Search results for " learning."

showing 10 items of 5179 documents

“I started reading even though I didn’t understand much”: The significance of reading and writing fanfiction in extra-curricular language learning

2018

Kouluajan ulkopuolella tapahtuu oppimista jatkuvasti, erityisesti englannin kielen suhteen. Lingua francana toimivalta englannin kieleltä on lähes mahdoton välttyä, koska se on osa monen jokapäiväistä elämää esimerkiksi eri medioiden kautta. Suurin osa tästä oppimisesta tapahtuu alitajuisesti, eikä henkilö tee tietoista valintaa oppia altistuessaan kielelle tavalla tai toisella. Lukemisen merkitys kielen oppimisessa on laajasti tutkittu aihe (ks. esim. Krashen, 1989; Krashen and Bland, 2014). Yleinen näkemys on, että kohdekielellä lukeminen tukee kielen oppimista. Lukeminen ei kuitenkaan tyypillisesti korostu opetussuunnitelmissa muita oppimismenetelmiä enemmän. Vieraan kielen oppimisessa m…

extra-curricular language learningreadingfanfiction
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Evaluación de la reacción de alumnos y docentes en un modelo mixto de aprendizaje para Educación Superior

2014

Si bien en la educación presencial uno de los factores clave del éxito es el desempeño del docente dentro del salón de clase, es evidente que dentro de la educación en línea el papel del docente será distinto a su papel tradicional. Por ello, deben revalorarse los factores que garantizarán la calidad en este nuevo tipo de oferta educativa. En este estudio se muestran los resultados obtenidos de un análisis de caso de educación mixta (blended learning) para educación superior, y se enlistan los factores de éxito resultantes, así como algunas barreras para la adecuada implantación.

factores clave del éxitoestándaresobjeto de aprendizajeEducacióncalidadeducación superiorBlended learning online learning quality quality assess-ment key success factors higher education distance edu-cation Moodle learning object instructional design organizational barriers standardsEducationaprendizaje en líneabarreras organizacionalesevaluación de la calidadeducación a distanciaAprendizaje híbridoMoodlediseño instruccional
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Propaganda Barometer : A Supportive Tool to Improve Media Literacy Towards Building a Critically Thinking Society

2018

To smartly consume a huge and constantly growing volume of information, to identify fake news and resist propaganda in the context of Information Warfare, to improve personal critical thinking capabilities and increase media literacy, people require supportive environment with sophisticated technology facilitated tools. With rapid development of media, widespread popularity of social networks and fast growing amount of information distribution channels, propaganda and information warfare enter an absolutely new digital technology supported cyber era. Propaganda mining is not a trivial and very time consuming process for human. And, as with any new technology, human need certain time to unde…

fake detectionfaktantarkistussupportive learning environmentIBM WatsontekoälyNLPpropagandaskills development toolkriittinen ajattelupropaganda miningcognitive computinginformaatiosodankäyntimedialukutaitotiedonlouhintavaleuutiset
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The optimal musical pause : the effects of expectancies, musical training, and personality

2016

The musical pause is an acoustic space between musical phrases, and is an important auditory quality because it can enhance tension by delaying the expected. It has been proposed that expectancies develop from long-term schematic knowledge learned through exposure; however, the dynamic attending theory indicates that expectancies arise from localized short-term knowledge found in the stimulus. This study aims to measure the optimal duration of the pause by assessing the influence of low-level musical features, long-term familiarity, musical ability, and personality. Musical excerpts were chosen from a variety of genres to include two phrases (separable by a silence), from which participants…

familiarityoppiminenshort-term memoryentrainmentmusiikkischematic learninghiljaisuussäilömuistimusical pauseprediction effecttyömuistilong-term memorysilencedynamic attending theoryexpectation
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The experience of risk in families: conceptualisations and implications for transformative consumer research

2014

International audience; Families represent an important context for understanding and addressing the various forms of risk experienced by consumers. This article defines and discusses the concept of risk as it applies to the familial unit, with a particular focus on the liminal transitions that occur within families and the resiliency required for families to identify and adopt effective coping strategies to manage these transitions. A framework is proposed that offers researchers an approach for applying concepts related to family risk to various consumption-related problems and issues. This framework constitutes a starting point that can be developed and expanded to facilitate a deeper un…

familyliminalityStrategy and Managementmedia_common.quotation_subjectContext (language use)Consumer research[SHS]Humanities and Social SciencesUnit (housing)Sociologyta512resilienceriskmedia_commonMarketingConsumption (economics)JEL: M - Business Administration and Business Economics • Marketing • Accounting • Personnel Economicsbusiness.industryField (Bourdieu)Public relationsTransformative learning[SHS.GESTION]Humanities and Social Sciences/Business administrationPsychological resiliencetransformative consumer researchbusinessLiminalitySocial psychologyJournal of Marketing Management
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Comparison of feature importance measures as explanations for classification models

2021

AbstractExplainable artificial intelligence is an emerging research direction helping the user or developer of machine learning models understand why models behave the way they do. The most popular explanation technique is feature importance. However, there are several different approaches how feature importances are being measured, most notably global and local. In this study we compare different feature importance measures using both linear (logistic regression with L1 penalization) and non-linear (random forest) methods and local interpretable model-agnostic explanations on top of them. These methods are applied to two datasets from the medical domain, the openly available breast cancer …

feature importanceComputer scienceGeneral Chemical EngineeringGeneral Physics and Astronomy02 engineering and technologyinterpretable modelstekoälyMachine learningcomputer.software_genreLogistic regressionDomain (software engineering)020204 information systems0202 electrical engineering electronic engineering information engineeringFeature (machine learning)General Materials ScienceGeneral Environmental Scienceluokitus (toiminta)explainable artificial intelligencebusiness.industrylogistic regressionGeneral EngineeringRandom forestkoneoppiminenTrustworthinessInjury dataGeneral Earth and Planetary Sciences020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerrandom forestSN Applied Sciences
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Machine learning for mortality analysis in patients with COVID-19

2020

This paper analyzes a sample of patients hospitalized with COVID-19 in the region of Madrid (Spain). Survival analysis, logistic regression, and machine learning techniques (both supervised and unsupervised) are applied to carry out the analysis where the endpoint variable is the reason for hospital discharge (home or deceased). The different methods applied show the importance of variables such as age, O2 saturation at Emergency Rooms (ER), and whether the patient comes from a nursing home. In addition, biclustering is used to globally analyze the patient-drug dataset, extracting segments of patients. We highlight the validity of the classifiers developed to predict the mortality, reaching…

feature importanceComputer scienceHealth Toxicology and MutagenesisPneumonia ViralDecision treelcsh:MedicineSample (statistics)Machine learningcomputer.software_genreLogistic regressionArticlesurvival analysisBiclustering03 medical and health sciencesBetacoronavirus0302 clinical medicineMachine learningRisk of mortalitygraphical modelsHumans030212 general & internal medicineGraphical modelPandemicsSurvival analysisInformática0303 health sciences030306 microbiologybusiness.industrySARS-CoV-2Decision Treeslcsh:RPublic Health Environmental and Occupational HealthCOVID-19Decision ruleSurvival analysisFeature importancemachine learningSpainArtificial intelligenceGraphical modelsbusinessCoronavirus Infectionscomputer
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Exploiting Data Analytics and Deep Learning Systems to Support Pavement Maintenance Decisions

2021

Road networks are critical infrastructures within any region and it is imperative to maintain their conditions for safe and effective movement of goods and services. Road Management, therefore, plays a key role to ensure consistent efficient operation. However, significant resources are required to perform necessary maintenance activities to achieve and maintain high levels of service. Pavement maintenance can typically be very expensive and decisions are needed concerning planning and prioritizing interventions. Data are key towards enabling adequate maintenance planning but in many instances, there is limited available information especially in small or under-resourced urban road authorit…

feature importancepavement management systemComputer science0211 other engineering and technologiespavement maintenance decision02 engineering and technologypavement management systemslcsh:Technologylcsh:ChemistryGoods and services021105 building & construction0502 economics and business11. SustainabilitySettore ICAR/04 - Strade Ferrovie Ed AeroportiGeneral Materials Scienceroad asset databasesInstrumentationlcsh:QH301-705.5Fluid Flow and Transfer Processes050210 logistics & transportationbusiness.industryLevel of servicelcsh:TProcess Chemistry and TechnologyDeep learning05 social sciencesGeneral EngineeringPavement managementdeep learningTimelinedata mininglcsh:QC1-999Computer Science Applicationsroad asset databaseWorkflowRisk analysis (engineering)lcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040Key (cryptography)Settore ICAR/17 - DisegnoArtificial intelligencepavement maintenance decisionsbusinesslcsh:Engineering (General). Civil engineering (General)Predictive modellinglcsh:PhysicsApplied Sciences
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A Curvature Based Method for Blind Mesh Visual Quality Assessment Using a General Regression Neural Network

2016

International audience; No-reference quality assessment is a challenging issue due to the non-existence of any information related to the reference and the unknown distortion type. The main goal is to design a computational method to objectively predict the human perceived quality of a distorted mesh and deal with the practical situation when the reference is not available. In this work, we design a no reference method that relies on the general regression neural network (GRNN). Our network is trained using the mean curvature which is an important perceptual feature representing the visual aspect of a 3D mesh. Relatively to the human subjective scores, the trained network successfully asses…

feature learning[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer sciencemedia_common.quotation_subjectFeature extractiondistorted meshGRNNmean curvature02 engineering and technologyMachine learningcomputer.software_genreCurvaturevisual aspect representation[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingDistortioncomputational method0202 electrical engineering electronic engineering information engineeringFeature (machine learning)computational geometrymean opinion scoresQuality (business)Polygon meshmedia_commonArtificial neural networkbusiness.industrycompetitive scores Author Keywords Blind mesh visual quality assessmentperceptual feature020207 software engineeringregression analysis INSPEC: Non-Controlled Indexing curvature based methodblind mesh visual quality assessmentno-reference quality assessmentvisual qualityVisualizationgeneral regression neural network traininggeneral regression neural networkmesh generationneural netssubject scoreshuman perceived quality predictionhuman subjective scores020201 artificial intelligence & image processinglearning (artificial intelligence)Artificial intelligencepredicted objective scoresbusiness3D meshcomputer
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Prototyping Crop Traits Retrieval Models for CHIME: Dimensionality Reduction Strategies Applied to PRISMA Data

2022

In preparation for new-generation imaging spectrometer missions and the accompanying unprecedented inflow of hyperspectral data, optimized models are needed to generate vegetation traits routinely. Hybrid models, combining radiative transfer models with machine learning algorithms, are preferred, however, dealing with spectral collinearity imposes an additional challenge. In this study, we analyzed two spectral dimensionality reduction methods: principal component analysis (PCA) and band ranking (BR), embedded in a hybrid workflow for the retrieval of specific leaf area (SLA), leaf area index (LAI), canopy water content (CWC), canopy chlorophyll content (CCC), the fraction of absorbed photo…

feature selectionCHIMEactive learningGeneral Earth and Planetary Scienceshybrid methodPRISMAprincipal component analysibiochemical and biophysical traitGaussian process regressionPRISMA; CHIME; hybrid methods; biochemical and biophysical traits; Gaussian process regression; active learning; principal component analysis; feature selectionRemote Sensing
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