindi name derived from a plant name, from the Sanskrit word lata, LATA means "creeper," in reference to a creeping plant.
Male
English
English name possibly derived from the Old English word drǽfend, DRAVEN means "hunter."Â
Female
Polish
 Variant spelling of Polish Dyta, DITA means "rich battle." Compare with another form of Dita.
DATA DRIVEN-LEARNING
DATA DRIVEN-LEARNING
Boy/Male
Hindu
With beautiful hair, Lord of happiness
Boy/Male
Tamil
Morning, Dawn
Boy/Male
English
French name Gervaise 'spearman.
Girl/Female
Indian
Whole, Complete
Boy/Male
Tamil
Godly
Boy/Male
American, British, Celtic, English
Sea Friend; White
Girl/Female
Tamil
The sign of the zodiac, Collection
Girl/Female
Australian, French, Indian, Latin, Polish
Youthful; Jove's Child; Female Version of Julius; Soft Bearded
Boy/Male
Gujarati, Hindu, Indian
Part of Happiness
Girl/Female
Indian, Sanskrit
Beam of Light; Flame; Enlightening
DATA DRIVEN-LEARNING
DATA DRIVEN-LEARNING
DATA DRIVEN-LEARNING
DATA DRIVEN-LEARNING
DATA DRIVEN-LEARNING
n.
The point of time at which a transaction or event takes place, or is appointed to take place; a given point of time; epoch; as, the date of a battle.
imp.
of Drive.
n.
The driving wheel of a locomotive.
v. t.
To note or fix the time of, as of an event; to give the date of; as, to date the building of the pyramids.
n.
A boat driven by the tide.
n.
One who drives cattle or sheep to market; one who makes it his business to purchase cattle, and drive them to market.
imp.
of Drive
a.
Driven to the end, as a nail; driven close.
p. pr. & vb. n.
of Drive
n.
A collection of cattle driven, or cattle collected for driving; a number of animals, as oxen, sheep, or swine, driven in a body.
n.
A collection of objects that are driven; a mass of logs to be floated down a river.
p. p.
of Drive
a.
Driven by winds or storms; forced by stress of weather.
p. p.
of Drive.
n.
A place suitable or agreeable for driving; a road prepared for driving.
p. p.
Driven.
v. t.
To impel or urge onward by force in a direction away from one, or along before one; to push forward; to compel to move on; to communicate motion to; as, to drive cattle; to drive a nail; smoke drives persons from a room.
p. p.
of Drive. Also adj.
n.
The fruit of the date palm; also, the date palm itself.