Search results for "Team learning"

showing 10 items of 30 documents

Hierarchies of probabilistic and team FIN-learning

2001

AbstractA FIN-learning machine M receives successive values of the function f it is learning and at some moment outputs a conjecture which should be a correct index of f. FIN learning has two extensions: (1) If M flips fair coins and learns a function with certain probability p, we have FIN〈p〉-learning. (2) When n machines simultaneously try to learn the same function f and at least k of these machines output correct indices of f, we have learning by a [k,n]FIN team. Sometimes a team or a probabilistic learner can simulate another one, if their probabilities p1,p2 (or team success ratios k1/n1,k2/n2) are close enough (Daley et al., in: Valiant, Waranth (Eds.), Proc. 5th Annual Workshop on C…

Discrete mathematics020203 distributed computingProbabilistic learningConjectureFinGeneral Computer ScienceIndex (typography)Probabilistic logicInductive inference0102 computer and information sciences02 engineering and technologyFunction (mathematics)01 natural sciencesTheoretical Computer ScienceMoment (mathematics)Computational learning theory010201 computation theory & mathematics0202 electrical engineering electronic engineering information engineeringTeam learningAlgorithmComputer Science(all)MathematicsTheoretical Computer Science
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Team learning as a game

1997

A machine FIN-learning machine M receives successive values of the function f it is learning; at some point M outputs conjecture which should be a correct index of f. When n machines simultaneously learn the same function f and at least k of these machines outut correct indices of f, we have team learning [k,n]FIN. Papers [DKV92, DK96] show that sometimes a team or a robabilistic learner can simulate another one, if its probability p (or team success ratio k/n) is close enough. On the other hand, there are critical ratios which mae simulation o FIN(p2) by FIN(p1) imossible whenever p2 _< r < p1 or some critical ratio r. Accordingly to [DKV92] the critical ratio closest to 1/2 rom the let is…

Discrete mathematicsFinite-state machineConjectureTeam learningAlgorithm complexityFunction (mathematics)Critical ratioAlgorithmMathematics
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Introducing Team Learning in a Developing Economy : Students’ Experiences of Experiential Entrepreneurship Education in Namibia

2017

Entrepreneurship is considered to be a driving force behind nations’ economic development, and entrepreneurship education’s role is essential in shaping entrepreneurial attitudes, skills and culture. The objective of this study was to investigate students’ experiences of entrepreneurship education in a developing economy, especially as regards learning in and through teams. The research project was conducted in Namibia, where the challenges to breaking out of poverty are huge. Methodologically, the study was based on qualitative thematic analysis of semi-structured interviews (2009–2014) of higher education students ([Formula: see text]) taking part in an action-based, experiential entrepr…

EntrepreneurshipoppimisympäristöoppiminenExperiential educationDeveloping countryExperiential learningtiimitEntrepreneurship educationyrittäjyyskasvatuslearning environment0502 economics and businessPedagogyta516Sociologydeveloping economiesexperiential entrepreneurship educationLearning environment05 social sciences050301 educationyrittäjyysteamTeam learningkehitysmaat0503 education050203 business & management
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Probabilistic and team PFIN-type learning: General properties

2008

We consider the probability hierarchy for Popperian FINite learning and study the general properties of this hierarchy. We prove that the probability hierarchy is decidable, i.e. there exists an algorithm that receives p_1 and p_2 and answers whether PFIN-type learning with the probability of success p_1 is equivalent to PFIN-type learning with the probability of success p_2. To prove our result, we analyze the topological structure of the probability hierarchy. We prove that it is well-ordered in descending ordering and order-equivalent to ordinal epsilon_0. This shows that the structure of the hierarchy is very complicated. Using similar methods, we also prove that, for PFIN-type learning…

FOS: Computer and information sciencesComputer Science::Machine LearningTheoretical computer scienceComputer Networks and CommunicationsExistential quantificationStructure (category theory)DecidabilityType (model theory)Learning in the limitTheoretical Computer ScienceMachine Learning (cs.LG)Probability of successFinite limitsMathematicsOrdinalsDiscrete mathematicsHierarchybusiness.industryApplied MathematicsAlgorithmic learning theoryProbabilistic logicF.1.1 I.2.6Inductive inferenceInductive reasoningDecidabilityComputer Science - LearningTeam learningComputational Theory and MathematicsArtificial intelligencebusinessJournal of Computer and System Sciences
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Higher education teachers' descriptions of their own learning : large scale study of Finnish Universities of Applied Sciences

2016

In this large-scale study, higher education teachers’ descriptions of their own learning were examined with qualitative analysis involving application of principles of phenomenographic research. This study is unique: it is unusual to use large-scale data in qualitative studies. The data were collected through an e-mail survey sent to 5960 teachers at universities of applied sciences in Finland. The number of respondents was 1622. Four hierarchically structured categories of learning were found: individual learning, collegial learning, team learning and innovative partnership learning. The role of teachers in higher education demands innovative partnership learning: being active at the socie…

Higher educationphenomenographyexperiences of learningEducationProfessional learning communityhigher education teachers0502 economics and businessMathematics educationComputingMilieux_COMPUTERSANDEDUCATIONta516university of applied sciencesPhenomenographybusiness.industry05 social sciencesEducational technology050301 educationOpen learningLearning sciencesTeam learningfenomenografiabusinessPsychologykvalitatiivinen tutkimus0503 education050203 business & managementqualitative researchQualitative researchHigher education research and development
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Innovation, Learning and Communities

2012

Human-Computer InteractionTeam learningKnowledge managementSocial Psychologybusiness.industryCommunicationSociologyOpen learningbusinessHuman Technology: An Interdisciplinary Journal on Humans In ICT Environments
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A Collaborative Classroom-Based Teacher Professional Learning Model

2017

This article reviews the Latvian experience of exploring a teacher continuous professional learning model, with an emphasis on teacher collaboration for professional learning. The developed model focuses on lessons taught in real-life classrooms and their subsequent analysis. The model consists of a set of regularly scheduled workshops in a period of a school year. It is based on the idea of a multiple activity cycle of “observe–reflect–write–discuss” conducted several times during every workshop. Every participant has an opportunity to experience two roles: that of a leader, teach a demonstration lesson to his/her colleagues, and that of a learner, observe, analyse and reflect on a colleag…

Medical educationTeam learningProfessional learning communityProfessional developmentComputingMilieux_COMPUTERSANDEDUCATIONEducational technologylanguageLatvianCollaborative learningSet (psychology)PsychologyProfessional studieslanguage.human_language
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Co-teaching as a context for teachers' professional learning and joint knowledge construction

2012

Abstract The study examined two primary teachers' professional learning and joint knowledge construction in the context of co-teaching. The teachers narrated their learning as a collaborative process with serendipitous origins. Shared knowledge construction was crucial in the learning process, as was implementing the resulting new ideas in practice. It is concluded that experiences of co-teaching may support teachers in meeting their professional responsibilities effectively. Professional development programmes need to be sensitive to teachers' individual and collaborative learning experiences to be able better to support them in the natural context of those experiences in particular local …

Professional developmentEducational technologyCollaborative learningExperiential learningEducationTeam learningProfessional learning communityActive learningTeaching and learning centerPedagogyComputingMilieux_COMPUTERSANDEDUCATIONMathematics educationta516PsychologyTeaching and Teacher Education
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Multidisciplinary and Phenomenonbased Learning in a STEAM Framework

2019

STEAM learningoppiminenmatematiikkateknologiataiteenlajittiedeilmiötmonialaisuus
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How team feedback and team trust influence information processing and learning in virtual teams: A moderated mediation model

2015

We study how team feedback influences information processing and learning in virtual teams.Group information is positively related to team learning in virtual teams.The indirect effect of team feedback on team learning via group information elaboration is moderated by team trust. This study examines a moderated mediation model in which team trust moderates the indirect effect of team feedback on team learning through group information elaboration in virtual teams. An experimental study in a laboratory was conducted with 54 teams randomly assigned to a team feedback condition or a control condition. Results provided empirical support to the moderated mediation model. We found that the indire…

Team compositionKnowledge managementbusiness.industryControl (management)Information processingTeam effectivenessPsychological safetyHuman-Computer InteractionModerated mediationTeam learningArts and Humanities (miscellaneous)Social exchange theorybusinessPsychologyGeneral PsychologyComputers in Human Behavior
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