Search results for "active learning"

showing 10 items of 184 documents

Considering Learners’ Perceptions in Designing Effective 21st Century Learning Environments for Basic Education in Finland

2014

Focusing on so called Key Competences or 21st Century Skills urges educational organizations to redesign their psychosocial and physical learning environments. Inspired by studies indicating that considering learners’ perceptions of learning environments can have a positive impact on learning and wellbeing, our study aims at developing design principles for involving learners in the learning environment design. This pilot case study analyzed 7- to 14-years old Finns’ (n = 80) perceptions by using web questionnaires and design workshops. The results are in line with research indicating that Finnish learners value aspects such as safety and peacefulness, the possibilities for rest and physica…

EngineeringEducational Organizationoppimisympäristötbusiness.industryStrategy and ManagementLearning environmentEducational technologyCollaborative learningOpen learningExperiential learningLearning EnvironmentsLearning sciencesEducationSynchronous learningPedagogyActive learningoppilaitoksetbusinessosallistava suunnittelu
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Develop of Innovation for Overall Successful Learning

2013

Innovation has many forms and thus many ways of being acquired. Restricted by time and space, our aim here is limited to showing some of the ways to develop of innovation in learning. We suppose that certain skills are efficient in reaching this goal such as modeling, situation management, operational control, teamwork, appropriate orientation and that, in addition, certain personal or social factors like motivation also play a role. We try to provide a theoretical conceptual basis for designing guidelines for innovative learning and provide a foundation for its continued development. We believe that it is crucial to establish reference methods to strengthen the relationship between innovat…

EngineeringTeamworkKnowledge managementbusiness.industryOperation controlSituation managementmedia_common.quotation_subjectActive learningFoundation (evidence)Conceptual basisbusinessmedia_commonInternational Journal of Technology and Inclusive Education
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ACTIVE LEARNING METHODS IN STUDIES: STUDENTS’ OPINIONS AND EXPERIENCES

2021

Rapid changes in education and pedagogy are related not only to the global crisis caused by COVID-19, but also to other changes determined by globalization and technological convergence—labour mobility, changes in different professions and changes in teacher–student relations—that are also affected by intergenerational differences. Changes in the pedagogical paradigm, which are included in the content of the Paris Communiqué (2018) and outlined in many important educational development and planning documents, emphasise students’ transition from being mere recipients of information to being participants actively engaged with new information in a learning environment. Following the identifica…

EnthusiasmHigher educationbusiness.industryLearning environmentmedia_common.quotation_subjectTeaching methodFocus groupActive learningMathematics educationComputingMilieux_COMPUTERSANDEDUCATIONStudent-centred learningActive learning Active learning methods Learning environment Student-centred learningbusinessPsychologyErasmus+media_commonSOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference
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Using Interactive Methods in Teaching Accounting

2016

Abstract Active learning shifts the focus of instruction from what the teacher should teach or deliver to students, to what the students should be able to do with the course material. Interactive methods are modern ways of stimulating teaching, representing tools of learning which favor the interchange of ideas, experiences, and knowledge. The purpose of this paper is to present a series of active teaching methods for the accounting data as being an alternative in the process of improving the teaching and learning of the accounting process.

EntrepreneurshipHF5001-6182Social Psychologybusiness.industryComputer scienceProcess (engineering)Teaching method05 social sciencesEconomics Econometrics and Finance (miscellaneous)accounting050301 educationAccounting050201 accountingactive learning0502 economics and businessActive learningTeaching and learning centerComputingMilieux_COMPUTERSANDEDUCATIONBusiness Management and Accounting (miscellaneous)BusinessbusinessBusiness management0503 educationStudies in Business and Economics
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HUMAN: Hierarchical Universal Modular ANnotator

2020

A lot of real-world phenomena are complex and cannot be captured by single task annotations. This causes a need for subsequent annotations, with interdependent questions and answers describing the nature of the subject at hand. Even in the case a phenomenon is easily captured by a single task, the high specialisation of most annotation tools can result in having to switch to another tool if the task only slightly changes. We introduce HUMAN, a novel web-based annotation tool that addresses the above problems by a) covering a variety of annotation tasks on both textual and image data, and b) the usage of an internal deterministic state machine, allowing the researcher to chain different anno…

FOS: Computer and information sciences0303 health sciencesComputer Science - Computation and Languagebusiness.industryActive learning (machine learning)Computer science02 engineering and technology[INFO] Computer Science [cs]Modular designVariety (cybernetics)Task (project management)03 medical and health sciencesAnnotationHuman–computer interaction0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing[INFO]Computer Science [cs]businessComputation and Language (cs.CL)030304 developmental biologyGraphical user interface
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Learning User's Confidence for Active Learning

2013

In this paper, we study the applicability of active learning in operative scenarios: more particularly, we consider the well-known contradiction between the active learning heuristics, which rank the pixels according to their uncertainty, and the user's confidence in labeling, which is related to both the homogeneity of the pixel context and user's knowledge of the scene. We propose a filtering scheme based on a classifier that learns the confidence of the user in labeling, thus minimizing the queries where the user would not be able to provide a class for the pixel. The capacity of a model to learn the user's confidence is studied in detail, also showing the effect of resolution is such a …

FOS: Computer and information sciencesComputer Science - Machine LearningActive learning (machine learning)Computer scienceComputer Vision and Pattern Recognition (cs.CV)SVM0211 other engineering and technologiesComputer Science - Computer Vision and Pattern RecognitionContext (language use)02 engineering and technologyMachine learningcomputer.software_genreTask (project management)Machine Learning (cs.LG)Classifier (linguistics)0202 electrical engineering electronic engineering information engineeringFOS: Electrical engineering electronic engineering information engineeringbad statesElectrical and Electronic Engineeringphotointerpretationuser's confidence021101 geological & geomatics engineeringActive learning (AL)Pixelbusiness.industryRank (computer programming)Image and Video Processing (eess.IV)very high resolution (VHR) imagery020206 networking & telecommunicationsElectrical Engineering and Systems Science - Image and Video ProcessingClass (biology)General Earth and Planetary SciencesArtificial intelligenceHeuristicsbusinesscomputerIEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
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Active emulation of computer codes with Gaussian processes – Application to remote sensing

2020

Many fields of science and engineering rely on running simulations with complex and computationally expensive models to understand the involved processes in the system of interest. Nevertheless, the high cost involved hamper reliable and exhaustive simulations. Very often such codes incorporate heuristics that ironically make them less tractable and transparent. This paper introduces an active learning methodology for adaptively constructing surrogate models, i.e. emulators, of such costly computer codes in a multi-output setting. The proposed technique is sequential and adaptive, and is based on the optimization of a suitable acquisition function. It aims to achieve accurate approximations…

FOS: Computer and information sciencesComputer Science - Machine LearningActive learningActive learning (machine learning)Computer sciencemedia_common.quotation_subjectMachine Learning (stat.ML)Radiative transfer model02 engineering and technology01 natural sciencesMachine Learning (cs.LG)symbols.namesakeArtificial IntelligenceStatistics - Machine Learning0103 physical sciences0202 electrical engineering electronic engineering information engineeringCode (cryptography)Emulation010306 general physicsFunction (engineering)Gaussian processGaussian process emulatorGaussian processRemote sensingmedia_commonEmulationbusiness.industrySampling (statistics)Remote sensingSignal ProcessingGlobal Positioning Systemsymbols020201 artificial intelligence & image processingComputer codeComputer Vision and Pattern RecognitionbusinessHeuristicsSoftwareDesign of experimentsPattern Recognition
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A survey of active learning algorithms for supervised remote sensing image classification

2011

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active …

FOS: Computer and information sciencesComputer scienceComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionMachine learningcomputer.software_genreactive learningHyperspectral image classificationEntropy (information theory)Electrical and Electronic EngineeringArchitectureRemote sensingvery high resolution (VHR)PixelContextual image classificationbusiness.industryHyperspectral imagingSupport vector machinehyperspectraltraining set definitionSignal Processingsupport vector machine (SVM)Artificial intelligenceHeuristicsbusinessAlgorithmcomputerimage classification
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Automatic Content Analysis of Computer-Supported Collaborative Inquiry-Based Learning Using Deep Networks and Attention Mechanisms

2020

Computer-supported collaborative inquiry-based learning (CSCIL) represents a form of active learning in which students jointly pose questions and investigate them in technology-enhanced settings. Scaffolds can enhance CSCIL processes so that students can complete more challenging problems than they could without scaffolds. Scaffolding CSCIL, however, would optimally adapt to the needs of a specific context, group, and stage of the group's learning process. In CSCIL, the stage of the learning process can be characterized by the inquiry-based learning (IBL) phase (orientation, conceptualization, investigation, conclusion, and discussion). In this presentation, we illustrate the potential of a…

Feature engineeringWord embeddingComputer scienceProcess (engineering)Context (language use)neuroverkot010501 environmental sciencesoppimisanalytiikkaMachine learningcomputer.software_genre01 natural sciencesluonnollinen kielitietokoneavusteinen oppimineninquiry based learningnatural language processingyhteisöllinen oppiminentutkiva oppiminen0105 earth and related environmental sciencesInterpretabilityArtificial neural networkbusiness.industry05 social sciences050301 educationsisällönanalyysideep neural networksActive learningInquiry-based learningArtificial intelligencebusiness0503 educationcomputer
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Game Mechanics in the Design of a Collaborative 3D Serious Game

2014

Background. This article investigates the potential of utilizing game mechanics in designing 3-D serious games for Computer-Supported Collaborative Learning (CSCL) and attempt to produce new information about designing collaborative serious games. Aim. This article has two aims: first, to clarify how theoretical knowledge of collaborative learning was related to game design in previous studies; and, second, to design a collaborative serious game based on theoretical knowledge of collaborative learning and game design. Results. The reviewed studies revealed the potential of using collaborative games in education. However, they showed that collaborative learning games were typically designed …

Game testingGame mechanicsKnowledge managementGame design documentComputer sciencebusiness.industryEducation theoryPerspective (graphical)Computer-Supported Collaborative Learning (CSCL)pelisuunnitteluComputingMilieux_PERSONALCOMPUTINGreviewGeneral Social Sciencescollaborative serious gamesCollaborative learningComputer Science Applicationsgame mechanicsinteractive learning environmentsGame designta5163D serious gamesserious gameyhteisöllinen oppiminenGame Developerbusiness
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