985 resultados para Learning difficulty
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How can we best understand the emergence of the European Security and Defence Policy (ESDP)? This paper applies the theories of historical institutionalism and experiential learning to offer a dynamic conceptualisation of moves towards an ESDP which highlights some of the causal factors that a more temporally-restricted analysis would miss. It firstly shows how the institutional and functional expansion of European Political Cooperation (EPC) over the course of the 1970s and 80s gave rise to a context in which the development of a security and defence dimension came to be viewed as more logical and even necessary. It then goes on to analyse some of the external factors (in the form of actors, events and institutions) that further pushed in this direction and proved to influence the policy’s subsequent evolution. The paper is therefore intended to act as a first-step to understanding the ESDP’s development from this perspective.
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This file contains the ontology of patterns of educational settings, as part of the formal framework for specifying, reusing and implementing educational settings. Furthermore, it includes the set of rules that extend the ontology of educational scenarios as well as a brief description of the level of patters of such ontological framework.
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1. Dietary conditions affect cognitive abilities of many species, but it is unclear to what extent this physiological effect translates into an evolutionary relationship. 2. A reduction of competitive ability under nutritional stress has been reported as a correlated response to selection for learning ability in Drosophila melanogaster. Here we test whether the reverse holds as well, i.e. whether an evolutionary adaptation to poor food conditions leads to a decrease in learning capacities. 3. Populations of D. melanogaster were: (i) not subject to selection (control), (ii) selected for improved learning ability, (iii) selected for survival and fast development on poor food, or (iv) subject to both selection regimes. 4. There was no detectable response to selection for learning ability. 5. Selection on poor food led to higher survival, faster development and smaller adult size as a direct response, and to reduced learning ability as a correlated response. This study supports the hypothesis that adaptation to poor nutrition is likely to trade off with the evolution of improved learning ability.
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The age-dependent choice between expressing individual learning (IL) or social learning (SL) affects cumulative cultural evolution. A learning schedule in which SL precedes IL is supportive of cumulative culture because the amount of nongenetically encoded adaptive information acquired by previous generations can be absorbed by an individual and augmented. Devoting time and energy to learning, however, reduces the resources available for other life-history components. Learning schedules and life history thus coevolve. Here, we analyze a model where individuals may have up to three distinct life stages: "infants" using IL or oblique SL, "juveniles" implementing IL or horizontal SL, and adults obtaining material resources with learned information. We study the dynamic allocation of IL and SL within life stages and how this coevolves with the length of the learning stages. Although no learning may be evolutionary stable, we find conditions where cumulative cultural evolution can be selected for. In that case, the evolutionary stable learning schedule causes individuals to use oblique SL during infancy and a mixture between IL and horizontal SL when juvenile. We also find that the selected pattern of oblique SL increases the amount of information in the population, but horizontal SL does not do so.
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BACKGROUND: Recent data indicate a slight decrease in the prevalence of smoking in Switzerland, but little is known regarding the intention and difficulty to quit smoking among current smokers. Hence, we aimed to quantify the difficulty and intention to quit smoking among current smokers in Switzerland. METHODS: Cross-sectional study including 607 female and 658 male smokers. Difficulty, intention and motivation to quit smoking were assessed by questionnaire. RESULTS: 90% of women and 85% of men reported being "very difficult" or "difficult" to quit smoking. Almost three quarters of smokers (73% of women and 71% of men) intended to quit; however, less than 20% of them were in the preparation stage and 40% were in the precontemplation stage. On multivariate analysis, difficulty to quit was lower among men (Odds ratio and 95% [confidence interval]: 0.51 [0.35-0.74]) and increased with nicotine dependence and number of previous quitting attempts (OR=3.14 [1.75-5.63] for 6+ attempts compared to none). Intention to quit decreased with increasing age (OR=0.48 [0.30-0.75] for ≥65 years compared to <45 years) and increased with nicotine dependence, the number of previous quitting attempts (OR=4.35 [2.76-6.83] for 6+ attempts compared to none) and among non-cigarette smokers (OR=0.51 [0.28-0.92]). Motivation to quit was inversely associated with nicotine dependence and positively associated with the number of previous quitting attempts and personal history of lung disease. CONCLUSION: Over two thirds of Swiss smokers want to quit. However, only a small fraction wishes to do so in the short term. Nicotine dependence, previous attempts to quit or previous history of lung disease are independently associated with difficulty and intention to quit.
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This work shows the use of adaptation techniques involved in an e-learning system that considers students' learning styles and students' knowledge states. The mentioned e-learning system is built on a multiagent framework designed to examine opportunities to improve the teaching and to motivate the students to learn what they want in a user-friendly and assisted environment
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The purpose of this paper is to describe the collaboration between librarians and scholars, from a virtual university, in order to facilitate collaborative learning on how to manage information resources. The personal information behaviour of e-learning students when managing information resources for academic, professional and daily life purposes was studied from 24 semi-structured face-to-face interviews. The results of the content analysis of the interview' transcriptions, highlighted that in the workplace and daily life contexts, competent information behaviour is always linked to a proactive attitude, that is to say, that participants seek for information without some extrinsic reward or avoiding punishment. In the academic context, it was observed a low level of information literacy and it seems to be related with a prevalent uninvolved attitude.
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Hintergrund: Trotz ihrer Etablierung als essentieller Bestandteil der medizinischen Weiter-/Fortbildung werden europa- wie schweizweit kaum Kurse in evidenzbasierter Medizin (ebm) angeboten, die - integriert im klinischen Alltag - gezielt Fertigkeiten in ebm vermitteln. Noch grössere Defizite finden sich bei ebm- Weiterbildungsmöglichkeiten für klinische Ausbilder (z.B. Oberärzte). Als Weiterführung eines EU-finanzierten, klinisch integrierten E-learning- Programms für Weiterbildungsassistenten (www.ebm-unity.org) entwickelte eine europäische Gruppe von medical educators gezielt für Ausbilder ein e-learning-Curriculum zur Vermittlung von ebm im Rahmen der klinischen Weiterbildung. Methode: Die Entwicklung des Curriculums umfasst folgende Schritte: Beschreibung von Lernzielen, Identifikation von klinisch relevanten Lernumgebungen, Entwicklung von Lerninhalten und exemplarischen didaktischen Strategien, zugeschnitten auf die jeweilige Lernumgebungen, Design von web-basierten Selbst-Lernsequenzen mit Möglichkeiten zur Selbstevaluation, Erstellung eines Handbuchs. Ergebnisse: Lernziele des Tutoren-Lehrgangs sind der Erwerb von Fertigkeiten zur Vermittlung der 5 klassischen ebm-Schritte: PICO- (Patient-Intervention-Comparison-Outcome)-Fragen, Literatursuche, kritische Literaturbewertung, Übertragung der Ergebnisse im eigenen Setting und Implementierung). Die Lehrbeispiele zeigen angehenden ebm-Tutoren, wie sich typische klinische Situationen wie z.B. Stationsvisite, Ambulanzsprechstunde, Journalclub, offizielle Konferenzen, Audit oder das klinische Assessment von Weiterbildungsassistenten gezielt für die Vermittlung von ebm nutzen lassen. Kurze E-Learning-Module mit exemplarischen «real-life»-Video-Clips erlauben flexibles Lernen zugeschnitten auf das knappe Zeitkontingent von Ärzten. Eine Selbst-Evaluation ermöglicht die Überprüfung der gelernten Inhalte. Die Pilotierung des Tutoren-Lehrgangs mit klinisch tätigen Tutoren sowie die Übersetzung des Moduls in weitere Sprachen sind derzeit in Vorbereitung. chlussfolgerung: Der modulare Train-the-Trainer-Kurs zur Vermittlung von ebm im klinischen Alltag schliesst eine wichtige Lücke in der Dissemination von klinischer ebm. Webbasierte Beispiele mit kurzen Sequenzen demonstrieren typische Situationen zur Vermittlung der ebm-Kernfertigkeiten und bieten medical educators wie Oberärzten einen niedrigschwelligen Einstieg in «ebm» am Krankenbett. Langfristiges Ziel ist eine europäische Qualifikation für ebm- Learning und -Teaching in der Fort- und Weiterbildung. Nach Abschluss der Evaluation steht das Curriculum interessierten Personen und Gruppen unter «not-for-profit»-Bedingungen zur Verfügung. Auskünfte erhältlich von rkunz@uhbs.ch. Finanziert durch die Europäische Kommission - Leonardo da Vinci Programme - Transfer of Innovation - Pilot Project for Lifelong Learn- ing 2007 und das Schweizerische Staatssekretariat für Bildung und Forschung.
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This paper presents and discusses the use of Bayesian procedures - introduced through the use of Bayesian networks in Part I of this series of papers - for 'learning' probabilities from data. The discussion will relate to a set of real data on characteristics of black toners commonly used in printing and copying devices. Particular attention is drawn to the incorporation of the proposed procedures as an integral part in probabilistic inference schemes (notably in the form of Bayesian networks) that are intended to address uncertainties related to particular propositions of interest (e.g., whether or not a sample originates from a particular source). The conceptual tenets of the proposed methodologies are presented along with aspects of their practical implementation using currently available Bayesian network software.
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Peer-reviewed
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We present a novel filtering method for multispectral satellite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments carried out on multiclass one-against-all classification and target detection show the capabilities of the learned spatial filters.
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The explosive growth of Internet during the last years has been reflected in the ever-increasing amount of the diversity and heterogeneity of user preferences, types and features of devices and access networks. Usually the heterogeneity in the context of the users which request Web contents is not taken into account by the servers that deliver them implying that these contents will not always suit their needs. In the particular case of e-learning platforms this issue is especially critical due to the fact that it puts at stake the knowledge acquired by their users. In the following paper we present a system that aims to provide the dotLRN e-learning platform with the capability to adapt to its users context. By integrating dotLRN with a multi-agent hypermedia system, online courses being undertaken by students as well as their learning environment are adapted in real time
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Learning object economies are marketplaces for the sharing and reuse of learning objects (LO). There are many motivations for stimulating the development of the LO economy. The main reason is the possibility of providing the right content, at the right time, to the right learner according to adequate quality standards in the context of a lifelong learning process; in fact, this is also the main objective of education. However, some barriers to the development of a LO economy, such as the granularity and editability of LO, must be overcome. Furthermore, some enablers, such as learning design generation and standards usage, must be promoted in order to enhance LO economy. For this article, we introduced the integration of distributed learning object repositories (DLOR) as sources of LO that could be placed in adaptive learning designs to assist teachers’ design work. Two main issues presented as a result: how to access distributed LO, and where to place the LO in the learning design. To address these issues, we introduced two processes: LORSE, a distributed LO searching process, and LOOK, a micro context-based positioning process, respectively. Using these processes, the teachers were able to reuse LO from different sources to semi-automatically generate an adaptive learning design without leaving their virtual environment. A layered evaluation yielded good results for the process of placing learning objects from controlled learning object repositories into a learning design, and permitting educators to define different open issues that must be covered when they use uncontrolled learning object repositories for this purpose. We verified the satisfaction users had with our solution
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We propose and validate a multivariate classification algorithm for characterizing changes in human intracranial electroencephalographic data (iEEG) after learning motor sequences. The algorithm is based on a Hidden Markov Model (HMM) that captures spatio-temporal properties of the iEEG at the level of single trials. Continuous intracranial iEEG was acquired during two sessions (one before and one after a night of sleep) in two patients with depth electrodes implanted in several brain areas. They performed a visuomotor sequence (serial reaction time task, SRTT) using the fingers of their non-dominant hand. Our results show that the decoding algorithm correctly classified single iEEG trials from the trained sequence as belonging to either the initial training phase (day 1, before sleep) or a later consolidated phase (day 2, after sleep), whereas it failed to do so for trials belonging to a control condition (pseudo-random sequence). Accurate single-trial classification was achieved by taking advantage of the distributed pattern of neural activity. However, across all the contacts the hippocampus contributed most significantly to the classification accuracy for both patients, and one fronto-striatal contact for one patient. Together, these human intracranial findings demonstrate that a multivariate decoding approach can detect learning-related changes at the level of single-trial iEEG. Because it allows an unbiased identification of brain sites contributing to a behavioral effect (or experimental condition) at the level of single subject, this approach could be usefully applied to assess the neural correlates of other complex cognitive functions in patients implanted with multiple electrodes.