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Sample records for rank-based hebbian learning

  1. Stereo matching using Hebbian learning.

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    Pajares, G; Cruz, J M; Lopez-Orozco, J A

    1999-01-01

    This paper presents an approach to the local stereo matching problem using edge segments as features with several attributes. We have verified that the differences in attributes for the true matches cluster in a cloud around a center. The correspondence is established on the basis of the minimum distance criterion, computing the Mahalanobis distance between the difference of the attributes for a current pair of features and the cluster center (similarity constraint). We introduce a learning strategy based on the Hebbian Learning to get the best cluster center. A comparative analysis among methods without learning and with other learning strategies is illustrated.

  2. Hebbian learning and predictive mirror neurons for actions, sensations and emotions

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    Keysers, C.; Gazzola, Valeria

    2014-01-01

    Spike-timing-dependent plasticity is considered the neurophysiological basis of Hebbian learning and has been shown to be sensitive to both contingency and contiguity between pre- and postsynaptic activity. Here, we will examine how applying this Hebbian learning rule to a system of interconnected

  3. Learning to Generate Sequences with Combination of Hebbian and Non-hebbian Plasticity in Recurrent Spiking Neural Networks.

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    Panda, Priyadarshini; Roy, Kaushik

    2017-01-01

    Synaptic Plasticity, the foundation for learning and memory formation in the human brain, manifests in various forms. Here, we combine the standard spike timing correlation based Hebbian plasticity with a non-Hebbian synaptic decay mechanism for training a recurrent spiking neural model to generate sequences. We show that inclusion of the adaptive decay of synaptic weights with standard STDP helps learn stable contextual dependencies between temporal sequences, while reducing the strong attractor states that emerge in recurrent models due to feedback loops. Furthermore, we show that the combined learning scheme suppresses the chaotic activity in the recurrent model substantially, thereby enhancing its' ability to generate sequences consistently even in the presence of perturbations.

  4. A rank-based Prediction Algorithm of Learning User's Intention

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    Shen, Jie; Gao, Ying; Chen, Cang; Gong, HaiPing

    Internet search has become an important part in people's daily life. People can find many types of information to meet different needs through search engines on the Internet. There are two issues for the current search engines: first, the users should predetermine the types of information they want and then change to the appropriate types of search engine interfaces. Second, most search engines can support multiple kinds of search functions, each function has its own separate search interface. While users need different types of information, they must switch between different interfaces. In practice, most queries are corresponding to various types of information results. These queries can search the relevant results in various search engines, such as query "Palace" contains the websites about the introduction of the National Palace Museum, blog, Wikipedia, some pictures and video information. This paper presents a new aggregative algorithm for all kinds of search results. It can filter and sort the search results by learning three aspects about the query words, search results and search history logs to achieve the purpose of detecting user's intention. Experiments demonstrate that this rank-based method for multi-types of search results is effective. It can meet the user's search needs well, enhance user's satisfaction, provide an effective and rational model for optimizing search engines and improve user's search experience.

  5. Behavioral analysis of differential Hebbian learning in closed-loop systems

    DEFF Research Database (Denmark)

    Kulvicius, Tomas; Kolodziejski, Christoph; Tamosiunaite, Minija

    2010-01-01

    measuring information of inputs. In this study we analyze a specific type of closed loop system by looking at the input as well as the output space. For this, we investigate simulated agents that perform differential Hebbian learning (STDP). In the first part we show that analytical solutions can be found...

  6. Beta Hebbian Learning as a New Method for Exploratory Projection Pursuit.

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    Quintián, Héctor; Corchado, Emilio

    2017-09-01

    In this research, a novel family of learning rules called Beta Hebbian Learning (BHL) is thoroughly investigated to extract information from high-dimensional datasets by projecting the data onto low-dimensional (typically two dimensional) subspaces, improving the existing exploratory methods by providing a clear representation of data's internal structure. BHL applies a family of learning rules derived from the Probability Density Function (PDF) of the residual based on the beta distribution. This family of rules may be called Hebbian in that all use a simple multiplication of the output of the neural network with some function of the residuals after feedback. The derived learning rules can be linked to an adaptive form of Exploratory Projection Pursuit and with artificial distributions, the networks perform as the theory suggests they should: the use of different learning rules derived from different PDFs allows the identification of "interesting" dimensions (as far from the Gaussian distribution as possible) in high-dimensional datasets. This novel algorithm, BHL, has been tested over seven artificial datasets to study the behavior of BHL parameters, and was later applied successfully over four real datasets, comparing its results, in terms of performance, with other well-known Exploratory and projection models such as Maximum Likelihood Hebbian Learning (MLHL), Locally-Linear Embedding (LLE), Curvilinear Component Analysis (CCA), Isomap and Neural Principal Component Analysis (Neural PCA).

  7. Spike-Based Bayesian-Hebbian Learning of Temporal Sequences

    DEFF Research Database (Denmark)

    Tully, Philip J; Lindén, Henrik; Hennig, Matthias H

    2016-01-01

    in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods...... of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model's feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx). We show that the learning...... and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times...

  8. Spike-Based Bayesian-Hebbian Learning of Temporal Sequences.

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    Philip J Tully

    2016-05-01

    Full Text Available Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model's feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx. We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison.

  9. Enhancing Hebbian Learning to Control Brain Oscillatory Activity.

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    Soekadar, Surjo R; Witkowski, Matthias; Birbaumer, Niels; Cohen, Leonardo G

    2015-09-01

    Sensorimotor rhythms (SMR, 8-15 Hz) are brain oscillations associated with successful motor performance, imagery, and imitation. Voluntary modulation of SMR can be used to control brain-machine interfaces (BMI) in the absence of any physical movements. The mechanisms underlying acquisition of such skill are unknown. Here, we provide evidence for a causal link between function of the primary motor cortex (M1), active during motor skill learning and retention, and successful acquisition of abstract skills such as control over SMR. Thirty healthy participants were trained on 5 consecutive days to control SMR oscillations. Each participant was randomly assigned to one of 3 groups that received either 20 min of anodal, cathodal, or sham transcranial direct current stimulation (tDCS) over M1. Learning SMR control across training days was superior in the anodal tDCS group relative to the other 2. Cathodal tDCS blocked the beneficial effects of training, as evidenced with sham tDCS. One month later, the newly acquired skill remained superior in the anodal tDCS group. Thus, application of weak electric currents of opposite polarities over M1 differentially modulates learning SMR control, pointing to this primary cortical region as a common substrate for acquisition of physical motor skills and learning to control brain oscillatory activity. Published by Oxford University Press 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

  10. Dynamic Hebbian Cross-Correlation Learning Resolves the Spike Timing Dependent Plasticity Conundrum

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    Tjeerd V. olde Scheper

    2018-01-01

    Full Text Available Spike Timing-Dependent Plasticity has been found to assume many different forms. The classic STDP curve, with one potentiating and one depressing window, is only one of many possible curves that describe synaptic learning using the STDP mechanism. It has been shown experimentally that STDP curves may contain multiple LTP and LTD windows of variable width, and even inverted windows. The underlying STDP mechanism that is capable of producing such an extensive, and apparently incompatible, range of learning curves is still under investigation. In this paper, it is shown that STDP originates from a combination of two dynamic Hebbian cross-correlations of local activity at the synapse. The correlation of the presynaptic activity with the local postsynaptic activity is a robust and reliable indicator of the discrepancy between the presynaptic neuron and the postsynaptic neuron's activity. The second correlation is between the local postsynaptic activity with dendritic activity which is a good indicator of matching local synaptic and dendritic activity. We show that this simple time-independent learning rule can give rise to many forms of the STDP learning curve. The rule regulates synaptic strength without the need for spike matching or other supervisory learning mechanisms. Local differences in dendritic activity at the synapse greatly affect the cross-correlation difference which determines the relative contributions of different neural activity sources. Dendritic activity due to nearby synapses, action potentials, both forward and back-propagating, as well as inhibitory synapses will dynamically modify the local activity at the synapse, and the resulting STDP learning rule. The dynamic Hebbian learning rule ensures furthermore, that the resulting synaptic strength is dynamically stable, and that interactions between synapses do not result in local instabilities. The rule clearly demonstrates that synapses function as independent localized

  11. Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex.

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    Lindsay, Grace W; Rigotti, Mattia; Warden, Melissa R; Miller, Earl K; Fusi, Stefano

    2017-11-08

    Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear "mixed" selectivity is an important neurophysiological trait for enabling complex and context-dependent behaviors. Here we investigate (1) the extent to which the PFC exhibits computationally relevant properties, such as mixed selectivity, and (2) how such properties could arise via circuit mechanisms. We show that PFC cells recorded from male and female rhesus macaques during a complex task show a moderate level of specialization and structure that is not replicated by a model wherein cells receive random feedforward inputs. While random connectivity can be effective at generating mixed selectivity, the data show significantly more mixed selectivity than predicted by a model with otherwise matched parameters. A simple Hebbian learning rule applied to the random connectivity, however, increases mixed selectivity and enables the model to match the data more accurately. To explain how learning achieves this, we provide analysis along with a clear geometric interpretation of the impact of learning on selectivity. After learning, the model also matches the data on measures of noise, response density, clustering, and the distribution of selectivities. Of two styles of Hebbian learning tested, the simpler and more biologically plausible option better matches the data. These modeling results provide clues about how neural properties important for cognition can arise in a circuit and make clear experimental predictions regarding how various measures of selectivity would evolve during animal training. SIGNIFICANCE STATEMENT The prefrontal cortex is a brain region believed to support the ability of animals to engage in complex behavior. How neurons in this area respond to stimuli-and in particular, to combinations of stimuli ("mixed

  12. Frequency-multiplexing ability of complex-valued Hebbian learning in logic gates.

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    Kawata, Sotaro; Hirose, Akira

    2008-04-01

    Lightwave has attractive characteristics such as spatial parallelism, temporal rapidity in signal processing, and frequency band vastness. In particular, the vast carrier frequency bandwidth promises novel information processing. In this paper, we propose a novel optical logic gate that learns multiple functions at frequencies different from one another, and analyze the frequency-domain multiplexing ability in the learning based on complex-valued Hebbian rule. We evaluate the averaged error function values in the learning process and the error probabilities in the realized logic functions. We investigate optimal learning parameters as well as performance dependence on the number of learning iterations and the number of parallel paths per neuron. Results show a trade-off among the learning parameters such as learning time constant and learning gain. We also find that when we prepare 10 optical path differences and conduct 200 learning iterations, the error probability completely decreases to zero in a three-function multiplexing case. However, at the same time, the error probability is tolerant of the path number. That is, even if the path number is reduced by half, error probability is found almost zero. The results can be useful to determine neural parameters for future optical neural network systems and devices that utilize the vast frequency bandwidth for frequency-domain multiplexing.

  13. Effects of Hebbian learning on the dynamics and structure of random networks with inhibitory and excitatory neurons.

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    Siri, Benoît; Quoy, Mathias; Delord, Bruno; Cessac, Bruno; Berry, Hugues

    2007-01-01

    The aim of the present paper is to study the effects of Hebbian learning in random recurrent neural networks with biological connectivity, i.e. sparse connections and separate populations of excitatory and inhibitory neurons. We furthermore consider that the neuron dynamics may occur at a (shorter) time scale than synaptic plasticity and consider the possibility of learning rules with passive forgetting. We show that the application of such Hebbian learning leads to drastic changes in the network dynamics and structure. In particular, the learning rule contracts the norm of the weight matrix and yields a rapid decay of the dynamics complexity and entropy. In other words, the network is rewired by Hebbian learning into a new synaptic structure that emerges with learning on the basis of the correlations that progressively build up between neurons. We also observe that, within this emerging structure, the strongest synapses organize as a small-world network. The second effect of the decay of the weight matrix spectral radius consists in a rapid contraction of the spectral radius of the Jacobian matrix. This drives the system through the "edge of chaos" where sensitivity to the input pattern is maximal. Taken together, this scenario is remarkably predicted by theoretical arguments derived from dynamical systems and graph theory.

  14. Logarithmic distributions prove that intrinsic learning is Hebbian [version 2; referees: 2 approved

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    Gabriele Scheler

    2017-10-01

    Full Text Available In this paper, we present data for the lognormal distributions of spike rates, synaptic weights and intrinsic excitability (gain for neurons in various brain areas, such as auditory or visual cortex, hippocampus, cerebellum, striatum, midbrain nuclei. We find a remarkable consistency of heavy-tailed, specifically lognormal, distributions for rates, weights and gains in all brain areas examined. The difference between strongly recurrent and feed-forward connectivity (cortex vs. striatum and cerebellum, neurotransmitter (GABA (striatum or glutamate (cortex or the level of activation (low in cortex, high in Purkinje cells and midbrain nuclei turns out to be irrelevant for this feature. Logarithmic scale distribution of weights and gains appears to be a general, functional property in all cases analyzed. We then created a generic neural model to investigate adaptive learning rules that create and maintain lognormal distributions. We conclusively demonstrate that not only weights, but also intrinsic gains, need to have strong Hebbian learning in order to produce and maintain the experimentally attested distributions. This provides a solution to the long-standing question about the type of plasticity exhibited by intrinsic excitability.

  15. In search for the neural mechanisms of individual development: behavior-driven differential Hebbian learning

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    Ralf eDer

    2016-01-01

    Full Text Available When Donald Hebb published his 1949 book ``The Organization of Behavior'' he opened a new way of thinking in theoretical neuroscience which, in retrospective, is very close to contemporary ideas in self-organization. His metaphor of ``wiring'' together what ``fires together'' matches very closely the commonparadigm that global organization can derive from simple local rules. While ingenious at his time and inspiring the research over decades, the results still fall short of the expectations. For instance,unsupervised as they are, such neural mechanisms should be able to explain and realize the self-organizedacquisition of sensorimotor competencies. This paper proposes a new synaptic law which replaces Hebb's original metaphor by that of ``chaining together'' what ``changes together''. Starting from differential Hebbian learning,the new rule grounds the behavior of the agent directly in the internal synaptic dynamics.Therefore, one may call this a behavior-driven synaptic plasticity.Neurorobotics is an ideal testing ground for this new, unsupervised learning rule. This paper focuses on the close coupling between body, control, and environmentin challenging physical settings. The examples demonstrate how the new synaptic mechanism induces a self-determined ``search and converge'' strategy in behavior space, generating spontaneously a variety of sensorimotor competencies. The emerging behavior patterns are qualified by involving body and environment inan irreducible conjunction with the internal mechanism.The results may not only be of immediate interest for the further development of embodied intelligence.They also offer a new view on the role of self-learning processes in natural evolutionand in the brain.Videos and further details may be found under url{http://robot.informatik.uni-leipzig.de/research/supplementary/NeuroAutonomy/}.

  16. A mathematical analysis of the effects of Hebbian learning rules on the dynamics and structure of discrete-time random recurrent neural networks.

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    Siri, Benoît; Berry, Hugues; Cessac, Bruno; Delord, Bruno; Quoy, Mathias

    2008-12-01

    We present a mathematical analysis of the effects of Hebbian learning in random recurrent neural networks, with a generic Hebbian learning rule, including passive forgetting and different timescales, for neuronal activity and learning dynamics. Previous numerical work has reported that Hebbian learning drives the system from chaos to a steady state through a sequence of bifurcations. Here, we interpret these results mathematically and show that these effects, involving a complex coupling between neuronal dynamics and synaptic graph structure, can be analyzed using Jacobian matrices, which introduce both a structural and a dynamical point of view on neural network evolution. Furthermore, we show that sensitivity to a learned pattern is maximal when the largest Lyapunov exponent is close to 0. We discuss how neural networks may take advantage of this regime of high functional interest.

  17. A neuroanatomically grounded Hebbian-learning model of attention-language interactions in the human brain.

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    Garagnani, Max; Wennekers, Thomas; Pulvermüller, Friedemann

    2008-01-01

    Meaningful familiar stimuli and senseless unknown materials lead to different patterns of brain activation. A late major neurophysiological response indexing 'sense' is the negative component of event-related potential peaking at around 400 ms (N400), an event-related potential that emerges in attention-demanding tasks and is larger for senseless materials (e.g. meaningless pseudowords) than for matched meaningful stimuli (words). However, the mismatch negativity (latency 100-250 ms), an early automatic brain response elicited under distraction, is larger to words than to pseudowords, thus exhibiting the opposite pattern to that seen for the N400. So far, no theoretical account has been able to reconcile and explain these findings by means of a single, mechanistic neural model. We implemented a neuroanatomically grounded neural network model of the left perisylvian language cortex and simulated: (i) brain processes of early language acquisition and (ii) cortical responses to familiar word and senseless pseudoword stimuli. We found that variation of the area-specific inhibition (the model correlate of attention) modulated the simulated brain response to words and pseudowords, producing either an N400- or a mismatch negativity-like response depending on the amount of inhibition (i.e. available attentional resources). Our model: (i) provides a unifying explanatory account, at cortical level, of experimental observations that, so far, had not been given a coherent interpretation within a single framework; (ii) demonstrates the viability of purely Hebbian, associative learning in a multilayered neural network architecture; and (iii) makes clear predictions on the effects of attention on latency and magnitude of event-related potentials to lexical items. Such predictions have been confirmed by recent experimental evidence.

  18. Cooperation-induced topological complexity: a promising road to fault tolerance and Hebbian learning

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    Malgorzata eTuralska

    2012-03-01

    Full Text Available According to an increasing number of researchers intelligence emerges from criticality as a consequence of locality breakdown and long-range correlation, well known properties of phase transition processes. We study a model of interacting units, as an idealization of real cooperative systems such as the brain or a flock of birds, for the purpose of discussing the emergence of long-range correlation from the coupling of any unit with its nearest neighbors. We focus on the critical condition that has been recently shown to maximize information transport and we study the topological structure of the network of dynamically linked nodes. Although the topology of this network depends on the arbitrary choice of correlation threshold, namely the correlation intensity selected to establish a link between two nodes; the numerical calculations of this paper afford some important indications on the dynamically induced topology. The first important property is the emergence of a perception length as large as the flock size, thanks to some nodes with a large number of links, thus playing the leadership role. All the units are equivalent and leadership moves in time from one to another set of nodes, thereby insuring fault tolerance. Then we focus on the correlation threshold generating a scale-free topology with power index and we find that if this topological structure is selected to establish consensus through the linked nodes, the control parameter necessary to generate criticality is close to the critical value corresponding to the all-to-all coupling condition. We find that criticality in this case generates also a third state, corresponding to a total lack of consensus. However, we make a numerical analysis of the dynamically induced network, and we find that it consists of two almost independent structures, each of which is equivalent to a network in the all-to-all coupling condition. We argue that these results are compatible with Hebbian learning and

  19. A burst-based "Hebbian" learning rule at retinogeniculate synapses links retinal waves to activity-dependent refinement.

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    Daniel A Butts

    2007-03-01

    Full Text Available Patterned spontaneous activity in the developing retina is necessary to drive synaptic refinement in the lateral geniculate nucleus (LGN. Using perforated patch recordings from neurons in LGN slices during the period of eye segregation, we examine how such burst-based activity can instruct this refinement. Retinogeniculate synapses have a novel learning rule that depends on the latencies between pre- and postsynaptic bursts on the order of one second: coincident bursts produce long-lasting synaptic enhancement, whereas non-overlapping bursts produce mild synaptic weakening. It is consistent with "Hebbian" development thought to exist at this synapse, and we demonstrate computationally that such a rule can robustly use retinal waves to drive eye segregation and retinotopic refinement. Thus, by measuring plasticity induced by natural activity patterns, synaptic learning rules can be linked directly to their larger role in instructing the patterning of neural connectivity.

  20. Cortical plasticity induced by rapid Hebbian learning of novel tonal word-forms : Evidence from mismatch negativity

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    Yue, Jinxing; Bastiaanse, Roelien; Alter, Kai

    2014-01-01

    Although several experiments reported rapid cortical plasticity induced by passive exposure to novel segmental patterns, few studies have devoted attention to the neural dynamics during the rapid learning of novel tonal word-forms in tonal languages, such as Chinese. In the current study, native

  1. Adaptive Game Level Creation through Rank-based Interactive Evolution

    DEFF Research Database (Denmark)

    Liapis, Antonios; Martínez, Héctor Pérez; Togelius, Julian

    2013-01-01

    This paper introduces Rank-based Interactive Evolution (RIE) which is an alternative to interactive evolution driven by computational models of user preferences to generate personalized content. In RIE, the computational models are adapted to the preferences of users which, in turn, are used...... as fitness functions for the optimization of the generated content. The preference models are built via ranking-based preference learning, while the content is generated via evolutionary search. The proposed method is evaluated on the creation of strategy game maps, and its performance is tested using...

  2. Hebbian plasticity requires compensatory processes on multiple timescales

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    Gerstner, Wulfram

    2017-01-01

    We review a body of theoretical and experimental research on Hebbian and homeostatic plasticity, starting from a puzzling observation: while homeostasis of synapses found in experiments is a slow compensatory process, most mathematical models of synaptic plasticity use rapid compensatory processes (RCPs). Even worse, with the slow homeostatic plasticity reported in experiments, simulations of existing plasticity models cannot maintain network stability unless further control mechanisms are implemented. To solve this paradox, we suggest that in addition to slow forms of homeostatic plasticity there are RCPs which stabilize synaptic plasticity on short timescales. These rapid processes may include heterosynaptic depression triggered by episodes of high postsynaptic firing rate. While slower forms of homeostatic plasticity are not sufficient to stabilize Hebbian plasticity, they are important for fine-tuning neural circuits. Taken together we suggest that learning and memory rely on an intricate interplay of diverse plasticity mechanisms on different timescales which jointly ensure stability and plasticity of neural circuits. This article is part of the themed issue ‘Integrating Hebbian and homeostatic plasticity’. PMID:28093557

  3. Generative models of rich clubs in Hebbian neuronal networks and large-scale human brain networks.

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    Vértes, Petra E; Alexander-Bloch, Aaron; Bullmore, Edward T

    2014-10-05

    Rich clubs arise when nodes that are 'rich' in connections also form an elite, densely connected 'club'. In brain networks, rich clubs incur high physical connection costs but also appear to be especially valuable to brain function. However, little is known about the selection pressures that drive their formation. Here, we take two complementary approaches to this question: firstly we show, using generative modelling, that the emergence of rich clubs in large-scale human brain networks can be driven by an economic trade-off between connection costs and a second, competing topological term. Secondly we show, using simulated neural networks, that Hebbian learning rules also drive the emergence of rich clubs at the microscopic level, and that the prominence of these features increases with learning time. These results suggest that Hebbian learning may provide a neuronal mechanism for the selection of complex features such as rich clubs. The neural networks that we investigate are explicitly Hebbian, and we argue that the topological term in our model of large-scale brain connectivity may represent an analogous connection rule. This putative link between learning and rich clubs is also consistent with predictions that integrative aspects of brain network organization are especially important for adaptive behaviour. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  4. A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation.

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    Fiebig, Florian; Lansner, Anders

    2017-01-04

    A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism. Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and neurophysiology of the underlying

  5. Apoptosis, neurogenesis, and information content in Hebbian networks.

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    Crick, Christopher; Miranker, Willard

    2006-01-01

    The functional significance of alternate forms of plasticity in the brain (such as apoptosis and neurogenesis) is not easily observable with biological methods. Employing Hebbian dynamics for synaptic weight development, a three-layer neural network model of the hippocampus is used to simulate nonsupervised (autonomous) learning in the context of apoptosis and neurogenesis. This learning is applied to the characters of a pair of related alphabets, first the Roman and then the Greek, resulting in a set of encodings endogenously developed by the network. The learning performance takes the form of a U-shaped curve, showing that apoptosis and neurogenesis favorably inform memory development. We also discover that networks that converge very quickly on the Roman alphabet take much longer to handle the Greek, while networks which converge over an extended timeframe can then adapt very quickly to the new language. We find that the effect becomes increasingly pronounced as the number of neurons in the dentate gyrus layer decreases, and identify a strong correlation between cases where the Roman alphabet is quickly learned and cases where a few neurons saturate many of their weights almost immediately, minimizing participation of other neurons. Cases where learning the Roman alphabet requires more time lead to larger numbers of neurons participating with a larger diversity in synaptic weights. We present an information-theoretic argument about why this implies a better, more flexible learning system and why it leads to faster subsequent correlated Greek alphabet learning, and propose that the reason that apoptosis and neurogenesis work is that they promote this effect.

  6. The dependence of neuronal encoding efficiency on Hebbian plasticity and homeostatic regulation of neurotransmitter release

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    Faramarz eFaghihi

    2015-04-01

    Full Text Available Synapses act as information filters by different molecular mechanisms including retrograde messenger that affect neuronal spiking activity. One of the well-known effects of retrograde messenger in presynaptic neurons is a change of the probability of neurotransmitter release. Hebbian learning describe a strengthening of a synapse between a presynaptic input onto a postsynaptic neuron when both pre- and postsynaptic neurons are coactive. In this work, a theory of homeostatic regulation of neurotransmitter release by retrograde messenger and Hebbian plasticity in neuronal encoding is presented. Encoding efficiency was measured for different synaptic conditions. In order to gain high encoding efficiency, the spiking pattern of a neuron should be dependent on the intensity of the input and show low levels of noise. In this work, we represent spiking trains as zeros and ones (corresponding to non-spike or spike in a time bin, respectively as words with length equal to three. Then the frequency of each word (here eight words is measured using spiking trains. These frequencies are used to measure neuronal efficiency in different conditions and for different parameter values. Results show that neurons that have synapses acting as band-pass filters show the highest efficiency to encode their input when both Hebbian mechanism and homeostatic regulation of neurotransmitter release exist in synapses. Specifically, the integration of homeostatic regulation of feedback inhibition with Hebbian mechanism and homeostatic regulation of neurotransmitter release in the synapses leads to even higher efficiency when high stimulus intensity is presented to the neurons. However, neurons with synapses acting as high-pass filters show no remarkable increase in encoding efficiency for all simulated synaptic plasticity mechanisms.

  7. Reward-Modulated Hebbian Plasticity as Leverage for Partially Embodied Control in Compliant Robotics

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    Burms, Jeroen; Caluwaerts, Ken; Dambre, Joni

    2015-01-01

    In embodied computation (or morphological computation), part of the complexity of motor control is offloaded to the body dynamics. We demonstrate that a simple Hebbian-like learning rule can be used to train systems with (partial) embodiment, and can be extended outside of the scope of traditional neural networks. To this end, we apply the learning rule to optimize the connection weights of recurrent neural networks with different topologies and for various tasks. We then apply this learning rule to a simulated compliant tensegrity robot by optimizing static feedback controllers that directly exploit the dynamics of the robot body. This leads to partially embodied controllers, i.e., hybrid controllers that naturally integrate the computations that are performed by the robot body into a neural network architecture. Our results demonstrate the universal applicability of reward-modulated Hebbian learning. Furthermore, they demonstrate the robustness of systems trained with the learning rule. This study strengthens our belief that compliant robots should or can be seen as computational units, instead of dumb hardware that needs a complex controller. This link between compliant robotics and neural networks is also the main reason for our search for simple universal learning rules for both neural networks and robotics. PMID:26347645

  8. Reward-Modulated Hebbian Plasticity as Leverage for Partially Embodied Control in Compliant Robotics.

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    Burms, Jeroen; Caluwaerts, Ken; Dambre, Joni

    2015-01-01

    In embodied computation (or morphological computation), part of the complexity of motor control is offloaded to the body dynamics. We demonstrate that a simple Hebbian-like learning rule can be used to train systems with (partial) embodiment, and can be extended outside of the scope of traditional neural networks. To this end, we apply the learning rule to optimize the connection weights of recurrent neural networks with different topologies and for various tasks. We then apply this learning rule to a simulated compliant tensegrity robot by optimizing static feedback controllers that directly exploit the dynamics of the robot body. This leads to partially embodied controllers, i.e., hybrid controllers that naturally integrate the computations that are performed by the robot body into a neural network architecture. Our results demonstrate the universal applicability of reward-modulated Hebbian learning. Furthermore, they demonstrate the robustness of systems trained with the learning rule. This study strengthens our belief that compliant robots should or can be seen as computational units, instead of dumb hardware that needs a complex controller. This link between compliant robotics and neural networks is also the main reason for our search for simple universal learning rules for both neural networks and robotics.

  9. Reward modulated Hebbian plasticity as leverage for partially embodied control in compliant robotics

    Directory of Open Access Journals (Sweden)

    Jeroen eBurms

    2015-08-01

    Full Text Available In embodied computation (or morphological computation, part of the complexity of motor control is offloaded to the body dynamics. We demonstrate that a simple Hebbian-like learning rule can be used to train systems with (partial embodiment, and can be extended outside of the scope of traditional neural networks. To this end, we apply the learning rule to optimise the connection weights of recurrent neural networks with different topologies and for various tasks. We then apply this learning rule to a simulated compliant tensegrity robot by optimizing static feedback controllers that directly exploit the dynamics of the robot body. This leads to partially embodied controllers, i.e., hybrid controllers that naturally integrate the computations that are performed by the robot body into a neural network architecture. Our results demonstrate the universal applicability of reward-modulated Hebbian learning. Furthermore, they demonstrate the robustness of systems trained with the learning rule. This study strengthens our belief that compliant robots should or can be seen as computational units, instead of dumb hardware that needs a complex controller. This link between compliant robotics and neural networks is also the main reason for our search for simple universal learning rules for both neural networks and robotics.

  10. International Conference on Robust Rank-Based and Nonparametric Methods

    CERN Document Server

    McKean, Joseph

    2016-01-01

    The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaborated with Joseph McKean to develop underlying theory for these methods, obtain small sample corrections, and develop efficient algorithms for their computation. The papers cover the scope of the area, including robust nonparametric rank-based procedures through Bayesian and big data rank-based analyses. Areas of application include biostatistics and spatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably. These procedures generalize traditional Wilcoxon-type methods for one- and two-sample location problems. Research into these procedures has culminated in complete analyses for many of the models used in practice including linear, generalized linear, mixed, and nonlinear models. Settings are both multivariate and univariate. With the development of R packages in these areas, computation of these procedures is easily shared with r...

  11. Cocaine Promotes Coincidence Detection and Lowers Induction Threshold during Hebbian Associative Synaptic Potentiation in Prefrontal Cortex.

    Science.gov (United States)

    Ruan, Hongyu; Yao, Wei-Dong

    2017-01-25

    Addictive drugs usurp neural plasticity mechanisms that normally serve reward-related learning and memory, primarily by evoking changes in glutamatergic synaptic strength in the mesocorticolimbic dopamine circuitry. Here, we show that repeated cocaine exposure in vivo does not alter synaptic strength in the mouse prefrontal cortex during an early period of withdrawal, but instead modifies a Hebbian quantitative synaptic learning rule by broadening the temporal window and lowers the induction threshold for spike-timing-dependent LTP (t-LTP). After repeated, but not single, daily cocaine injections, t-LTP in layer V pyramidal neurons is induced at +30 ms, a normally ineffective timing interval for t-LTP induction in saline-exposed mice. This cocaine-induced, extended-timing t-LTP lasts for ∼1 week after terminating cocaine and is accompanied by an increased susceptibility to potentiation by fewer pre-post spike pairs, indicating a reduced t-LTP induction threshold. Basal synaptic strength and the maximal attainable t-LTP magnitude remain unchanged after cocaine exposure. We further show that the cocaine facilitation of t-LTP induction is caused by sensitized D1-cAMP/protein kinase A dopamine signaling in pyramidal neurons, which then pathologically recruits voltage-gated l-type Ca 2+ channels that synergize with GluN2A-containing NMDA receptors to drive t-LTP at extended timing. Our results illustrate a mechanism by which cocaine, acting on a key neuromodulation pathway, modifies the coincidence detection window during Hebbian plasticity to facilitate associative synaptic potentiation in prefrontal excitatory circuits. By modifying rules that govern activity-dependent synaptic plasticity, addictive drugs can derail the experience-driven neural circuit remodeling process important for executive control of reward and addiction. It is believed that addictive drugs often render an addict's brain reward system hypersensitive, leaving the individual more susceptible to

  12. Evidence from a rare case-study for Hebbian-like changes in structural connectivity induced by long-term deep brain stimulation

    Directory of Open Access Journals (Sweden)

    Tim J Van Hartevelt

    2015-06-01

    Full Text Available It is unclear whether Hebbian-like learning occurs at the level of long-range white matter connections in humans, i.e. where measurable changes in structural connectivity are correlated with changes in functional connectivity. However, the behavioral changes observed after deep brain stimulation (DBS suggest the existence of such Hebbian-like mechanisms occurring at the structural level with functional consequences. In this rare case study, we obtained the full network of white matter connections of one patient with Parkinson's disease before and after long-term DBS and combined it with a computational model of ongoing activity to investigate the effects of DBS-induced long-term structural changes. The results show that the long-term effects of DBS on resting-state functional connectivity is best obtained in the computational model by changing the structural weights from the subthalamic nucleus to the putamen and the thalamus in a Hebbian-like manner. Moreover, long-term DBS also significantly changed the structural connectivity towards normality in terms of model-based measures of segregation and integration of information processing, two key concepts of brain organization. This novel approach using computational models to model the effects of Hebbian-like changes in structural connectivity allowed us to causally identify the possible underlying neural mechanisms of long-term DBS using rare case study data. In time, this could help predict the efficacy of individual DBS targeting and identify novel DBS targets.

  13. An Approximation of the Error Backpropagation Algorithm in a Predictive Coding Network with Local Hebbian Synaptic Plasticity.

    Science.gov (United States)

    Whittington, James C R; Bogacz, Rafal

    2017-05-01

    To efficiently learn from feedback, cortical networks need to update synaptic weights on multiple levels of cortical hierarchy. An effective and well-known algorithm for computing such changes in synaptic weights is the error backpropagation algorithm. However, in this algorithm, the change in synaptic weights is a complex function of weights and activities of neurons not directly connected with the synapse being modified, whereas the changes in biological synapses are determined only by the activity of presynaptic and postsynaptic neurons. Several models have been proposed that approximate the backpropagation algorithm with local synaptic plasticity, but these models require complex external control over the network or relatively complex plasticity rules. Here we show that a network developed in the predictive coding framework can efficiently perform supervised learning fully autonomously, employing only simple local Hebbian plasticity. Furthermore, for certain parameters, the weight change in the predictive coding model converges to that of the backpropagation algorithm. This suggests that it is possible for cortical networks with simple Hebbian synaptic plasticity to implement efficient learning algorithms in which synapses in areas on multiple levels of hierarchy are modified to minimize the error on the output.

  14. Rank-Based Analysis of Unbalanced Repeated Measures Data

    Directory of Open Access Journals (Sweden)

    M. Mushfiqur Rashid

    2012-07-01

    Full Text Available Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} In this article, we have developed a rank (intra-subject based analysis of clinical trials with unbalanced repeated measures data. We assume that the errors within each patient are exchangeable and continuous random variables. This rank-based inference is valid when the unbalanced data are missing either completely at random or by design. A drop in dispersion test is developed for general linear hypotheses. A numerical example is given to illustrate the procedure.

  15. Enhanced detection threshold for in vivo cortical stimulation produced by Hebbian conditioning

    Science.gov (United States)

    Rebesco, James M.; Miller, Lee E.

    2011-02-01

    Normal brain function requires constant adaptation, as an organism learns to associate important sensory stimuli with the appropriate motor actions. Neurological disorders may disrupt these learned associations and require the nervous system to reorganize itself. As a consequence, neural plasticity is a crucial component of normal brain function and a critical mechanism for recovery from injury. Associative, or Hebbian, pairing of pre- and post-synaptic activity has been shown to alter stimulus-evoked responses in vivo; however, to date, such protocols have not been shown to affect the animal's subsequent behavior. We paired stimulus trains separated by a brief time delay to two electrodes in rat sensorimotor cortex, which changed the statistical pattern of spikes during subsequent behavior. These changes were consistent with strengthened functional connections from the leading electrode to the lagging electrode. We then trained rats to respond to a microstimulation cue, and repeated the paradigm using the cue electrode as the leading electrode. This pairing lowered the rat's ICMS-detection threshold, with the same dependence on intra-electrode time lag that we found for the functional connectivity changes. The timecourse of the behavioral effects was very similar to that of the connectivity changes. We propose that the behavioral changes were a consequence of strengthened functional connections from the cue electrode to other regions of sensorimotor cortex. Such paradigms might be used to augment recovery from a stroke, or to promote adaptation in a bidirectional brain-machine interface.

  16. Robotic Assistance for Training Finger Movement Using a Hebbian Model: A Randomized Controlled Trial.

    Science.gov (United States)

    Rowe, Justin B; Chan, Vicky; Ingemanson, Morgan L; Cramer, Steven C; Wolbrecht, Eric T; Reinkensmeyer, David J

    2017-08-01

    Robots that physically assist movement are increasingly used in rehabilitation therapy after stroke, yet some studies suggest robotic assistance discourages effort and reduces motor learning. To determine the therapeutic effects of high and low levels of robotic assistance during finger training. We designed a protocol that varied the amount of robotic assistance while controlling the number, amplitude, and exerted effort of training movements. Participants (n = 30) with a chronic stroke and moderate hemiparesis (average Box and Blocks Test 32 ± 18 and upper extremity Fugl-Meyer score 46 ± 12) actively moved their index and middle fingers to targets to play a musical game similar to GuitarHero 3 h/wk for 3 weeks. The participants were randomized to receive high assistance (causing 82% success at hitting targets) or low assistance (55% success). Participants performed ~8000 movements during 9 training sessions. Both groups improved significantly at the 1-month follow-up on functional and impairment-based motor outcomes, on depression scores, and on self-efficacy of hand function, with no difference between groups in the primary endpoint (change in Box and Blocks). High assistance boosted motivation, as well as secondary motor outcomes (Fugl-Meyer and Lateral Pinch Strength)-particularly for individuals with more severe finger motor deficits. Individuals with impaired finger proprioception at baseline benefited less from the training. Robot-assisted training can promote key psychological outcomes known to modulate motor learning and retention. Furthermore, the therapeutic effectiveness of robotic assistance appears to derive at least in part from proprioceptive stimulation, consistent with a Hebbian plasticity model.

  17. Ranking Based Locality Sensitive Hashing Enabled Cancelable Biometrics: Index-of-Max Hashing

    OpenAIRE

    Jin, Zhe; Lai, Yen-Lung; Hwang, Jung-Yeon; Kim, Soohyung; Teoh, Andrew Beng Jin

    2017-01-01

    In this paper, we propose a ranking based locality sensitive hashing inspired two-factor cancelable biometrics, dubbed "Index-of-Max" (IoM) hashing for biometric template protection. With externally generated random parameters, IoM hashing transforms a real-valued biometric feature vector into discrete index (max ranked) hashed code. We demonstrate two realizations from IoM hashing notion, namely Gaussian Random Projection based and Uniformly Random Permutation based hashing schemes. The disc...

  18. The Use of Hebbian Cell Assemblies for Nonlinear Computation

    DEFF Research Database (Denmark)

    Tetzlaff, Christian; Dasgupta, Sakyasingha; Kulvicius, Tomas

    2015-01-01

    preserving a rich diversity of neural dynamics needed for computation is still unknown. Here we show that the combination of synaptic plasticity with the slower process of synaptic scaling achieves (i) the formation of cell assemblies and (ii) enhances the diversity of neural dynamics facilitating...... the learning of complex calculations. Due to synaptic scaling the dynamics of different cell assemblies do not interfere with each other. As a consequence, this type of self-organization allows executing a difficult, six degrees of freedom, manipulation task with a robot where assemblies need to learn...

  19. Pareto-Ranking Based Quantum-Behaved Particle Swarm Optimization for Multiobjective Optimization

    Directory of Open Access Journals (Sweden)

    Na Tian

    2015-01-01

    Full Text Available A study on pareto-ranking based quantum-behaved particle swarm optimization (QPSO for multiobjective optimization problems is presented in this paper. During the iteration, an external repository is maintained to remember the nondominated solutions, from which the global best position is chosen. The comparison between different elitist selection strategies (preference order, sigma value, and random selection is performed on four benchmark functions and two metrics. The results demonstrate that QPSO with preference order has comparative performance with sigma value according to different number of objectives. Finally, QPSO with sigma value is applied to solve multiobjective flexible job-shop scheduling problems.

  20. Stream-based Hebbian eigenfilter for real-time neuronal spike discrimination

    Directory of Open Access Journals (Sweden)

    Yu Bo

    2012-04-01

    Full Text Available Abstract Background Principal component analysis (PCA has been widely employed for automatic neuronal spike sorting. Calculating principal components (PCs is computationally expensive, and requires complex numerical operations and large memory resources. Substantial hardware resources are therefore needed for hardware implementations of PCA. General Hebbian algorithm (GHA has been proposed for calculating PCs of neuronal spikes in our previous work, which eliminates the needs of computationally expensive covariance analysis and eigenvalue decomposition in conventional PCA algorithms. However, large memory resources are still inherently required for storing a large volume of aligned spikes for training PCs. The large size memory will consume large hardware resources and contribute significant power dissipation, which make GHA difficult to be implemented in portable or implantable multi-channel recording micro-systems. Method In this paper, we present a new algorithm for PCA-based spike sorting based on GHA, namely stream-based Hebbian eigenfilter, which eliminates the inherent memory requirements of GHA while keeping the accuracy of spike sorting by utilizing the pseudo-stationarity of neuronal spikes. Because of the reduction of large hardware storage requirements, the proposed algorithm can lead to ultra-low hardware resources and power consumption of hardware implementations, which is critical for the future multi-channel micro-systems. Both clinical and synthetic neural recording data sets were employed for evaluating the accuracy of the stream-based Hebbian eigenfilter. The performance of spike sorting using stream-based eigenfilter and the computational complexity of the eigenfilter were rigorously evaluated and compared with conventional PCA algorithms. Field programmable logic arrays (FPGAs were employed to implement the proposed algorithm, evaluate the hardware implementations and demonstrate the reduction in both power consumption and

  1. RANWAR: rank-based weighted association rule mining from gene expression and methylation data.

    Science.gov (United States)

    Mallik, Saurav; Mukhopadhyay, Anirban; Maulik, Ujjwal

    2015-01-01

    Ranking of association rules is currently an interesting topic in data mining and bioinformatics. The huge number of evolved rules of items (or, genes) by association rule mining (ARM) algorithms makes confusion to the decision maker. In this article, we propose a weighted rule-mining technique (say, RANWAR or rank-based weighted association rule-mining) to rank the rules using two novel rule-interestingness measures, viz., rank-based weighted condensed support (wcs) and weighted condensed confidence (wcc) measures to bypass the problem. These measures are basically depended on the rank of items (genes). Using the rank, we assign weight to each item. RANWAR generates much less number of frequent itemsets than the state-of-the-art association rule mining algorithms. Thus, it saves time of execution of the algorithm. We run RANWAR on gene expression and methylation datasets. The genes of the top rules are biologically validated by Gene Ontologies (GOs) and KEGG pathway analyses. Many top ranked rules extracted from RANWAR that hold poor ranks in traditional Apriori, are highly biologically significant to the related diseases. Finally, the top rules evolved from RANWAR, that are not in Apriori, are reported.

  2. Detecting determinism with improved sensitivity in time series: Rank-based nonlinear predictability score

    Science.gov (United States)

    Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G.

    2014-09-01

    The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

  3. Detecting determinism with improved sensitivity in time series: rank-based nonlinear predictability score.

    Science.gov (United States)

    Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G

    2014-09-01

    The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

  4. Domain-specific and domain-general constraints on word and sequence learning

    National Research Council Canada - National Science Library

    Archibald, Lisa M. D; Joanisse, Marc F

    2013-01-01

    ... with and without specific deficits in either language or working memory. Children recalled lists of words in a Hebbian learning protocol in which occasional lists repeated, yielding improved recall over the course of the task on the repeated lists...

  5. Combinations of stroke neurorehabilitation to facilitate motor recovery: perspectives on Hebbian plasticity and homeostatic metaplasticity.

    Science.gov (United States)

    Takeuchi, Naoyuki; Izumi, Shin-Ichi

    2015-01-01

    Motor recovery after stroke involves developing new neural connections, acquiring new functions, and compensating for impairments. These processes are related to neural plasticity. Various novel stroke rehabilitation techniques based on basic science and clinical studies of neural plasticity have been developed to aid motor recovery. Current research aims to determine whether using combinations of these techniques can synergistically improve motor recovery. When different stroke neurorehabilitation therapies are combined, the timing of each therapeutic program must be considered to enable optimal neural plasticity. Synchronizing stroke rehabilitation with voluntary neural and/or muscle activity can lead to motor recovery by targeting Hebbian plasticity. This reinforces the neural connections between paretic muscles and the residual motor area. Homeostatic metaplasticity, which stabilizes the activity of neurons and neural circuits, can either augment or reduce the synergic effect depending on the timing of combination therapy and types of neurorehabilitation that are used. Moreover, the possibility that the threshold and degree of induced plasticity can be altered after stroke should be noted. This review focuses on the mechanisms underlying combinations of neurorehabilitation approaches and their future clinical applications. We suggest therapeutic approaches for cortical reorganization and maximal functional gain in patients with stroke, based on the processes of Hebbian plasticity and homeostatic metaplasticity. Few of the possible combinations of stroke neurorehabilitation have been tested experimentally; therefore, further studies are required to determine the appropriate combination for motor recovery.

  6. Stochastic Thermodynamics of Learning

    Science.gov (United States)

    Goldt, Sebastian; Seifert, Udo

    2017-01-01

    Virtually every organism gathers information about its noisy environment and builds models from those data, mostly using neural networks. Here, we use stochastic thermodynamics to analyze the learning of a classification rule by a neural network. We show that the information acquired by the network is bounded by the thermodynamic cost of learning and introduce a learning efficiency η ≤1 . We discuss the conditions for optimal learning and analyze Hebbian learning in the thermodynamic limit.

  7. Assembly line balancing with resource constraints using new rank-based crossovers

    Science.gov (United States)

    Kamarudin, N. H.; Rashid, M. F. F. Ab.

    2017-10-01

    Assembly line balancing (ALB) is about distributing the assembly tasks into workstations with the almost equal workload. Recently, researchers started to consider the resource constraints in ALB such as machine and worker, to make the assembly layout more efficient. This paper presents an ALB with resource constraints (ALB-RC) to minimize the workstation, machine and worker. For the optimization purpose, genetic algorithm (GA) with two new crossovers is introduced. The crossovers are developed using ranking approach and known as rank-based crossover type I and type II (RBC-I and RBC-II). These crossovers are tested against popular combinatorial crossovers using 17 benchmark problems. The computational experiment results indicated that the RBC-II has better overall performance because of the balance between divergence and guidance in the reproduction process. In future, the RBC-I and RBC-II will be tested for different variant of ALB problems.

  8. An Efficient VLSI Architecture for Multi-Channel Spike Sorting Using a Generalized Hebbian Algorithm.

    Science.gov (United States)

    Chen, Ying-Lun; Hwang, Wen-Jyi; Ke, Chi-En

    2015-08-13

    A novel VLSI architecture for multi-channel online spike sorting is presented in this paper. In the architecture, the spike detection is based on nonlinear energy operator (NEO), and the feature extraction is carried out by the generalized Hebbian algorithm (GHA). To lower the power consumption and area costs of the circuits, all of the channels share the same core for spike detection and feature extraction operations. Each channel has dedicated buffers for storing the detected spikes and the principal components of that channel. The proposed circuit also contains a clock gating system supplying the clock to only the buffers of channels currently using the computation core to further reduce the power consumption. The architecture has been implemented by an application-specific integrated circuit (ASIC) with 90-nm technology. Comparisons to the existing works show that the proposed architecture has lower power consumption and hardware area costs for real-time multi-channel spike detection and feature extraction.

  9. An objective function for Hebbian self-limiting synaptic plasticity rules

    Science.gov (United States)

    Gros, Claudius; Eckmann, Samuel; Echeveste, Rodrigo

    Objective functions, formulated in terms of information theoretical measures with respect to the input and output probability distributions, provide a useful framework for the formulation of guiding principles for information processing systems, such as neural networks. In the present work, a guiding principle for neural plasticity is formulated in terms of an objective function expressed as the Fisher information with respect to an operator that we denote as the synaptic flux. By minimization of this objective function, we obtain Hebbian self-limiting synaptic plasticity rules, avoiding unbounded weight growth. Furthermore, we show how the rules are selective to directions of maximal negative excess kurtosis, making them suitable for independent component analysis. As an application, the non-linear bars problem is studied, in which each neuron is presented with a non-linear superposition of horizontal and vertical bars. We show that, under the here presented rules, the neurons are able to find the independent components of the input.

  10. Hebbian Wiring Plasticity Generates Efficient Network Structures for Robust Inference with Synaptic Weight Plasticity.

    Science.gov (United States)

    Hiratani, Naoki; Fukai, Tomoki

    2016-01-01

    In the adult mammalian cortex, a small fraction of spines are created and eliminated every day, and the resultant synaptic connection structure is highly nonrandom, even in local circuits. However, it remains unknown whether a particular synaptic connection structure is functionally advantageous in local circuits, and why creation and elimination of synaptic connections is necessary in addition to rich synaptic weight plasticity. To answer these questions, we studied an inference task model through theoretical and numerical analyses. We demonstrate that a robustly beneficial network structure naturally emerges by combining Hebbian-type synaptic weight plasticity and wiring plasticity. Especially in a sparsely connected network, wiring plasticity achieves reliable computation by enabling efficient information transmission. Furthermore, the proposed rule reproduces experimental observed correlation between spine dynamics and task performance.

  11. Fuzzy ranking based non-dominated sorting genetic algorithm-II for network overload alleviation

    Directory of Open Access Journals (Sweden)

    Pandiarajan K.

    2014-09-01

    Full Text Available This paper presents an effective method of network overload management in power systems. The three competing objectives 1 generation cost 2 transmission line overload and 3 real power loss are optimized to provide pareto-optimal solutions. A fuzzy ranking based non-dominated sorting genetic algorithm-II (NSGA-II is used to solve this complex nonlinear optimization problem. The minimization of competing objectives is done by generation rescheduling. Fuzzy ranking method is employed to extract the best compromise solution out of the available non-dominated solutions depending upon its highest rank. N-1 contingency analysis is carried out to identify the most severe lines and those lines are selected for outage. The effectiveness of the proposed approach is demonstrated for different contingency cases in IEEE 30 and IEEE 118 bus systems with smooth cost functions and their results are compared with other single objective evolutionary algorithms like Particle swarm optimization (PSO and Differential evolution (DE. Simulation results show the effectiveness of the proposed approach to generate well distributed pareto-optimal non-dominated solutions of multi-objective problem

  12. Data depth and rank-based tests for covariance and spectral density matrices

    KAUST Repository

    Chau, Joris

    2017-06-26

    In multivariate time series analysis, objects of primary interest to study cross-dependences in the time series are the autocovariance or spectral density matrices. Non-degenerate covariance and spectral density matrices are necessarily Hermitian and positive definite, and our primary goal is to develop new methods to analyze samples of such matrices. The main contribution of this paper is the generalization of the concept of statistical data depth for collections of covariance or spectral density matrices by exploiting the geometric properties of the space of Hermitian positive definite matrices as a Riemannian manifold. This allows one to naturally characterize most central or outlying matrices, but also provides a practical framework for rank-based hypothesis testing in the context of samples of covariance or spectral density matrices. First, the desired properties of a data depth function acting on the space of Hermitian positive definite matrices are presented. Second, we propose two computationally efficient pointwise and integrated data depth functions that satisfy each of these requirements. Several applications of the developed methodology are illustrated by the analysis of collections of spectral matrices in multivariate brain signal time series datasets.

  13. Rank-based biomarker index to assess cadmium ecotoxicity on the earthworm Eisenia andrei.

    Science.gov (United States)

    Panzarino, O; Hyršl, P; Dobeš, P; Vojtek, L; Vernile, P; Bari, G; Terzano, R; Spagnuolo, M; de Lillo, E

    2016-02-01

    A proper soil risk assessment needs to estimate the processes that affect the fate and the behaviour of a contaminant, which are influenced by soil biotic and abiotic components. For this reason, the measurement of biomarkers in soil bioindicator organisms, such as earthworms, has recently received increasing attention. In this study, the earthworm Eisenia andrei was used to assess the pollutant-induced stress syndrome after exposure to sublethal concentrations of Cd (10 or 100 μg g(-1)) in OECD soil, after 14 d of exposure. Cadmium bioaccumulation and potential biomarkers such as catalase (CAT), hydrogen peroxide (H2O2), glutathione-S-transferase (GST), malondialdehyde (MDA), phenoloxidase (PO), metallothioneins (MTs) and genotoxic damage were determined. Results suggested that the exposure to 10 and 100 μg g(-1) Cd significantly increased Cd bioaccumulation, MTs and MDA; 100 μg g(-1) Cd contamination evidenced significantly higher values of H2O2 content and PO activity; CAT activity was inhibited at the higher concentration while GST and Comet assay did not show any significant differences from the control. Rank-based biomarker index showed that both different contaminated soils had an effect on the earthworms and allowed to validate the ecotoxicological relevance of this battery of biomarkers for a promising integrated multi-marker approach in soil monitoring and assessment. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Rank-Based Methods for Selection of Landscape Metrics for Land Cover Pattern Change Detection

    Directory of Open Access Journals (Sweden)

    Priyakant Sinha

    2016-02-01

    Full Text Available Often landscape metrics are not thoroughly evaluated with respect to remote sensing data characteristics, such as their behavior in relation to variation in spatial and temporal resolution, number of land cover classes or dominant land cover categories. In such circumstances, it may be difficult to ascertain whether a change in a metric is due to landscape pattern change or due to the inherent variability in multi-temporal data. This study builds on this important consideration and proposes a rank-based metric selection process through computation of four difference-based indices (β, γ, ξ and θ using a Max–Min/Max normalization approach. Land cover classification was carried out for two contrasting provinces, the Liverpool Range (LR and Liverpool Plains (LP, of the Brigalow Belt South Bioregion (BBSB of NSW, Australia. Landsat images, Multi Spectral Scanner (MSS of 1972–1973 and TM of 1987–1988, 1993–1994, 1999–2000 and 2009–2010 were classified using object-based image analysis methods. A total of 30 landscape metrics were computed and their sensitivities towards variation in spatial and temporal resolutions, number of land cover classes and dominant land cover categories were evaluated by computing a score based on Max–Min/Max normalization. The landscape metrics selected on the basis of the proposed methods (Diversity index (MSIDI, Area weighted mean patch fractal dimension (SHAPE_AM, Mean core area (CORE_MN, Total edge (TE, No. of patches (NP, Contagion index (CONTAG, Mean nearest neighbor index (ENN_MN and Mean patch fractal dimension (FRAC_MN were successful and effective in identifying changes over five different change periods. Major changes in land cover pattern after 1993 were observed, and though the trends were similar in both cases, the LP region became more fragmented than the LR. The proposed method was straightforward to apply, and can deal with multiple metrics when selection of an appropriate set can become

  15. A rank-based sequence aligner with applications in phylogenetic analysis.

    Directory of Open Access Journals (Sweden)

    Liviu P Dinu

    Full Text Available Recent tools for aligning short DNA reads have been designed to optimize the trade-off between correctness and speed. This paper introduces a method for assigning a set of short DNA reads to a reference genome, under Local Rank Distance (LRD. The rank-based aligner proposed in this work aims to improve correctness over speed. However, some indexing strategies to speed up the aligner are also investigated. The LRD aligner is improved in terms of speed by storing [Formula: see text]-mer positions in a hash table for each read. Another improvement, that produces an approximate LRD aligner, is to consider only the positions in the reference that are likely to represent a good positional match of the read. The proposed aligner is evaluated and compared to other state of the art alignment tools in several experiments. A set of experiments are conducted to determine the precision and the recall of the proposed aligner, in the presence of contaminated reads. In another set of experiments, the proposed aligner is used to find the order, the family, or the species of a new (or unknown organism, given only a set of short Next-Generation Sequencing DNA reads. The empirical results show that the aligner proposed in this work is highly accurate from a biological point of view. Compared to the other evaluated tools, the LRD aligner has the important advantage of being very accurate even for a very low base coverage. Thus, the LRD aligner can be considered as a good alternative to standard alignment tools, especially when the accuracy of the aligner is of high importance. Source code and UNIX binaries of the aligner are freely available for future development and use at http://lrd.herokuapp.com/aligners. The software is implemented in C++ and Java, being supported on UNIX and MS Windows.

  16. A rank based social norms model of how people judge their levels of drunkenness whilst intoxicated.

    Science.gov (United States)

    Moore, Simon C; Wood, Alex M; Moore, Laurence; Shepherd, Jonathan; Murphy, Simon; Brown, Gordon D A

    2016-09-13

    A rank based social norms model predicts that drinkers' judgements about their drinking will be based on the rank of their breath alcohol level amongst that of others in the immediate environment, rather than their actual breath alcohol level, with lower relative rank associated with greater feelings of safety. This study tested this hypothesis and examined how people judge their levels of drunkenness and the health consequences of their drinking whilst they are intoxicated in social drinking environments. Breath alcohol testing of 1,862 people (mean age = 26.96 years; 61.86 % male) in drinking environments. A subset (N = 400) also answered four questions asking about their perceptions of their drunkenness and the health consequences of their drinking (plus background measures). Perceptions of drunkenness and the health consequences of drinking were regressed on: (a) breath alcohol level, (b) the rank of the breath alcohol level amongst that of others in the same environment, and (c) covariates. Only rank of breath alcohol level predicted perceptions: How drunk they felt (b 3.78, 95 % CI 1.69 5.87), how extreme they regarded their drinking that night (b 3.7, 95 % CI 1.3 6.20), how at risk their long-term health was due to their current level of drinking (b 4.1, 95 % CI 0.2 8.0) and how likely they felt they would experience liver cirrhosis (b 4.8. 95 % CI 0.7 8.8). People were more influenced by more sober others than by more drunk others. Whilst intoxicated and in drinking environments, people base judgements regarding their drinking on how their level of intoxication ranks relative to that of others of the same gender around them, not on their actual levels of intoxication. Thus, when in the company of others who are intoxicated, drinkers were found to be more likely to underestimate their own level of drinking, drunkenness and associated risks. The implications of these results, for example that increasing the numbers of sober people in night time

  17. A rank based social norms model of how people judge their levels of drunkenness whilst intoxicated

    Directory of Open Access Journals (Sweden)

    Simon C. Moore

    2016-09-01

    Full Text Available Abstract Background A rank based social norms model predicts that drinkers’ judgements about their drinking will be based on the rank of their breath alcohol level amongst that of others in the immediate environment, rather than their actual breath alcohol level, with lower relative rank associated with greater feelings of safety. This study tested this hypothesis and examined how people judge their levels of drunkenness and the health consequences of their drinking whilst they are intoxicated in social drinking environments. Methods Breath alcohol testing of 1,862 people (mean age = 26.96 years; 61.86 % male in drinking environments. A subset (N = 400 also answered four questions asking about their perceptions of their drunkenness and the health consequences of their drinking (plus background measures. Results Perceptions of drunkenness and the health consequences of drinking were regressed on: (a breath alcohol level, (b the rank of the breath alcohol level amongst that of others in the same environment, and (c covariates. Only rank of breath alcohol level predicted perceptions: How drunk they felt (b 3.78, 95 % CI 1.69 5.87, how extreme they regarded their drinking that night (b 3.7, 95 % CI 1.3 6.20, how at risk their long-term health was due to their current level of drinking (b 4.1, 95 % CI 0.2 8.0 and how likely they felt they would experience liver cirrhosis (b 4.8. 95 % CI 0.7 8.8. People were more influenced by more sober others than by more drunk others. Conclusion Whilst intoxicated and in drinking environments, people base judgements regarding their drinking on how their level of intoxication ranks relative to that of others of the same gender around them, not on their actual levels of intoxication. Thus, when in the company of others who are intoxicated, drinkers were found to be more likely to underestimate their own level of drinking, drunkenness and associated risks. The implications of these results, for example

  18. Neural development of binaural tuning through Hebbian learning predicts frequency-dependent best delays.

    Science.gov (United States)

    Fontaine, Bertrand; Brette, Romain

    2011-08-10

    Birds use microsecond differences in the arrival times of the sounds at the two ears to infer the location of a sound source in the horizontal plane. These interaural time differences (ITDs) are encoded by binaural neurons which fire more when the ITD matches their "best delay." In the textbook model of sound localization, the best delays of binaural neurons reflect the differences in axonal delays of their monaural inputs, but recent observations have cast doubts on this classical view because best delays were found to depend on preferred frequency. Here, we show that these observations are in fact consistent with the notion that best delays are created by differences in axonal delays, provided ITD tuning is created during development through spike-timing-dependent plasticity: basilar membrane filtering results in correlations between inputs to binaural neurons, which impact the selection of synapses during development, leading to the observed distribution of best delays.

  19. Cooperation-Induced Topological Complexity: A Promising Road to Fault Tolerance and Hebbian Learning

    Science.gov (United States)

    2012-03-16

    Information Science Directorate, United States Army Research Office, Durham, NC, USA 4 Istituto di Fisiologia Clinica del Consiglio Nazionale delle...Vadim Uritsky, Catholic University of America at NASA Goddard Space Flight Center, USA *Correspondence: Paolo Allegrini , Istituto di Fisiologia Clinica

  20. A novel generic hebbian ordering-based fuzzy rule base reduction approach to mamdani neuro-fuzzy system.

    Science.gov (United States)

    Liu, Feng; Quek, Chai; Ng, Geok See

    2007-06-01

    There are two important issues in neuro-fuzzy modeling: (1) interpretability--the ability to describe the behavior of the system in an interpretable way--and (2) accuracy--the ability to approximate the outcome of the system accurately. As these two objectives usually exert contradictory requirements on the neuro-fuzzy model, certain compromise has to be undertaken. This letter proposes a novel rule reduction algorithm, namely, Hebb rule reduction, and an iterative tuning process to balance interpretability and accuracy. The Hebb rule reduction algorithm uses Hebbian ordering, which represents the degree of coverage of the samples by the rule, as an importance measure of each rule to merge the membership functions and hence reduces the number of the rules. Similar membership functions (MFs) are merged by a specified similarity measure in an order of Hebbian importance, and the resultant equivalent rules are deleted from the rule base. The rule with a higher Hebbian importance will be retained among a set of rules. The MFs are tuned through the least mean square (LMS) algorithm to reduce the modeling error. The tuning of the MFs and the reduction of the rules proceed iteratively to achieve a balance between interpretability and accuracy. Three published data sets by Nakanishi (Nakanishi, Turksen, & Sugeno, 1993), the Pat synthetic data set (Pal, Mitra, & Mitra, 2003), and the traffic flow density prediction data set are used as benchmarks to demonstrate the effectiveness of the proposed method. Good interpretability, as well as high modeling accuracy, are derivable simultaneously and are suitably benchmarked against other well-established neuro-fuzzy models.

  1. An Adaptive Temporal-Causal Network Model for Enabling Learning of Social Interaction

    NARCIS (Netherlands)

    Commu, Charlotte; Theelen, Mathilde; Treur, J.

    2017-01-01

    In this study, an adaptive temporal-causal network model is present-ed for learning of basic skills for social interaction. It focuses on greeting a known person and how that relates to learning how to recognize a person from seeing his or her face. The model involves a Hebbian learning process. The

  2. An Efficient Normalized Rank Based SVM for Room Level Indoor WiFi Localization with Diverse Devices

    Directory of Open Access Journals (Sweden)

    Yasmine Rezgui

    2017-01-01

    Full Text Available This paper proposes an efficient and effective WiFi fingerprinting-based indoor localization algorithm, which uses the Received Signal Strength Indicator (RSSI of WiFi signals. In practical harsh indoor environments, RSSI variation and hardware variance can significantly degrade the performance of fingerprinting-based localization methods. To address the problem of hardware variance and signal fluctuation in WiFi fingerprinting-based localization, we propose a novel normalized rank based Support Vector Machine classifier (NR-SVM. Moving from RSSI value based analysis to the normalized rank transformation based analysis, the principal features are prioritized and the dimensionalities of signature vectors are taken into account. The proposed method has been tested using sixteen different devices in a shopping mall with 88 shops. The experimental results demonstrate its robustness with no less than 98.75% correct estimation in 93.75% of the tested cases and 100% correct rate in 56.25% of cases. In the experiments, the new method shows better performance over the KNN, Naïve Bayes, Random Forest, and Neural Network algorithms. Furthermore, we have compared the proposed approach with three popular calibration-free transformation based methods, including difference method (DIFF, Signal Strength Difference (SSD, and the Hyperbolic Location Fingerprinting (HLF based SVM. The results show that the NR-SVM outperforms these popular methods.

  3. A rank-based approach for correcting systematic biases in spatial disaggregation of coarse-scale climate simulations

    Science.gov (United States)

    Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

    2017-07-01

    Use of General Circulation Model (GCM) precipitation and evapotranspiration sequences for hydrologic modelling can result in unrealistic simulations due to the coarse scales at which GCMs operate and the systematic biases they contain. The Bias Correction Spatial Disaggregation (BCSD) method is a popular statistical downscaling and bias correction method developed to address this issue. The advantage of BCSD is its ability to reduce biases in the distribution of precipitation totals at the GCM scale and then introduce more realistic variability at finer scales than simpler spatial interpolation schemes. Although BCSD corrects biases at the GCM scale before disaggregation; at finer spatial scales biases are re-introduced by the assumptions made in the spatial disaggregation process. Our study focuses on this limitation of BCSD and proposes a rank-based approach that aims to reduce the spatial disaggregation bias especially for both low and high precipitation extremes. BCSD requires the specification of a multiplicative bias correction anomaly field that represents the ratio of the fine scale precipitation to the disaggregated precipitation. It is shown that there is significant temporal variation in the anomalies, which is masked when a mean anomaly field is used. This can be improved by modelling the anomalies in rank-space. Results from the application of the rank-BCSD procedure improve the match between the distributions of observed and downscaled precipitation at the fine scale compared to the original BCSD approach. Further improvements in the distribution are identified when a scaling correction to preserve mass in the disaggregation process is implemented. An assessment of the approach using a single GCM over Australia shows clear advantages especially in the simulation of particularly low and high downscaled precipitation amounts.

  4. Bidirectional Hebbian Plasticity Induced by Low-Frequency Stimulation in Basal Dendrites of Rat Barrel Cortex Layer 5 Pyramidal Neurons

    Science.gov (United States)

    Díez-García, Andrea; Barros-Zulaica, Natali; Núñez, Ángel; Buño, Washington; Fernández de Sevilla, David

    2017-01-01

    According to Hebb's original hypothesis (Hebb, 1949), synapses are reinforced when presynaptic activity triggers postsynaptic firing, resulting in long-term potentiation (LTP) of synaptic efficacy. Long-term depression (LTD) is a use-dependent decrease in synaptic strength that is thought to be due to synaptic input causing a weak postsynaptic effect. Although the mechanisms that mediate long-term synaptic plasticity have been investigated for at least three decades not all question have as yet been answered. Therefore, we aimed at determining the mechanisms that generate LTP or LTD with the simplest possible protocol. Low-frequency stimulation of basal dendrite inputs in Layer 5 pyramidal neurons of the rat barrel cortex induces LTP. This stimulation triggered an EPSP, an action potential (AP) burst, and a Ca2+ spike. The same stimulation induced LTD following manipulations that reduced the Ca2+ spike and Ca2+ signal or the AP burst. Low-frequency whisker deflections induced similar bidirectional plasticity of action potential evoked responses in anesthetized rats. These results suggest that both in vitro and in vivo similar mechanisms regulate the balance between LTP and LTD. This simple induction form of bidirectional hebbian plasticity could be present in the natural conditions to regulate the detection, flow, and storage of sensorimotor information. PMID:28203145

  5. Paired associative stimulation of left and right human motor cortex shapes interhemispheric motor inhibition based on a Hebbian mechanism.

    Science.gov (United States)

    Rizzo, V; Siebner, H S; Morgante, F; Mastroeni, C; Girlanda, P; Quartarone, A

    2009-04-01

    This study was designed to examine whether corticocortical paired associative stimulation (cc-PAS) can modulate interhemispheric inhibition (IHI) in the human brain. Twelve healthy right-handed volunteers received 90 paired transcranial stimuli to the right and left primary motor hand area (M1(HAND)) at an interstimulus interval (ISI) of 8 ms. Left-to-right cc-PAS (first pulse given to left M1(HAND)) attenuated left-to-right IHI for one hour after cc-PAS. Left-to-right cc-PAS also increased corticospinal excitability in the conditioned right M1(HAND). These effects were not seen in an asymptomatic individual with callosal agenesis. Additional experiments showed no changes in left-to-right IHI or corticospinal excitability when left-to-right cc-PAS was given at an ISI of 1 ms or at multiple ISIs in random order. At the behavioral level, left-to-right cc-PAS speeded responses with the left but not right index finger during a simple reaction time task. Right-to-left cc-PAS (first pulse given to right M1(HAND)) reduced right-to-left IHI without increasing corticospinal excitability in left M1(HAND). These results provide a proof of principle that cc-PAS can induce associative plasticity in connections between the targeted cortical areas. The efficacy of cc-PAS to induce lasting changes in excitability depends on the exact timing of the stimulus pairs suggesting an underlying Hebbian mechanism.

  6. Learning pattern recognition and decision making in the insect brain

    Science.gov (United States)

    Huerta, R.

    2013-01-01

    We revise the current model of learning pattern recognition in the Mushroom Bodies of the insects using current experimental knowledge about the location of learning, olfactory coding and connectivity. We show that it is possible to have an efficient pattern recognition device based on the architecture of the Mushroom Bodies, sparse code, mutual inhibition and Hebbian leaning only in the connections from the Kenyon cells to the output neurons. We also show that despite the conventional wisdom that believes that artificial neural networks are the bioinspired model of the brain, the Mushroom Bodies actually resemble very closely Support Vector Machines (SVMs). The derived SVM learning rules are situated in the Mushroom Bodies, are nearly identical to standard Hebbian rules, and require inhibition in the output. A very particular prediction of the model is that random elimination of the Kenyon cells in the Mushroom Bodies do not impair the ability to recognize odorants previously learned.

  7. Learning lateral interactions for feature binding and sensory segmentation from prototypic basis interactions.

    Science.gov (United States)

    Weng, Sebastian; Wersing, Heiko; Steil, Jochen J; Ritter, Helge

    2006-07-01

    We present a hybrid learning method bridging the fields of recurrent neural networks, unsupervised Hebbian learning, vector quantization, and supervised learning to implement a sophisticated image and feature segmentation architecture. This architecture is based on the competitive layer model (CLM), a dynamic feature binding model, which is applicable on a wide range of perceptual grouping and segmentation problems. A predefined target segmentation can be achieved as attractor states of this linear threshold recurrent network, if the lateral weights are chosen by Hebbian learning. The weight matrix is given by the correlation matrix of special pattern vectors with a structure dependent on the target labeling. Generalization is achieved by applying vector quantization on pair-wise feature relations, like proximity and similarity, defined by external knowledge. We show the successful application of the method to a number of artifical test examples and a medical image segmentation problem of fluorescence microscope cell images.

  8. Brain Behavior Evolution during Learning: Emergence of Hierarchical Temporal Memory

    Science.gov (United States)

    2013-08-30

    network, Hebbian learning Donald A. Drew Rensselaer Polytechnic Institute Office of Sponsored Research 110 8th Street Troy, NY 12180 -3522 REPORT...Sciences Rensselaer Polytechnic Institute , Troy, NY 12180 Contents 1 Introduction 3 1.1 Hierarchy...10990-10995, August 2008. [57] McCulloch, W. and Pitts, W., A logical calculus of the ideas imma- nent in nervous activity. Bulletin of Mathematical

  9. Manifold ranking based scoring system with its application to cardiac arrest prediction: A retrospective study in emergency department patients.

    Science.gov (United States)

    Liu, Tianchi; Lin, Zhiping; Ong, Marcus Eng Hock; Koh, Zhi Xiong; Pek, Pin Pin; Yeo, Yong Kiang; Oh, Beom-Seok; Ho, Andrew Fu Wah; Liu, Nan

    2015-12-01

    The recently developed geometric distance scoring system has shown the effectiveness of scoring systems in predicting cardiac arrest within 72h and the potential to predict other clinical outcomes. However, the geometric distance scoring system predicts scores based on only local structure embedded by the data, thus leaving much room for improvement in terms of prediction accuracy. We developed a novel scoring system for predicting cardiac arrest within 72h. The scoring system was developed based on a semi-supervised learning algorithm, manifold ranking, which explores both the local and global consistency of the data. System evaluation was conducted on emergency department patients׳ data, including both vital signs and heart rate variability (HRV) parameters. Comparison of the proposed scoring system with previous work was given in terms of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV). Out of 1025 patients, 52 (5.1%) met the primary outcome. Experimental results show that the proposed scoring system was able to achieve higher area under the curve (AUC) on both the balanced dataset (0.907 vs. 0.824) and the imbalanced dataset (0.774 vs. 0.734) compared to the geometric distance scoring system. The proposed scoring system improved the prediction accuracy by utilizing the global consistency of the training data. We foresee the potential of extending this scoring system, as well as manifold ranking algorithm, to other medical decision making problems. Furthermore, we will investigate the parameter selection process and other techniques to improve performance on the imbalanced dataset. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Neuromodulated Spike-Timing-Dependent Plasticity, and Theory of Three-Factor Learning Rules

    Science.gov (United States)

    Frémaux, Nicolas; Gerstner, Wulfram

    2016-01-01

    Classical Hebbian learning puts the emphasis on joint pre- and postsynaptic activity, but neglects the potential role of neuromodulators. Since neuromodulators convey information about novelty or reward, the influence of neuromodulators on synaptic plasticity is useful not just for action learning in classical conditioning, but also to decide “when” to create new memories in response to a flow of sensory stimuli. In this review, we focus on timing requirements for pre- and postsynaptic activity in conjunction with one or several phasic neuromodulatory signals. While the emphasis of the text is on conceptual models and mathematical theories, we also discuss some experimental evidence for neuromodulation of Spike-Timing-Dependent Plasticity. We highlight the importance of synaptic mechanisms in bridging the temporal gap between sensory stimulation and neuromodulatory signals, and develop a framework for a class of neo-Hebbian three-factor learning rules that depend on presynaptic activity, postsynaptic variables as well as the influence of neuromodulators. PMID:26834568

  11. Molecular circuits for associative learning in single-celled organisms.

    Science.gov (United States)

    Fernando, Chrisantha T; Liekens, Anthony M L; Bingle, Lewis E H; Beck, Christian; Lenser, Thorsten; Stekel, Dov J; Rowe, Jonathan E

    2009-05-06

    We demonstrate how a single-celled organism could undertake associative learning. Although to date only one previous study has found experimental evidence for such learning, there is no reason in principle why it should not occur. We propose a gene regulatory network that is capable of associative learning between any pre-specified set of chemical signals, in a Hebbian manner, within a single cell. A mathematical model is developed, and simulations show a clear learned response. A preliminary design for implementing this model using plasmids within Escherichia coli is presented, along with an alternative approach, based on double-phosphorylated protein kinases.

  12. A Reinforcement Learning Framework for Spiking Networks with Dynamic Synapses

    Directory of Open Access Journals (Sweden)

    Karim El-Laithy

    2011-01-01

    Full Text Available An integration of both the Hebbian-based and reinforcement learning (RL rules is presented for dynamic synapses. The proposed framework permits the Hebbian rule to update the hidden synaptic model parameters regulating the synaptic response rather than the synaptic weights. This is performed using both the value and the sign of the temporal difference in the reward signal after each trial. Applying this framework, a spiking network with spike-timing-dependent synapses is tested to learn the exclusive-OR computation on a temporally coded basis. Reward values are calculated with the distance between the output spike train of the network and a reference target one. Results show that the network is able to capture the required dynamics and that the proposed framework can reveal indeed an integrated version of Hebbian and RL. The proposed framework is tractable and less computationally expensive. The framework is applicable to a wide class of synaptic models and is not restricted to the used neural representation. This generality, along with the reported results, supports adopting the introduced approach to benefit from the biologically plausible synaptic models in a wide range of intuitive signal processing.

  13. Social norm influences on evaluations of the risks associated with alcohol consumption: applying the rank-based decision by sampling model to health judgments.

    Science.gov (United States)

    Wood, Alex M; Brown, Gordon D A; Maltby, John

    2012-01-01

    The research first tested whether perceptions of other people's alcohol consumption influenced drinkers' perceptions of the riskiness of their own consumption. Second, the research tested how such comparisons are made-whether, for example, people compare their drinking to the 'average' drinker's or 'rank' their consumption amongst other people's. The latter untested possibility, suggested by the recent Decision by Sampling Model of judgment, would imply different cognitive mechanisms and suggest that information should be presented differently to people in social norm interventions. Study 1 surveyed students who provided information on (a) their own drinking, (b) their perceptions of the distribution of drinking in the UK and (c) their perceived risk of various alcohol-related disorders. Study 2 experimentally manipulated the rank of 'target' units of alcohol within the context of units viewed simultaneously. In both studies, the rank of an individual's drinking in a context of other drinkers predicted perceptions of developing alcohol-related disorders. There was no evidence for the alternative hypothesis that people compared with the average of other drinkers' consumptions. The position that subjects believed they occupied in the ranking of other drinkers predicted their perceived risk, and did so as strongly as how much they actually drank. Drinking comparisons are rank-based, which is consistent with other judgments in social, emotional and psychophysical domains. Interventions should be designed to work with people's natural ways of information processing, through providing clients with information on their drinking rank rather than how their drinking differs from the average.

  14. Theta coordinated error-driven learning in the hippocampus.

    Directory of Open Access Journals (Sweden)

    Nicholas Ketz

    Full Text Available The learning mechanism in the hippocampus has almost universally been assumed to be Hebbian in nature, where individual neurons in an engram join together with synaptic weight increases to support facilitated recall of memories later. However, it is also widely known that Hebbian learning mechanisms impose significant capacity constraints, and are generally less computationally powerful than learning mechanisms that take advantage of error signals. We show that the differential phase relationships of hippocampal subfields within the overall theta rhythm enable a powerful form of error-driven learning, which results in significantly greater capacity, as shown in computer simulations. In one phase of the theta cycle, the bidirectional connectivity between CA1 and entorhinal cortex can be trained in an error-driven fashion to learn to effectively encode the cortical inputs in a compact and sparse form over CA1. In a subsequent portion of the theta cycle, the system attempts to recall an existing memory, via the pathway from entorhinal cortex to CA3 and CA1. Finally the full theta cycle completes when a strong target encoding representation of the current input is imposed onto the CA1 via direct projections from entorhinal cortex. The difference between this target encoding and the attempted recall of the same representation on CA1 constitutes an error signal that can drive the learning of CA3 to CA1 synapses. This CA3 to CA1 pathway is critical for enabling full reinstatement of recalled hippocampal memories out in cortex. Taken together, these new learning dynamics enable a much more robust, high-capacity model of hippocampal learning than was available previously under the classical Hebbian model.

  15. The effect of STDP temporal kernel structure on the learning dynamics of single excitatory and inhibitory synapses.

    Directory of Open Access Journals (Sweden)

    Yotam Luz

    Full Text Available Spike-Timing Dependent Plasticity (STDP is characterized by a wide range of temporal kernels. However, much of the theoretical work has focused on a specific kernel - the "temporally asymmetric Hebbian" learning rules. Previous studies linked excitatory STDP to positive feedback that can account for the emergence of response selectivity. Inhibitory plasticity was associated with negative feedback that can balance the excitatory and inhibitory inputs. Here we study the possible computational role of the temporal structure of the STDP. We represent the STDP as a superposition of two processes: potentiation and depression. This allows us to model a wide range of experimentally observed STDP kernels, from Hebbian to anti-Hebbian, by varying a single parameter. We investigate STDP dynamics of a single excitatory or inhibitory synapse in purely feed-forward architecture. We derive a mean-field-Fokker-Planck dynamics for the synaptic weight and analyze the effect of STDP structure on the fixed points of the mean field dynamics. We find a phase transition along the Hebbian to anti-Hebbian parameter from a phase that is characterized by a unimodal distribution of the synaptic weight, in which the STDP dynamics is governed by negative feedback, to a phase with positive feedback characterized by a bimodal distribution. The critical point of this transition depends on general properties of the STDP dynamics and not on the fine details. Namely, the dynamics is affected by the pre-post correlations only via a single number that quantifies its overlap with the STDP kernel. We find that by manipulating the STDP temporal kernel, negative feedback can be induced in excitatory synapses and positive feedback in inhibitory. Moreover, there is an exact symmetry between inhibitory and excitatory plasticity, i.e., for every STDP rule of inhibitory synapse there exists an STDP rule for excitatory synapse, such that their dynamics is identical.

  16. Competitive STDP Learning of Overlapping Spatial Patterns.

    Science.gov (United States)

    Krunglevicius, Dalius

    2015-08-01

    Spike-timing-dependent plasticity (STDP) is a set of Hebbian learning rules firmly based on biological evidence. It has been demonstrated that one of the STDP learning rules is suited for learning spatiotemporal patterns. When multiple neurons are organized in a simple competitive spiking neural network, this network is capable of learning multiple distinct patterns. If patterns overlap significantly (i.e., patterns are mutually inclusive), however, competition would not preclude trained neuron's responding to a new pattern and adjusting synaptic weights accordingly. This letter presents a simple neural network that combines vertical inhibition and Euclidean distance-dependent synaptic strength factor. This approach helps to solve the problem of pattern size-dependent parameter optimality and significantly reduces the probability of a neuron's forgetting an already learned pattern. For demonstration purposes, the network was trained for the first ten letters of the Braille alphabet.

  17. Domain-specific and domain-general constraints on word and sequence learning.

    Science.gov (United States)

    Archibald, Lisa M D; Joanisse, Marc F

    2013-02-01

    The relative influences of language-related and memory-related constraints on the learning of novel words and sequences were examined by comparing individual differences in performance of children with and without specific deficits in either language or working memory. Children recalled lists of words in a Hebbian learning protocol in which occasional lists repeated, yielding improved recall over the course of the task on the repeated lists. The task involved presentation of pictures of common nouns followed immediately by equivalent presentations of the spoken names. The same participants also completed a paired-associate learning task involving word-picture and nonword-picture pairs. Hebbian learning was observed for all groups. Domain-general working memory constrained immediate recall, whereas language abilities impacted recall in the auditory modality only. In addition, working memory constrained paired-associate learning generally, whereas language abilities disproportionately impacted novel word learning. Overall, all of the learning tasks were highly correlated with domain-general working memory. The learning of nonwords was additionally related to general intelligence, phonological short-term memory, language abilities, and implicit learning. The results suggest that distinct associations between language- and memory-related mechanisms support learning of familiar and unfamiliar phonological forms and sequences.

  18. Learning tinnitus

    Science.gov (United States)

    van Hemmen, J. Leo

    Tinnitus, implying the perception of sound without the presence of any acoustical stimulus, is a chronic and serious problem for about 2% of the human population. In many cases, tinnitus is a pitch-like sensation associated with a hearing loss that confines the tinnitus frequency to an interval of the tonotopic axis. Even in patients with a normal audiogram the presence of tinnitus may be associated with damage of hair-cell function in this interval. It has been suggested that homeostatic regulation and, hence, increase of activity leads to the emergence of tinnitus. For patients with hearing loss, we present spike-timing-dependent Hebbian plasticity (STDP) in conjunction with homeostasis as a mechanism for ``learning'' tinnitus in a realistic neuronal network with tonotopically arranged synaptic excitation and inhibition. In so doing we use both dynamical scaling of the synaptic strengths and altering the resting potential of the cells. The corresponding simulations are robust to parameter changes. Understanding the mechanisms of tinnitus induction, such as here, may help improving therapy. Work done in collaboration with Julie Goulet and Michael Schneider. JLvH has been supported partially by BCCN - Munich.

  19. Associative Learning in Invertebrates

    Science.gov (United States)

    Hawkins, Robert D.; Byrne, John H.

    2015-01-01

    This work reviews research on neural mechanisms of two types of associative learning in the marine mollusk Aplysia, classical conditioning of the gill- and siphon-withdrawal reflex and operant conditioning of feeding behavior. Basic classical conditioning is caused in part by activity-dependent facilitation at sensory neuron–motor neuron (SN–MN) synapses and involves a hybrid combination of activity-dependent presynaptic facilitation and Hebbian potentiation, which are coordinated by trans-synaptic signaling. Classical conditioning also shows several higher-order features, which might be explained by the known circuit connections in Aplysia. Operant conditioning is caused in part by a different type of mechanism, an intrinsic increase in excitability of an identified neuron in the central pattern generator (CPG) for feeding. However, for both classical and operant conditioning, adenylyl cyclase is a molecular site of convergence of the two signals that are associated. Learning in other invertebrate preparations also involves many of the same mechanisms, which may contribute to learning in vertebrates as well. PMID:25877219

  20. Biased Random-Walk Learning A Neurobiological Correlate to Trial-and-Error

    CERN Document Server

    Anderson, R W

    1993-01-01

    Neural network models offer a theoretical testbed for the study of learning at the cellular level. The only experimentally verified learning rule, Hebb's rule, is extremely limited in its ability to train networks to perform complex tasks. An identified cellular mechanism responsible for Hebbian-type long-term potentiation, the NMDA receptor, is highly versatile. Its function and efficacy are modulated by a wide variety of compounds and conditions and are likely to be directed by non-local phenomena. Furthermore, it has been demonstrated that NMDA receptors are not essential for some types of learning. We have shown that another neural network learning rule, the chemotaxis algorithm, is theoretically much more powerful than Hebb's rule and is consistent with experimental data. A biased random-walk in synaptic weight space is a learning rule immanent in nervous activity and may account for some types of learning -- notably the acquisition of skilled movement.

  1. A QSAR/QSTR study on the human health impact of the rocket fuel 1,1-dimethyl hydrazine and its transformation products Multicriteria hazard ranking based on partial order methodologies.

    Science.gov (United States)

    Carlsen, Lars; Kenessov, Bulat N; Batyrbekova, Svetlana Ye

    2009-05-01

    The possible impact of the rocket fuel 1,1-dimethyl hydrazine (heptyl) (1) and its transformation products on human health has been studied using (Quantitative) Structure Activity/Toxicity ((Q)SAR/(Q)STR) modelling, including both ADME models and models for acute toxicity, organ specific adverse haematological effects, the cardiovascular and gastrointestinal systems, the kidneys, the liver and the lungs, as well as a model predicting the biological activity of the compounds. It was predicted that all compounds studied are readily bioavailable through oral intake and that significant amounts of the compounds will be freely available in the systemic circulation. In general, the compounds are not predicted to be acutely toxic apart from hydrogen cyanide, whereas several compounds are predicted to cause adverse organ specific human health effects. Further, several compounds are predicted to exhibit high probabilities for potential carcinogenicity, mutagenicity, teratogenicity and/or embryotoxicity. The compounds were ranked based on their predicted human health impact using partial order ranking methodologies that highlight which compounds on a cumulative basis should receive the major attention, i.e., N-nitroso dimethyl amine, 1,1,4,4-tetramethyl tetrazene, trimethyl, trimethyl hydrazine, acetaldehyde dimethyl hydrazone, 1, 1-formyl 2,2-dimethyl hydrazine and formaldehyde dimethyl hydrazone, respectively. Copyright © 2009 Elsevier B.V. All rights reserved.

  2. Concurrent Unimodal Learning Enhances Multisensory Responses of Bi-Directional Crossmodal Learning in Robotic Audio-Visual Tracking

    DEFF Research Database (Denmark)

    Shaikh, Danish; Bodenhagen, Leon; Manoonpong, Poramate

    2018-01-01

    .e. the reliabilities of the participating stimulus cues. We present a Hebbian-like temporal correlation learning-based adaptive neural circuit for crossmodal cue integration that does not require such a priori information. The circuit correlates stimulus cues within each modality as well as bidirectionally across......Crossmodal sensory cue integration is a fundamental process in the brain by which stimulus cues from different sensory modalities are combined together to form an coherent and unified representation of observed events in the world. Crossmodal integration is a developmental process involving...... learning, with neuroplasticity as its underlying mechanism. Bayesian models of crossmodal cue integration form a unified percept as a sum of stimulus cues weighted by their respective reliabilities. This approach however requires a priori knowledge of the underlying stimulus noise distributions, i...

  3. Learning

    Directory of Open Access Journals (Sweden)

    Mohsen Laabidi

    2014-01-01

    Full Text Available Nowadays learning technologies transformed educational systems with impressive progress of Information and Communication Technologies (ICT. Furthermore, when these technologies are available, affordable and accessible, they represent more than a transformation for people with disabilities. They represent real opportunities with access to an inclusive education and help to overcome the obstacles they met in classical educational systems. In this paper, we will cover basic concepts of e-accessibility, universal design and assistive technologies, with a special focus on accessible e-learning systems. Then, we will present recent research works conducted in our research Laboratory LaTICE toward the development of an accessible online learning environment for persons with disabilities from the design and specification step to the implementation. We will present, in particular, the accessible version “MoodleAcc+” of the well known e-learning platform Moodle as well as new elaborated generic models and a range of tools for authoring and evaluating accessible educational content.

  4. Thermodynamic efficiency of learning a rule in neural networks

    Science.gov (United States)

    Goldt, Sebastian; Seifert, Udo

    2017-11-01

    Biological systems have to build models from their sensory input data that allow them to efficiently process previously unseen inputs. Here, we study a neural network learning a binary classification rule for these inputs from examples provided by a teacher. We analyse the ability of the network to apply the rule to new inputs, that is to generalise from past experience. Using stochastic thermodynamics, we show that the thermodynamic costs of the learning process provide an upper bound on the amount of information that the network is able to learn from its teacher for both batch and online learning. This allows us to introduce a thermodynamic efficiency of learning. We analytically compute the dynamics and the efficiency of a noisy neural network performing online learning in the thermodynamic limit. In particular, we analyse three popular learning algorithms, namely Hebbian, Perceptron and AdaTron learning. Our work extends the methods of stochastic thermodynamics to a new type of learning problem and might form a suitable basis for investigating the thermodynamics of decision-making.

  5. Learning in AN Oscillatory Cortical Model

    Science.gov (United States)

    Scarpetta, Silvia; Li, Zhaoping; Hertz, John

    We study a model of generalized-Hebbian learning in asymmetric oscillatory neural networks modeling cortical areas such as hippocampus and olfactory cortex. The learning rule is based on the synaptic plasticity observed experimentally, in particular long-term potentiation and long-term depression of the synaptic efficacies depending on the relative timing of the pre- and postsynaptic activities during learning. The learned memory or representational states can be encoded by both the amplitude and the phase patterns of the oscillating neural populations, enabling more efficient and robust information coding than in conventional models of associative memory or input representation. Depending on the class of nonlinearity of the activation function, the model can function as an associative memory for oscillatory patterns (nonlinearity of class II) or can generalize from or interpolate between the learned states, appropriate for the function of input representation (nonlinearity of class I). In the former case, simulations of the model exhibits a first order transition between the "disordered state" and the "ordered" memory state.

  6. A Learning Model for L/M Specificity in Ganglion Cells

    Science.gov (United States)

    Ahumada, Albert J.

    2016-01-01

    An unsupervised learning model for developing LM specific wiring at the ganglion cell level would support the research indicating LM specific wiring at the ganglion cell level (Reid and Shapley, 2002). Removing the contributions to the surround from cells of the same cone type improves the signal-to-noise ratio of the chromatic signals. The unsupervised learning model used is Hebbian associative learning, which strengthens the surround input connections according to the correlation of the output with the input. Since the surround units of the same cone type as the center are redundant with the center, their weights end up disappearing. This process can be thought of as a general mechanism for eliminating unnecessary cells in the nervous system.

  7. Habit learning and brain-machine interfaces (BMI): a tribute to Valentino Braitenberg's "Vehicles".

    Science.gov (United States)

    Birbaumer, Niels; Hummel, Friedhelm C

    2014-10-01

    Brain-Machine Interfaces (BMI) allow manipulation of external devices and computers directly with brain activity without involvement of overt motor actions. The neurophysiological principles of such robotic brain devices and BMIs follow Hebbian learning rules as described and realized by Valentino Braitenberg in his book "Vehicles," in the concept of a "thought pump" residing in subcortical basal ganglia structures. We describe here the application of BMIs for brain communication in totally locked-in patients and argue that the thought pump may extinguish-at least partially-in those people because of extinction of instrumentally learned cognitive responses and brain responses. We show that Pavlovian semantic conditioning may allow brain communication even in the completely paralyzed who does not show response-effect contingencies. Principles of skill learning and habit acquisition as formulated by Braitenberg are the building blocks of BMIs and neuroprostheses.

  8. MOLECULAR MECHANISMS OF FEAR LEARNING AND MEMORY

    Science.gov (United States)

    Johansen, Joshua P.; Cain, Christopher K.; Ostroff, Linnaea E.; LeDoux, Joseph E.

    2011-01-01

    Pavlovian fear conditioning is a useful behavioral paradigm for exploring the molecular mechanisms of learning and memory because a well-defined response to a specific environmental stimulus is produced through associative learning processes. Synaptic plasticity in the lateral nucleus of the amygdala (LA) underlies this form of associative learning. Here we summarize the molecular mechanisms that contribute to this synaptic plasticity in the context of auditory fear conditioning, the form of fear conditioning best understood at the molecular level. We discuss the neurotransmitter systems and signaling cascades that contribute to three phases of auditory fear conditioning: acquisition, consolidation, and reconsolidation. These studies suggest that multiple intracellular signaling pathways, including those triggered by activation of Hebbian processes and neuromodulatory receptors, interact to produce neural plasticity in the LA and behavioral fear conditioning. Together, this research illustrates the power of fear conditioning as a model system for characterizing the mechanisms of learning and memory in mammals, and potentially for understanding fear related disorders, such as PTSD and phobias. PMID:22036561

  9. Learning of Chunking Sequences in Cognition and Behavior

    Science.gov (United States)

    Rabinovich, Mikhail

    2015-01-01

    We often learn and recall long sequences in smaller segments, such as a phone number 858 534 22 30 memorized as four segments. Behavioral experiments suggest that humans and some animals employ this strategy of breaking down cognitive or behavioral sequences into chunks in a wide variety of tasks, but the dynamical principles of how this is achieved remains unknown. Here, we study the temporal dynamics of chunking for learning cognitive sequences in a chunking representation using a dynamical model of competing modes arranged to evoke hierarchical Winnerless Competition (WLC) dynamics. Sequential memory is represented as trajectories along a chain of metastable fixed points at each level of the hierarchy, and bistable Hebbian dynamics enables the learning of such trajectories in an unsupervised fashion. Using computer simulations, we demonstrate the learning of a chunking representation of sequences and their robust recall. During learning, the dynamics associates a set of modes to each information-carrying item in the sequence and encodes their relative order. During recall, hierarchical WLC guarantees the robustness of the sequence order when the sequence is not too long. The resulting patterns of activities share several features observed in behavioral experiments, such as the pauses between boundaries of chunks, their size and their duration. Failures in learning chunking sequences provide new insights into the dynamical causes of neurological disorders such as Parkinson’s disease and Schizophrenia. PMID:26584306

  10. Learning of Chunking Sequences in Cognition and Behavior.

    Directory of Open Access Journals (Sweden)

    Jordi Fonollosa

    2015-11-01

    Full Text Available We often learn and recall long sequences in smaller segments, such as a phone number 858 534 22 30 memorized as four segments. Behavioral experiments suggest that humans and some animals employ this strategy of breaking down cognitive or behavioral sequences into chunks in a wide variety of tasks, but the dynamical principles of how this is achieved remains unknown. Here, we study the temporal dynamics of chunking for learning cognitive sequences in a chunking representation using a dynamical model of competing modes arranged to evoke hierarchical Winnerless Competition (WLC dynamics. Sequential memory is represented as trajectories along a chain of metastable fixed points at each level of the hierarchy, and bistable Hebbian dynamics enables the learning of such trajectories in an unsupervised fashion. Using computer simulations, we demonstrate the learning of a chunking representation of sequences and their robust recall. During learning, the dynamics associates a set of modes to each information-carrying item in the sequence and encodes their relative order. During recall, hierarchical WLC guarantees the robustness of the sequence order when the sequence is not too long. The resulting patterns of activities share several features observed in behavioral experiments, such as the pauses between boundaries of chunks, their size and their duration. Failures in learning chunking sequences provide new insights into the dynamical causes of neurological disorders such as Parkinson's disease and Schizophrenia.

  11. Learning of Chunking Sequences in Cognition and Behavior.

    Science.gov (United States)

    Fonollosa, Jordi; Neftci, Emre; Rabinovich, Mikhail

    2015-11-01

    We often learn and recall long sequences in smaller segments, such as a phone number 858 534 22 30 memorized as four segments. Behavioral experiments suggest that humans and some animals employ this strategy of breaking down cognitive or behavioral sequences into chunks in a wide variety of tasks, but the dynamical principles of how this is achieved remains unknown. Here, we study the temporal dynamics of chunking for learning cognitive sequences in a chunking representation using a dynamical model of competing modes arranged to evoke hierarchical Winnerless Competition (WLC) dynamics. Sequential memory is represented as trajectories along a chain of metastable fixed points at each level of the hierarchy, and bistable Hebbian dynamics enables the learning of such trajectories in an unsupervised fashion. Using computer simulations, we demonstrate the learning of a chunking representation of sequences and their robust recall. During learning, the dynamics associates a set of modes to each information-carrying item in the sequence and encodes their relative order. During recall, hierarchical WLC guarantees the robustness of the sequence order when the sequence is not too long. The resulting patterns of activities share several features observed in behavioral experiments, such as the pauses between boundaries of chunks, their size and their duration. Failures in learning chunking sequences provide new insights into the dynamical causes of neurological disorders such as Parkinson's disease and Schizophrenia.

  12. AHaH Computing–From Metastable Switches to Attractors to Machine Learning

    Science.gov (United States)

    Nugent, Michael Alexander; Molter, Timothy Wesley

    2014-01-01

    Modern computing architecture based on the separation of memory and processing leads to a well known problem called the von Neumann bottleneck, a restrictive limit on the data bandwidth between CPU and RAM. This paper introduces a new approach to computing we call AHaH computing where memory and processing are combined. The idea is based on the attractor dynamics of volatile dissipative electronics inspired by biological systems, presenting an attractive alternative architecture that is able to adapt, self-repair, and learn from interactions with the environment. We envision that both von Neumann and AHaH computing architectures will operate together on the same machine, but that the AHaH computing processor may reduce the power consumption and processing time for certain adaptive learning tasks by orders of magnitude. The paper begins by drawing a connection between the properties of volatility, thermodynamics, and Anti-Hebbian and Hebbian (AHaH) plasticity. We show how AHaH synaptic plasticity leads to attractor states that extract the independent components of applied data streams and how they form a computationally complete set of logic functions. After introducing a general memristive device model based on collections of metastable switches, we show how adaptive synaptic weights can be formed from differential pairs of incremental memristors. We also disclose how arrays of synaptic weights can be used to build a neural node circuit operating AHaH plasticity. By configuring the attractor states of the AHaH node in different ways, high level machine learning functions are demonstrated. This includes unsupervised clustering, supervised and unsupervised classification, complex signal prediction, unsupervised robotic actuation and combinatorial optimization of procedures–all key capabilities of biological nervous systems and modern machine learning algorithms with real world application. PMID:24520315

  13. AHaH computing-from metastable switches to attractors to machine learning.

    Directory of Open Access Journals (Sweden)

    Michael Alexander Nugent

    Full Text Available Modern computing architecture based on the separation of memory and processing leads to a well known problem called the von Neumann bottleneck, a restrictive limit on the data bandwidth between CPU and RAM. This paper introduces a new approach to computing we call AHaH computing where memory and processing are combined. The idea is based on the attractor dynamics of volatile dissipative electronics inspired by biological systems, presenting an attractive alternative architecture that is able to adapt, self-repair, and learn from interactions with the environment. We envision that both von Neumann and AHaH computing architectures will operate together on the same machine, but that the AHaH computing processor may reduce the power consumption and processing time for certain adaptive learning tasks by orders of magnitude. The paper begins by drawing a connection between the properties of volatility, thermodynamics, and Anti-Hebbian and Hebbian (AHaH plasticity. We show how AHaH synaptic plasticity leads to attractor states that extract the independent components of applied data streams and how they form a computationally complete set of logic functions. After introducing a general memristive device model based on collections of metastable switches, we show how adaptive synaptic weights can be formed from differential pairs of incremental memristors. We also disclose how arrays of synaptic weights can be used to build a neural node circuit operating AHaH plasticity. By configuring the attractor states of the AHaH node in different ways, high level machine learning functions are demonstrated. This includes unsupervised clustering, supervised and unsupervised classification, complex signal prediction, unsupervised robotic actuation and combinatorial optimization of procedures-all key capabilities of biological nervous systems and modern machine learning algorithms with real world application.

  14. Learning by stimulation avoidance: A principle to control spiking neural networks dynamics.

    Science.gov (United States)

    Sinapayen, Lana; Masumori, Atsushi; Ikegami, Takashi

    2017-01-01

    Learning based on networks of real neurons, and learning based on biologically inspired models of neural networks, have yet to find general learning rules leading to widespread applications. In this paper, we argue for the existence of a principle allowing to steer the dynamics of a biologically inspired neural network. Using carefully timed external stimulation, the network can be driven towards a desired dynamical state. We term this principle "Learning by Stimulation Avoidance" (LSA). We demonstrate through simulation that the minimal sufficient conditions leading to LSA in artificial networks are also sufficient to reproduce learning results similar to those obtained in biological neurons by Shahaf and Marom, and in addition explains synaptic pruning. We examined the underlying mechanism by simulating a small network of 3 neurons, then scaled it up to a hundred neurons. We show that LSA has a higher explanatory power than existing hypotheses about the response of biological neural networks to external simulation, and can be used as a learning rule for an embodied application: learning of wall avoidance by a simulated robot. In other works, reinforcement learning with spiking networks can be obtained through global reward signals akin simulating the dopamine system; we believe that this is the first project demonstrating sensory-motor learning with random spiking networks through Hebbian learning relying on environmental conditions without a separate reward system.

  15. Continuous Online Sequence Learning with an Unsupervised Neural Network Model.

    Science.gov (United States)

    Cui, Yuwei; Ahmad, Subutar; Hawkins, Jeff

    2016-09-14

    The ability to recognize and predict temporal sequences of sensory inputs is vital for survival in natural environments. Based on many known properties of cortical neurons, hierarchical temporal memory (HTM) sequence memory recently has been proposed as a theoretical framework for sequence learning in the cortex. In this letter, we analyze properties of HTM sequence memory and apply it to sequence learning and prediction problems with streaming data. We show the model is able to continuously learn a large number of variableorder temporal sequences using an unsupervised Hebbian-like learning rule. The sparse temporal codes formed by the model can robustly handle branching temporal sequences by maintaining multiple predictions until there is sufficient disambiguating evidence. We compare the HTM sequence memory with other sequence learning algorithms, including statistical methods: autoregressive integrated moving average; feedforward neural networks-time delay neural network and online sequential extreme learning machine; and recurrent neural networks-long short-term memory and echo-state networks on sequence prediction problems with both artificial and real-world data. The HTM model achieves comparable accuracy to other state-of-the-art algorithms. The model also exhibits properties that are critical for sequence learning, including continuous online learning, the ability to handle multiple predictions and branching sequences with high-order statistics, robustness to sensor noise and fault tolerance, and good performance without task-specific hyperparameter tuning. Therefore, the HTM sequence memory not only advances our understanding of how the brain may solve the sequence learning problem but is also applicable to real-world sequence learning problems from continuous data streams.

  16. Neural Networks that Learn Temporal Sequences by Selection

    Science.gov (United States)

    Dehaene, Stanislas; Changeux, Jean-Pierre; Nadal, Jean-Pierre

    1987-05-01

    A model for formal neural networks that learn temporal sequences by selection is proposed on the basis of observations on the acquisition of song by birds, on sequence-detecting neurons, and on allosteric receptors. The model relies on hypothetical elementary devices made up of three neurons, the synaptic triads, which yield short-term modification of synaptic efficacy through heterosynaptic interactions, and on a local Hebbian learning rule. The functional units postulated are mutually inhibiting clusters of synergic neurons and bundles of synapses. Networks formalized on this basis display capacities for passive recognition and for production of temporal sequences that may include repetitions. Introduction of the learning rule leads to the differentiation of sequence-detecting neurons and to the stabilization of ongoing temporal sequences. A network architecture composed of three layers of neuronal clusters is shown to exhibit active recognition and learning of time sequences by selection: the network spontaneously produces prerepresentations that are selected according to their resonance with the input percepts. Predictions of the model are discussed.

  17. Methods for reducing interference in the Complementary Learning Systems model: oscillating inhibition and autonomous memory rehearsal.

    Science.gov (United States)

    Norman, Kenneth A; Newman, Ehren L; Perotte, Adler J

    2005-11-01

    The stability-plasticity problem (i.e. how the brain incorporates new information into its model of the world, while at the same time preserving existing knowledge) has been at the forefront of computational memory research for several decades. In this paper, we critically evaluate how well the Complementary Learning Systems theory of hippocampo-cortical interactions addresses the stability-plasticity problem. We identify two major challenges for the model: Finding a learning algorithm for cortex and hippocampus that enacts selective strengthening of weak memories, and selective punishment of competing memories; and preventing catastrophic forgetting in the case of non-stationary environments (i.e. when items are temporarily removed from the training set). We then discuss potential solutions to these problems: First, we describe a recently developed learning algorithm that leverages neural oscillations to find weak parts of memories (so they can be strengthened) and strong competitors (so they can be punished), and we show how this algorithm outperforms other learning algorithms (CPCA Hebbian learning and Leabra at memorizing overlapping patterns. Second, we describe how autonomous re-activation of memories (separately in cortex and hippocampus) during REM sleep, coupled with the oscillating learning algorithm, can reduce the rate of forgetting of input patterns that are no longer present in the environment. We then present a simple demonstration of how this process can prevent catastrophic interference in an AB-AC learning paradigm.

  18. Sensorimotor learning biases choice behavior: a learning neural field model for decision making.

    Directory of Open Access Journals (Sweden)

    Christian Klaes

    Full Text Available According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action

  19. Word learning emerges from the interaction of online referent selection and slow associative learning

    Science.gov (United States)

    McMurray, Bob; Horst, Jessica S.; Samuelson, Larissa K.

    2013-01-01

    Classic approaches to word learning emphasize the problem of referential ambiguity: in any naming situation the referent of a novel word must be selected from many possible objects, properties, actions, etc. To solve this problem, researchers have posited numerous constraints, and inference strategies, but assume that determining the referent of a novel word is isomorphic to learning. We present an alternative model in which referent selection is an online process that is independent of long-term learning. This two timescale approach creates significant power in the developing system. We illustrate this with a dynamic associative model in which referent selection is simulated as dynamic competition between competing referents, and learning is simulated using associative (Hebbian) learning. This model can account for a range of findings including the delay in expressive vocabulary relative to receptive vocabulary, learning under high degrees of referential ambiguity using cross-situational statistics, accelerating (vocabulary explosion) and decelerating (power-law) learning rates, fast-mapping by mutual exclusivity (and differences in bilinguals), improvements in familiar word recognition with development, and correlations between individual differences in speed of processing and learning. Five theoretical points are illustrated. 1) Word learning does not require specialized processes – general association learning buttressed by dynamic competition can account for much of the literature. 2) The processes of recognizing familiar words are not different than those that support novel words (e.g., fast-mapping). 3) Online competition may allow the network (or child) to leverage information available in the task to augment performance or behavior despite what might be relatively slow learning or poor representations. 4) Even associative learning is more complex than previously thought – a major contributor to performance is the pruning of incorrect associations

  20. Temporal sequence learning, prediction, and control: a review of different models and their relation to biological mechanisms.

    Science.gov (United States)

    Wörgötter, Florentin; Porr, Bernd

    2005-02-01

    In this review, we compare methods for temporal sequence learning (TSL) across the disciplines machine-control, classical conditioning, neuronal models for TSL as well as spike-timing-dependent plasticity (STDP). This review introduces the most influential models and focuses on two questions: To what degree are reward-based (e.g., TD learning) and correlation-based (Hebbian) learning related? and How do the different models correspond to possibly underlying biological mechanisms of synaptic plasticity? We first compare the different models in an open-loop condition, where behavioral feedback does not alter the learning. Here we observe that reward-based and correlation-based learning are indeed very similar. Machine control is then used to introduce the problem of closed-loop control (e.g., actor-critic architectures). Here the problem of evaluative (rewards) versus nonevaluative (correlations) feedback from the environment will be discussed, showing that both learning approaches are fundamentally different in the closed-loop condition. In trying to answer the second question, we compare neuronal versions of the different learning architectures to the anatomy of the involved brain structures (basal-ganglia, thalamus, and cortex) and the molecular biophysics of glutamatergic and dopaminergic synapses. Finally, we discuss the different algorithms used to model STDP and compare them to reward-based learning rules. Certain similarities are found in spite of the strongly different timescales. Here we focus on the biophysics of the different calcium-release mechanisms known to be involved in STDP.

  1. Neural learning circuits utilizing nano-crystalline silicon transistors and memristors.

    Science.gov (United States)

    Cantley, Kurtis D; Subramaniam, Anand; Stiegler, Harvey J; Chapman, Richard A; Vogel, Eric M

    2012-04-01

    Properties of neural circuits are demonstrated via SPICE simulations and their applications are discussed. The neuron and synapse subcircuits include ambipolar nano-crystalline silicon transistor and memristor device models based on measured data. Neuron circuit characteristics and the Hebbian synaptic learning rule are shown to be similar to biology. Changes in the average firing rate learning rule depending on various circuit parameters are also presented. The subcircuits are then connected into larger neural networks that demonstrate fundamental properties including associative learning and pulse coincidence detection. Learned extraction of a fundamental frequency component from noisy inputs is demonstrated. It is then shown that if the fundamental sinusoid of one neuron input is out of phase with the rest, its synaptic connection changes differently than the others. Such behavior indicates that the system can learn to detect which signals are important in the general population, and that there is a spike-timing-dependent component of the learning mechanism. Finally, future circuit design and considerations are discussed, including requirements for the memristive device.

  2. Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights

    Science.gov (United States)

    Mohammed, Husam Jasim; Kasim, Maznah Mat; Shaharanee, Izwan Nizal Mohd

    2017-11-01

    This paper compares the performances of four rank-based weighting assessment techniques, Rank Sum (RS), Rank Reciprocal (RR), Rank Exponent (RE), and Rank Order Centroid (ROC) on five identified e-learning criteria to select the best weights method. A total of 35 experts in a public university in Malaysia were asked to rank the criteria and to evaluate five e-learning approaches which include blended learning, flipped classroom, ICT supported face to face learning, synchronous learning, and asynchronous learning. The best ranked criteria weights are defined as weights that have the least total absolute differences with the geometric mean of all weights, were then used to select the most suitable e-learning approach by using TOPSIS method. The results show that RR weights are the best, while flipped classroom approach implementation is the most suitable approach. This paper has developed a decision framework to aid decision makers (DMs) in choosing the most suitable weighting method for solving MCDM problems.

  3. Coherence of gamma-band EEG activity as a basis for associative learning

    Science.gov (United States)

    Miltner, Wolfgang H. R.; Braun, Christoph; Arnold, Matthias; Witte, Herbert; Taub, Edward

    1999-02-01

    Different regions of the brain must communicate with each other to provide the basis for the integration of sensory information, sensory-motor coordination and many other functions that are critical for learning, memory, information processing, perception and the behaviour of organisms. Hebb suggested that this is accomplished by the formation of assemblies of cells whose synaptic linkages are strengthened whenever the cells are activated or `ignited' synchronously. Hebb's seminal concept has intrigued investigators since its formulation, but the technology to demonstrate its existence had been lacking until the past decade. Previous studies have shown that very fast electroencephalographic activity in the gamma band (20-70Hz) increases during, and may be involved in, the formation of percepts and memory, linguistic processing, and other behavioural and preceptual functions. We show here that increased gamma-band activity is also involved in associative learning. In addition, we find that another measure, gamma-band coherence, increases between regions of the brain that receive the two classes of stimuli involved in an associative-learning procedure in humans. An increase in coherence could fulfil the criteria required for the formation of hebbian cell assemblies, binding together parts of the brain that must communicate with one another in order for associative learning to take place. In this way, coherence may be a signature for this and other types of learning.

  4. Unsupervised learning in neural networks with short range synapses

    Science.gov (United States)

    Brunnet, L. G.; Agnes, E. J.; Mizusaki, B. E. P.; Erichsen, R., Jr.

    2013-01-01

    Different areas of the brain are involved in specific aspects of the information being processed both in learning and in memory formation. For example, the hippocampus is important in the consolidation of information from short-term memory to long-term memory, while emotional memory seems to be dealt by the amygdala. On the microscopic scale the underlying structures in these areas differ in the kind of neurons involved, in their connectivity, or in their clustering degree but, at this level, learning and memory are attributed to neuronal synapses mediated by longterm potentiation and long-term depression. In this work we explore the properties of a short range synaptic connection network, a nearest neighbor lattice composed mostly by excitatory neurons and a fraction of inhibitory ones. The mechanism of synaptic modification responsible for the emergence of memory is Spike-Timing-Dependent Plasticity (STDP), a Hebbian-like rule, where potentiation/depression is acquired when causal/non-causal spikes happen in a synapse involving two neurons. The system is intended to store and recognize memories associated to spatial external inputs presented as simple geometrical forms. The synaptic modifications are continuously applied to excitatory connections, including a homeostasis rule and STDP. In this work we explore the different scenarios under which a network with short range connections can accomplish the task of storing and recognizing simple connected patterns.

  5. Embedding responses in spontaneous neural activity shaped through sequential learning.

    Science.gov (United States)

    Kurikawa, Tomoki; Kaneko, Kunihiko

    2013-01-01

    Recent experimental measurements have demonstrated that spontaneous neural activity in the absence of explicit external stimuli has remarkable spatiotemporal structure. This spontaneous activity has also been shown to play a key role in the response to external stimuli. To better understand this role, we proposed a viewpoint, "memories-as-bifurcations," that differs from the traditional "memories-as-attractors" viewpoint. Memory recall from the memories-as-bifurcations viewpoint occurs when the spontaneous neural activity is changed to an appropriate output activity upon application of an input, known as a bifurcation in dynamical systems theory, wherein the input modifies the flow structure of the neural dynamics. Learning, then, is a process that helps create neural dynamical systems such that a target output pattern is generated as an attractor upon a given input. Based on this novel viewpoint, we introduce in this paper an associative memory model with a sequential learning process. Using a simple hebbian-type learning, the model is able to memorize a large number of input/output mappings. The neural dynamics shaped through the learning exhibit different bifurcations to make the requested targets stable upon an increase in the input, and the neural activity in the absence of input shows chaotic dynamics with occasional approaches to the memorized target patterns. These results suggest that these dynamics facilitate the bifurcations to each target attractor upon application of the corresponding input, which thus increases the capacity for learning. This theoretical finding about the behavior of the spontaneous neural activity is consistent with recent experimental observations in which the neural activity without stimuli wanders among patterns evoked by previously applied signals. In addition, the neural networks shaped by learning properly reflect the correlations of input and target-output patterns in a similar manner to those designed in our previous study.

  6. Embedding responses in spontaneous neural activity shaped through sequential learning.

    Directory of Open Access Journals (Sweden)

    Tomoki Kurikawa

    Full Text Available Recent experimental measurements have demonstrated that spontaneous neural activity in the absence of explicit external stimuli has remarkable spatiotemporal structure. This spontaneous activity has also been shown to play a key role in the response to external stimuli. To better understand this role, we proposed a viewpoint, "memories-as-bifurcations," that differs from the traditional "memories-as-attractors" viewpoint. Memory recall from the memories-as-bifurcations viewpoint occurs when the spontaneous neural activity is changed to an appropriate output activity upon application of an input, known as a bifurcation in dynamical systems theory, wherein the input modifies the flow structure of the neural dynamics. Learning, then, is a process that helps create neural dynamical systems such that a target output pattern is generated as an attractor upon a given input. Based on this novel viewpoint, we introduce in this paper an associative memory model with a sequential learning process. Using a simple hebbian-type learning, the model is able to memorize a large number of input/output mappings. The neural dynamics shaped through the learning exhibit different bifurcations to make the requested targets stable upon an increase in the input, and the neural activity in the absence of input shows chaotic dynamics with occasional approaches to the memorized target patterns. These results suggest that these dynamics facilitate the bifurcations to each target attractor upon application of the corresponding input, which thus increases the capacity for learning. This theoretical finding about the behavior of the spontaneous neural activity is consistent with recent experimental observations in which the neural activity without stimuli wanders among patterns evoked by previously applied signals. In addition, the neural networks shaped by learning properly reflect the correlations of input and target-output patterns in a similar manner to those designed in

  7. Image Re-Ranking Based on Topic Diversity.

    Science.gov (United States)

    Qian, Xueming; Lu, Dan; Wang, Yaxiong; Zhu, Li; Tang, Yuan Yan; Wang, Meng

    2017-08-01

    Social media sharing Websites allow users to annotate images with free tags, which significantly contribute to the development of the web image retrieval. Tag-based image search is an important method to find images shared by users in social networks. However, how to make the top ranked result relevant and with diversity is challenging. In this paper, we propose a topic diverse ranking approach for tag-based image retrieval with the consideration of promoting the topic coverage performance. First, we construct a tag graph based on the similarity between each tag. Then, the community detection method is conducted to mine the topic community of each tag. After that, inter-community and intra-community ranking are introduced to obtain the final retrieved results. In the inter-community ranking process, an adaptive random walk model is employed to rank the community based on the multi-information of each topic community. Besides, we build an inverted index structure for images to accelerate the searching process. Experimental results on Flickr data set and NUS-Wide data sets show the effectiveness of the proposed approach.

  8. Cardinal priority ranking based decision making for economic ...

    African Journals Online (AJOL)

    To access the indifference band, interaction with the decision maker is obtained via cardinal priority ranking (CPR) of the objectives. The cardinal priority ranking is constructed in the functional space and then transformed into the decision space, so the cardinal priority ranking of objectives relate the decision maker's ...

  9. Influences of cognitive control on numerical cognition--adaptation by binding for implicit learning.

    Science.gov (United States)

    Moeller, Korbinian; Klein, Elise; Nuerk, Hans-Christoph

    2013-04-01

    Recently, an associative learning account of cognitive control has been suggested (Verguts & Notebaert, 2009). In this so-called adaptation by binding theory, Hebbian learning of stimulus-stimulus and stimulus-response associations is assumed to drive the adaptation of human behavior. In this study, we evaluated the validity of the adaptation-by-binding account for the case of implicit learning of regularities within a stimulus set (i.e., the frequency of specific unit digit combinations in a two-digit number magnitude comparison task) and their association with a particular response. Our data indicated that participants indeed learned these regularities and adapted their behavior accordingly. In particular, influences of cognitive control were even able to override the numerical distance effect--one of the most robust effects in numerical cognition research. Thus, the general cognitive processes involved in two-digit number magnitude comparison seem much more complex than previously assumed. Multi-digit number magnitude comparison may not be automatic and inflexible but influenced by processes of cognitive control being highly adaptive to stimulus set properties and task demands on multiple levels. Copyright © 2013 Cognitive Science Society, Inc.

  10. Land cover classification in multispectral satellite imagery using sparse approximations on learned dictionaries

    Science.gov (United States)

    Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; Altmann, Garrett L.

    2014-05-01

    Techniques for automated feature extraction, including neuroscience-inspired machine vision, are of great interest for landscape characterization and change detection in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methodologies to the environmental sciences, using state-of-theart adaptive signal processing, combined with compressive sensing and machine learning techniques. We use a modified Hebbian learning rule to build spectral-textural dictionaries that are tailored for classification. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labels are automatically generated using CoSA: unsupervised Clustering of Sparse Approximations. We demonstrate our method on multispectral WorldView-2 data from a coastal plain ecosystem in Barrow, Alaska (USA). Our goal is to develop a robust classification methodology that will allow for automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties (e.g., soil moisture and inundation), and topographic/geomorphic characteristics. In this paper, we explore learning from both raw multispectral imagery, as well as normalized band difference indexes. We explore a quantitative metric to evaluate the spectral properties of the clusters, in order to potentially aid in assigning land cover categories to the cluster labels.

  11. Origins of learned reciprocity in solitary ciliates searching grouped 'courting' assurances at quantum efficiencies.

    Science.gov (United States)

    Clark, Kevin B

    2010-01-01

    Learning to reciprocate socially valued actions, such as cheating and cooperation, marks evolutionary advances in animal intelligence thought unequalled by even colonial microbes known to secure respective individual or group fitness tradeoffs through genetic and epigenetic processes. However, solitary ciliates, unique among microbes for their emulation of simple Hebbian-like learning contingent upon feedback between behavioral output and vibration-activated mechanosensitive Ca(2+) channels, might be the best candidates to learn to reciprocate necessary preconjugant touches perceived during complex 'courtship rituals'. Testing this hypothesis here with mock social trials involving an ambiguous vibration source, the large heterotrich ciliate Spirostomum ambiguum showed it can indeed learn to modify emitted signals about mating fitness to encourage paired reproduction. Ciliates, improving their signaling expertise with each felt vibration, grouped serial escape strategies gesturing opposite 'courting' assurances of playing 'harder to get' or 'easier to get' into separate, topologically invariant computational networks. Stored strategies formed patterns of action or heuristics with which ciliates performed fast, quantum-like distributed modular searches to guide future replies of specific fitness content. Heuristic-guided searches helped initial inferior repliers, ciliates with high initial reproductive costs, learn to sensitize their behavioral output and opportunistically compete with presumptive mating 'rivals' advertising higher quality fitness. Whereas, initial superior repliers, ciliates with low initial reproductive costs, learned with the aid of heuristics to habituate their behavioral output and sacrifice net reproductive payoffs to cooperate with presumptive 'suitors', a kind of learned altruism only before attributed to animal social intelligences. The present findings confirm that ciliates are highly competent decision makers capable of achieving paired

  12. A BCM theory of meta-plasticity for online self-reorganizing fuzzy-associative learning.

    Science.gov (United States)

    Tan, Javan; Quek, Chai

    2010-06-01

    Self-organizing neurofuzzy approaches have matured in their online learning of fuzzy-associative structures under time-invariant conditions. To maximize their operative value for online reasoning, these self-sustaining mechanisms must also be able to reorganize fuzzy-associative knowledge in real-time dynamic environments. Hence, it is critical to recognize that they would require self-reorganizational skills to rebuild fluid associative structures when their existing organizations fail to respond well to changing circumstances. In this light, while Hebbian theory (Hebb, 1949) is the basic computational framework for associative learning, it is less attractive for time-variant online learning because it suffers from stability limitations that impedes unlearning. Instead, this paper adopts the Bienenstock-Cooper-Munro (BCM) theory of neurological learning via meta-plasticity principles (Bienenstock et al., 1982) that provides for both online associative and dissociative learning. For almost three decades, BCM theory has been shown to effectively brace physiological evidence of synaptic potentiation (association) and depression (dissociation) into a sound mathematical framework for computational learning. This paper proposes an interpretation of the BCM theory of meta-plasticity for an online self-reorganizing fuzzy-associative learning system to realize online-reasoning capabilities. Experimental findings are twofold: 1) the analysis using S&P-500 stock index illustrated that the self-reorganizing approach could follow the trajectory shifts in the time-variant S&P-500 index for about 60 years, and 2) the benchmark profiles showed that the fuzzy-associative approach yielded comparable results with other fuzzy-precision models with similar online objectives.

  13. Proposed mechanism for learning and memory erasure in a white-noise-driven sleeping cortex

    Science.gov (United States)

    Steyn-Ross, Moira L.; Steyn-Ross, D. A.; Sleigh, J. W.; Wilson, M. T.; Wilcocks, Lara C.

    2005-12-01

    Understanding the structure and purpose of sleep remains one of the grand challenges of neurobiology. Here we use a mean-field linearized theory of the sleeping cortex to derive statistics for synaptic learning and memory erasure. The growth in correlated low-frequency high-amplitude voltage fluctuations during slow-wave sleep (SWS) is characterized by a probability density function that becomes broader and shallower as the transition into rapid-eye-movement (REM) sleep is approached. At transition, the Shannon information entropy of the fluctuations is maximized. If we assume Hebbian-learning rules apply to the cortex, then its correlated response to white-noise stimulation during SWS provides a natural mechanism for a synaptic weight change that will tend to shut down reverberant neural activity. In contrast, during REM sleep the weights will evolve in a direction that encourages excitatory activity. These entropy and weight-change predictions lead us to identify the final portion of deep SWS that occurs immediately prior to transition into REM sleep as a time of enhanced erasure of labile memory. We draw a link between the sleeping cortex and Landauer’s dissipation theorem for irreversible computing [R. Landauer, IBM J. Res. Devel. 5, 183 (1961)], arguing that because information erasure is an irreversible computation, there is an inherent entropy cost as the cortex transits from SWS into REM sleep.

  14. Brain-like associative learning using a nanoscale non-volatile phase change synaptic device array

    Directory of Open Access Journals (Sweden)

    Sukru Burc Eryilmaz

    2014-07-01

    Full Text Available Recent advances in neuroscience together with nanoscale electronic device technology have resulted in huge interests in realizing brain-like computing hardwares using emerging nanoscale memory devices as synaptic elements. Although there has been experimental work that demonstrated the operation of nanoscale synaptic element at the single device level, network level studies have been limited to simulations. In this work, we demonstrate, using experiments, array level associative learning using phase change synaptic devices connected in a grid like configuration similar to the organization of the biological brain. Implementing Hebbian learning with phase change memory cells, the synaptic grid was able to store presented patterns and recall missing patterns in an associative brain-like fashion. We found that the system is robust to device variations, and large variations in cell resistance states can be accommodated by increasing the number of training epochs. We illustrated the tradeoff between variation tolerance of the network and the overall energy consumption, and found that energy consumption is decreased significantly for lower variation tolerance.

  15. Learning How To Learn.

    Science.gov (United States)

    Barnett, Demian

    2000-01-01

    In one California high school, learning to learn is a measurable outcome assessed by all students' participation in graduation by exhibition. Students must meet state requirements and demonstrate learning prowess by publicly exhibiting their skills in math, science, language arts, social science, service learning, and postgraduation planning. (MLH)

  16. Learning How to Learn

    DEFF Research Database (Denmark)

    Lauridsen, Karen M.; Lauridsen, Ole

    Ole Lauridsen, Aarhus School of Business and Social Sciences, Aarhus University, Denmark Karen M. Lauridsen, Aarhus School of Business and Social Sciences, Aarhus University, Denmark Learning Styles in Higher Education – Learning How to Learn Applying learning styles (LS) in higher education...... teaching leads to positive results and enhanced student learning. However, learning styles should not only be considered a didactic matter for the teacher, but also a tool for the individual students to improve their learning capabilities – not least in contexts where information is not necessarily...... presented in a way that suits their individual LS preferences. In this presentation you will see how we as teachers can assist students in applying LS strategies that cater to their individual learning strengths. This will be based on general recommendations for HE teaching and learning supported...

  17. Just Imagine! Learning to Emulate and Infer Actions with a Stochastic Generative Architecture

    Directory of Open Access Journals (Sweden)

    Fabian eSchrodt

    2016-03-01

    Full Text Available Theories on embodied cognition emphasize that our mind develops by processing and inferring structures given the encountered bodily experiences. Here we propose a distributed neural network architecture that learns a stochastic generative model from experiencing bodily actions. Our modular system learns from various manifolds of action perceptions in the form of (i relative positional motion of the individual body parts, (ii angular motion of joints, as well as (iii relatively stable top-down action identities. By Hebbian learning, this information is spatially segmented in separate neural modules that provide embodied state codes as well as temporal predictions of the state progression inside and across the modules. The network is generative in space and time, thus, being able to predict both, missing sensory information as well as next sensory information. We link the developing encodings to visuo-motor and multimodal representations that appear to be involved in action observation. Our results show that the system learns to infer action types as well as motor codes from partial sensory information by emulating observed actions with the own developing body model. We further evaluate the generative capabilities by showing that the system is able to generate internal imaginations of the learned types of actions without sensory stimulation, including visual images of the actions. The model highlights the important roles of motor cognition and embodied simulation for bootstrapping action understanding capabilities. We conclude that stochastic generative models appear very suitable for both, generating goal-directed actions, as well as predicting observed visuo-motor trajectories and action goals.

  18. Learning Networks, Networked Learning

    NARCIS (Netherlands)

    Sloep, Peter; Berlanga, Adriana

    2010-01-01

    Sloep, P. B., & Berlanga, A. J. (2011). Learning Networks, Networked Learning [Redes de Aprendizaje, Aprendizaje en Red]. Comunicar, XIX(37), 55-63. Retrieved from http://dx.doi.org/10.3916/C37-2011-02-05

  19. Change detection in Arctic satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

    Science.gov (United States)

    Moody, Daniela I.; Wilson, Cathy J.; Rowland, Joel C.; Altmann, Garrett L.

    2015-06-01

    Advanced pattern recognition and computer vision algorithms are of great interest for landscape characterization, change detection, and change monitoring in satellite imagery, in support of global climate change science and modeling. We present results from an ongoing effort to extend neuroscience-inspired models for feature extraction to the environmental sciences, and we demonstrate our work using Worldview-2 multispectral satellite imagery. We use a Hebbian learning rule to derive multispectral, multiresolution dictionaries directly from regional satellite normalized band difference index data. These feature dictionaries are used to build sparse scene representations, from which we automatically generate land cover labels via our CoSA algorithm: Clustering of Sparse Approximations. These data adaptive feature dictionaries use joint spectral and spatial textural characteristics to help separate geologic, vegetative, and hydrologic features. Land cover labels are estimated in example Worldview-2 satellite images of Barrow, Alaska, taken at two different times, and are used to detect and discuss seasonal surface changes. Our results suggest that an approach that learns from both spectral and spatial features is promising for practical pattern recognition problems in high resolution satellite imagery.

  20. Image Annotation by Latent Community Detection and Multikernel Learning.

    Science.gov (United States)

    Gu, Yun; Qian, Xueming; Li, Qing; Wang, Meng; Hong, Richang; Tian, Qi

    2015-11-01

    Automatic image annotation is an attractive service for users and administrators of online photo sharing websites. In this paper, we propose an image annotation approach that exploits latent semantic community of labels and multikernel learning (LCMKL). First, a concept graph is constructed for labels indicating the relationship between the concepts. Based on the concept graph, semantic communities are explored using an automatic community detection method. For an image to be annotated, a multikernel support vector machine is used to determine the image's latent community from its visual features. Then, a candidate label ranking based approach is determined by intracommunity and intercommunity ranking. Experiments on the NUS-WIDE database and IAPR TC-12 data set demonstrate that LCMKL outperforms some state-of-the-art approaches.

  1. Concurrent TMS to the primary motor cortex augments slow motor learning

    Science.gov (United States)

    Narayana, Shalini; Zhang, Wei; Rogers, William; Strickland, Casey; Franklin, Crystal; Lancaster, Jack L.; Fox, Peter T.

    2013-01-01

    Transcranial magnetic stimulation (TMS) has shown promise as a treatment tool, with one FDA approved use. While TMS alone is able to up- (or down-) regulate a targeted neural system, we argue that TMS applied as an adjuvant is more effective for repetitive physical, behavioral and cognitive therapies, that is, therapies which are designed to alter the network properties of neural systems through Hebbian learning. We tested this hypothesis in the context of a slow motor learning paradigm. Healthy right-handed individuals were assigned to receive 5 Hz TMS (TMS group) or sham TMS (sham group) to the right primary motor cortex (M1) as they performed daily motor practice of a digit sequence task with their non-dominant hand for 4 weeks. Resting cerebral blood flow (CBF) was measured by H215O PET at baseline and after 4 weeks of practice. Sequence performance was measured daily as the number of correct sequences performed, and modeled using a hyperbolic function. Sequence performance increased significantly at 4 weeks relative to baseline in both groups. The TMS group had a significant additional improvement in performance, specifically, in the rate of skill acquisition. In both groups, an improvement in sequence timing and transfer of skills to non-trained motor domains was also found. Compared to the sham group, the TMS group demonstrated increases in resting CBF specifically in regions known to mediate skill learning namely, the M1, cingulate cortex, putamen, hippocampus, and cerebellum. These results indicate that TMS applied concomitantly augments behavioral effects of motor practice, with corresponding neural plasticity in motor sequence learning network. These findings are the first demonstration of the behavioral and neural enhancing effects of TMS on slow motor practice and have direct application in neurorehabilitation where TMS could be applied in conjunction with physical therapy. PMID:23867557

  2. Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity.

    Science.gov (United States)

    Albers, Christian; Westkott, Maren; Pawelzik, Klaus

    2016-01-01

    Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP). Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious) and strong (teacher) spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns.

  3. Ciliates learn to diagnose and correct classical error syndromes in mating strategies

    Directory of Open Access Journals (Sweden)

    Kevin Bradley Clark

    2013-08-01

    Full Text Available Preconjugal ciliates learn classical repetition error-correction codes to safeguard mating messages and replies from corruption by rivals and local ambient noise. Because individual cells behave as memory channels with Szilárd engine attributes, these coding schemes also might be used to limit, diagnose, and correct mating-signal errors due to noisy intracellular information processing. The present study, therefore, assessed whether heterotrich ciliates effect fault-tolerant signal planning and execution by modifying engine performance, and consequently entropy content of codes, during mock cell-cell communication. Socially meaningful serial vibrations emitted from an ambiguous artificial source initiated ciliate behavioral signaling performances known to advertise mating fitness with varying courtship strategies. Microbes, employing calcium-dependent Hebbian-like decision making, learned to diagnose then correct error syndromes by recursively matching Boltzmann entropies between signal planning and execution stages via power or refrigeration cycles. All eight serial contraction and reversal strategies incurred errors in entropy magnitude by the execution stage of processing. Absolute errors, however, subtended expected threshold values for single bit-flip errors in three-bit replies, indicating coding schemes protected information content throughout signal production. Ciliate preparedness for vibrations selectively and significantly affected the magnitude and valence of Szilárd engine performance during modal and nonmodal strategy corrective cycles. But entropy fidelity for all replies mainly improved across learning trials as refinements in engine efficiency. Fidelity neared maximum levels for only modal signals coded in resilient three-bit repetition error-correction sequences. Together, these findings demonstrate microbes can elevate survival/reproductive success by learning to implement classical fault-tolerant information processing in

  4. Undercomplete learned dictionaries for land cover classification in multispectral imagery of Arctic landscapes using CoSA: clustering of sparse approximations

    Science.gov (United States)

    Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; Gangodagamage, Chandana

    2013-05-01

    Techniques for automated feature extraction, including neuroscience-inspired machine vision, are of great interest for landscape characterization and change detection in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methodologies to the environmental sciences, using state-of-theart adaptive signal processing, combined with compressive sensing and machine learning techniques. We use a Hebbian learning rule to build undercomplete spectral-textural dictionaries that are adapted to the data. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labels are automatically generated using our CoSA algorithm: unsupervised Clustering of Sparse Approximations. We demonstrate our method using multispectral Worldview-2 data from three Arctic study areas: Barrow, Alaska; the Selawik River, Alaska; and a watershed near the Mackenzie River delta in northwest Canada. Our goal is to develop a robust classification methodology that will allow for the automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties, and geomorphic characteristics. To interpret and assign land cover categories to the clusters we both evaluate the spectral properties of the clusters and compare the clusters to both field- and remote sensing-derived classifications of landscape attributes. Our work suggests that neuroscience-based models are a promising approach to practical pattern recognition problems in remote sensing.

  5. Learning Disabilities

    Science.gov (United States)

    ... Situations Talking to Your Parents - or Other Adults Learning Disabilities KidsHealth > For Teens > Learning Disabilities Print A ... study engineering as he'd hoped? What Are Learning Disabilities? For someone diagnosed with a learning disability, ...

  6. Learning to Learn Differently

    Science.gov (United States)

    Olsen, Trude Høgvold; Glad, Tone; Filstad, Cathrine

    2018-01-01

    Purpose: This paper aims to investigate whether the formal and informal learning patterns of community health-care nurses changed in the wake of a reform that altered their work by introducing new patient groups, and to explore whether conditions in the new workplaces facilitated or impeded shifts in learning patterns. Design/methodology/approach:…

  7. Object segmentation and reconstruction via an oscillatory neural network: interaction among learning, memory, topological organization and gamma-band synchronization.

    Science.gov (United States)

    Magosso, E; Cuppini, C; Ursino, M

    2006-01-01

    Synchronization of neuronal activity in the gamma-band has been shown to play an important role in higher cognitive functions, by grouping together the necessary information in different cortical areas to achieve a coherent perception. In the present work, we used a neural network of Wilson-Cowan oscillators to analyze the problem of binding and segmentation of high-level objects. Binding is achieved by implementing in the network the similarity and prior knowledge Gestalt rules. Similarity law is realized via topological maps within the network. Prior knowledge originates by means of a Hebbian rule of synaptic change; objects are memorized in the network with different strengths. Segmentation is realized via a global inhibitor which allows desynchronisation among multiple objects avoiding interference. Simulation results performed with a 40x40 neural grid, using three simultaneous input objects, show that the network is able to recognize and segment objects in several different conditions (different degrees of incompleteness or distortion of input patterns), exhibiting the higher reconstruction performances the higher the strength of object memory. The presented model represents an integrated approach for investigating the relationships among learning, memory, topological organization and gamma-band synchronization.

  8. Learning Pitch with STDP: A Computational Model of Place and Temporal Pitch Perception Using Spiking Neural Networks.

    Directory of Open Access Journals (Sweden)

    Nafise Erfanian Saeedi

    2016-04-01

    Full Text Available Pitch perception is important for understanding speech prosody, music perception, recognizing tones in tonal languages, and perceiving speech in noisy environments. The two principal pitch perception theories consider the place of maximum neural excitation along the auditory nerve and the temporal pattern of the auditory neurons' action potentials (spikes as pitch cues. This paper describes a biophysical mechanism by which fine-structure temporal information can be extracted from the spikes generated at the auditory periphery. Deriving meaningful pitch-related information from spike times requires neural structures specialized in capturing synchronous or correlated activity from amongst neural events. The emergence of such pitch-processing neural mechanisms is described through a computational model of auditory processing. Simulation results show that a correlation-based, unsupervised, spike-based form of Hebbian learning can explain the development of neural structures required for recognizing the pitch of simple and complex tones, with or without the fundamental frequency. The temporal code is robust to variations in the spectral shape of the signal and thus can explain the phenomenon of pitch constancy.

  9. Distance Learning

    National Research Council Canada - National Science Library

    Braddock, Joseph

    1997-01-01

    A study reviewing the existing Army Distance Learning Plan (ADLP) and current Distance Learning practices, with a focus on the Army's training and educational challenges and the benefits of applying Distance Learning techniques...

  10. Learning Leaders for Learning Schools

    Science.gov (United States)

    Brown, Frederick; Psencik, Kay

    2017-01-01

    Principals who pay attention to their own learning serve as models for others. What principals do every day, how they view and value student and educator learning, how they organize their staff into learning communities, and the designs they support for those teams to learn make a significant difference in the learning of those they serve. In this…

  11. Learning contracts

    Directory of Open Access Journals (Sweden)

    Nena Mijoč

    2006-12-01

    Full Text Available There are four different expressions to describe the method of learning, which increases the efficiency of adult learning. The article explains the translation of »learning contract« into Slovene as a method in adult learning area, which came in use in USA in 1970, also in organizations offering formal education. In the period of lifelong learning, when everyone is supposed to be able to learn efficiently from different sources it is even more important to have the skills to plan our learning. Learning contract develops these competencies and has already become established in organizations, which support learning processes. Learning contract is slowly gaining ground also to the area of formal education. Learning contract is an agreement in writing between two people, where one of them offers advice, the other undertakes the learning process. How do we prepare the agreement, who is responsible for its preparation and execution? Learning contract in writing explains objectives, techniques, strategies and how the learning process will be assessed. At the same time, learning is also limited in time. It is a strong motivational took, since it comprises needs of an individual and is adapted to the interests and learning style of a particular individual. This is especially suitable method for acquiring competencies, for field work and experiential learning at work. Learning contract is very suitable and efficient also for independent academical studies, especially when combined with the method of discussion.

  12. Blended learning

    DEFF Research Database (Denmark)

    Dau, Susanne

    2016-01-01

    Blended Learning has been implemented, evaluated and researched for the last decades within different educational areas and levels. Blended learning has been coupled with different epistemological understandings and learning theories, but the fundamental character and dimensions of learning...... in blended learning are still insufficient. Moreover, blended learning is a misleading concept described as learning, despite the fact that it fundamentally is an instructional and didactic approach (Oliver & Trigwell, 2005) addressing the learning environment (Inglis, Palipoana, Trenhom & Ward, 2011......) instead of the learning processes behind. Much of the existing research within the field seems to miss this perspective. The consequence is a lack of acknowledgement of the driven forces behind the context and the instructional design limiting the knowledge foundation of learning in blended learning. Thus...

  13. Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition

    Science.gov (United States)

    Bill, Johannes; Buesing, Lars; Habenschuss, Stefan; Nessler, Bernhard; Maass, Wolfgang; Legenstein, Robert

    2015-01-01

    During the last decade, Bayesian probability theory has emerged as a framework in cognitive science and neuroscience for describing perception, reasoning and learning of mammals. However, our understanding of how probabilistic computations could be organized in the brain, and how the observed connectivity structure of cortical microcircuits supports these calculations, is rudimentary at best. In this study, we investigate statistical inference and self-organized learning in a spatially extended spiking network model, that accommodates both local competitive and large-scale associative aspects of neural information processing, under a unified Bayesian account. Specifically, we show how the spiking dynamics of a recurrent network with lateral excitation and local inhibition in response to distributed spiking input, can be understood as sampling from a variational posterior distribution of a well-defined implicit probabilistic model. This interpretation further permits a rigorous analytical treatment of experience-dependent plasticity on the network level. Using machine learning theory, we derive update rules for neuron and synapse parameters which equate with Hebbian synaptic and homeostatic intrinsic plasticity rules in a neural implementation. In computer simulations, we demonstrate that the interplay of these plasticity rules leads to the emergence of probabilistic local experts that form distributed assemblies of similarly tuned cells communicating through lateral excitatory connections. The resulting sparse distributed spike code of a well-adapted network carries compressed information on salient input features combined with prior experience on correlations among them. Our theory predicts that the emergence of such efficient representations benefits from network architectures in which the range of local inhibition matches the spatial extent of pyramidal cells that share common afferent input. PMID:26284370

  14. Learning Organization

    Directory of Open Access Journals (Sweden)

    Zdenka Birman Forjanič

    2006-12-01

    Full Text Available The article raises interests of what the learning organization is. The concept of a learning organization shall be introduced, we will also address conditions, necessary for creating learning organizations. Methodological research includes 205 Slovene organizations. Questionnaires will examine the fact whether learning organizations truly invest more into development and training of staff in comparison with non-learning organizations. Six characteristics, which appear as the ones to describe a learning organization best will be assisting in establishing organizations as learning and non-learning ones. Should an organization have four or more of these characteristics it has been established as a learning one and should there be fewer it has been established as a non-learning one.

  15. LEARN HOW TO LEARN

    African Journals Online (AJOL)

    Mekonnen

    It looks for solutions to problems through creativity and adaptation. Creativity is an essential capacity for working with complex and unpredictable learning situations such as those we encounter in our working and personal lives. It involves convergent and divergent thinking. And adaptation is doing or producing things that ...

  16. Learning English, Learning Science

    Science.gov (United States)

    Nelson, Virginia

    2010-01-01

    Using science notebooks effectively in the classroom can encourage students who are learning English to keep up and keep interested. English language proficiency might head the list of content areas that schools can teach properly and effectively through science. Amaral, Garrison, and Klentschy (2002) reported that a successful inquiry-based…

  17. Learning Organization

    OpenAIRE

    Zdenka Birman Forjanič

    2006-01-01

    The article raises interests of what the learning organization is. The concept of a learning organization shall be introduced, we will also address conditions, necessary for creating learning organizations. Methodological research includes 205 Slovene organizations. Questionnaires will examine the fact whether learning organizations truly invest more into development and training of staff in comparison with non-learning organizations. Six characteristics, which appear as the ones to describe ...

  18. Learn, how to learn

    Science.gov (United States)

    Narayanan, M.

    2002-12-01

    Ernest L. Boyer, in his 1990 book, "Scholarship Reconsidered: Priorities of the Professorate" cites some ground breaking studies and offers a new paradigm that identifies the need to recognize the growing conversation about teaching, scholarship and research in the Universities. The use of `ACORN' model suggested by Hawkins and Winter to conquer and mastering change, may offer some helpful hints for the novice professor, whose primary objective might be to teach students to `learn how to learn'. Action : It is possible to effectively change things only when a teaching professor actually tries out a new idea. Communication : Changes are successful only when the new ideas effectively communicated and implemented. Ownership : Support for change is extremely important and is critical. Only strong commitment for accepting changes demonstrates genuine leadership. Reflection : Feedback helps towards thoughtful evaluation of the changes implemented. Only reflection can provide a tool for continuous improvement. Nurture : Implemented changes deliver results only when nurtured and promoted with necessary support systems, documentation and infrastructures. Inspired by the ACORN model, the author experimented on implementing certain principles of `Total Quality Management' in the classroom. The author believes that observing the following twenty principles would indeed help the student learners how to learn, on their own towards achieving the goal of `Lifelong Learning'. The author uses an acronym : QUOTES : Quality Underscored On Teaching Excellence Strategy, to describe his methods for improving classroom teacher-learner participation. 1. Break down all barriers. 2. Create consistency of purpose with a plan. 3. Adopt the new philosophy of quality. 4. Establish high Standards. 5. Establish Targets / Goals. 6. Reduce dependence on Lectures. 7. Employ Modern Methods. 8. Control the Process. 9. Organize to reach goals. 10. Prevention vs. Correction. 11. Periodic Improvements. 12

  19. Posthuman learning

    DEFF Research Database (Denmark)

    Hasse, Cathrine

    and cognitivism. Both are today immensely important for machine learning, whereas the third and more recent school of social and situated learning theory have had much less impact on the engineering sciences. These socio-material theories move people from the center and place humans as embedded in larger......This book shall explore the concept of learning from the new perspective of the posthuman. The vast majority of cognitive, behavioral and part of the constructionist learning theories operate with an autonomous individual who learn in a world of separate objects. Technology is (if mentioned at all......) understood as separate from the individual learner and perceived as tools. Learning theory has in general not been acknowledging materiality in their theorizing about what learning is. A new posthuman learning theory is needed to keep up with the transformations of human learning resulting from new...

  20. Learning e-Learning

    Directory of Open Access Journals (Sweden)

    Gabriel ZAMFIR

    2009-01-01

    Full Text Available What You Understand Is What Your Cognitive Integrates. Scientific research develops, as a native environment, knowledge. This environment consists of two interdependent divisions: theory and technology. First division occurs as a recursive research, while the second one becomes an application of the research activity. Over time, theories integrate methodologies and technology extends as infrastructure. The engine of this environment is learning, as the human activity of knowledge work. The threshold term of this model is the concepts map; it is based on Bloom’ taxonomy for the cognitive domain and highlights the notion of software scaffolding which is grounded in Vygotsky’s Social Development Theory with its major theme, Zone of Proximal Development. This article is designed as a conceptual paper, which analyzes specific structures of this type of educational research: the model reflects a foundation for a theory and finally, the theory evolves as groundwork for a system. The outcomes of this kind of approach are the examples, which are, theoretically, learning outcomes, and practically exist as educational objects, so-called e-learning.

  1. Blended Learning

    NARCIS (Netherlands)

    Van der Baaren, John

    2009-01-01

    Van der Baaren, J. (2009). Blended Learning. Presentation given at the Mini symposium 'Blended Learning the way to go?'. November, 5, 2009, The Hague, The Netherlands: Netherlands Defence Academy (NDLA).

  2. Interface learning

    DEFF Research Database (Denmark)

    Thorhauge, Sally

    2014-01-01

    "Interface learning - New goals for museum and upper secondary school collaboration" investigates and analyzes the learning that takes place when museums and upper secondary schools in Denmark work together in local partnerships to develop and carry out school-related, museum-based coursework...... for students. The research focuses on the learning that the students experience in the interface of the two learning environments: The formal learning environment of the upper secondary school and the informal learning environment of the museum. Focus is also on the learning that the teachers and museum...... professionals experience as a result of their collaboration. The dissertation demonstrates how a given partnership’s collaboration affects the students’ learning experiences when they are doing the coursework. The dissertation presents findings that museum-school partnerships can use in order to develop...

  3. Workplace learning

    DEFF Research Database (Denmark)

    Warring, Niels

    2005-01-01

    In November 2004 the Research Consortium on workplace learning under Learning Lab Denmark arranged the international conference “Workplace Learning – from the learner’s perspective”. The conference’s aim was to bring together researchers from different countries and institutions to explore...... and discuss recent developments in our understanding of workplace and work-related learning. The conference had nearly 100 participants with 59 papers presented, and among these five have been selected for presentation is this Special Issue....

  4. Learning Disabilities

    Science.gov (United States)

    Sittiprapaporn, Wichian, Ed.

    2012-01-01

    Learning disability is a classification that includes several disorders in which a person has difficulty learning in a typical manner. Depending on the type and severity of the disability, interventions may be used to help the individual learn strategies that will foster future success. Some interventions can be quite simplistic, while others are…

  5. Just Learning

    Science.gov (United States)

    Larsen-Freeman, Diane

    2017-01-01

    In this "First Person Singular" essay, the author describes her education, teaching experience, and interest in understanding the learning of language. Anyone reading this essay will not be surprised to learn that the author's questions about language learning and optimal teaching methods were only met with further questions, and no…

  6. Blended Learning

    Science.gov (United States)

    Imbriale, Ryan

    2013-01-01

    Teachers always have been and always will be the essential element in the classroom. They can create magic inside four walls, but they have never been able to create learning environments outside the classroom like they can today, thanks to blended learning. Blended learning allows students and teachers to break free of the isolation of the…

  7. Learning Networks for Lifelong Learning

    OpenAIRE

    Sloep, Peter

    2008-01-01

    Presentation in a seminar organized by Christopher Hoadley at Penn State University, October 2004.Contains general introduction into the Learning Network Programme and a demonstration of the Netlogo Simulation of a Learning Network.

  8. Learning organisations

    Directory of Open Access Journals (Sweden)

    Sabina Jelenc Krašovec

    2000-12-01

    Full Text Available A vast array of economical, social, political, cultural and other factors influences the transformed role of learning and education in the society, as well as the functioning of local community and its social and communication patterns. The influences which are manifested as global problems can only be successfully solved on the level of local community. Analogously with the society in general, there is a great need of transforming a local community into a learning, flexible and interconnected environment which takes into account different interests, wishes and needs regarding learning and being active. The fundamental answer to changes is the strategy of lifelong learning and education which requires reorganisation of all walks of life (work, free time, family, mass media, culture, sport, education and transforming of organisations into learning organisations. With learning society based on networks of knowledge individuals are turning into learning individuals, and organisations into learning organisations; people who learn take the responsibility of their progress, learning denotes partnership among learning people, teachers, parents, employers and local community, so that they work together to achieve better results.

  9. Learning Processes and Learning Outcomes

    Science.gov (United States)

    1992-06-01

    taxonomy of learning skills. In P.L. Ackerman, R.J. Sternberg, & R. Glaser (Eds.), Learning and individual differences (pp. 117-163). New York: W.H. Freeman...R. Glaser (Eds.), Learning and individual differences (pp. 279-326). New York: W.H. Freeman. Shute, V.J., Woltz, D.J., & Regian, J.W. (1989). An

  10. Learning Opportunities for Group Learning

    Science.gov (United States)

    Gil, Alfonso J.; Mataveli, Mara

    2017-01-01

    Purpose: This paper aims to analyse the impact of organizational learning culture and learning facilitators in group learning. Design/methodology/approach: This study was conducted using a survey method applied to a statistically representative sample of employees from Rioja wine companies in Spain. A model was tested using a structural equation…

  11. Children's learning.

    Science.gov (United States)

    Siegler, Robert S

    2005-11-01

    A new field of children's learning is emerging. This new field differs from the old in recognizing that children's learning includes active as well as passive mechanisms and qualitative as well as quantitative changes. Children's learning involves substantial variability of representations and strategies within individual children as well as across different children. The path of learning involves the introduction of new approaches as well as changes in the frequency of prior ones. The rate and the breadth of learning tend to occur at a human scale, intermediate between the extremes depicted by symbolic and connectionist models. Learning has many sources; one that is particularly promising for educational purposes is self-explanations. Overall, contemporary analyses show that learning and development have a great deal in common. Copyright (c) 2005 APA, all rights reserved.

  12. Deep learning

    CERN Document Server

    Goodfellow, Ian; Courville, Aaron

    2016-01-01

    Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language proces...

  13. Doing learning

    DEFF Research Database (Denmark)

    Mathiasen, John Bang; Koch, Christian

    2014-01-01

    Purpose: To investigate how learning occurs in a systems development project, using a company developing wind turbine control systems in collaboration with customers as case. Design/methodology/approach: Dewey’s approach to learning is used, emphasising reciprocity between the individual’s experi......Purpose: To investigate how learning occurs in a systems development project, using a company developing wind turbine control systems in collaboration with customers as case. Design/methodology/approach: Dewey’s approach to learning is used, emphasising reciprocity between the individual...... development companies can safeguard their learning and product embedded knowledge when engaging in interorganisational collaboration handling the risk of giving knowledge away. Originality/value: The specific contribution involves Dewey’s approach to learning with focus on micro-processes of the individual...

  14. Machine Learning

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    Machine learning, which builds on ideas in computer science, statistics, and optimization, focuses on developing algorithms to identify patterns and regularities in data, and using these learned patterns to make predictions on new observations. Boosted by its industrial and commercial applications, the field of machine learning is quickly evolving and expanding. Recent advances have seen great success in the realms of computer vision, natural language processing, and broadly in data science. Many of these techniques have already been applied in particle physics, for instance for particle identification, detector monitoring, and the optimization of computer resources. Modern machine learning approaches, such as deep learning, are only just beginning to be applied to the analysis of High Energy Physics data to approach more and more complex problems. These classes will review the framework behind machine learning and discuss recent developments in the field.

  15. Metric learning

    CERN Document Server

    Bellet, Aurelien; Sebban, Marc

    2015-01-01

    Similarity between objects plays an important role in both human cognitive processes and artificial systems for recognition and categorization. How to appropriately measure such similarities for a given task is crucial to the performance of many machine learning, pattern recognition and data mining methods. This book is devoted to metric learning, a set of techniques to automatically learn similarity and distance functions from data that has attracted a lot of interest in machine learning and related fields in the past ten years. In this book, we provide a thorough review of the metric learnin

  16. PageRank-based identification of signaling crosstalk from transcriptomics data: the case of Arabidopsis thaliana.

    Science.gov (United States)

    Omranian, Nooshin; Mueller-Roeber, Bernd; Nikoloski, Zoran

    2012-04-01

    The levels of cellular organization, from gene transcription to translation to protein-protein interaction and metabolism, operate via tightly regulated mutual interactions, facilitating organismal adaptability and various stress responses. Characterizing the mutual interactions between genes, transcription factors, and proteins involved in signaling, termed crosstalk, is therefore crucial for understanding and controlling cells' functionality. We aim at using high-throughput transcriptomics data to discover previously unknown links between signaling networks. We propose and analyze a novel method for crosstalk identification which relies on transcriptomics data and overcomes the lack of complete information for signaling pathways in Arabidopsis thaliana. Our method first employs a network-based transformation of the results from the statistical analysis of differential gene expression in given groups of experiments under different signal-inducing conditions. The stationary distribution of a random walk (similar to the PageRank algorithm) on the constructed network is then used to determine the putative transcripts interrelating different signaling pathways. With the help of the proposed method, we analyze a transcriptomics data set including experiments from four different stresses/signals: nitrate, sulfur, iron, and hormones. We identified promising gene candidates, downstream of the transcription factors (TFs), associated to signaling crosstalk, which were validated through literature mining. In addition, we conduct a comparative analysis with the only other available method in this field which used a biclustering-based approach. Surprisingly, the biclustering-based approach fails to robustly identify any candidate genes involved in the crosstalk of the analyzed signals. We demonstrate that our proposed method is more robust in identifying gene candidates involved downstream of the signaling crosstalk for species for which large transcriptomics data sets, normalized with the same techniques, are available. Moreover, unlike approaches based on biclustering, our approach does not rely on any hidden parameters.

  17. Rank-Based miRNA Signatures for Early Cancer Detection

    Directory of Open Access Journals (Sweden)

    Mario Lauria

    2014-01-01

    Full Text Available We describe a new signature definition and analysis method to be used as biomarker for early cancer detection. Our new approach is based on the construction of a reference map of transcriptional signatures of both healthy and cancer affected individuals using circulating miRNA from a large number of subjects. Once such a map is available, the diagnosis for a new patient can be performed by observing the relative position on the map of his/her transcriptional signature. To demonstrate its efficacy for this specific application we report the results of the application of our method to published datasets of circulating miRNA, and we quantify its performance compared to current state-of-the-art methods. A number of additional features make this method an ideal candidate for large-scale use, for example, as a mass screening tool for early cancer detection or for at-home diagnostics. Specifically, our method is minimally invasive (because it works well with circulating miRNA, it is robust with respect to lab-to-lab protocol variability and batch effects (it requires that only the relative ranking of expression value of miRNA in a profile be accurate not their absolute values, and it is scalable to a large number of subjects. Finally we discuss the need for HPC capability in a widespread application of our or similar methods.

  18. Non-Convex Sparse and Low-Rank Based Robust Subspace Segmentation for Data Mining.

    Science.gov (United States)

    Cheng, Wenlong; Zhao, Mingbo; Xiong, Naixue; Chui, Kwok Tai

    2017-07-15

    Parsimony, including sparsity and low-rank, has shown great importance for data mining in social networks, particularly in tasks such as segmentation and recognition. Traditionally, such modeling approaches rely on an iterative algorithm that minimizes an objective function with convex l₁-norm or nuclear norm constraints. However, the obtained results by convex optimization are usually suboptimal to solutions of original sparse or low-rank problems. In this paper, a novel robust subspace segmentation algorithm has been proposed by integrating lp-norm and Schatten p-norm constraints. Our so-obtained affinity graph can better capture local geometrical structure and the global information of the data. As a consequence, our algorithm is more generative, discriminative and robust. An efficient linearized alternating direction method is derived to realize our model. Extensive segmentation experiments are conducted on public datasets. The proposed algorithm is revealed to be more effective and robust compared to five existing algorithms.

  19. Discovering urban mobility patterns with PageRank based traffic modeling and prediction

    Science.gov (United States)

    Wang, Minjie; Yang, Su; Sun, Yi; Gao, Jun

    2017-11-01

    Urban transportation system can be viewed as complex network with time-varying traffic flows as links to connect adjacent regions as networked nodes. By computing urban traffic evolution on such temporal complex network with PageRank, it is found that for most regions, there exists a linear relation between the traffic congestion measure at present time and the PageRank value of the last time. Since the PageRank measure of a region does result from the mutual interactions of the whole network, it implies that the traffic state of a local region does not evolve independently but is affected by the evolution of the whole network. As a result, the PageRank values can act as signatures in predicting upcoming traffic congestions. We observe the aforementioned laws experimentally based on the trajectory data of 12000 taxies in Beijing city for one month.

  20. Do PageRank-based author rankings outperform simple citation counts?

    CERN Document Server

    Fiala, Dalibor; Žitnik, Slavko; Bajec, Marko

    2015-01-01

    The basic indicators of a researcher's productivity and impact are still the number of publications and their citation counts. These metrics are clear, straightforward, and easy to obtain. When a ranking of scholars is needed, for instance in grant, award, or promotion procedures, their use is the fastest and cheapest way of prioritizing some scientists over others. However, due to their nature, there is a danger of oversimplifying scientific achievements. Therefore, many other indicators have been proposed including the usage of the PageRank algorithm known for the ranking of webpages and its modifications suited to citation networks. Nevertheless, this recursive method is computationally expensive and even if it has the advantage of favouring prestige over popularity, its application should be well justified, particularly when compared to the standard citation counts. In this study, we analyze three large datasets of computer science papers in the categories of artificial intelligence, software engineering,...

  1. Dual channel rank-based intensity weighting for quantitative co-localization of microscopy images

    LENUS (Irish Health Repository)

    Singan, Vasanth R

    2011-10-21

    Abstract Background Accurate quantitative co-localization is a key parameter in the context of understanding the spatial co-ordination of molecules and therefore their function in cells. Existing co-localization algorithms consider either the presence of co-occurring pixels or correlations of intensity in regions of interest. Depending on the image source, and the algorithm selected, the co-localization coefficients determined can be highly variable, and often inaccurate. Furthermore, this choice of whether co-occurrence or correlation is the best approach for quantifying co-localization remains controversial. Results We have developed a novel algorithm to quantify co-localization that improves on and addresses the major shortcomings of existing co-localization measures. This algorithm uses a non-parametric ranking of pixel intensities in each channel, and the difference in ranks of co-localizing pixel positions in the two channels is used to weight the coefficient. This weighting is applied to co-occurring pixels thereby efficiently combining both co-occurrence and correlation. Tests with synthetic data sets show that the algorithm is sensitive to both co-occurrence and correlation at varying levels of intensity. Analysis of biological data sets demonstrate that this new algorithm offers high sensitivity, and that it is capable of detecting subtle changes in co-localization, exemplified by studies on a well characterized cargo protein that moves through the secretory pathway of cells. Conclusions This algorithm provides a novel way to efficiently combine co-occurrence and correlation components in biological images, thereby generating an accurate measure of co-localization. This approach of rank weighting of intensities also eliminates the need for manual thresholding of the image, which is often a cause of error in co-localization quantification. We envisage that this tool will facilitate the quantitative analysis of a wide range of biological data sets, including high resolution confocal images, live cell time-lapse recordings, and high-throughput screening data sets.

  2. Interpretation of personal genome sequencing data in terms of disease ranks based on mutual information.

    Science.gov (United States)

    Na, Young-Ji; Sohn, Kyung-Ah; Kim, Ju Han

    2015-01-01

    The rapid advances in genome sequencing technologies have resulted in an unprecedented number of genome variations being discovered in humans. However, there has been very limited coverage of interpretation of the personal genome sequencing data in terms of diseases. In this paper we present the first computational analysis scheme for interpreting personal genome data by simultaneously considering the functional impact of damaging variants and curated disease-gene association data. This method is based on mutual information as a measure of the relative closeness between the personal genome and diseases. We hypothesize that a higher mutual information score implies that the personal genome is more susceptible to a particular disease than other diseases. The method was applied to the sequencing data of 50 acute myeloid leukemia (AML) patients in The Cancer Genome Atlas. The utility of associations between a disease and the personal genome was explored using data of healthy (control) people obtained from the 1000 Genomes Project. The ranks of the disease terms in the AML patient group were compared with those in the healthy control group using "Leukemia, Myeloid, Acute" (C04.557.337.539.550) as the corresponding MeSH disease term. Overall, the area under the receiver operating characteristics curve was significantly larger for the AML patient data than for the healthy controls. This methodology could contribute to consequential discoveries and explanations for mining personal genome sequencing data in terms of diseases, and have versatility with respect to genomic-based knowledge such as drug-gene and environmental-factor-gene interactions.

  3. Learning to learn in MOOCs

    DEFF Research Database (Denmark)

    Milligan, Sandra; Ringtved, Ulla Lunde

    This paper outlines one way of understanding what it is about learning in MOOCs that is so distinctive, and explores the implications for the design of MOOCs. It draws on an ongoing research study into the nature of learning in MOOCs at the University of Melbourne.......This paper outlines one way of understanding what it is about learning in MOOCs that is so distinctive, and explores the implications for the design of MOOCs. It draws on an ongoing research study into the nature of learning in MOOCs at the University of Melbourne....

  4. Creative Learning

    Science.gov (United States)

    Wiggins, Grant

    2017-01-01

    This article consists of short quotations from the author's chapter "Creative Learning" written for the "Routledge International Handbook of Creative Learning." It argues that, when assessing creativity, we should look for fitness to purpose as well as inventiveness, and that creativity can be assessed and recognised in a wide…

  5. Virtual Learning

    Science.gov (United States)

    Cvetkovic, Dragan, Ed.

    2016-01-01

    The first chapter provides an overview of the popular systems for distance learning. In the second chapter, a review of all major social and economic activities in order to improve the system of virtual learning is given. The third chapter deals with the influence of technology in the management of educational institutions. The fourth chapter…

  6. Advanced Learning

    Science.gov (United States)

    Hijon-Neira, Raquel, Ed.

    2009-01-01

    The education industry has obviously been influenced by the Internet revolution. Teaching and learning methods have changed significantly since the coming of the Web and it is very likely they will keep evolving many years to come thanks to it. A good example of this changing reality is the spectacular development of e-Learning. In a more…

  7. Distance learning

    Directory of Open Access Journals (Sweden)

    Katarina Pucelj

    2006-12-01

    Full Text Available I would like to underline the role and importance of knowledge, which is acquired by individuals as a result of a learning process and experience. I have established that a form of learning, such as distance learning definitely contributes to a higher learning quality and leads to innovative, dynamic and knowledgebased society. Knowledge and skills enable individuals to cope with and manage changes, solve problems and also create new knowledge. Traditional learning practices face new circumstances, new and modern technologies appear, which enable quick and quality-oriented knowledge implementation. The centre of learning process at distance learning is to increase the quality of life of citizens, their competitiveness on the workforce market and ensure higher economic growth. Intellectual capital is the one, which represents the biggest capital of each society and knowledge is the key factor for succes of everybody, who are fully aware of this. Flexibility, openness and willingness of people to follow new IT solutions form suitable environment for developing and deciding to take up distance learning.

  8. Blended learning

    DEFF Research Database (Denmark)

    Staugaard, Hans Jørgen

    2012-01-01

    Forsøg på at indkredse begrebet blended learning i forbindelse med forberedelsen af projekt FlexVid.......Forsøg på at indkredse begrebet blended learning i forbindelse med forberedelsen af projekt FlexVid....

  9. Pervasive Learning

    DEFF Research Database (Denmark)

    Helms, Niels Henrik; Larsen, Lasse Juel

    2009-01-01

    , it is not a specific place where you can access scarce information. Pervasive or ubiquitous communication opens up for taking the organizing and design of learning landscapes a step further. Furthermore it calls for theoretical developments, which can open up for a deeper understanding of the relationship between...... emerging contexts, design of contexts and learning....

  10. Mobile Learning

    Science.gov (United States)

    Hockly, Nicky

    2013-01-01

    In this series, we explore current technology-related themes and topics. The series aims to discuss and demystify what may be new areas for some readers and to consider their relevance to English language teachers. In future articles, we will be covering topics such as learning technologies in low-resource environments, personal learning networks,…

  11. Learning Cultures

    DEFF Research Database (Denmark)

    Rasmussen, Lauge Baungaard

    1998-01-01

    the article present different concepts and modelsof learning. It discuss some strutural tendenciesof developing environmental management systemsand point out alternatives to increasing formalization of rules.......the article present different concepts and modelsof learning. It discuss some strutural tendenciesof developing environmental management systemsand point out alternatives to increasing formalization of rules....

  12. Flipped Learning

    DEFF Research Database (Denmark)

    Hachmann, Roland; Holmboe, Peter

    arbejde med faglige problemstillinger gennem problembaserede og undersøgende didaktiske designs. Flipped Learning er dermed andet og mere end at distribuere digitale materialer til eleverne forud for undervisning. Flipped Learning er i lige så høj grad et syn på, hvordan undervisning med digitale medier...

  13. Flipped Learning

    DEFF Research Database (Denmark)

    Holmboe, Peter; Hachmann, Roland

    I FLIPPED LEARNING – FLIP MED VIDEO kan du læse om, hvordan du som underviser kommer godt i gang med at implementere video i undervisning, der har afsæt i tankerne omkring flipped learning. Bogen indeholder fire dele: I Del 1 fokuserer vi på det metarefleksive i at tænke video ind i undervisningen...

  14. Learning Disabilities.

    Science.gov (United States)

    McCarthy, James J.; McCarthy, Joan F.

    An attempt to collate basic knowledge concerning learning disabilities, the text discusses the background and definition of learning disabilities, and its identification, etiology, and epidemiology. Guidelines for diagnostic evaluation are presented as are approaches from perceptual motor, developmental, visual, neurophysiological, linguistic, and…

  15. Blended Learning

    DEFF Research Database (Denmark)

    Gynther, Karsten

    2012-01-01

    Artiklen giver en grundlæggende introduktion til begrebet blended learning og sætter fokus på didaktiske spørgsmål som: Hvad er blended learning? Hvilke forskellige former ser vi i dag i danske uddannelser? Hvorfor udbydes uddannelser i stigende grad i et blended learning format? Hvilke didaktiske...... principper kan man som underviser tage i brug, når man skal designe et blended learning forløb? Hvad er den grundlæggende didaktiske forskel på tilstedeværelsesundervisning og netbaseret undervisning? Og hvilke kritiske perspektiver er det vigtigt at have med, når en uddannelsesinstitution beslutter sig...... for at re-designe traditionel tilstedeværelsesundervisning til blended learning?...

  16. Blended Learning as Transformational Institutional Learning

    Science.gov (United States)

    VanDerLinden, Kim

    2014-01-01

    This chapter reviews institutional approaches to blended learning and the ways in which institutions support faculty in the intentional redesign of courses to produce optimal learning. The chapter positions blended learning as a strategic opportunity to engage in organizational learning.

  17. Learning Networks for Lifelong Learning

    NARCIS (Netherlands)

    Koper, Rob

    2004-01-01

    Presentation in a seminar organized by Christopher Hoadley at Penn State University, October 2004.Contains general introduction into the Learning Network Programme and a demonstration of the Netlogo Simulation of a Learning Network.

  18. Teacher learning as workplace learning

    NARCIS (Netherlands)

    Imants, J.; Van Veen, K.

    2010-01-01

    Against the background of increasing attention in teacher professional development programs for situating teacher learning in the workplace, an overview is given of what is known in general and in educational workplace learning literature on the characteristics and conditions of the workplace.

  19. Altruistic learning

    Directory of Open Access Journals (Sweden)

    Ben Seymour

    2009-09-01

    Full Text Available The origin of altruism remains one of the most enduring puzzles of human behaviour. Indeed, true altruism is often thought either not to exist, or to arise merely as a miscalculation of otherwise selfish behaviour. In this paper, we argue that altruism emerges directly from the way in which distinct human decision-making systems learn about rewards. Using insights provided by neurobiological accounts of human decision-making, we suggest that reinforcement learning in game-theoretic social interactions (habitization over either individuals or games and observational learning (either imitative of inference based lead to altruistic behaviour. This arises not only as a result of computational efficiency in the face of processing complexity, but as a direct consequence of optimal inference in the face of uncertainty. Critically, we argue that the fact that evolutionary pressure acts not over the object of learning ('what' is learned, but over the learning systems themselves ('how' things are learned, enables the evolution of altruism despite the direct threat posed by free-riders.

  20. Altruistic learning.

    Science.gov (United States)

    Seymour, Ben; Yoshida, Wako; Dolan, Ray

    2009-01-01

    The origin of altruism remains one of the most enduring puzzles of human behaviour. Indeed, true altruism is often thought either not to exist, or to arise merely as a miscalculation of otherwise selfish behaviour. In this paper, we argue that altruism emerges directly from the way in which distinct human decision-making systems learn about rewards. Using insights provided by neurobiological accounts of human decision-making, we suggest that reinforcement learning in game-theoretic social interactions (habitisation over either individuals or games) and observational learning (either imitative of inference based) lead to altruistic behaviour. This arises not only as a result of computational efficiency in the face of processing complexity, but as a direct consequence of optimal inference in the face of uncertainty. Critically, we argue that the fact that evolutionary pressure acts not over the object of learning ('what' is learned), but over the learning systems themselves ('how' things are learned), enables the evolution of altruism despite the direct threat posed by free-riders.

  1. Learning Spaces

    CERN Document Server

    Falmagne, Jean-Claude

    2011-01-01

    Learning spaces offer a rigorous mathematical foundation for practical systems of educational technology. Learning spaces generalize partially ordered sets and are special cases of knowledge spaces. The various structures are investigated from the standpoints of combinatorial properties and stochastic processes. Leaning spaces have become the essential structures to be used in assessing students' competence of various topics. A practical example is offered by ALEKS, a Web-based, artificially intelligent assessment and learning system in mathematics and other scholarly fields. At the heart of A

  2. Supportive Learning: Linear Learning and Collaborative Learning

    Science.gov (United States)

    Lee, Bih Ni; Abdullah, Sopiah; Kiu, Su Na

    2016-01-01

    This is a conceptual paper which is trying to look at the educational technology is not limited to high technology. However, electronic educational technology, also known as e-learning, has become an important part of today's society, which consists of a wide variety of approaches to digitization, components and methods of delivery. In the…

  3. Learning Disabilities

    Science.gov (United States)

    ... NICHD) See all related organizations Publications Problemas de aprendizaje Order NINDS Publications Patient Organizations CHADD - Children and ... NICHD) See all related organizations Publications Problemas de aprendizaje Order NINDS Publications Definition Learning disabilities are disorders ...

  4. Learning Leadership

    DEFF Research Database (Denmark)

    Hertel, Frederik; Fast, Alf Michael

    2018-01-01

    to lead the organization. While asked they are unable to describe how, where and when they think a practitioner develops leadership skills necessary for leading fellows. In the following we will start analysing the case in order to comprehend and discuss both the professional leaders and the practitioners......Is leadership a result of inheritance or is it something one learns during formal learning in e.g. business schools? This is the essential question addressed in this article. The article is based on a case study involving a new leader in charge of a group of profession practitioners. The leader...... promotes his leadership as a profession comparable to the professions of practitioners. This promotion implies that leadership is something one can and probably must learn during formal learning. The practitioners on the other hand reject this comprehension of leadership and long for a fellow practitioner...

  5. Machine Learning

    Energy Technology Data Exchange (ETDEWEB)

    Chikkagoudar, Satish; Chatterjee, Samrat; Thomas, Dennis G.; Carroll, Thomas E.; Muller, George

    2017-04-21

    The absence of a robust and unified theory of cyber dynamics presents challenges and opportunities for using machine learning based data-driven approaches to further the understanding of the behavior of such complex systems. Analysts can also use machine learning approaches to gain operational insights. In order to be operationally beneficial, cybersecurity machine learning based models need to have the ability to: (1) represent a real-world system, (2) infer system properties, and (3) learn and adapt based on expert knowledge and observations. Probabilistic models and Probabilistic graphical models provide these necessary properties and are further explored in this chapter. Bayesian Networks and Hidden Markov Models are introduced as an example of a widely used data driven classification/modeling strategy.

  6. Learning Problems

    Science.gov (United States)

    ... have a learning disability, such as dyslexia or dyscalculia (serious trouble with math), remember that you are ... Kids who have trouble with math may have dyscalculia (say: diss-kal-KYOO-lee-uh). And people ...

  7. Application of Unsupervised Clustering using Sparse Representations on Learned Dictionaries to develop Land Cover Classifications in Arctic Landscapes

    Science.gov (United States)

    Rowland, J. C.; Moody, D. I.; Brumby, S.; Gangodagamage, C.

    2012-12-01

    Techniques for automated feature extraction, including neuroscience-inspired machine vision, are of great interest for landscape characterization and change detection in support of global climate change science and modeling. Successful application of novel unsupervised feature extraction and clustering algorithms for use in Land Cover Classification requires the ability to determine what landscape attributes are represented by automated clustering. A closely related challenge is learning how to precondition the input data streams to the unsupervised classification algorithms in order to obtain clusters that represent Land Cover category of relevance to landsurface change and modeling applications. We present results from an ongoing effort to apply novel clustering methodologies developed primarily for neuroscience machine vision applications to the environmental sciences. We use a Hebbian learning rule to build spectral-textural dictionaries that are adapted to the data. We learn our dictionaries from millions of overlapping image patches and then use a pursuit search to generate sparse classification features. These sparse representations of pixel patches are used to perform unsupervised k-means clustering. In our application, we use 8-band multispectral Worldview-2 data from three arctic study areas: Barrow, Alaska; the Selawik River, Alaska; and a watershed near the Mackenzie River delta in northwest Canada. Our goal is to develop a robust classification methodology that will allow for the automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties (e.g. soil moisture and inundation), and topographic/geomorphic characteristics. The challenge of developing a meaningful land cover classification includes both learning how optimize the clustering algorithm and successfully interpreting the results. In applying the unsupervised clustering, we have the flexibility of selecting both the window

  8. Deep learning

    Science.gov (United States)

    Lecun, Yann; Bengio, Yoshua; Hinton, Geoffrey

    2015-05-01

    Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically improved the state-of-the-art in speech recognition, visual object recognition, object detection and many other domains such as drug discovery and genomics. Deep learning discovers intricate structure in large data sets by using the backpropagation algorithm to indicate how a machine should change its internal parameters that are used to compute the representation in each layer from the representation in the previous layer. Deep convolutional nets have brought about breakthroughs in processing images, video, speech and audio, whereas recurrent nets have shone light on sequential data such as text and speech.

  9. Learning SPARQL

    CERN Document Server

    DuCharme, Bob

    2011-01-01

    Get hands-on experience with SPARQL, the RDF query language that's become a key component of the semantic web. With this concise book, you will learn how to use the latest version of this W3C standard to retrieve and manipulate the increasing amount of public and private data available via SPARQL endpoints. Several open source and commercial tools already support SPARQL, and this introduction gets you started right away. Begin with how to write and run simple SPARQL 1.1 queries, then dive into the language's powerful features and capabilities for manipulating the data you retrieve. Learn wha

  10. Resonant learning

    DEFF Research Database (Denmark)

    Lindvang, Charlotte

    2013-01-01

    The article presents a part of the authors PhD-study in music therapy about self-experiential training and the development of music therapeutic competencies. One of the purposes of the study was to explore and generate understanding and insight into the phenomena of learning through self-experien......The article presents a part of the authors PhD-study in music therapy about self-experiential training and the development of music therapeutic competencies. One of the purposes of the study was to explore and generate understanding and insight into the phenomena of learning through self...

  11. Situating learning

    DEFF Research Database (Denmark)

    Ribeiro, Gustavo; Georg, Susse; Finchman, Rob

    2004-01-01

    This paper looks at learning experiences in South Africa and Thailand by highlighting the role of context and culture in the learning process. The authors are based at Danish and South African higher education institutions and have contributed to DUCED's TFS programme in the positions of overall....... Such exploration involves the participation of students as actors in the process of urban management and in the implementation of environmental projects by NGO's, CBO's and public institutions. It involves contact with communities and interaction with students and staff from local universities under the LUCED co...

  12. Overcoming Math Anxiety by Learning about Learning.

    Science.gov (United States)

    Frankenstein, Marilyn

    1984-01-01

    Some misconceptions about learning are discussed and specific suggestions for helping students in a college developmental mathematics class learn how to learn mathematics are presented. Extensive footnotes are appended. (MNS)

  13. Mastering machine learning with scikit-learn

    CERN Document Server

    Hackeling, Gavin

    2014-01-01

    If you are a software developer who wants to learn how machine learning models work and how to apply them effectively, this book is for you. Familiarity with machine learning fundamentals and Python will be helpful, but is not essential.

  14. Deep Learning in Open Source Learning Streams

    DEFF Research Database (Denmark)

    Kjærgaard, Thomas

    2016-01-01

    This chapter presents research on deep learning in a digital learning environment and raises the question if digital instructional designs can catalyze deeper learning than traditional classroom teaching. As a theoretical point of departure the notion of ‘situated learning’ is utilized...... and contrasted to the notion of functionalistic learning in a digital context. The mechanism that enables deep learning in this context is ‘The Open Source Learning Stream’. ‘The Open Source Learning Stream’ is the notion of sharing ‘learning instances’ in a digital space (discussion board, Facebook group......, unistructural, multistructural or relational learning. The research concludes that ‘The Open Source Learning Stream’ can catalyze deep learning and that there are four types of ‘Open Source Learning streams’; individual/ asynchronous, individual/synchronous, shared/asynchronous and shared...

  15. Learning Gene Regulatory Networks Computationally from Gene Expression Data Using Weighted Consensus

    KAUST Repository

    Fujii, Chisato

    2015-04-16

    Gene regulatory networks analyze the relationships between genes allowing us to un- derstand the gene regulatory interactions in systems biology. Gene expression data from the microarray experiments is used to obtain the gene regulatory networks. How- ever, the microarray data is discrete, noisy and non-linear which makes learning the networks a challenging problem and existing gene network inference methods do not give consistent results. Current state-of-the-art study uses the average-ranking-based consensus method to combine and average the ranked predictions from individual methods. However each individual method has an equal contribution to the consen- sus prediction. We have developed a linear programming-based consensus approach which uses learned weights from linear programming among individual methods such that the methods have di↵erent weights depending on their performance. Our result reveals that assigning di↵erent weights to individual methods rather than giving them equal weights improves the performance of the consensus. The linear programming- based consensus method is evaluated and it had the best performance on in silico and Saccharomyces cerevisiae networks, and the second best on the Escherichia coli network outperformed by Inferelator Pipeline method which gives inconsistent results across a wide range of microarray data sets.

  16. Learning disabilities.

    Science.gov (United States)

    Lyon, G R

    1996-01-01

    Approximately 5% of all public school students are identified as having a learning disability (LD). LD is not a single disorder, but includes disabilities in any of seven areas related to reading, language, and mathematics. These separate types of learning disabilities frequently co-occur with one another and with social skill deficits and emotional or behavioral disorders. Most of the available information concerning learning disabilities relates to reading disabilities, and the majority of children with learning disabilities have their primary deficits in basic reading skills. An important part of the definition of LD is its exclusions: learning disabilities cannot be attributed primarily to mental retardation, emotional disturbance, cultural difference, or disadvantage. Thus, the concept of LD focuses on the notion of a discrepancy between a child's academic achievement and his or her apparent capacity to learn. Recent research indicates, however, that disability in basic reading skills is primarily caused by deficits in phonological awareness, which is independent of any achievement-capacity discrepancy. Deficits in phonological awareness can be identified in late kindergarten and first grade using inexpensive, straightforward testing protocol. Interventions have varying effectiveness, depending largely on the severity of the individual child's disability. The prevalence of learning disability identification has increased dramatically in the past 20 years. The "real" prevalence of LD is subject to much dispute because of the lack of an agreed-upon definition of LD with objective identification criteria. Some researchers have argued that the currently recognized 5% prevalence rate is inflated; others argue that LD is still underidentified. In fact, it appears that there are both sound and unsound reasons for the increase in identification rates. Sound reasons for the increase include better research, a broader definition of disability in reading, focusing on

  17. Learning Disabilities and ADHD

    Science.gov (United States)

    ... disabilities Learning disabilities and ADHD Learning disabilities and ADHD Learning disabilities affect how you understand, remember, and ... learning skills, including memory tips from LD Online. Attention deficit hyperactivity disorder (ADHD) top ADHD is a medical condition that ...

  18. Deepening Learning through Learning-by-Inventing

    OpenAIRE

    Apiola, Mikko; Tedre, Matti

    2013-01-01

    It has been shown that deep approaches to learning, intrinsic motivation, and self-regulated learning have strong positive effects on learning. How those pedagogical theories can be integrated in computing curricula is, however, still lacking empirically grounded analyses. This study integrated, in a robotics-based programming class, a method of learning-by-inventing, and studied its qualitative effects on students’ learning through 144 interviews. Five findings were related with learning the...

  19. Learning interactive learning strategy with genetic algorithm

    OpenAIRE

    Hanzel, Jan

    2014-01-01

    The main goal of this thesis was to develop an algoritem for learning the best strategy in the case of interactive learning between a human and a robot. We presented the definition and formalization of a learning strategy. A learning strategy specifies the behaviour of a student and a teacher in a interactive learning process. We also presented a genetic algorithm to resolve our optimisation problem. We tryed to inpruve vectors which are used to present learning strategies. The vectors were...

  20. Adaptive learning and testing with learning objects

    OpenAIRE

    Yau, Jane Yin-Kim; Joy, Mike

    2004-01-01

    Learning objects are pedagogic software components which are interoperable, exchangeable and reusable between web-based learning environments, and adaptive learning and testing can provide each student with personalized learning content or assessment questions. In this paper, we describe our existing adaptive authoring tool which can be used to convert a non-adaptive course into an adaptive one which uses learning objects. Learning material can be reused in our framework which consists of les...

  1. From Learning Organization to Learning Community: Sustainability through Lifelong Learning

    Science.gov (United States)

    Kearney, Judith; Zuber-Skerritt, Ortrun

    2012-01-01

    Purpose: This paper aims to: extend the concept of "The learning organization" to "The learning community," especially disadvantaged communities; demonstrate how leaders in a migrant community can achieve positive change at the personal, professional, team and community learning levels through participatory action learning and…

  2. Animated Learning.

    Science.gov (United States)

    Algava, Alisa

    1999-01-01

    A class of fourth-graders-turned-film-producers created an animated video about national parks. The experience helped students acquire academic skills and knowledge, use technology meaningfully, feel confident about themselves and their learning, value cooperation, understand the creative process, sustain a vision, and have fun in school. (MLH)

  3. Learning Styles.

    Science.gov (United States)

    Zapalska, Alina M.; Dabb, Helen

    2002-01-01

    Describes an assessment instrument (VARK) that college professors can use to identify their own teaching strategies as well as to help student become more aware of their own learning strategies and motivations. Discusses its use with students in West Virginia and New Zealand, and potential use in Central and Eastern Europe. (EV)

  4. Privileged Learning

    Science.gov (United States)

    Wagoner, Norma E.; Romero-O'Connell, Josina M.

    2009-01-01

    Students often attain memorable experiences from cadaver dissections through reflective writing. For many, facing a dissection for the first time elicits a wide range of emotions. These may include thoughts of their own mortality to the sheer admiration of knowing that someone cared enough to help others learn about the body, even in death. Poems…

  5. Reflective Learning

    African Journals Online (AJOL)

    dell

    students who used learning log and those who did not especially for the course Pschopharmacology, but the mean scores did not show a significant difference for the course Psychology of Gender. The reflective reports of the students also roughly indicated that the students developed positive attitudes towards using ...

  6. Learning Together.

    Science.gov (United States)

    Saunders, Laserik

    1998-01-01

    By successfully creating links with the larger community, one San Diego high school principal discovered the keys to building a true learning community. Community building requires a shared, research-based vision; specific educational goals; a meaningfully aligned curriculum; constituent involvement; careful monitoring; ongoing professional…

  7. Learning Ionic

    CERN Document Server

    Ravulavaru, Arvind

    2015-01-01

    This book is intended for those who want to learn how to build hybrid mobile applications using Ionic. It is also ideal for people who want to explore theming for Ionic apps. Prior knowledge of AngularJS is essential to complete this book successfully.

  8. Lessons Learned.

    Science.gov (United States)

    Haynes, Norris M.

    1998-01-01

    Discusses lessons learned in the implementation of James Comer's School Development Program including: (1) leadership; (2) overcoming resistance to change; (3) time required for change; (4) creating a supportive climate; (5) staff commitment and staff time; (6) personnel and staff training; (7) parent involvement; (8) connecting school and…

  9. Documenting Learning

    Science.gov (United States)

    Ashbrook, Peggy

    2010-01-01

    Children's work documents their thinking and the details they note as they learn more. Over time, by drawing, dictating, or writing about their observations, children can reveal and deepen their understanding of science concepts. Documenting work to further understanding and sharing information is part of the National Science Education Teaching…

  10. Learning Ansible

    CERN Document Server

    Mohaan, Madhurranjan

    2014-01-01

    If you want to learn how to use Ansible to automate an infrastructure, either from scratch or to augment your current tooling with Ansible, then this is the book for you. It has plenty of practical examples to help you get to grips with Ansible.

  11. Sustainable Learning

    Science.gov (United States)

    Cadwell, Louise; Dillon, Robert

    2011-01-01

    Green schools have moved into a new era that focuses on building a culture of sustainability in every aspect of learning in schools. In the early stages of sustainability education, the focus was on recycling and turning off the lights. Now, students and adults together are moving into the areas of advocacy and action that are based on a deep…

  12. Learning Literacies.

    Science.gov (United States)

    Minter, Deborah Williams; And Others

    1995-01-01

    Describes a service learning course for which students participated in a seminar on literacy and an after-school tutoring program for children. Shows how undergraduate representations of literacy share common features with conversations among well-known writers (such as Walter Ong and David Olson) and also implicitly critique them. (TB)

  13. Learning Mongoid

    CERN Document Server

    Rege, Gautam

    2013-01-01

    A step-by-step tutorial with focused examples that will help you build scalable, high performance Rails web applications with Mongoid.If you are an application developer who wants to learn how to use Mongoid in a Rails application, this book will be great for you. You are expected to be familiar with MongoDB and Ruby.

  14. Neural correlates of motor learning, transfer of learning, and learning to learn.

    Science.gov (United States)

    Seidler, Rachael D

    2010-01-01

    Recent studies on the neural bases of sensorimotor adaptation demonstrate that the cerebellar and striatal thalamocortical pathways contribute to early learning. Transfer of learning involves a reduction in the contribution of early learning networks and increased reliance on the cerebellum. The neural correlates of learning to learn remain to be determined but likely involve enhanced functioning of the general aspects of early learning.

  15. Deep Learning in Open Source Learning Streams

    DEFF Research Database (Denmark)

    Kjærgaard, Thomas

    2016-01-01

    This chapter presents research on deep learning in a digital learning environment and raises the question if digital instructional designs can catalyze deeper learning than traditional classroom teaching. As a theoretical point of departure the notion of ‘situated learning’ is utilized...... and contrasted to the notion of functionalistic learning in a digital context. The mechanism that enables deep learning in this context is ‘The Open Source Learning Stream’. ‘The Open Source Learning Stream’ is the notion of sharing ‘learning instances’ in a digital space (discussion board, Facebook group......, Twitter hashtags etc.). The ‘learning instances’ are described as mediated signs of learning expressed through text in the stream that is further developed by peers and by the teacher. The expressions of ‘learning instances’ are analyzed and categorized according to whether it expresses prestructural...

  16. How we learn

    DEFF Research Database (Denmark)

    Illeris, Knud

    How We Learn, deals with the fundamental issues of the processes of learning, critically assessing different types of learning and obstacles to learning. It also considers a broad range of other important questions in relation to learning such as: modern research into learning and brain functions......, self-perception, motivation and competence development, teaching, intelligence and learning style, learning in relation to gender and life age. The book provides a comprehensive introduction to both traditional learning theory and the newest international research into learning processes, while...... at the same time being an innovative contribution to a new and more holistic understanding of learning including discussion on school-based learning, net-based learning, workplace learning and educational politics. How We Learn examines all the key factors that help to create a holistic understanding of what...

  17. Learning to Improve Improved Learning

    NARCIS (Netherlands)

    J.W.M. Weggelaar-Jansen (Anne Marie)

    2015-01-01

    markdownabstractThis thesis focuses on the connection between learning and quality improvement in health care. I explored this from the macro, meso and micro level perspectives. The central research question of this thesis is: Which issues support and hinder the development of

  18. Learning Networks for Lifelong Learning

    NARCIS (Netherlands)

    Koper, Rob

    2004-01-01

    Presentation at: "Learning Designs in a Networked World A Dutch - Canada Education Seminar", October 15th, 2004, University of Alberta, Edmonton, Canada. Similar presentation as: http://hdl.handle.net/1820/278

  19. Learning to Learn about Uncertain Feedback

    Science.gov (United States)

    Faraut, Mailys C. M.; Procyk, Emmanuel; Wilson, Charles R. E.

    2016-01-01

    Unexpected outcomes can reflect noise in the environment or a change in the current rules. We should ignore noise but shift strategy after rule changes. How we learn to do this is unclear, but one possibility is that it relies on learning to learn in uncertain environments. We propose that acquisition of latent task structure during learning to…

  20. Social Media and Seamless Learning: Lessons Learned

    Science.gov (United States)

    Panke, Stefanie; Kohls, Christian; Gaiser, Birgit

    2017-01-01

    The paper discusses best practice approaches and metrics for evaluation that support seamless learning with social media. We draw upon the theoretical frameworks of social learning theory, transfer learning (bricolage), and educational design patterns to elaborate upon different ideas for ways in which social media can support seamless learning.…

  1. Professional Learning Communities: Teaching, Learning, Understanding

    Science.gov (United States)

    Early, Phaedra Bell

    2012-01-01

    The purpose of this study was to focus on teacher learning as it relates to professional learning communities. It is often touted that schools are a place for student learning, but many teachers now see school as a place for them to become learners as well through professional learning communities. This qualitative case study was designed to…

  2. Using Learning Games to Meet Learning Objectives

    DEFF Research Database (Denmark)

    Henriksen, Thomas Duus

    2013-01-01

    This paper addresses the question on how learning games can be used to meet with the different levels in Bloom’s and the SOLO taxonomy, which are commonly used for evaluating the learning outcome of educational activities. The paper discusses the quality of game-based learning outcomes based...... on a case study of the learning game 6Styles....

  3. Open Learning Materials and Learning Centres.

    Science.gov (United States)

    Clarke, Alan; Walmsley, Joyce

    The availability and nature of open learning materials and centers in Great Britain were examined in a study that focused on the following: the open learning market; learning materials; commercial suppliers; basic skills materials; information technology materials; online learning; information technology and tutors; qualifications; prices;…

  4. Lifelong Learning

    DEFF Research Database (Denmark)

    Krogh, Lone; Jensen, Annie Aarup

    2010-01-01

    University has during the last 9 years made it possible for adults from public and private organizations to go through continued academic education. This paper presents some of the results of a research project investigating the adult students' motives and needs for participating in a master education......Master education for adults has become a strategy for Lifelong Learning among many well-educated people in Denmark. This type of master education is part of the ‘parallel education system' in Denmark. As one of the first Danish universities who offered this type of Master education, Aalborg...... the intended as well as the unintended effects (personal and professional) of the master education. The data have been gathered among graduates from a specific master education, Master in Learning Processes, and the paper will draw on results from a quantitative survey based on a questionnaire answered by 120...

  5. Learning Java

    CERN Document Server

    Niemeyer, Patrick

    2005-01-01

    Version 5.0 of the Java 2 Standard Edition SDK is the most important upgrade since Java first appeared a decade ago. With Java 5.0, you'll not only find substantial changes in the platform, but to the language itself-something that developers of Java took five years to complete. The main goal of Java 5.0 is to make it easier for you to develop safe, powerful code, but none of these improvements makes Java any easier to learn, even if you've programmed with Java for years. And that means our bestselling hands-on tutorial takes on even greater significance. Learning Java is the most widely sou

  6. Blended learning

    OpenAIRE

    渡辺, 史央; 北川, 幸子

    2015-01-01

    In recent years, the training initiatives in blended learning increased enormously as a result of the different demands to integrate the Information and Communication Technologies (ICT) in educational systems. In Higher Education, the blend approach is highly pursued because of its unique flexibility that allows the teacher to propose, in every situation, more advantageous train- ing solutions for their students, contrary to mandatory classroom in Basic and Secondary schools. It seems that th...

  7. Learning Raspbian

    CERN Document Server

    Harrington, William

    2015-01-01

    This book is intended for developers who have worked with the Raspberry Pi and who want to learn how to make the most of the Raspbian operating system and their Raspberry Pi. Whether you are a beginner to the Raspberry Pi or a seasoned expert, this book will make you familiar with the Raspbian operating system and teach you how to get your Raspberry Pi up and running.

  8. Organizational Learning and the Concept of Learning Schools.

    Science.gov (United States)

    Reed, Heather A.; Kinzie, Mable B.; Ross, Melvin V.

    2001-01-01

    Reviews organizational learning and learning organizations literature, especially the work of Peter Senge. Discusses requirements to transform schools into learning organizations (learning schools). (Contains 22 references.) (PKP)

  9. Development of learning science after learning psychology

    OpenAIRE

    森, 敏昭

    2015-01-01

    Learning psychology began as a branch of psychology in the last couple of decades of the nineteenth century, and its history is therefore as long as that of psychology itself. However, learning science is a relatively young discipline: its development may be traced to 1991, when the first international conference was held and Journal of the Learning Sciences was first published. In the short subsequent period, learning science has grown rapidly as an interdisciplinary approach to learning and...

  10. Human Machine Learning Symbiosis

    Science.gov (United States)

    Walsh, Kenneth R.; Hoque, Md Tamjidul; Williams, Kim H.

    2017-01-01

    Human Machine Learning Symbiosis is a cooperative system where both the human learner and the machine learner learn from each other to create an effective and efficient learning environment adapted to the needs of the human learner. Such a system can be used in online learning modules so that the modules adapt to each learner's learning state both…

  11. Approaches to Machine Learning.

    Science.gov (United States)

    Langley, Pat; Carbonell, Jaime G.

    1984-01-01

    Reviews approaches to machine learning (development of techniques to automate acquisition of new information, skills, and ways of organizing existing information) in symbolic domains. Four categorical tasks addressed in machine learning literature are examined: learning from examples, learning search heuristics, learning by observation, and…

  12. Interorganizational learning systems

    DEFF Research Database (Denmark)

    Hjalager, Anne Mette

    1999-01-01

    The occurrence of organizational and interorganizational learning processes is not only the result of management endeavors. Industry structures and market related issues have substantial spill-over effects. The article reviews literature, and it establishes a learning model in which elements from...... from learning), and S-learning (learning in social networks or clans). The situation related to service industries illustrates the typology....

  13. Evaluation of learning materials

    DEFF Research Database (Denmark)

    Bundsgaard, Jeppe; Hansen, Thomas Illum

    2011-01-01

    This paper presents a holistic framework for evaluating learning materials and designs for learning. A holistic evaluation comprises investigations of the potential learning potential, the actualized learning potential, and the actual learning. Each aspect is explained and exemplified through...... theoretical models and definitions....

  14. Learning Cypher

    CERN Document Server

    Panzarino, Onofrio

    2014-01-01

    An easy-to-follow guide full of tips and examples of real-world applications. In each chapter, a thorough example will show you the concepts in action, followed by a detailed explanation.This book is intended for those who want to learn how to create, query, and maintain a graph database, or who want to migrate to a graph database from SQL. It would be helpful to have some familiarity with Java and/or SQL, but no prior experience is required.

  15. Learning Perl

    CERN Document Server

    Schwartz, Randal; Phoenix, Tom

    2011-01-01

    If you're just getting started with Perl, this is the book you want-whether you're a programmer, system administrator, or web hacker. Nicknamed "the Llama" by two generations of users, this bestseller closely follows the popular introductory Perl course taught by the authors since 1991. This 6th edition covers recent changes to the language up to version 5.14. Perl is suitable for almost any task on almost any platform, from short fixes to complete web applications. Learning Perl teaches you the basics and shows you how to write programs up to 128 lines long-roughly the size of 90% of the Pe

  16. Learning Vaadin

    CERN Document Server

    Frankel, Nicolas

    2011-01-01

    This book begins with a tutorial on Vaadin 7, followed by a process of planning, analyzing, building, and deploying a fully functional RIA while covering troubleshooting details along the way, making it an invaluable resource for answers to all your Vaadin questions. If you are a Java developer with some experience in Java web development and want to enter the world of Rich Internet Applications this technology and book are ideal for you. Learning Vaadin will be perfect as your next step towards building eye-candy dynamic web applications on a Java-based platform.

  17. Targeted Learning

    CERN Document Server

    van der Laan, Mark J

    2011-01-01

    The statistics profession is at a unique point in history. The need for valid statistical tools is greater than ever; data sets are massive, often measuring hundreds of thousands of measurements for a single subject. The field is ready to move towards clear objective benchmarks under which tools can be evaluated. Targeted learning allows (1) the full generalization and utilization of cross-validation as an estimator selection tool so that the subjective choices made by humans are now made by the machine, and (2) targeting the fitting of the probability distribution of the data toward the targe

  18. Learning scikit-learn machine learning in Python

    CERN Document Server

    Garreta, Raúl

    2013-01-01

    The book adopts a tutorial-based approach to introduce the user to Scikit-learn.If you are a programmer who wants to explore machine learning and data-based methods to build intelligent applications and enhance your programming skills, this the book for you. No previous experience with machine-learning algorithms is required.

  19. Digital Learning Projection. Learning performance estimation from multimodal learning experiences

    NARCIS (Netherlands)

    Di Mitri, Daniele

    2017-01-01

    Multiple modalities of the learning process can now be captured on real-time through wearable and contextual sensors. By annotating these multimodal data (the input space) by expert assessments or self-reports (the output space), machine learning models can be trained to predict the learning

  20. Learning, Labour and Union Learning Representatives: Promoting Workplace Learning

    Science.gov (United States)

    Ball, Malcolm

    2011-01-01

    The initiative by the Trades Union Congress (TUC) and affiliated trade unions in the UK to appoint trade union learning representatives (ULRs), to promote learning among their members, is a significant development in adult learning. Understandably, the initiative has attracted the attention of academic researchers, but primarily from the…

  1. Mobile Inquiry Based Learning

    NARCIS (Netherlands)

    Specht, Marcus

    2012-01-01

    Specht, M. (2012, 8 November). Mobile Inquiry Based Learning. Presentation given at the Workshop "Mobile inquiry-based learning" at the Mobile Learning Day 2012 at the Fernuniversität Hagen, Hagen, Germany.

  2. Choosing for learning objects

    NARCIS (Netherlands)

    Schoonenboom, Judith; Emans, Bruno; Meijer, Joost

    2006-01-01

    Choosing for learning objects discusses eight educational ambitions and the possible roles of learning objects in realising these ambitions. The eight educational ambitions are: (1) Creating independent learning pathways, for example for lifelong learners; (2) Making education more flexible; (3)

  3. Learning in Parallel Universes

    OpenAIRE

    Berthold, Michael R.; Wiswedel, Bernd

    2007-01-01

    This abstract summarizes a brief, preliminary formalization of learning in parallel universes. It also attempts to highlight a few neighboring learning paradigms to illustrate how parallel learning fits into the greater picture.

  4. Deep Learning in Open Source Learning Streams

    DEFF Research Database (Denmark)

    Kjærgaard, Thomas

    2016-01-01

    This chapter presents research on deep learning in a digital learning environment and raises the question if digital instructional designs can catalyze deeper learning than traditional classroom teaching. As a theoretical point of departure the notion of ‘situated learning’ is utilized and contra......This chapter presents research on deep learning in a digital learning environment and raises the question if digital instructional designs can catalyze deeper learning than traditional classroom teaching. As a theoretical point of departure the notion of ‘situated learning’ is utilized......, Twitter hashtags etc.). The ‘learning instances’ are described as mediated signs of learning expressed through text in the stream that is further developed by peers and by the teacher. The expressions of ‘learning instances’ are analyzed and categorized according to whether it expresses prestructural......, unistructural, multistructural or relational learning. The research concludes that ‘The Open Source Learning Stream’ can catalyze deep learning and that there are four types of ‘Open Source Learning streams’; individual/ asynchronous, individual/synchronous, shared/asynchronous and shared...

  5. Coordinated activation of distinct Ca2+ sources and metabotropic glutamate receptors encodes Hebbian synaptic plasticity

    Science.gov (United States)

    Tigaret, Cezar M.; Olivo, Valeria; Sadowski, Josef H.L.P.; Ashby, Michael C.; Mellor, Jack R.

    2016-01-01

    At glutamatergic synapses, induction of associative synaptic plasticity requires time-correlated presynaptic and postsynaptic spikes to activate postsynaptic NMDA receptors (NMDARs). The magnitudes of the ensuing Ca2+ transients within dendritic spines are thought to determine the amplitude and direction of synaptic change. In contrast, we show that at mature hippocampal Schaffer collateral synapses the magnitudes of Ca2+ transients during plasticity induction do not match this rule. Indeed, LTP induced by time-correlated pre- and postsynaptic spikes instead requires the sequential activation of NMDARs followed by voltage-sensitive Ca2+ channels within dendritic spines. Furthermore, LTP requires inhibition of SK channels by mGluR1, which removes a negative feedback loop that constitutively regulates NMDARs. Therefore, rather than being controlled simply by the magnitude of the postsynaptic calcium rise, LTP induction requires the coordinated activation of distinct sources of Ca2+ and mGluR1-dependent facilitation of NMDAR function. PMID:26758963

  6. Greedy Deep Dictionary Learning

    OpenAIRE

    Tariyal, Snigdha; Majumdar, Angshul; Singh, Richa; Vatsa, Mayank

    2016-01-01

    In this work we propose a new deep learning tool called deep dictionary learning. Multi-level dictionaries are learnt in a greedy fashion, one layer at a time. This requires solving a simple (shallow) dictionary learning problem, the solution to this is well known. We apply the proposed technique on some benchmark deep learning datasets. We compare our results with other deep learning tools like stacked autoencoder and deep belief network; and state of the art supervised dictionary learning t...

  7. Learning analytics in education

    OpenAIRE

    Štrukelj, Tajda

    2015-01-01

    Learning analytics is a young field in computer supported learning, which could have a great impact on education in the future. It is a set of analytical tools which measure, collect, analyze and report about students' data for the purpose of understanding and optimizing students' learning and environments in which this learning occurs. Today, more and more learning related activities are placed on the web. Teachers are creating virtual learning environments (VLE), in which a great set of...

  8. Toward Learning Teams

    DEFF Research Database (Denmark)

    Hoda, Rashina; Babb, Jeff; Nørbjerg, Jacob

    2013-01-01

    Today's software development challenges require learning teams that can continuously apply new engineering and management practices, new and complex technical skills, cross-functional skills, and experiential lessons learned. The pressure of delivering working software often forces software teams...... to sacrifice learning-focused practices. Effective learning under pressure involves conscious efforts to implement original agile practices such as retrospectives and adapted strategies such as learning spikes. Teams, their management, and customers must all recognize the importance of creating learning teams...

  9. Selective learning enabled by intention to learn in sequence learning.

    Science.gov (United States)

    Miyawaki, Kaori

    2012-01-01

    This study investigated whether a target sequence that people intend to learn is learned selectively when it is interleaved with another (non-target) sequence. Three experiments used a serial reaction time task in which different spatial and color stimuli occurred alternately. Each of the two interleaved sequences had structural regularity. Participants in an intentional learning group were instructed to learn the target (spatial) sequence whereas those in an incidental learning group were not. In Experiments 1 and 2 spatial and color sequences were correlated. Results showed that the intentional group learned the spatial sequence better than the incidental group and learned it independently of the color sequence, whereas the incidental group learned the two sequences as a combined sequence. In Experiment 3 the sequences were uncorrelated. Results showed that the intentional group was no longer superior in learning the spatial sequence. Findings indicate that the intention to learn a target sequence enables selective learning of it only when it is correlated with a non-target sequence.

  10. Learning Design Development for Blended Learning

    DEFF Research Database (Denmark)

    Hansen, Janne Saltoft

    Learning design development for blended learning We started implementing Blackboard at Aarhus University in 2013. At the Health Faculty Blackboard replaced AULA which was a LMS with functionality for file distribution and only a vague focus on learning tools. Most teachers therefore had...... no experiences with blended leaning and technology supported out-of-class activities. At the pedagogical unit at the Health faculty we wanted to follow the Blackboard implementation with pedagogical tools for learning design to evolve the pedagogical use of the system. We needed to make development of blended...... learning courses easier for the teachers and also ensure quality in the courses. This poster describes the process from development of the learning design to implementation of the learning design at the faculty: 1. How to place demands on a learning design-model and how to develop and use such a model. 2...

  11. Learning Networks for Professional Development & Lifelong Learning

    NARCIS (Netherlands)

    Sloep, Peter

    2009-01-01

    Sloep, P. B. (2009). Learning Networks for Professional Development & Lifelong Learning. Presentation at a NeLLL seminar with Etienne Wenger held at the Open Universiteit Nederland. September, 10, 2009, Heerlen, The Netherlands.

  12. Learning Dashboards: Visual Learning Analytics Workshop

    NARCIS (Netherlands)

    Charleer, Sven; Firssova, Olga; Prinsen, Fleur

    2014-01-01

    Learning Analytics focust op het verzamelen van learner traces, sporen van activiteiten die studenten achterlaten. Learning Dashboards, visualisaties van deze learner traces, kunnen studenten en docenten helpen interessante informatie te halen uit deze data. Studenten krijgen een overzicht van hun

  13. Use of blended learning in workplace learning

    DEFF Research Database (Denmark)

    Georgsen, Marianne; Løvstad, Charlotte Vange

    2014-01-01

    -based teaching materials. This paper presents the experiences of this particular project, and goes on to discuss the following points: • The blended learning design – use of IT for teaching, learning and communication • Digital learning materials – principals of design and use • Work place learning and learning......In 2014, a new system has been put in place for the inspection and approval of social welfare institutions in Denmark. In as little as 10 weeks, 330 new employees in five regional centres participated in an introductory course, designed as work place learning with extensive use of e-learning and IT...... from work – the interplay between experiences of the learner and the curriculum of the program •The approach taken to customising the e-learning design to the needs and demands of a particular case....

  14. Judgments of Learning in Collaborative Learning Environments

    NARCIS (Netherlands)

    Helsdingen, Anne

    2010-01-01

    Helsdingen, A. S. (2010, March). Judgments of Learning in Collaborative Learning Environments. Poster presented at the 1st International Air Transport and Operations Symposium (ATOS 2010), Delft, The Netherlands: Delft University of Technology.

  15. When Learning Never Stops: From Learning to Lifelong Learning, over e-Learning

    OpenAIRE

    Alotaibi, Sara

    2010-01-01

    The unprecedented development of Information and Communication Technology (ICT) has transformed conventional learning to the technology driven, flexible and open mechanism of e-Learning. e-Learning itself has evolved from the comparatively static e-Learning 1.0, based on Web 2.0 technologies, to the more vibrant, dynamic and interactive user-centric e-Learning 2.0 with its defining Personal Learning Environments which facilitates lifelong learning. With Web 3.0 on the horizon, e-Learning 3.0,...

  16. Personalized Adaptive Learning

    NARCIS (Netherlands)

    Kravcik, Milos; Specht, Marcus; Naeve, Ambjorn

    2009-01-01

    Kravcik, M., Specht, M., & Naeve, A. (2008). Personalized Adaptive Learning. Presentation of PROLEARN WP1 Personalized Adaptive Learning at the final review meeting. February, 27, 2008, Hannover, Germany.

  17. Blended Learning: An Innovative Approach

    Science.gov (United States)

    Lalima; Dangwal, Kiran Lata

    2017-01-01

    Blended learning is an innovative concept that embraces the advantages of both traditional teaching in the classroom and ICT supported learning including both offline learning and online learning. It has scope for collaborative learning; constructive learning and computer assisted learning (CAI). Blended learning needs rigorous efforts, right…

  18. Group learning

    DEFF Research Database (Denmark)

    Pimentel, Ricardo; Noguira, Eloy Eros da Silva; Elkjær, Bente

    The article presents a study that aims at the apprehension of the group learning in a top management team composed by teachers in a Brazilian Waldorf school whose management is collective. After deciding to extend the school, they had problems recruiting teachers who were already trained based...... on the Steiner´s ideas, which created practical problems for conducting management activities. The research seeks to understand how that group of teachers collectively manage the school, facing the lack of resources, a significant heterogeneity in the relationships, and the conflicts and contradictions...... with which they coexist. To achieve this, the research adopted phenomenology as a method and ethnography as strategy, using participant observation, in-depth interviews, and interviews-to-the-double. The results show that the collective management practice is a crossroad of other practices...

  19. Stimulating Deep Learning Using Active Learning Techniques

    Science.gov (United States)

    Yew, Tee Meng; Dawood, Fauziah K. P.; a/p S. Narayansany, Kannaki; a/p Palaniappa Manickam, M. Kamala; Jen, Leong Siok; Hoay, Kuan Chin

    2016-01-01

    When students and teachers behave in ways that reinforce learning as a spectator sport, the result can often be a classroom and overall learning environment that is mostly limited to transmission of information and rote learning rather than deep approaches towards meaningful construction and application of knowledge. A group of college instructors…

  20. When Learning Analytics Meets E-Learning

    Science.gov (United States)

    Czerkawski, Betul C.

    2015-01-01

    While student data systems are nothing new and most educators have been dealing with student data for many years, learning analytics has emerged as a new concept to capture educational big data. Learning analytics is about better understanding of the learning and teaching process and interpreting student data to improve their success and learning…

  1. Deepening Learning through Learning-by-Inventing

    Science.gov (United States)

    Apiola, Mikko; Tedre, Matti

    2013-01-01

    It has been shown that deep approaches to learning, intrinsic motivation, and self-regulated learning have strong positive effects on learning. How those pedagogical theories can be integrated in computing curricula is, however, still lacking empirically grounded analyses. In a more general level, it has been widely acknowledged that in…

  2. FORUM: Affective Learning. Reclaiming Affective Learning

    Science.gov (United States)

    Housley Gaffney, Amy L.; Dannels, Deanna P.

    2015-01-01

    The mission of "Communication Education" is to publish the best research on communication and learning. Researchers study the communication-learning interface in many ways, but a common approach is to explore how instructor and student communication can lead to better learning outcomes. Although scholars have long classified learning…

  3. Assessing the "Learning" in Learning Communities

    Science.gov (United States)

    Gansemer-Topf, Ann M.; Tietjen, Kari

    2015-01-01

    Although assessment has been an integral part of the development and expansion of learning communities, much of the assessment was focused on investigating student satisfaction, retention, and graduation. This chapter provides a case study illustrating one learning community's efforts to create assessments focused on student learning.

  4. From learning objects to learning activities

    DEFF Research Database (Denmark)

    Dalsgaard, Christian

    2005-01-01

    This paper discusses and questions the current metadata standards for learning objects from a pedagogical point of view. From a social constructivist approach, the paper discusses how learning objects can support problem based, self-governed learning activities. In order to support this approach...... based, self-governed activities. Further, a new way of thinking pedagogy into learning objects is introduced. It is argued that a lack of pedagogical thinking in learning objects is not solved through pedagogical metadata. Instead, the paper suggests the concept of references as an alternative...... to pedagogical metadata....

  5. Online transfer learning with extreme learning machine

    Science.gov (United States)

    Yin, Haibo; Yang, Yun-an

    2017-05-01

    In this paper, we propose a new transfer learning algorithm for online training. The proposed algorithm, which is called Online Transfer Extreme Learning Machine (OTELM), is based on Online Sequential Extreme Learning Machine (OSELM) while it introduces Semi-Supervised Extreme Learning Machine (SSELM) to transfer knowledge from the source to the target domain. With the manifold regularization, SSELM picks out instances from the source domain that are less relevant to those in the target domain to initialize the online training, so as to improve the classification performance. Experimental results demonstrate that the proposed OTELM can effectively use instances in the source domain to enhance the learning performance.

  6. Professional learning versus interprofessional learning

    DEFF Research Database (Denmark)

    Nielsen, Cathrine Sand

    2014-01-01

    Tværsproject and collaboration interprofessionally and across sectors impact on the development of the professional identity of the student? Methodology, Methods, Research Instruments or Sources Used: This Industrial PhD Project is conducted as a research-based evaluation of an educational experiment. The methodological...... approach is described as a mix of evaluation research, ethnographic methods and action research similar to research by Dahler-Larsen, Borgnakke, Hammersley and Greenwood (10-15). The project aims to explore InterTværs from concept to practice. The field and institutional levels will thereby be identified...... of professional learning • Classroom research related to inter-professional meetings • Participant logbooks, synopsis made on the case study as well as videos of presentations. Theoretical framework: Via InterTværs the project moves from vision into practical reality in the clinical training setting. The project...

  7. Practice and Group Learning

    Science.gov (United States)

    Hager, Paul

    2014-01-01

    Although learning has always been a central topic for philosophy of education, little attention has been paid to the notion of group learning. This article outlines and discusses some plausible examples of group learning. Drawing on these examples, various principles and issues that surround the notion of group learning are identified and…

  8. Teaching for Deep Learning

    Science.gov (United States)

    Smith, Tracy Wilson; Colby, Susan A.

    2007-01-01

    The authors have been engaged in research focused on students' depth of learning as well as teachers' efforts to foster deep learning. Findings from a study examining the teaching practices and student learning outcomes of sixty-four teachers in seventeen different states (Smith et al. 2005) indicated that most of the learning in these classrooms…

  9. Active Learning Methods

    Science.gov (United States)

    Zayapragassarazan, Z.; Kumar, Santosh

    2012-01-01

    Present generation students are primarily active learners with varied learning experiences and lecture courses may not suit all their learning needs. Effective learning involves providing students with a sense of progress and control over their own learning. This requires creating a situation where learners have a chance to try out or test their…

  10. Cultural Learning Redux

    Science.gov (United States)

    Tomasello, Michael

    2016-01-01

    M. Tomasello, A. Kruger, and H. Ratner (1993) proposed a theory of cultural learning comprising imitative learning, instructed learning, and collaborative learning. Empirical and theoretical advances in the past 20 years suggest modifications to the theory; for example, children do not just imitate but overimitate in order to identify and…

  11. Records for learning

    DEFF Research Database (Denmark)

    Binder, Thomas

    2005-01-01

    The article present and discuss findings from a participatory development of new learning practices among intensive care nurses, with an emphasize on the role of place making in informal learning activities.......The article present and discuss findings from a participatory development of new learning practices among intensive care nurses, with an emphasize on the role of place making in informal learning activities....

  12. Algorithms for Reinforcement Learning

    CERN Document Server

    Szepesvari, Csaba

    2010-01-01

    Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms'

  13. Rethinking e-learning

    DEFF Research Database (Denmark)

    Bang, Jørgen; Dalsgaard, Christian

    2006-01-01

    “Technology alone does not deliver educational success. It only becomes valuable in education if learners and teachers can do something useful with it” (E-Learning: The Partnership Challenge, 2001, p. 24). This quotation could be used as a bon mot for this chapter. Our main goal is to rethink e-learning...... by shifting the focus of attention from learning resources (learning objects) to learning activities, which also implies a refocusing of the pedagogical discussion of the learning process.Firstly, we try to identify why e-learning has not been able to deliver the educational results as expected five years ago...

  14. Structure learning in action

    Science.gov (United States)

    Braun, Daniel A.; Mehring, Carsten; Wolpert, Daniel M.

    2010-01-01

    Learning to learn’ phenomena have been widely investigated in cognition, perception and more recently also in action. During concept learning tasks, for example, it has been suggested that characteristic features are abstracted from a set of examples with the consequence that learning of similar tasks is facilitated—a process termed ‘learning to learn’. From a computational point of view such an extraction of invariants can be regarded as learning of an underlying structure. Here we review the evidence for structure learning as a ‘learning to learn’ mechanism, especially in sensorimotor control where the motor system has to adapt to variable environments. We review studies demonstrating that common features of variable environments are extracted during sensorimotor learning and exploited for efficient adaptation in novel tasks. We conclude that structure learning plays a fundamental role in skill learning and may underlie the unsurpassed flexibility and adaptability of the motor system. PMID:19720086

  15. Lessons Learned

    Science.gov (United States)

    Davis, Michaela

    2015-01-01

    The public health nurses’ scope of practice explicitly includes child protection within their role, which places them in a prime position to identify child protection concerns. This role compliments that of other professions and voluntary agenices who work with children. Public health nurses are in a privileged position as they form a relationship with the child’s parent(s)/guardian(s) and are able to see the child in its own environment, which many professionals cannot. Child protection in Ireland, while influenced by other countries, has progressed through a distinct pathway that streamlined protocols and procedures. However, despite the above serious failures have occurred in the Irish system, and inquiries over the past 20 years persistently present similar contributing factors, namely, the lack of standardized and comprehensive service responses. Moreover, poor practice is compounded by the lack of recognition of the various interactional processes taking place within and between the different agencies of child protection, leading to psychological barriers in communication. This article will explore the lessons learned for public health nurses practice in safeguarding children in the Republic of Ireland. PMID:27335944

  16. Lessons Learned

    Directory of Open Access Journals (Sweden)

    Amanda Phelan BNS, MSc, PhD

    2015-03-01

    Full Text Available The public health nurses’ scope of practice explicitly includes child protection within their role, which places them in a prime position to identify child protection concerns. This role compliments that of other professions and voluntary agenices who work with children. Public health nurses are in a privileged position as they form a relationship with the child’s parent(s/guardian(s and are able to see the child in its own environment, which many professionals cannot. Child protection in Ireland, while influenced by other countries, has progressed through a distinct pathway that streamlined protocols and procedures. However, despite the above serious failures have occurred in the Irish system, and inquiries over the past 20 years persistently present similar contributing factors, namely, the lack of standardized and comprehensive service responses. Moreover, poor practice is compounded by the lack of recognition of the various interactional processes taking place within and between the different agencies of child protection, leading to psychological barriers in communication. This article will explore the lessons learned for public health nurses practice in safeguarding children in the Republic of Ireland.

  17. Learning after acquired brain injury. Learning the hard way

    NARCIS (Netherlands)

    Boosman, H.

    2015-01-01

    Background: When the brain has suffered damage, the learning process can be considerably disturbed. Brain damage can influence what is learned, but also how learning takes place. What patients can learn can be viewed in terms of ‘learning ability’ and how patients learn in terms of ‘learning style’.

  18. Online Learning with Ensembles

    OpenAIRE

    Urbanczik, R.

    1999-01-01

    Supervised online learning with an ensemble of students randomized by the choice of initial conditions is analyzed. For the case of the perceptron learning rule, asymptotically the same improvement in the generalization error of the ensemble compared to the performance of a single student is found as in Gibbs learning. For more optimized learning rules, however, using an ensemble yields no improvement. This is explained by showing that for any learning rule $f$ a transform $\\tilde{f}$ exists,...

  19. Does Observation Influence Learning?

    OpenAIRE

    Olivier Armantier

    2001-01-01

    A common value auction experiment is run to compare the relative influence of observation and experience on learning. It is shown that the ex-post observation of opponents' actions and payoffs homogenizes behavior and accelerates learning toward the Nash equilibrium. Besides, experiential and observational learning are both relevant and of comparable magnitude. A general reinforcement model for continuous strategies, encompassing choice reinforcement learning, direction learning and payoff de...

  20. Budgeted Interactive Learning

    Science.gov (United States)

    2017-06-15

    protocols that combine the benefits of online and batch learning , (2) protocols that improve interactive learning with other sources of information, and...algorithms for interactive learning with batch-like feedback (for 1) and algorithms for online digestion of representation (for 1 and 3). The team has...also addressed real-world needs for considering concept drift during online learning (for 2) and utilizing costs during deep learning , multi-label

  1. Learning Theories in Instructional Multimedia for English Learning

    OpenAIRE

    Farani, Rizki

    2012-01-01

    Learning theory is the concept of human learning. This concept is one of the important components in instructional for learning, especially English learning. English subject becomes one of important subjects for students but learning English needs specific strategy since it is not our vernacular. Considering human learning process in English learning is expected to increase students' motivation to understand English better. Nowadays, the application of learning theories in English learning ha...

  2. NMDA Receptors Mediate Stimulus-Timing-Dependent Plasticity and Neural Synchrony in the Dorsal Cochlear Nucleus.

    Science.gov (United States)

    Stefanescu, Roxana A; Shore, Susan E

    2015-01-01

    Auditory information relayed by auditory nerve fibers and somatosensory information relayed by granule cell parallel fibers converge on the fusiform cells (FCs) of the dorsal cochlear nucleus, the first brain station of the auditory pathway. In vitro, parallel fiber synapses on FCs exhibit spike-timing-dependent plasticity with Hebbian learning rules, partially mediated by the NMDA receptor (NMDAr). Well-timed bimodal auditory-somatosensory stimulation, in vivo equivalent of spike-timing-dependent plasticity, can induce stimulus-timing-dependent plasticity (StTDP) of the FCs spontaneous and tone-evoked firing rates. In healthy guinea pigs, the resulting distribution of StTDP learning rules across a FC neural population is dominated by a Hebbian profile while anti-Hebbian, suppressive and enhancing LRs are less frequent. In this study, we investigate in vivo, the NMDAr contribution to FC baseline activity and long term plasticity. We find that blocking the NMDAr decreases the synchronization of FC- spontaneous activity and mediates differential modulation of FC rate-level functions such that low, and high threshold units are more likely to increase, and decrease, respectively, their maximum amplitudes. Three significant alterations in mean learning-rule profiles were identified: transitions from an initial Hebbian profile towards (1) an anti-Hebbian; (2) a suppressive profile; and (3) transitions from an anti-Hebbian to a Hebbian profile. FC units preserving their learning rules showed instead, NMDAr-dependent plasticity to unimodal acoustic stimulation, with persistent depression of tone-evoked responses changing to persistent enhancement following the NMDAr antagonist. These results reveal a crucial role of the NMDAr in mediating FC baseline activity and long-term plasticity which have important implications for signal processing and auditory pathologies related to maladaptive plasticity of dorsal cochlear nucleus circuitry.

  3. Personalized Learning Network Teaching Model

    Science.gov (United States)

    Feng, Zhou

    Adaptive learning system on the salient features, expounded personalized learning is adaptive learning system adaptive to learners key to learning. From the perspective of design theory, put forward an adaptive learning system to learn design thinking individual model, and using data mining techniques, the initial establishment of personalized adaptive systems model of learning.

  4. Learning Approach and Learning: Exploring a New Technological Learning System

    Science.gov (United States)

    Aflalo, Ester; Gabay, Eyal

    2013-01-01

    This study furthers the understanding of the connections between learning approaches and learning. The research population embraced 44 males from the Jewish ultraorthodox community, who abide by distinct methods of study. One group follows the very didactic, linear and structured approach of a methodical and gradual order, while the second group…

  5. Designing Learning Resources in Synchronous Learning Environments

    DEFF Research Database (Denmark)

    Christiansen, Rene B

    2015-01-01

    Computer-mediated Communication (CMC) and synchronous learning environments offer new solutions for teachers and students that transcend the singular one-way transmission of content knowledge from teacher to student. CMC makes it possible not only to teach computer mediated but also to design...... and create new learning resources targeted to a specific group of learners. This paper addresses the possibilities of designing learning resources within synchronous learning environments. The empirical basis is a cross-country study involving students and teachers in primary schools in three Nordic...... Countries (Denmark, Sweden and Norway). On the basis of these empirical studies a set of design examples is drawn with the purpose of showing how the design fulfills the dual purpose of functioning as a remote, synchronous learning environment and - using the learning materials used and recordings...

  6. Robot Learning Using Learning Classifier Systems Approach

    OpenAIRE

    Jabin, Suraiya

    2010-01-01

    In this chapter, I have presented Learning Classifier Systems, which add to the classical Reinforcement Learning framework the possibility of representing the state as a vector of attributes and finding a compact expression of the representation so induced. Their formalism conveys a nice interaction between learning and evolution, which makes them a class of particularly rich systems, at the intersection of several research domains. As a result, they profit from the accumulated extensions of ...

  7. Who Needs Learning Theory Anyway?

    Science.gov (United States)

    Zemke, Ron

    2002-01-01

    Looks at a variety of learning theories: andragogy, behaviorism, cognitivism, conditions of learning, Gestalt, and social learning. Addresses the difficulty of selecting an appropriate theory for training. (JOW)

  8. Holistic evaluations of learning materials

    DEFF Research Database (Denmark)

    Bundsgaard, Jeppe; Hansen, Thomas Illum

    2011-01-01

    , and the competences supposedly supported when working with the material - the actualized learning potential, i.e. the potential for learning when the design for learning is enacted by integrating the learning material in a situation in a given context, and - the actual learning, i.e. how the participants actually...... develop their competences through working with a learning material or enacting a design for learning.......The aim of this paper is to present a holistic framework for evaluating learning materials and designs for learning. A holistic evaluation of learning material comprises investigations of - the potential learning potential, i.e. the affordances and challenges of the learning material...

  9. Refactoring of Learning Objects for Mobile Learning

    Science.gov (United States)

    Damaševičius, Robertas

    We analyze the problem of refactoring of learning object (LO) for m-Learning. We apply methods adopted from software engineering domain for redesigning the structure and user interface of a LO and aim both at increasing usability and accessibility of the learning material. We evaluate usability of a LO from the user interface point of view, following the user interface development principles that are common both for human-computer interaction (HCI) and e-Learning domains. We propose the LO refactoring framework based on user interface usability principles. In a case study, we demonstrate the refactoring of an array-sorting LO for a mobile device.

  10. Mobile learning in medicine

    Science.gov (United States)

    Serkan Güllüoüǧlu, Sabri

    2013-03-01

    This paper outlines the main infrastructure for implicating mobile learning in medicine and present a sample mobile learning application for medical learning within the framework of mobile learning systems. Mobile technology is developing nowadays. In this case it will be useful to develop different learning environments using these innovations in internet based distance education. M-learning makes the most of being on location, providing immediate access, being connected, and acknowledges learning that occurs beyond formal learning settings, in places such as the workplace, home, and outdoors. Central to m-learning is the principle that it is the learner who is mobile rather than the device used to deliver m learning. The integration of mobile technologies into training has made learning more accessible and portable. Mobile technologies make it possible for a learner to have access to a computer and subsequently learning material and activities; at any time and in any place. Mobile devices can include: mobile phone, personal digital assistants (PDAs), personal digital media players (eg iPods, MP3 players), portable digital media players, portable digital multimedia players. Mobile learning (m-learning) is particularly important in medical education, and the major users of mobile devices are in the field of medicine. The contexts and environment in which learning occurs necessitates m-learning. Medical students are placed in hospital/clinical settings very early in training and require access to course information and to record and reflect on their experiences while on the move. As a result of this paper, this paper strives to compare and contrast mobile learning with normal learning in medicine from various perspectives and give insights and advises into the essential characteristics of both for sustaining medical education.

  11. Transnational Learning Processes

    DEFF Research Database (Denmark)

    Nedergaard, Peter

    This paper analyses and compares the transnational learning processes in the employment field in the European Union and among the Nordic countries. Based theoretically on a social constructivist model of learning and methodologically on a questionnaire distributed to the relevant participants......, a number of hypotheses concerning transnational learning processes are tested. The paper closes with a number of suggestions regarding an optimal institutional setting for facilitating transnational learning processes.Key words: Transnational learning, Open Method of Coordination, Learning, Employment......, European Employment Strategy, European Union, Nordic countries....

  12. Learning to Innovate

    DEFF Research Database (Denmark)

    Mei, Maggie

    the relationship between organizational learning and innovation creation in an organizational context. Taking a nuanced view of organizational learning, the dissertation investigates how three different organizational learning processes could affect innovation creation at the firm level and project level...... to the understanding of managing organizational learning for innovation creation at firms. The three studies in this dissertation show how three prominent organizational learning processes impact on firms’ innovation performance. Furthermore, the studies in this dissertation emphasize that there are limitation...... and boundary conditions for different organizational learning processes....

  13. Pseudo-Gaussian and rank-based optimal tests for random individual effects in large n small T panels

    NARCIS (Netherlands)

    Bennala, N.; Hallin, M.; Paindaveine, D.

    2012-01-01

    We consider the problem of detecting unobserved heterogeneity, that is, the problem of testing the absence of random individual effects in an n × T panel. We establish a local asymptotic normality property–with respect to intercept, regression coefficient, the scale parameter σ of the error, and the

  14. e-Learning for Lifelong Learning in Denmark

    DEFF Research Database (Denmark)

    Buhl, Mie; Andreasen, Lars Birch

    2010-01-01

    The chapter on 'e-Learning for Lifelong Learning in Denmark' is part of an international White Paper, focusing on educational systems, describing status and characteristics and highlighting specific cases of e-learning and of lifelong learning....

  15. Can Blended Learning Aid Foreign Language Learning?

    Science.gov (United States)

    Genís Pedra, Marta; Martín de Lama, Mª Teresa

    2013-01-01

    There has always been a debate around the issue of what it is that improves learning: the instruction itself or the media used for it (Clark 1983; Kozma 1994). It has also been said (Kulik and Kulik 1991; Andrewartha & Wilmot 2001) that computer mediated learning, as opposed to traditional instruction, positively influences the students'…

  16. Constructivist learning theories and complex learning environments

    NARCIS (Netherlands)

    R-J. Simons; Dr. S. Bolhuis

    2004-01-01

    Learning theories broadly characterised as constructivist, agree on the importance to learning of the environment, but differ on what exactly it is that constitutes this importance. Accordingly, they also differ on the educational consequences to be drawn from the theoretical perspective. Cognitive

  17. LEARNING HOW TO LEARN A LANGUAGE

    CERN Multimedia

    Language Training; Tel. 73127; Andrée Fontbonne; Tel. 72844

    2001-01-01

    This bilingual seminar is for anyone who would like to develop learning strategies and skills for learning a foreign language. Languages: French and English. Length: 3 days, 7 hours per day. Dates: 5, 6, 7 November 2001. Price: 460 CHF per person (for a group of 8 people). If you are interested, please enrol through our Web pages: http://cern.ch/Training

  18. LEARNING HOW TO LEARN A LANGUAGE

    CERN Multimedia

    Language Training; Tel. 73127; Andrée Fontbonne; Tel. 72844

    2001-01-01

    This bilingual seminar is for anyone who would like to develop learning strategies and skills for learning a foreign language. Languages: French and English. Length: 3 days, 7 hours per day. Dates: 4, 5, 6 March 2002. Price: 460 CHF per person (for a group of 8 people). If you are interested, please enrol through our Web pages: http://cern.ch/Training

  19. Stealth Learning: Unexpected Learning Opportunities through Games

    Science.gov (United States)

    Sharp, Laura A.

    2012-01-01

    Educators across the country struggle to create engaging, motivating learning environments for their Net Gen students. These learners expect instant gratification that traditional lectures do not provide. This leaves educators searching for innovative ways to engage students in order to encourage learning. One solution is for educators to use…

  20. Messy Collaboration: Learning from a Learning Study

    Science.gov (United States)

    Adamson, Bob; Walker, Elizabeth

    2011-01-01

    Messy collaboration refers to complexity, unpredictability and management dilemmas when educators work together. Such messiness was evident in a Hong Kong English Learning Study, a structured cyclical process in which teachers and researcher-participants from a teacher education institution work collaboratively on effective student learning. This…

  1. Learning Novel Musical Pitch via Distributional Learning

    Science.gov (United States)

    Ong, Jia Hoong; Burnham, Denis; Stevens, Catherine J.

    2017-01-01

    Because different musical scales use different sets of intervals and, hence, different musical pitches, how do music listeners learn those that are in their native musical system? One possibility is that musical pitches are acquired in the same way as phonemes, that is, via distributional learning, in which learners infer knowledge from the…

  2. Generative Learning: Adults Learning within Ambiguity

    Science.gov (United States)

    Nicolaides, Aliki

    2015-01-01

    This study explored the extent to which ambiguity can serve as a catalyst for adult learning. The purpose of this study is to understand learning that is generated when encountering ambiguity agitated by the complexity of liquid modernity. "Ambiguity," in this study, describes an encounter with an appearance of reality that is at first…

  3. Transformative Learning: Personal Empowerment in Learning Mathematics

    Science.gov (United States)

    Hassi, Marja-Liisa; Laursen, Sandra L.

    2015-01-01

    This article introduces the concept of personal empowerment as a form of transformative learning. It focuses on commonly ignored but enhancing elements of mathematics learning and argues that crucial personal resources can be essentially promoted by high engagement in mathematical problem solving, inquiry, and collaboration. This personal…

  4. Learn about Lead

    Science.gov (United States)

    ... Protection Agency Search Search Lead Contact Us Share Learn about Lead General Lead Information Read more about ... water, soil, consumer products, food, and occupational settings. Learn more about sources of lead exposure: At home ...

  5. Learn About Silicosis

    Science.gov (United States)

    ... Lung Health and Diseases > Lung Disease Lookup > Silicosis Learn About Silicosis Silicosis is a lung disease caused ... 100 deaths each year in the United States. Learn more about living with silicosis . Next » This content ...

  6. Learn About Neuromuscular Disease

    Science.gov (United States)

    ... for MDA Blog Donate Search MDA.org Close Learn About Neuromuscular Disease Muscular dystrophy, ALS and related ... power of a multiple-disease approach, MDA leverages learnings from one disease to accelerate progress in others ...

  7. Learn About Tuberculosis

    Science.gov (United States)

    ... Health and Diseases > Lung Disease Lookup > Tuberculosis (TB) Learn About Tuberculosis Tuberculosis (TB) is an airborne bacterial ... against the resistant TB germs in the body. Learn more about the types of drug resistant TB . ...

  8. Learn About Sarcoidosis

    Science.gov (United States)

    ... Lung Health and Diseases > Lung Disease Lookup > Sarcoidosis Learn About Sarcoidosis Sarcoidosis is a disease of unknown ... file."); } }); } } --> Blank Section Header Lung Disease Lookup Sarcoidosis Learn About Sarcoidosis Sarcoidosis Symptoms, Causes and Risk Factors ...

  9. Learn About Cronobacter Infection

    Science.gov (United States)

    ... this? Submit What's this? Submit Button Past Emails Learn About Cronobacter Infection Language: English (US) Español (Spanish) ... but infections in young infants can be deadly. Learn what steps you can take to protect your ...

  10. Learning Media Programme

    NARCIS (Netherlands)

    Westera, Wim

    2009-01-01

    Westera, W. (2009). Learning Media Programme. Introductory presentation of Learning Media Programme for visitors of Kavala University of Technology, Kavala, Greece and National Institute of Multimedia Education, Chiba, Japan. March, 2, 2009, Heerlen, The Netherlands.

  11. (ICT) and Adult Learning

    African Journals Online (AJOL)

    characteristics on ICT learning of graduate students; to determine the extent to which graduate students' prior experience in operating computers affected their ICT learning; and to investigate the effect of graduate students' attitudes towards use of ...

  12. Teaching learning strategies

    OpenAIRE

    Chugunova, N.

    2012-01-01

    The paper describes instructional approaches focused on teaching. The paper discusses four learning strategies: rehearsal, elaboration, organization, and monitoring. Because it makes learning a collective experience, the reciprocal teaching method encourages students to become a community of learners

  13. Social Structures for Learning

    NARCIS (Netherlands)

    I.M. Bogenrieder (Irma); B. Nooteboom (Bart)

    2001-01-01

    textabstractThis article investigates what learning groups there are in organizations, other than the familiar 'communities of practice'. It first develops an interdisciplinary theoretical framework for identifying, categorizing and understanding learning groups. For this, it employs a

  14. MOOC Blended learning ontwikkelen

    NARCIS (Netherlands)

    Verjans, Steven

    2015-01-01

    Presentatie over het ontwerpen van leeractiviteiten (learning design) tijdens de zesde live sessie van de MOOC Blended learning ontwikkelen. Met gebruikmaking van presentatiematerialen van Diana Laurillard, Grainne Conole, Helen Beetham, Jos Fransen, Pieter Swager, Helen Keegan, Corinne Weisgerber.

  15. eLearning

    NARCIS (Netherlands)

    Hartog, R.J.M.; Schaaf, van der H.

    2003-01-01

    Uitleg van de betekenis en mogelijkheden van Learning Management Systemen (LMS), ook wel elektronische leeromgevingen (ELO's) of Virtual Learning Environments (VLE's) genoemd, waarbij wordt verwezen naar de situatie aan Wageningen UR

  16. Distributed Active Learning

    National Research Council Canada - National Science Library

    Shen, Pengcheng; Li, Chunguang; Zhang, Zhaoyang

    2016-01-01

    Active learning aims at obtaining high-accuracy models with as a few labeled data as possible, by iteratively and elaborately selecting most valuable data to query labels during the learning process...

  17. Learning about Carbohydrates

    Science.gov (United States)

    ... Videos for Educators Search English Español Learning About Carbohydrates KidsHealth / For Kids / Learning About Carbohydrates Print en ... source of energy for the body. What Are Carbohydrates? There are two major types of carbohydrates (or ...

  18. Learning about Proteins

    Science.gov (United States)

    ... Videos for Educators Search English Español Learning About Proteins KidsHealth / For Kids / Learning About Proteins What's in ... from the foods you eat. Different Kinds of Protein Protein from animal sources, such as meat and ...

  19. Pervasive Learning Environments

    DEFF Research Database (Denmark)

    Helms, Niels Henrik; Hundebøl, Jesper

    2006-01-01

    The potentials of pervasive communication in learning within industry and education are right know being explored through different R&D projects. This paper outlines the background for and the possible learning potentials in what we describe as pervasive learning environments (PLE). PLE's differ...... from virtual learning environments (VLE) primarily because in PLE's the learning content is very much related to the actual context in which the learner finds himself. Two local (Denmark) cases illustrate various aspects of pervasive learning. One is the eBag, a pervasive digital portfolio used...... in schools. The other is moreover related to work based learning in that it foresees a community of practitioners accessing, sharing and adding to knowledge and learning objects held within a pervasive business intelligence system. Limitations and needed developments of these and other systems are discussed...

  20. Pervasive Learning Environments

    DEFF Research Database (Denmark)

    Hundebøl, Jesper; Helms, Niels Henrik

    2006-01-01

    Abstract: The potentials of pervasive communication in learning within industry and education are right know being explored through different R&D projects. This paper outlines the background for and the possible learning potentials in what we describe as pervasive learning environments (PLE). PLE......'s differ from virtual learning environments (VLE) primarily because in PLE's the learning content is very much related to the actual context in which the learner finds himself. Two local (Denmark) cases illustrate various aspects of pervasive learning. One is the eBag, a pervasive digital portfolio used...... in schools. The other is moreover related to work based learning in that it foresees a community of practitioners accessing, sharing and adding to knowledge and learning objects held within a pervasive business intelligence system. Limitations and needed developments of these and other systems are discussed...

  1. Pervasive Learning Environments

    DEFF Research Database (Denmark)

    Hundebøl, Jesper; Helms, Niels Henrik

    2006-01-01

    The potentials of pervasive communication in learning within industry and education are right now being explored through different R&D projects. This paper outlines the background for and the possible learning potentials in what we describe as pervasive learning environments (PLE). PLE?s differ...... from virtual learning environments (VLE) primarily because in PLE?s the learning content is very much related to the actual context in which the learner finds himself. Two local (Denmark) cases illustrate various aspects of pervasive learning. One is the eBag, a pervasive digital portfolio used...... in schools. The other is moreover related to work-based learning in that it foresees a community of practitioners accessing, sharing and adding to knowledge and learning objects held within a pervasive business intelligence system. Limitations and needed developments of these and other systems are discussed...

  2. Effects of Cooperative E-Learning on Learning Outcomes

    Science.gov (United States)

    Yeh, Shang-Pao; Fu, Hsin-Wei

    2014-01-01

    This study aims to discuss the effects of E-Learning and cooperative learning on learning outcomes. E-Learning covers the dimensions of Interpersonal communication, abundant resources, Dynamic instruction, and Learning community; and, cooperative learning contains three dimensions of Cooperative motive, Social interaction, and Cognition…

  3. New learning : three ways to learn in a new balance

    NARCIS (Netherlands)

    Simons, P.R.J.

    2000-01-01

    Because people are learning all the time, we need criteria that can help us distinguish between better and worse kinds of learning. Organizations and societies as well as the psychology of learning ask for new learning outcomes, new learning processes and new forms of instruction. New learning

  4. Learning through reactions

    DEFF Research Database (Denmark)

    Hasse, Cathrine

    2007-01-01

    Universities can from the student?s point of view be seen as places of learning an explicit curriculum of a particular discipline. From a fieldwork among physicist students at the Niels Bohr Institute in Denmark, I argue that the learning of cultural code-curricula in higher educational instituti...... argue that this code-curriculum is learned through what I shall term indefinite learning processes, which are mainly pre-discursive to the newcomer...

  5. Pervasive e-learning

    DEFF Research Database (Denmark)

    Hundebøl, Jesper; Helms, Niels Henrik

    2009-01-01

    This article falls within planning, production and delivery of innovative learning resources. The establishment of pervasive learning environments is based on the successful combination and re-configuration of inter-connected sets of learning objects, databases and data-streams. The text presents...... a definition of Pervasive Learning Environments and discusses the pedagogical potentials and challenges in developing such environments with emphasis on context, new didactics, content and affordances....

  6. LEADING THE LEARNING ORGANIZATION

    OpenAIRE

    Sapna Rijal

    2009-01-01

    Researchers have identified leadership as being one of the most important factors that influence the development of learning organization. They suggest that creating a collective vision of the future, empowering and developing employees so that they are better able to handle environmental challenges, modeling learning behavior and creating a learning environment, are crucial skills for leaders of learning organization. These roles are suitable to a transformational leader. Despite the potenti...

  7. Reinforcement Learning: A Survey

    OpenAIRE

    Kaelbling, L. P.; Littman, M. L.; Moore, A. W.

    1996-01-01

    This paper surveys the field of reinforcement learning from a computer-science perspective. It is written to be accessible to researchers familiar with machine learning. Both the historical basis of the field and a broad selection of current work are summarized. Reinforcement learning is the problem faced by an agent that learns behavior through trial-and-error interactions with a dynamic environment. The work described here has a resemblance to work in psychology, but differs considerably in...

  8. Organizational learning viewed from a social learning perspective

    DEFF Research Database (Denmark)

    Elkjær, Bente; Brandi, Ulrik

    2011-01-01

    This chapter reviews the literature on organizational learning through the lens of a social learning perspective. We start with an individual learning perspective, before moving on to a social learning perspective with a particular focus upon pragmatism. The literature review covers the following......’ capacities to both adapt and change. Further, a pragmatist social learning perspective also provides tools for the analysis of learning as process by the notions of learning initiated by tensions and ruptures.......This chapter reviews the literature on organizational learning through the lens of a social learning perspective. We start with an individual learning perspective, before moving on to a social learning perspective with a particular focus upon pragmatism. The literature review covers the following...... four issues: the content of learning, the process of learning, the relation between individual and organization, and the concept of organization. An important separator between individual and social learning perspectives is the different emphasis on learning as acquisition of skills and knowledge...

  9. Action Learning in China

    Science.gov (United States)

    Marquardt, Michael J.

    2015-01-01

    Action learning was introduced into China less than 20 years ago, but has rapidly become a valuable tool for organizations seeking to solve problems, develop their leaders, and become learning organizations. This article provides an historical overview of action learning in China, its cultural underpinnings, and five case studies. It concludes…

  10. Reading to Learn

    Science.gov (United States)

    Herman, Phillip; Wardrip, Peter

    2012-01-01

    Science teachers expect high school students to know how to read, understand, and learn from texts at the core of the curriculum. But though students learn to read in grade school, many do not know how to "read to learn" science. And science teachers are often too busy teaching science to actively help students increase their science reading…

  11. My Teaching Learning Philosophy

    Science.gov (United States)

    Punjani, Neelam Saleem

    2014-01-01

    The heart of teaching learning philosophy is the concept of nurturing students and teaching them in a way that creates passion and enthusiasm in them for a lifelong learning. According to Duke (1990) education is a practice of artful action where teaching learning process is considered as design and knowledge is considered as colours. Teaching…

  12. KARATE WITH CONSTRUCTIVE LEARNING

    Directory of Open Access Journals (Sweden)

    Srikrishna Karanam

    2012-02-01

    Full Text Available Any conventional learning process involves the traditional hierarchy of garnering of information and then recall gathered information. Constructive learning is an important research area having wide impact on teaching methods in education, learning theories, and plays a major role in many education reform movements. It is observed that constructive learning advocates the interconnection between emotions and learning. Human teachers identify the emotions of students with varying degrees of accuracy and can improve the learning rate of the students by motivating them. In learning with computers, computers also should be given the capability to recognize emotions so as to optimize the learning process. Image Processing is a very popular tool used in the process of establishing the theory of Constructive Learning. In this paper we use the Optical Flow computation in image sequences to analyze the accuracy of the moves of a karate player. We have used the Lucas-Kanade method for computing the optical flow in image sequences. A database consisting of optical flow images by a group of persons learning karate is formed and the learning rates are analyzed in order to main constructive learning. The contours of flow images are compared with the standard images and the error graphs are plotted. Analysis of the emotion of the amateur karate player is made by observing the error plots.

  13. Innovazione nel mobile learning

    Directory of Open Access Journals (Sweden)

    Immaculada Arnedillo-Sànchez

    2008-01-01

    Full Text Available Descrizione, da una prospettiva europea, dell’innovazione nel settore del mobile learning e l’utilizzabilita’ del mobile learning in contesti educativi. Vengono illustrate i principali progetti europei di m-learning e si esamina le prospettive pedagogiche e teoriche relative al campo.

  14. Pervasive e-learning

    DEFF Research Database (Denmark)

    Hundebøl, Jesper; Helms, Niels Henrik

    2009-01-01

    This article falls within planning, production and delivery of innovative learning resources. The establishment of pervasive learning environments is based on the successful combination and re-configuration of inter-connected sets of learning objects, databases and data-streams. The text presents...

  15. Toddlers: Learning by Playing

    Science.gov (United States)

    ... Top 10 Homework Tips Raising Confident Kids Toddlers: Learning by Playing KidsHealth > For Parents > Toddlers: Learning by Playing Print A A A What's in ... child's play, but toddlers are hard at work learning important physical skills as they gain muscle control, ...

  16. Political learning among youth

    DEFF Research Database (Denmark)

    Solhaug, Trond; Kristensen, Niels Nørgaard

    2014-01-01

    This article focuses on students’ first political learning and explores the research question, what dynamic patterns of political learning can be explored among a selection of young, diverse Danish students’ first political interests? The authors use theories of learning in their analytical appro...

  17. Making Cooperative Learning Powerful

    Science.gov (United States)

    Slavin, Robert E.

    2014-01-01

    Just about everyone loves the "idea" of cooperative learning, children working productively and excitedly in groups, everyone getting along and enthusiastically helping one another learn. This article presents five strategies that teachers can use to get the greatest benefit possible from cooperative learning and ensure that…

  18. A learning space Odyssey

    NARCIS (Netherlands)

    Beckers, Ronald

    2016-01-01

    This dissertation addresses the alignment of learning space with higher education learning and teaching. Significant changes in higher education the past decades, such as increased information and communication technology (ICT) and new learning theories have resulted in the dilemma whether higher

  19. Adolescent Learning Styles.

    Science.gov (United States)

    Titus, Thomas G.; And Others

    1990-01-01

    Results are reported from a study of the learning styles of 306 high school students. The study examined learning style characteristics (abstraction, concreteness, reflection, activity); comparisons between adolescent and adult learning styles; and differences between freshmen and seniors, males and females, and slow-track and fast-track learners.…

  20. Taxonomy of Learning Skills

    Science.gov (United States)

    1988-04-01

    Learning and individual differences . San...engaged contributors to the original Learning and Individual Differences , and we believe (and hope to show how) the sophistication of the answer to this...an excellent research tool for investigating the time course of learning and individual differences therein. (3) Smithtown: Discovery World

  1. Games for Learning

    Science.gov (United States)

    Gee, James Paul

    2013-01-01

    Today there is a great deal of interest in and a lot of hype about using video games in schools. Video games are a new silver bullet. Games can create good learning because they teach in powerful ways. The theory behind game-based learning is not really new, but a traditional and well-tested approach to deep and effective learning, often…

  2. Organizational Learning? Look Again

    Science.gov (United States)

    Belle, Stuart

    2016-01-01

    Purpose: Despite the growth in research on conditions for successful learning by organizations and the introduction of expanding practices and approaches, a progressive and shared understanding of the link between organizational learning and governance is currently missing. This paper aims to take a closer look at organizational learning from a…

  3. Learning in Organization

    Science.gov (United States)

    Palos, Ramona; Veres Stancovici, Vesna

    2016-01-01

    Purpose: This study aims at identifying the presence of the dimensions of learning capabilities and the characteristics of a learning organization within two companies in the field of services, as well as identifying the relationships between their learning capability and the organizational culture. Design/methodology/approach: This has been a…

  4. A Blended Learning Experience

    Science.gov (United States)

    Gecer, Aynur; Dag, Funda

    2012-01-01

    Blended (hybrid) learning is one of the approaches that is utilized to help students for meaningful learning via information and communication technologies in educational settings. In this study, Computer II Course which is taught in faculties of education was planned and implemented in the form of a blended learning environment. The data were…

  5. Reflective Learning in Practice.

    Science.gov (United States)

    Brockbank, Anne, Ed.; McGill, Ian, Ed.; Beech, Nic, Ed.

    This book contains 22 papers on reflective learning in practice. The following papers are included: "Our Purpose" (Ann Brockbank, Ian McGill, Nic Beech); "The Nature and Context of Learning" (Ann Brockbank, Ian McGill, Nic Beech); "Reflective Learning and Organizations" (Ann Brockbank, Ian McGill, Nic Beech);…

  6. The Learning Theory Jungle

    Science.gov (United States)

    Minter, Robert L.

    2011-01-01

    This article addresses the myriad of pedagogical and andragogical issues facing university educators in the student learning process. It briefly explores the proliferation of learning theories in an attempt to develop awareness among faculty who teach at the university/college levels that not all theories of learning apply to the adult learner. In…

  7. Learning: An Evolutionary Analysis

    Science.gov (United States)

    Swann, Joanna

    2009-01-01

    This paper draws on the philosophy of Karl Popper to present a descriptive evolutionary epistemology that offers philosophical solutions to the following related problems: "What happens when learning takes place?" and "What happens in human learning?" It provides a detailed analysis of how learning takes place without any direct transfer of…

  8. Rethinking expansive learning

    DEFF Research Database (Denmark)

    Kolbæk, Ditte; Lundh Snis, Ulrika

    discussion forum on Google groups, they created new ways of reflecting and learning. We used netnography to select qualitative postings from the online community and expansive learning concepts for data analysis. The findings show how students changed practices of organisational learning...

  9. Learning physical space

    DEFF Research Database (Denmark)

    Hasse, Cathrine

    2002-01-01

    The article argues that cultural learning is a useful concept in analysing how neophytes learn from reactions and other forms of social designation. Through the newcomers learning process a concrete physical place takes on new cultural meaning. The specific example deals with first year students ...

  10. Deep Learning Online Course

    Science.gov (United States)

    2016-11-01

    TECHNICAL REPORT 3053 November 2016 Deep Learning Online Couse Katie Rainey Approved for public release...Science and Engineering (NISE) project entitled Deep Learning Online Course, executed in fiscal year 2016 at Space and Naval Warfare Systems Center...Pacific (SSC Pacific). RESULTS The project was successful in training a large group of scientists and engineers in the topic of deep learning , a

  11. LANGUAGE LEARNING--READINGS.

    Science.gov (United States)

    Modern Language Association of America, New York, NY.

    SELECTED ARTICLES ON SECOND LANGUAGE LEARNING AND REPORTS OF RESEARCH ON LANGUAGE LEARNING AND TEACHING, PUBLISHED FROM 1960 TO 1966, ARE PROVIDED IN THIS PACKET. INCLUDED ARE--(1) "UNDER-ACHIEVEMENT IN FL LEARNING" BY PAUL PIMSLEUR, DONALD M. SUNDLAND, AND RUTH D. MCINTYRE, (2) "THE PREDICTION OF SUCCESS IN INTENSIVE FL TRAINING" BY JOHN B.…

  12. Canadian Chefs' Workplace Learning

    Science.gov (United States)

    Cormier-MacBurnie, Paulette; Doyle, Wendy; Mombourquette, Peter; Young, Jeffrey D.

    2015-01-01

    Purpose: This paper aims to examine the formal and informal workplace learning of professional chefs. In particular, it considers chefs' learning strategies and outcomes as well as the barriers to and facilitators of their workplace learning. Design/methodology/approach: The methodology is based on in-depth, face-to-face, semi-structured…

  13. Mobile Learning Anytime, Anywhere

    Science.gov (United States)

    Hlodan, Oksana

    2010-01-01

    Some educational institutions are taking the leap to mobile learning (m-learning) by giving out free iPods. For example, Abilene Christian University gave iPods or iPhones to freshman students and developed 15 Web applications specifically for the mobile devices. The iPod is not the only ubiquitous m-learning device. Any technology that connects…

  14. Microsoft Azure machine learning

    CERN Document Server

    Mund, Sumit

    2015-01-01

    The book is intended for those who want to learn how to use Azure Machine Learning. Perhaps you already know a bit about Machine Learning, but have never used ML Studio in Azure; or perhaps you are an absolute newbie. In either case, this book will get you up-and-running quickly.

  15. A machine learning approach for ranking clusters of docked protein-protein complexes by pairwise cluster comparison.

    Science.gov (United States)

    Pfeiffenberger, Erik; Chaleil, Raphael A G; Moal, Iain H; Bates, Paul A

    2017-03-01

    Reliable identification of near-native poses of docked protein-protein complexes is still an unsolved problem. The intrinsic heterogeneity of protein-protein interactions is challenging for traditional biophysical or knowledge based potentials and the identification of many false positive binding sites is not unusual. Often, ranking protocols are based on initial clustering of docked poses followed by the application of an energy function to rank each cluster according to its lowest energy member. Here, we present an approach of cluster ranking based not only on one molecular descriptor (e.g., an energy function) but also employing a large number of descriptors that are integrated in a machine learning model, whereby, an extremely randomized tree classifier based on 109 molecular descriptors is trained. The protocol is based on first locally enriching clusters with additional poses, the clusters are then characterized using features describing the distribution of molecular descriptors within the cluster, which are combined into a pairwise cluster comparison model to discriminate near-native from incorrect clusters. The results show that our approach is able to identify clusters containing near-native protein-protein complexes. In addition, we present an analysis of the descriptors with respect to their power to discriminate near native from incorrect clusters and how data transformations and recursive feature elimination can improve the ranking performance. Proteins 2017; 85:528-543. © 2016 Wiley Periodicals, Inc. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

  16. How People Learn in an Asynchronous Online Learning Environment: The Relationships between Graduate Students' Learning Strategies and Learning Satisfaction

    Science.gov (United States)

    Choi, Beomkyu

    2016-01-01

    The purpose of this study was to examine the relationships between learners' learning strategies and learning satisfaction in an asynchronous online learning environment. In an attempt to shed some light on how people learn in an online learning environment, one hundred and sixteen graduate students who were taking online learning courses…

  17. How Do B-Learning and Learning Patterns Influence Learning Outcomes?

    OpenAIRE

    Sáiz Manzanares, María Consuelo; Marticorena Sánchez, Raúl; García Osorio, César Ignacio; Díez-Pastor, José F.

    2017-01-01

    Learning Management System (LMS) platforms provide a wealth of information on the learning patterns of students. Learning Analytics (LA) techniques permit the analysis of the logs or records of the activities of both students and teachers on the on-line platform. The learning patterns differ depending on the type of Blended Learning (B-Learning). In this study, we analyse: (1) whether significant differences exist between the learning outcomes of students and their learning patterns on the pl...

  18. Ensuring Effective Flexible Learning through Blended Learning

    Directory of Open Access Journals (Sweden)

    Nanda Van der Stap

    2017-02-01

    Full Text Available This paper discusses how Flexible Learning can be implemented through blended learning at the teacher trainer college of the University of Applied Sciences, Utrecht, Netherlands. To ensure quality blended learning programmes, it is essential that teachers developing blended learning courses are trained, particularly in relation to applied methodology. To understand how best to implement blended learning at the teacher trainer college extensive research was carried out, the findings of which were made available to the University's teachers in the form of a content-based, yet hands-on blended training programme with TPack as its exit point. The student results showed a marked improvement when following a blended learning course developed by teachers who were trained in the programme as compared to blended learning courses developed by non-trained teachers, In addition, the results of the blended courses (which were developed by trained teachers showed a vast improvement of the non-blended courses, it's so called 'regular' variant.

  19. Quantum machine learning

    Science.gov (United States)

    Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

    2017-09-01

    Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

  20. Efficient Learning Design

    DEFF Research Database (Denmark)

    Godsk, Mikkel

    engaging educators in the design process and developing teaching and learning, it is a shift in educational practice that potentially requires a stakeholder analysis and ultimately a business model for the deployment. What is most important is to balance the institutional, educator, and student...... perspectives and to consider all these in conjunction in order to obtain a sustainable, efficient learning design. The approach to deploying learning design in terms of the concept of efficient learning design, the catalyst for educational development, i.e. the learning design model and how it is being used...

  1. Machine learning with R

    CERN Document Server

    Lantz, Brett

    2013-01-01

    Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or

  2. Learning in context

    DEFF Research Database (Denmark)

    Keiding, Tina Bering

    2007-01-01

    through contingent handling of differences and that the individual emerge as learning through the actual construction. Selection of differences is influenced by the learner's actual knowledge, the nature of the environment and the current horizon of meaning in which the current adaptive perspective......This article offers a re-description of the concept of learning context. Drawing on Niklas Luhmann and Gregory Bateson it suggests an alternative to situated, social learning and activity theory. The conclusion is that learning context designates an individual's reconstruction of the environment...... becomes a significant factor. The re-description contributes to didaktik  through renewed understandings of participants' background in teaching and learning....

  3. The interprofessional learning experience

    DEFF Research Database (Denmark)

    Jakobsen, Flemming; Morcke, Anne Mette; Hansen, Torben Baek

    2017-01-01

    in a safe and challenging learning environment. The shift to the outpatient setting was strongly and practically supported by the management. This study indicates that student learning can be shifted to the outpatient clinic setting if there is supportive management and dedicated supervisors who establish...... a challenging yet safe interprofessional learning environment....... we ensure that this shift maximises learning. The purpose of this article is to understand the authentic learning experience in an interprofessional outpatient clinic setting. We performed an exploratory case study with interviews of four nursing students, 13 medical students, and six staff members...

  4. Learned helplessness at work.

    Science.gov (United States)

    Lennerlöf, L

    1988-01-01

    The development of theory and research on learned helplessness is reviewed and criticized on some points, e.g., for its reliance on artificial laboratory experiments. Some empirical findings are presented, indicating a connection between certain work characteristics and learned helplessness. Other research traditions have emphasized the importance of job qualifications, freedom of action, and development possibilities for well-being and health. There is, however, hardly and research on learned helplessness at work. Learned helplessness hypotheses should be tested on data from real life; if applied to work environment research, the theory of learned helplessness could generate important results.

  5. Learning and memory

    Directory of Open Access Journals (Sweden)

    P. A. J. Ryke

    1989-03-01

    Full Text Available Under various circumstances and in different species the outward expression of learning varies considerably, and this has led to the classification of different categories of learning. Just as there is no generally agreed on definition of learning, there is no one system of classification. Types of learning commonly recognized are: Habituation, sensitization, classical conditioning, operant conditioning, trial and error, taste aversion, latent learning, cultural learning, imprinting, insight learning, learning-set learning and instinct. The term memory must include at least two separate processes. It must involve, on the one hand, that of learning something and on the other, at some later date, recalling that thing. What lies between the learning and (he remembering must be some permanent record — a memory trace — within the brain. Memory exists in at least two forms: memory for very recent events (short-term which is relatively labile and easily disruptable; and long-term memory, which is much more stable. Not everything that gets into short-term memory becomes fixed in the long-term store; a filtering mechanism selects things that might be important and discards the rest.

  6. FLIPPED LEARNING: PRACTICAL ASPECTS

    Directory of Open Access Journals (Sweden)

    Olena Kuzminska

    2016-03-01

    Full Text Available The article is devoted to issues of implementation of the flipped learning technology in the practice of higher education institutions. The article defines the principles of technology and a model of the educational process, it notes the need to establish an information support system. The article defines online platforms and resources; it describes recommendations for the design of electronic training courses and organization of the students in the process of implementing the proposed model, as well as tools for assessing its effectiveness. The article provides a description of flipped learning implementation scenario and formulates suggestions regarding the use of this model as a mechanism to improve the efficiency of the learning process in the ICT-rich environment of high school: use of learning management systems (LMS and personal learning environments (PLE of participants in a learning process. The article provides an example of implementation of the flipped learning model as a part of the Information Technologies course in the National University of Life and Environmental Sciences of Ukraine (NULES. The article gives examples of tasks, resources and services, results of students’ research activity, as well as an example of the personal learning network, established in the course of implementation of the flipped learning model and elements of digital student portfolios. It presents the results of the monitoring of learning activities and students’ feedback. The author describes cautions against the mass introduction of the flipped learning model without monitoring of readiness of the participants of the educational process for its implementation

  7. Exploitative Learning by Exporting

    DEFF Research Database (Denmark)

    Golovko, Elena; Lopes Bento, Cindy; Sofka, Wolfgang

    Decisions on entering foreign markets are among the most challenging but also potentially rewarding strategy choices managers can make. In this study, we examine the effect of export entry on the firm investment decisions in two activities associated with learning about new technologies...... and learning about new markets ? R&D investments and marketing investments, in search of novel insights into the content and process underlying learning by exporting. We draw from organizational learning theory for predicting changes in both R&D and marketing investment patterns that accompany firm entry......, it is predominantly the marketing-related investment decisions associated with starting to export that lead to increases in firm productivity. We conclude that learning-by-exporting might be more properly characterized as ?learning about and exploiting new markets? rather than ?learning about new technologies...

  8. Learning From Experience

    DEFF Research Database (Denmark)

    Visholm, Steen; Beck, Ulla Charlotte

    2014-01-01

    University and NAPSO2). Seen from the horizon of their experience some of the basic concepts in the theories about GRC need clarifying, revision, and development. The GRC is a part of the learning from experience movement and as a consequence it stresses the underlying basis: learning is personal so everyone......In this paper the learning concept of group relation's conferences are discussed. The authors have worked with group relations conferences (GRC) in different contexts for many years-mainly as a part of educational programmes for managers and consultants (OPU at IGA Copenhagen, MPO at Roskilde...... decides for themselves what makes sense and what does not. This principle sometimes works as a defence against a closer examination of the two questions: do GRCs provide relevant experiences to learn from, and what is it you learn or can expect to learn at a GRC. Here the learning concept of the GRCs...

  9. Evaluation and Policy Learning

    DEFF Research Database (Denmark)

    Borrás, Susana; Højlund, Steven

    2015-01-01

    This article examines how evaluation induces policy learning – a question largely neglected by the scholarly literature on evaluation and policy learning. Following a learner's perspective, the article attempts to ascertain who the learners are, and what, and how, learners actually learn from...... evaluations. In so doing, it focuses on what different types of learners actually learn within the context of the evaluation framework (the set of administrative structures defining the evaluation goals and process). Taking the empirical case of three EU programme evaluations, the patterns of policy learning...... emanating from them are examined. The findings are that only two types of actors involved in the evaluation are actually learning (programme units and external evaluators), that learners learn different things (programme overview, small-scale programme adjustments, policy change and evaluation methods...

  10. Learning as Negotiating Identities

    DEFF Research Database (Denmark)

    Jørgensen, Kenneth Mølbjerg; Keller, Hanne Dauer

    of time - caught in the notion of trajectories of learning - that integrate past, present and future. Working with the learners' notion of time is significant because it is here that new learning possibilities become visible and meaningful for individuals. Further, we argue that the concept of identity......The paper explores the contribution of Communities of Practice (COP) to Human Resource Development (HRD). Learning as negotiating identities captures the contribution of COP to HRD. In COP the development of practice happens through negotiation of meaning. The learning process also involves modes...... of belonging constitutive of our identities. We suggest that COP makes a significant contribution by linking learning and identification. This means that learning becomes much less instrumental and much more linked to fundamental questions of being. We argue that the COP-framework links learning with the issue...

  11. Flipped learning: should it replace didactic learning?

    National Research Council Canada - National Science Library

    Osman A; Jalal SR; Azizi S

    2017-01-01

    Abdirahman Osman, Seyed Ramin Jalal, Saeed Azizi Faculty of Medicine, St George's Hospital Medical School, London, UKWe read with great interest the article by Pettit et al1 on the implementation of flipped learning...

  12. Workplaces as Transformative Learning Spaces

    DEFF Research Database (Denmark)

    Maslo, Elina

    2010-01-01

    words: learning, lifelong learning, adult learning, workplace learning, transformative learning spaces During many years of research on lifelong foreign language learning with very different groups of learners, we found some criteria, which make learning process successful. Since then we tried to find......Abstract to the Vietnam Forum on Lifelong Learning: Building a Learning Society Hanoi, 7-8 December 2010 Network 2: Competence development as Workplace Learning Title of proposal: Workplaces as Transformative Learning Spaces Author: Elina Maslo, dr. paed., University of Latvia, elina@latnet.lv Key...... some other examples on “successful learning” from the formal, informal and non-formal learning environments, trying to prove those criteria. This presentation provides a view on to new examples on transformative learning spaces we discovered doing research on Workplace Learning in Latvia as a part...

  13. CULTURAL VARIATIONS IN LEARNING AND LEARNING STYLES

    Directory of Open Access Journals (Sweden)

    Pegah OMIDVAR,, Putra University, MALAYSIA

    2012-08-01

    Full Text Available The need for cross-cultural understanding of the relationship between culture and learning style is becoming increasingly important because of the changing cultural mix of classrooms and society at large. The research done regarding the two variables is mostly quantitative. This review summarizes results of the existing research on cultural variations in learning styles. Limitations of the existing studies are discussed and some suggestion for future research is proposed.

  14. LEARNING HOW TO LEARN A LANGUAGE

    CERN Multimedia

    LANGUAGE TRAINING; Tel. 73127; Andrée Fontbonne; Tel. 72844

    2001-01-01

    This bilingual seminar is for anyone who would like to develop learning strategies and skills for learning a foreign language. Languages: French and English. Length: 3 days, 7 hours per day. Dates: 7, 8, 9 March 2001. Price: 462 CHF per person (for a group of 8 people). If you are interested, please enrol through our Web pages: http://training.web.cern.ch/Training/LANG/lang0_F.html

  15. LEARNING HOW TO LEARN A LANGUAGE

    CERN Multimedia

    Moniek Laurent

    2002-01-01

    This bilingual seminar is for anyone who would like to develop learning strategies and skills for learning a foreign language. Languages: French and English. Length: 3 days, 7 hours per day. Dates: 4, 5, 6 March 2002. Price: 460 CHF per person (for a group of 8 people). If you are interested, please enrol through our Web pages: http://cern.ch/Training   Language Training Moniek Laurent Tel. 78582 moniek.laurent@cern.ch

  16. LEARNING HOW TO LEARN A LANGUAGE

    CERN Document Server

    Formation en Langues; Andrée Fontbonne - Tél. 72844; Language Training; Françoise Benz - Tel. 73127; Andrée Fontbonne - Tel. 72844

    2000-01-01

    This bilingual seminar is for anyone who would like to develop learning strategies and skills for learning a foreign language. It is particularly recommended for those wishing to sign up for a 3-month self-study session in the Resource Centre. Languages: French and English. Length: 5 hours a day for one week. Dates: 27 November to December 2000. Price: 490 CHF per person (for a group of 8 people). If you are interested, please enrol through our Web pages.

  17. Gamification of the Learning Process: Lessons Learned

    OpenAIRE

    Llorens Largo, Faraón; Gallego-Durán, Francisco J.; Villagrá-Arnedo, Carlos-José; Compañ, Patricia; Satorre Cuerda, Rosana; Molina-Carmona, Rafael

    2016-01-01

    Although several definitions of gamification can be found in the literature, they all have in common certain aspects: the application of strategies, models, dynamics, mechanics, and elements of the games in other contexts than games, and the objective of producing a playful experience that fosters motivation, involvement, and fun. In this paper, our approach gamifying the learning process of a subject is presented. Our experience throughout time in using games and gamification in learning hav...

  18. Incidental auditory category learning.

    Science.gov (United States)

    Gabay, Yafit; Dick, Frederic K; Zevin, Jason D; Holt, Lori L

    2015-08-01

    Very little is known about how auditory categories are learned incidentally, without instructions to search for category-diagnostic dimensions, overt category decisions, or experimenter-provided feedback. This is an important gap because learning in the natural environment does not arise from explicit feedback and there is evidence that the learning systems engaged by traditional tasks are distinct from those recruited by incidental category learning. We examined incidental auditory category learning with a novel paradigm, the Systematic Multimodal Associations Reaction Time (SMART) task, in which participants rapidly detect and report the appearance of a visual target in 1 of 4 possible screen locations. Although the overt task is rapid visual detection, a brief sequence of sounds precedes each visual target. These sounds are drawn from 1 of 4 distinct sound categories that predict the location of the upcoming visual target. These many-to-one auditory-to-visuomotor correspondences support incidental auditory category learning. Participants incidentally learn categories of complex acoustic exemplars and generalize this learning to novel exemplars and tasks. Further, learning is facilitated when category exemplar variability is more tightly coupled to the visuomotor associations than when the same stimulus variability is experienced across trials. We relate these findings to phonetic category learning. (c) 2015 APA, all rights reserved).

  19. Humanization of mathematics learning

    Directory of Open Access Journals (Sweden)

    Sandra Bayu Kurniawan

    2017-09-01

    Full Text Available The study concerned here was to describe (1 the characteristics of humanistic mathematics learning and (2 the stages to actualize such learning. The said study was a qualitative one employing the phenomenological approach with six stages of inductive analysis. The data were validated by using the data source triangulation technique. The study involved 75 students of an elementary school, SD Mangunan, Berbah, Sleman, 36 students of a state senior high school, SMA Negeri 1 of Sewon, Bantul, and 42 students of another state senior high school, SMA Negeri 1 of Dlingo, Bantul. The results of the validation showed that the data were valid and consistent. The conclusions of the study are as follows. (1 Humanistic mathematics learning is characterized by the facts that the use of the mathematics learning media gives students space and time to explore and construct mathematical concept understanding and mathematics learning methods are applied by using an inductive approach. (2 The stages to realize humanistic mathematics learning include the setting of mathematics learning objectives based on humanism, existentialism, and religious teachings by building individual students’ strengths through independent and civilized manners, the setting of mathematics learning goals emphasizing balance among the domains of idea, intention, and action, and the setting of the development of contextual and cooperative mathematics learning strategies. Keywords: humanization, mathematics learning

  20. Individual Learning Style and the Learning Style Inventory.

    Science.gov (United States)

    Heffler, Bo

    2001-01-01

    Focuses on the experience learning theory (ELT) that views learning as a process, explaining that it entails a four-stage process that includes four learning modes. Presents the results of a study that used the learning style inventory (LSI) that examines one's approach to learning situations. Includes references. (CMK)

  1. Assessing Individuality in Learning: The Learning Skills Profile.

    Science.gov (United States)

    Boyatzis, Richard E.; Kolb, David A.

    1991-01-01

    Develops a typology of learning skills congruent with the learning style descriptions of experiential learning theory. Describes the Learning Skills Profile (LSP), an assessment instrument designed to assess learning skills. Suggests the LSP for providing personal and organizational feedback on skills. Suggests that the typology allows both…

  2. A Blended Mobile Learning Environment for Museum Learning

    Science.gov (United States)

    Hou, Huei-Tse; Wu, Sheng-Yi; Lin, Peng-Chun; Sung, Yao-Ting; Lin, Jhe-Wei; Chang, Kuo-En

    2014-01-01

    The use of mobile devices for informal learning has gained attention over recent years. Museum learning is also regarded as an important research topic in the field of informal learning. This study explored a blended mobile museum learning environment (BMMLE). Moreover, this study applied three blended museum learning modes: (a) the traditional…

  3. Entrepreneurial learning requires action

    DEFF Research Database (Denmark)

    Brink, Tove; Madsen, Svend Ole

    2014-01-01

    This paper reveals how managers of small- and medium-sized enterprises (SMEs) can utilise their participation in research-based training. Empirical research from a longitudinal study of 10 SMEs managers in the wind turbine industry is provided to describe a learning approach that SME managers can...... apply in industry. The findings of this study show that SME managers employ a practice-shaped holistic multi- and cross-disciplinary approach to learning. This learning approach is supported by theory dissemination, business challenge applications, and organisational prerequisites. Diversified learning...... that is enhanced by essential large-scale industry players and other SME managers are required to create action and value in learning. An open-mindedness to new learning approaches by SME managers and an open-mindedness to multi- and cross-disciplinary collaboration with SME managers by facilitators is required....

  4. Cultural Learning Redux.

    Science.gov (United States)

    Tomasello, Michael

    2016-05-01

    M. Tomasello, A. Kruger, and H. Ratner (1993) proposed a theory of cultural learning comprising imitative learning, instructed learning, and collaborative learning. Empirical and theoretical advances in the past 20 years suggest modifications to the theory; for example, children do not just imitate but overimitate in order to identify and affiliate with others in their cultural group, children learn from pedagogy not just episodic facts but the generic structure of their cultural worlds, and children collaboratively co-construct with those in their culture normative rules for doing things. In all, human children do not just culturally learn useful instrumental activities and information, they conform to the normative expectations of the cultural group and even contribute themselves to the creation of such normative expectations. © 2016 The Author. Child Development © 2016 Society for Research in Child Development, Inc.

  5. Blended Learning Design

    DEFF Research Database (Denmark)

    Pedersen, Lise

    2015-01-01

    for the individual subjects (for instance subjects with a high degree of complexity or difficulty) or groups of students (those in danger of dropping out for instance) without necessarily increasing face to face teaching, but by developing asynchronous study activities and learning resources for digital distance...... learning. 4. Blended learning can contribute to supporting and improving efficiency of educational efforts. This can for instance be done through programmes for several classes by using video conferencing, allocating traditional face to face teaching to synchronous and asynchronous study activities produce...... and Learning Resources (EILR) was asked to develop and support the blended learning implementation strategy. EILR is an inter-faculty unit in UCL, which develops and supports digitization and learning approaches in the professional bachelor programme. The paper addresses the potentials and the pitfalls...

  6. Problem Based Learning

    DEFF Research Database (Denmark)

    de Graaff, Erik; Guerra, Aida

    Problem-Based Learning (PBL) is an innovative method to organize the learning process in such a way that the students actively engage in finding answers by themselves. During the past 40 years PBL has evolved and diversified resulting in a multitude in variations in models and practices. However......, the key principles remain the same everywhere. Graaff & Kolmos (2003) identify the main PBL principles as follows: 1. Problem orientation 2. Project organization through teams or group work 3. Participant-directed 4. Experiental learning 5. Activity-based learning 6. Interdisciplinary learning and 7...... in Engineering Education. In answer to the requests for visits the Aalborg Centre for Problem Based Learning in Engineering Science and Sustainability under the auspices of UNESCO (UCPBL) a two days programme for visitors is offered two times a year. The workshop is an introduction workshop to the Aalborg PBL...

  7. Cultural dimensions of learning

    Science.gov (United States)

    Eyford, Glen A.

    1990-06-01

    How, what, when and where we learn is frequently discussed, as are content versus process, or right brain versus left brain learning. What is usually missing is the cultural dimension. This is not an easy concept to define, but various aspects can be identified. The World Decade for Cultural Development emphasizes the need for a counterbalance to a quantitative, economic approach. In the last century poets also warned against brutalizing materialism, and Sorokin and others have described culture more recently in terms of cohesive basic values expressed through aesthetics and institutions. Bloom's taxonomy incorporates the category of affective learning, which internalizes values. If cultural learning goes beyond knowledge acquisition, perhaps the surest way of understanding the cultural dimension of learning is to examine the aesthetic experience. This can use myths, metaphors and symbols, and to teach and learn by using these can help to unlock the human potential for vision and creativity.

  8. Deep learning with Python

    CERN Document Server

    Chollet, Francois

    2018-01-01

    DESCRIPTION Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. Deep Learning with Python is structured around a series of practical code examples that illustrate each new concept introduced and demonstrate best practices. By the time you reach the end of this book, you will have become a Keras expert and will be able to apply deep learning in your own projects. KEY FEATURES • Practical code examples • In-depth introduction to Keras • Teaches the difference between Deep Learning and AI ABOUT THE TECHNOLOGY Deep learning is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more. AUTHOR BIO Francois Chollet is the author of Keras, one of the most widely used libraries for deep learning in Python. He has been working with deep neural ...

  9. Blended learning in anatomy

    DEFF Research Database (Denmark)

    Østergaard, Gert Værge; Brogner, Heidi Marie

    The aim of the project was to bridge the gap between theory and practice by working more collaboratively, both peer-to-peer and between student and lecturer. Furthermore the aim was to create active learning environments. The methodology of the project is Design-Based Research (DBR). The idea...... and lecturers. LITERATURE CITED: 1) Collins et al, 2004, Design Research: Theoretical and Methodological Issues. Journal of the Learning Sciences, 13(1), 15-42. 2) Bergmen J, Sams A, 2014, Flipped Learning, International Society for Technology in Education...... behind DBR is that new knowledge is generated through processes that simultaneously develop, test and improve a design, in this case, an educational design (1) The main principles used in the project is blended learning and flipped learning (2). …"I definitely learn best in practice, but the theory...

  10. Exploring nurses' learning

    Directory of Open Access Journals (Sweden)

    Lioba Howatson-Jones

    2012-08-01

    Full Text Available The aim of this paper is to explore the concept of compelling space for learning. The research presented uses an auto/biographical methodology to explore nurses' learning. Theoretical perspective is drawn from biographical approaches and ideas around development of the self, to examine the nature of people's experience. The argument is advanced, through the narrations of three study participants from a PhD study, that there is a need for nurses to have space to tell their stories of learning and to reconnect with personal experience. The narrations focus upon learning by mistake, developing an interpretive imagination and using biography in teaching and learning and have something to contribute to the development of spaces of learning. This is developed further by considering how biographical method and reflexive responses offer opportunity to find the personal voice and make spaces more compelling and integrative as a different form of pedagogy for nurse education.

  11. COLLECTIVE LEARNING IN A LEARNING ORGANIZATION: GROWING TEAM LEARNING CULTURE TO SURVIVE AND DEVELOP

    OpenAIRE

    Adi Suryani

    2012-01-01

    A learning organization has a deep culture of learning. It is constantly encourage its member to learn. This learning activity is not only for adapting to the rapid changing of its internal and external environment, but also for growing. The effort of a learning organization to create a conducive learning climate can be indicated by training its members. Working towards a learning organization has both its strengths and drawbacks. The strengths are it can improve the organization performan...

  12. Unsupervised clustering with spiking neurons by sparse temporal coding and multi-layer RBF networks

    NARCIS (Netherlands)

    S.M. Bohte (Sander); J.A. La Poutré (Han); J.N. Kok (Joost)

    2000-01-01

    textabstractWe demonstrate that spiking neural networks encoding information in spike times are capable of computing and learning clusters from realistic data. We show how a spiking neural network based on spike-time coding and Hebbian learning can successfully perform unsupervised clustering on

  13. Introducere in Action Learning

    DEFF Research Database (Denmark)

    Clausen, Søren Witzel

    In these years action learning has become an increasing aspect of qualifying in service training of teachers in Western European countries. In this article the model of action learning which has been developed by teachers at VIA University College and introduced to the teachers at the SCAN...... in service program will be described and the interaction and the learning aspects in the model will be analyzed....

  14. Learning SQL in Steps

    OpenAIRE

    Philip Garner; John Mariani

    2015-01-01

    Learning SQL is a common problem for many Computer Science (CS) students, the steps involved are quite different to those mastered when learning procedural or object-oriented programming languages. The introduction of commercial products that include shortcuts into the learning environment can initially appear to benefit the student, however, transferring these skills to a textual environment can be difficult for many students. Computer Science students are required to build textual SQL queri...

  15. Pattern recognition & machine learning

    CERN Document Server

    Anzai, Y

    1992-01-01

    This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.

  16. Formalized Informal Learning

    DEFF Research Database (Denmark)

    Levinsen, Karin Tweddell; Sørensen, Birgitte Holm

    2013-01-01

    are examined and the relation between network society competences, learners’ informal learning strategies and ICT in formalized school settings over time is studied. The authors find that aspects of ICT like multimodality, intuitive interaction design and instant feedback invites an informal bricoleur approach....... When integrated into certain designs for teaching and learning, this allows for Formalized Informal Learning and support is found for network society competences building....

  17. Editorial: Advanced learning technologies

    OpenAIRE

    Yu-Ju Lan; Gang-Shan Fu; Yang, Stephen J. H.; Jeff J.S. Huang

    2012-01-01

    Recent rapid development of advanced information technology brings high expectations of its potential to improvement and innovations in learning. This special issue is devoted to using some of the emerging technologies issues related to the topic of education and knowledge sharing, involving several cutting edge research outcomes from recent advancement of learning technologies. Advanced learning technologies are the composition of various related technologies and concepts such as mobile tech...

  18. Unsupervised Learning and Generalization

    OpenAIRE

    Hansen, Lars Kai; Larsen, Jan

    1996-01-01

    The concept of generalization is defined for a general class of unsupervised learning machines. The generalization error is a straightforward extension of the corresponding concept for supervised learning, and may be estimated empirically using a test set or by statistical means-in close analogy with supervised learning. The empirical and analytical estimates are compared for principal component analysis and for K-means clustering based density estimation

  19. Lost in Language Learning

    OpenAIRE

    Nellemann, Kristian Lindhardt; Birk, Nikoline Aarup; Toft-Nielsen, Nina Kristine; Justice, Alexandra Isabella; Løkkegaard, Jakob Ludvig; Mørch, Cecilia

    2014-01-01

    This project seeks to investigate the intricate processes immigrants in Denmark go through when learning Danish as a foreign or second language. It builds from an understanding of language as a social practice and a view of language learning as having more than a cognitive level. By combining theory on second language acquisition with theory on identity and communities of practice, this project looks to explore how immigrants through investment in language learning create or maintain a meanin...

  20. Deep learning relevance

    DEFF Research Database (Denmark)

    Lioma, Christina; Larsen, Birger; Petersen, Casper

    2016-01-01

    train a Recurrent Neural Network (RNN) on existing relevant information to that query. We then use the RNN to "deep learn" a single, synthetic, and we assume, relevant document for that query. We design a crowdsourcing experiment to assess how relevant the "deep learned" document is, compared...... to existing relevant documents. Users are shown a query and four wordclouds (of three existing relevant documents and our deep learned synthetic document). The synthetic document is ranked on average most relevant of all....

  1. Learning Mathematics through Programming

    DEFF Research Database (Denmark)

    Misfeldt, Morten; Ejsing-Duun, Stine

    2015-01-01

    In this paper we explore the potentials for learning mathematics through programming by a combination of theoretically derived potentials and cases of practical pedagogical work. We propose a model with three interdependent learning potentials as programming which can: (1) help reframe the students...... to mathematics is paramount. Analyzing two cases, we suggest a number of ways in which didactical attention to epistemic mediation can support learning mathematics....

  2. Learning Perforce SCM

    CERN Document Server

    Cowham, Robert

    2013-01-01

    Learning Perforce SCM is written in a friendly and practical style with a focus on getting you started with Perforce efficiently and effectively. The book provides plenty of examples and screenshots to guide you through the process of learning.""Learning Perforce SCM"" is for anyone who wants to know how to adeptly manage software development activities using Perforce. Experience with other version control tools is a plus but is not required.

  3. Neurobiology of song learning

    Science.gov (United States)

    Mooney, Richard

    2016-01-01

    Birdsong is a culturally transmitted behavior that depends on a juvenile songbird’s ability to imitate the song of an adult tutor. Neurobiological studies of birdsong can reveal how a complex form of imitative learning, which bears strong parallels to human speech learning, can be understood at the level of underlying circuit, cellular, and synaptic mechanisms. This review focuses on recent studies that illuminate the neurobiological mechanisms for singing and song learning. PMID:19892546

  4. Discovery Learning Strategies in English

    Science.gov (United States)

    Singaravelu, G.

    2012-01-01

    The study substantiates that the effectiveness of Discovery Learning method in learning English Grammar for the learners at standard V. Discovery Learning is particularly beneficial for any student learning a second language. It promotes peer interaction and development of the language and the learning of concepts with content. Reichert and…

  5. Develop a Professional Learning Plan

    Science.gov (United States)

    Journal of Staff Development, 2013

    2013-01-01

    A professional learning plan establishes short-and long-term plans for professional learning and implementation of the learning. Such plans guide individuals, schools, districts, and states in coordinating learning experiences designed to achieve outcomes for educators and students. Professional learning plans focus on the program of educator…

  6. Readiness of Adults to Learn Using E-Learning, M-Learning and T-Learning Technologies

    Science.gov (United States)

    Vilkonis, Rytis; Bakanoviene, Tatjana; Turskiene, Sigita

    2013-01-01

    The article presents results of the empirical research revealing readiness of adults to participate in the lifelong learning process using e-learning, m-learning and t-learning technologies. The research has been carried out in the framework of the international project eBig3 aiming at development a new distance learning platform blending virtual…

  7. Learning efficient correlated equilibria

    KAUST Repository

    Borowski, Holly P.

    2014-12-15

    The majority of distributed learning literature focuses on convergence to Nash equilibria. Correlated equilibria, on the other hand, can often characterize more efficient collective behavior than even the best Nash equilibrium. However, there are no existing distributed learning algorithms that converge to specific correlated equilibria. In this paper, we provide one such algorithm which guarantees that the agents\\' collective joint strategy will constitute an efficient correlated equilibrium with high probability. The key to attaining efficient correlated behavior through distributed learning involves incorporating a common random signal into the learning environment.

  8. Learning Disorders in Epilepsy

    National Research Council Canada - National Science Library

    Beghi, Massimiliano; Cornaggia, Cesare Maria; Frigeni, Barbara; Beghi, Ettore

    2006-01-01

    Learning disorders (LD) are disorders interfering with academic performance or with daily living activities requiring reading, writing, or mathematical abilities in subjects with a normal intelligence quotient...

  9. Machine Learning for Hackers

    CERN Document Server

    Conway, Drew

    2012-01-01

    If you're an experienced programmer interested in crunching data, this book will get you started with machine learning-a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation. Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyz

  10. Paradigms for machine learning

    Science.gov (United States)

    Schlimmer, Jeffrey C.; Langley, Pat

    1991-01-01

    Five paradigms are described for machine learning: connectionist (neural network) methods, genetic algorithms and classifier systems, empirical methods for inducing rules and decision trees, analytic learning methods, and case-based approaches. Some dimensions are considered along with these paradigms vary in their approach to learning, and the basic methods are reviewed that are used within each framework, together with open research issues. It is argued that the similarities among the paradigms are more important than their differences, and that future work should attempt to bridge the existing boundaries. Finally, some recent developments in the field of machine learning are discussed, and their impact on both research and applications is examined.

  11. Researching workplace learning

    DEFF Research Database (Denmark)

    Jørgensen, Christian Helms; Warring, Niels

    2007-01-01

    This article presents a theoretical and methodological framework for understanding and researching learning in the workplace. The workplace is viewed in a societal context and the learner is viewed as more than an employee in order to understand the learning process in relation to the learner......'s life history.Moreover we will explain the need to establish a 'double view' by examining learning in the workplace both as an objective and as a subjective reality. The article is mainly theoretical, but can also be of interest to practitioners who wish to understand learning in the workplace both...

  12. Editorial: Advanced learning technologies

    Directory of Open Access Journals (Sweden)

    Yu-Ju Lan

    2012-03-01

    Full Text Available Recent rapid development of advanced information technology brings high expectations of its potential to improvement and innovations in learning. This special issue is devoted to using some of the emerging technologies issues related to the topic of education and knowledge sharing, involving several cutting edge research outcomes from recent advancement of learning technologies. Advanced learning technologies are the composition of various related technologies and concepts such as mobile technologies and social media towards learner centered learning. This editorial note provides an overview of relevant issues discussed in this special issue.

  13. Perspectives on ontology learning

    CERN Document Server

    Lehmann, J

    2014-01-01

    Perspectives on Ontology Learning brings together researchers and practitioners from different communities − natural language processing, machine learning, and the semantic web − in order to give an interdisciplinary overview of recent advances in ontology learning.Starting with a comprehensive introduction to the theoretical foundations of ontology learning methods, the edited volume presents the state-of-the-start in automated knowledge acquisition and maintenance. It outlines future challenges in this area with a special focus on technologies suitable for pushing the boundaries beyond the c

  14. Learning and Communicative Rationality

    DEFF Research Database (Denmark)

    Rasmussen, Palle

    The paper is an attempt to outline Habermas' contributions to a theory of learning. Such contributions are found in his work on individual learning and socialization, the constitution and reproduction of lifeworlds, the character of social evolution, the processes of public delibearation...... and democracy and the idea and role of universities. A "theory of learning" is not taken in a very formalised sense, rather the idea is to identify themes where Habermas' theoretical framework provide the opportunity for locating important aspects of learning in modern society....

  15. Students’ digital learning environments

    DEFF Research Database (Denmark)

    Caviglia, Francesco; Dalsgaard, Christian; Davidsen, Jacob

    2018-01-01

    The objective of the paper is to examine the nature of students’ digital learning environments to understand the interplay of institutional systems and tools that are managed by the students themselves. The paper is based on a study of 128 students’ digital learning environments. The objectives...... used tools in the students’ digital learning environments are Facebook, Google Drive, tools for taking notes, and institutional systems. Additionally, the study shows that the tools meet some very basic demands of the students in relation to collaboration, communication, and feedback. Finally...... learning environments in relation to existing and emerging needs....

  16. Georgia - Improved Learning Environment

    Data.gov (United States)

    Millennium Challenge Corporation — The school rehabilitation activity seeks to decrease student and teacher absenteeism, increase students’ time on task, and, ultimately, improve learning and labor...

  17. Machine Learning in Medicine

    National Research Council Canada - National Science Library

    Deo, Rahul C

    2015-01-01

    Spurred by advances in processing power, memory, storage, and an unprecedented wealth of data, computers are being asked to tackle increasingly complex learning tasks, often with astonishing success...

  18. Strengths-based Learning

    DEFF Research Database (Denmark)

    Ledertoug, Mette Marie

    Strength-based learning - Children͛s Character Strengths as Means to their Learning Potential͛ is a Ph.D.-project aiming to create a strength-based mindset in school settings and at the same time introducing strength-based interventions as specific tools to improve both learning and well......-being. The Ph.D.-project in Strength-based learning took place in a Danish school with 750 pupils age 6-16 and a similar school was functioning as a control group. The presentation will focus on both the aware-explore-apply processes and the practical implications for the schools involved, and on measurable...

  19. Effect of adaptive learning style scenarios on learning achievements

    NARCIS (Netherlands)

    Bozhilov, Danail; Stefanov, Krassen; Stoyanov, Slavi

    2009-01-01

    Bozhilov, D., Stefanov, K., & Stoyanov, S. (2009). Effect of adaptive learning style scenarios on learning achievements [Special issue]. International Journal of Continuing Engineering Education and Lifelong Learning (IJCEELL), 19(4/5/6), 381-398.

  20. Personalized learning Ecologies in Problem and Project Based Learning Environments

    DEFF Research Database (Denmark)

    Rongbutsri, Nikorn; Ryberg, Thomas; Zander, Pär-Ola

    2012-01-01

    education, institutions leverage learning by providing courses, learning spaces and also different ICT systems as tools to support students’ learning (Virtual learning environments). However, courses, physical learning environments, and Virtual Learning Environments are just temporary learning scaffoldings.......0 tools in their academic life. As such students’ engagements with technology are composed of formal administrative systems, virtual learning environments, various other learning technologies and also a range of ‘life’-technologies, such as Facebook, Youtube and many other services which form important...... is in contrast to an artificial learning setting often found in traditional education. As many other higher education institutions, Aalborg University aims at providing learning environments that support the underlying pedagogical approach employed, and which can lead to different online and offline learning...

  1. Learned-Helplessness Theory: Implications for Research in Learning Disabilities.

    Science.gov (United States)

    Canino, Frank J.

    1981-01-01

    The application of learned helplessness theory to achievement is discussed within the context of implications for research in learning disabilities. Finally, the similarities between helpless children and learning disabled students in terms of problems solving and attention are discussed. (Author)

  2. E-LEARNING-IMPLICATIONS FOR ADULT LEARNING

    Directory of Open Access Journals (Sweden)

    Roxana CRIU

    2013-04-01

    Full Text Available If a few decades ago, the education received in school could be in most of the cases enough to go with for the rest of one’s entire life, today the situation has changed dramatically. The individual has to be prepared for a new type of life and training, namely lifelong learning. The individual’s survival in society could depend on his capacity to learn, to re-qualify, to forget what he once learned and to train for the future in an entirely different manner. Within this context, e-learning and distance education can be viable alternatives for the necessary and imperative adaptation process. Modern man’s education has to go beyond the stage of level oriented education (limited in terms of trainee number and training duration and advance towards continuous education, which is able to train the individual irrespective of his location and with no limitations in terms of time. The passage towards the information society involves mutations in the object of the activities, mainly in terms of selecting, storing, preserving, managing and protecting information. Against this extremely fluctuant background, a relevant question rises: is the adult capable of coping, both individually and socially, with the challenge of e-learning?

  3. COLLECTIVE LEARNING IN A LEARNING ORGANIZATION: GROWING TEAM LEARNING CULTURE TO SURVIVE AND DEVELOP

    Directory of Open Access Journals (Sweden)

    Adi Suryani

    2012-11-01

    Full Text Available A learning organization has a deep culture of learning. It is constantly encourage its member to learn. This learning activity is not only for adapting to the rapid changing of its internal and external environment, but also for growing. The effort of a learning organization to create a conducive learning climate can be indicated by training its members. Working towards a learning organization has both its strengths and drawbacks. The strengths are it can improve the organization performance and organization survival. However, learning too rapid can lead to learning stress. Moreover it can lead to harsh internal competition.

  4. On-the-Fly Learning in a Perpetual Learning Machine

    OpenAIRE

    Simpson, Andrew J. R.

    2015-01-01

    Despite the promise of brain-inspired machine learning, deep neural networks (DNN) have frustratingly failed to bridge the deceptively large gap between learning and memory. Here, we introduce a Perpetual Learning Machine; a new type of DNN that is capable of brain-like dynamic 'on the fly' learning because it exists in a self-supervised state of Perpetual Stochastic Gradient Descent. Thus, we provide the means to unify learning and memory within a machine learning framework. We also explore ...

  5. GENDER DIFFERENCES IN LANGUAGE LEARNING STYLE AND LANGUAGE LEARNING STRATEGIES

    OpenAIRE

    Chayata Viriya; Sutthirak Sapsirin

    2014-01-01

    Abstract: This paper seeks to investigate the gender differences in language learning style and language learning strategies. The study used the perceptual learning-style preference questionnaire (PLSPQ) to investigate the learning style preferences and the Strategy Inventory for Language Learning (SILL) version 7.0 designed by Oxford (1990) to find the learning strategy preferences of first year University students at the faculty of Information and Communication Technology (ICT) in Thailand....

  6. Learning to learn: theta oscillations predict new learning, which enhances related learning and neurogenesis.

    Science.gov (United States)

    Nokia, Miriam S; Sisti, Helene M; Choksi, Monica R; Shors, Tracey J

    2012-01-01

    Animals in the natural world continuously encounter learning experiences of varying degrees of novelty. New neurons in the hippocampus are especially responsive to learning associations between novel events and more cells survive if a novel and challenging task is learned. One might wonder whether new neurons would be rescued from death upon each new learning experience or whether there is an internal control system that limits the number of cells that are retained as a function of learning. In this experiment, it was hypothesized that learning a task that was similar in content to one already learned previously would not increase cell survival. We further hypothesized that in situations in which the cells are rescued hippocampal theta oscillations (3-12 Hz) would be involved and perhaps necessary for increasing cell survival. Both hypotheses were disproved. Adult male Sprague-Dawley rats were trained on two similar hippocampus-dependent tasks, trace and very-long delay eyeblink conditioning, while recording hippocampal local-field potentials. Cells that were generated after training on the first task were labeled with bromodeoxyuridine and quantified after training on both tasks had ceased. Spontaneous theta activity predicted performance on the first task and the conditioned stimulus induced a theta-band response early in learning the first task. As expected, performance on the first task correlated with performance on the second task. However, theta activity did not increase during training on the second task, even though more cells were present in animals that had learned. Therefore, as long as learning occurs, relatively small changes in the environment are sufficient to increase the number of surviving neurons in the adult hippocampus and they can do so in the absence of an increase in theta activity. In conclusion, these data argue against an upper limit on the number of neurons that can be rescued from death by learning.

  7. Learning to learn: theta oscillations predict new learning, which enhances related learning and neurogenesis.

    Directory of Open Access Journals (Sweden)

    Miriam S Nokia

    Full Text Available Animals in the natural world continuously encounter learning experiences of varying degrees of novelty. New neurons in the hippocampus are especially responsive to learning associations between novel events and more cells survive if a novel and challenging task is learned. One might wonder whether new neurons would be rescued from death upon each new learning experience or whether there is an internal control system that limits the number of cells that are retained as a function of learning. In this experiment, it was hypothesized that learning a task that was similar in content to one already learned previously would not increase cell survival. We further hypothesized that in situations in which the cells are rescued hippocampal theta oscillations (3-12 Hz would be involved and perhaps necessary for increasing cell survival. Both hypotheses were disproved. Adult male Sprague-Dawley rats were trained on two similar hippocampus-dependent tasks, trace and very-long delay eyeblink conditioning, while recording hippocampal local-field potentials. Cells that were generated after training on the first task were labeled with bromodeoxyuridine and quantified after training on both tasks had ceased. Spontaneous theta activity predicted performance on the first task and the conditioned stimulus induced a theta-band response early in learning the first task. As expected, performance on the first task correlated with performance on the second task. However, theta activity did not increase during training on the second task, even though more cells were present in animals that had learned. Therefore, as long as learning occurs, relatively small changes in the environment are sufficient to increase the number of surviving neurons in the adult hippocampus and they can do so in the absence of an increase in theta activity. In conclusion, these data argue against an upper limit on the number of neurons that can be rescued from death by learning.

  8. Learning to learn in the European Reference Framework for lifelong learning

    NARCIS (Netherlands)

    Pirrie, Anne; Thoutenhoofd, Ernst D.

    2013-01-01

    This article explores the construction of learning to learn that is implicit in the document Key Competences for Lifelong LearningEuropean Reference Framework and related education policy from the European Commission. The authors argue that the hallmark of learning to learn is the development of a

  9. Learning Science, Learning about Science, Doing Science: Different Goals Demand Different Learning Methods

    Science.gov (United States)

    Hodson, Derek

    2014-01-01

    This opinion piece paper urges teachers and teacher educators to draw careful distinctions among four basic learning goals: learning science, learning about science, doing science and learning to address socio-scientific issues. In elaboration, the author urges that careful attention is paid to the selection of teaching/learning methods that…

  10. Peer Apprenticeship Learning in Networked Learning Communities: The Diffusion of Epistemic Learning

    Science.gov (United States)

    Jamaludin, Azilawati; Shaari, Imran

    2016-01-01

    This article discusses peer apprenticeship learning (PAL) as situated within networked learning communities (NLCs). The context revolves around the diffusion of technologically-mediated learning in Singapore schools, where teachers begin to implement inquiry-oriented learning, consistent with 21st century learning, among students. As these schools…

  11. From Self-Regulation to Learning to Learn: Observations on the Construction of Self and Learning

    Science.gov (United States)

    Thoutenhoofd, Ernst D.; Pirrie, Anne

    2015-01-01

    The purpose of this article is to clarify the epistemological basis of self-regulated learning. The authors note that learning to learn, a term that has pervaded education policy at EU and national levels in recent years is often conflated with self-regulated learning. As a result, there has been insufficient attention paid to learning as social…

  12. Does peer learning or higher levels of e-learning improve learning abilities?

    DEFF Research Database (Denmark)

    Worm, Bjarne Skjødt; Jensen, Kenneth

    2013-01-01

    The fast development of e-learning and social forums demands us to update our understanding of e-learning and peer learning. We aimed to investigate if higher, pre-defined levels of e-learning or social interaction in web forums improved students' learning ability....

  13. The Relationship among Self-Regulated Learning, Procrastination, and Learning Behaviors in Blended Learning Environment

    Science.gov (United States)

    Yamada, Masanori; Goda, Yoshiko; Matsuda, Takeshi; Kato, Hiroshi; Miyagawa, Hiroyuki

    2015-01-01

    This research aims to investigate the relationship among the awareness of self-regulated learning (SRL), procrastination, and learning behaviors in blended learning environment. One hundred seventy nine freshmen participated in this research, conducted in the blended learning style class using learning management system. Data collection was…

  14. Influence of Learning Styles on Conceptual Learning of Physics

    Science.gov (United States)

    Marin-Suarez, Teresita; Alarcon, Hugo

    2010-10-01

    Several studies have shown the influence of scientific reasoning on the conceptual learning of students in courses developed with methodologies that promote active learning. Given that learning styles may also influence conceptual learning of physics, a correlacional study was conducted which used two different approaches of learning styles: the Honey-Alonso and Felder-Silverman models. This quantitative study was performed in two groups of students using modeling instruction in a college course of introductory mechanics. The Force and Motion Conceptual Evaluation test (FMCE) was used to assess conceptual learning. The results of this work suggest the dependence of the conceptual learning of physics on the learning styles.

  15. E-Learning 2.0: Learning Redefined

    OpenAIRE

    Kumar, Rupesh

    2009-01-01

    The conventional e-learning approach emphasizes a learning system more than a learning environment. While traditional e-learning systems continue to be significant, there is a new set of services emerging, embracing the philosophy of Web 2.0. Known as e-learning 2.0, it aims to create a personalized learning environment. E-learning 2.0 combines the use of discrete but complementary tools and web services to support the creation of ad-hoc learning communities. This paper discusses the influenc...

  16. Student Readiness in Learning Arabic Language based on Blended Learning

    OpenAIRE

    Norasyikin Osman; Mohd Isa Hamzah

    2017-01-01

    Learning with technology or e-learning has been taking place in all areas of education including in learning and teaching of Arabic language. Despite the widespread use of e-learning for Arabic language, in line with the current technological advancements, the role of face-to-face classroom interactions must not be neglected. Face-to-face learning and e-learning have their own strengths.  Hence, a combination of both elements in teaching and learning as afforded by blended learning may be an ...

  17. The learning environment and learning styles: a guide for mentors.

    Science.gov (United States)

    Vinales, James Jude

    The learning environment provides crucial exposure for the pre-registration nursing student. It is during this time that the student nurse develops his or her repertoire of skills, knowledge, attitudes and behaviour in order to meet competencies and gain registration with the Nursing and Midwifery Council. The role of the mentor is vital within the learning environment for aspiring nurses. The learning environment is a fundamental platform for student learning, with mentors key to identifying what is conducive to learning. This article will consider the learning environment and learning styles, and how these two essential elements guide the mentor in making sure they are conducive to learning.

  18. Teaching Problem Based Learning as Blended Learning

    DEFF Research Database (Denmark)

    Kolbæk, Ditte; Nortvig, Anne-Mette

    2018-01-01

    of departure in Dewey and a methodological point of departure in netnography, this study focuses on an online module at Aalborg University where teaching is based on PBL. With the research question ‘How can teachers design for PBL online,’ this study explores the teacher’s role in a six weeks’ blended learning......Problem-based and project organized learning (PBL) was originally developed for collaboration between physically present students, but political decisions at many universities require that collaboration, dialogues, and other PBL activities take place online as well. With a theoretical point...... program, and we present suggestions for designs for blended learning PBL based on case studies from two PBL courses...

  19. Distance Learning as 'Learning by Doing'

    Directory of Open Access Journals (Sweden)

    Mary E. Lee

    1999-01-01

    Full Text Available The papers in this Special Issue of Educational Technology and Society are extensions of presentations given at the 1999 Texas Distance Learning Association (TxDLA Annual Conference held April 5-8, 1999, in Waco, Texas, U.S.A. TxDLA is pleased that our collaboration with IFETS has afforded the opportunity to present these papers for publication in their official Journal. The eight extended papers presented here were selected as representative of the issues, topics, and challenges presented and discussed at the 1999 TxDLA Annual Conference. They are also representative examples of the "learning by doing" state of distance education and training in today's society. Overall, the papers depict a movement in distance education and training toward practices that reflect "learning organization" principles.

  20. Collaborations in Open Learning Environments

    NARCIS (Netherlands)

    Spoelstra, Howard

    2015-01-01

    This thesis researches automated services for professionals aiming at starting collaborative learning projects in open learning environments, such as MOOCs. It investigates the theoretical backgrounds of team formation for collaborative learning. Based on the outcomes, a model is developed

  1. Drugs + HIV, Learn the Link

    Medline Plus

    Full Text Available ... Education Projects » Learn the Link - Drugs and HIV Learn the Link - Drugs and HIV Email Facebook Twitter ... research findings and news updates. Read on to Learn the Link between drug use and HIV and ...

  2. Performing Implementing Heritage Learning Outcomes

    DEFF Research Database (Denmark)

    Fristrup, Tine

    2014-01-01

    , complex and challenging ways that learning is supported and ‘delivered’ through performance; engagement, empathy, participation, challenge, understanding and taking ownership are also means through which learning may be generated. Whether we define learning along lines of personal transformation...

  3. Learning Spanish the Fenix Way

    Science.gov (United States)

    Wholey, Jane

    1977-01-01

    The Instituto Fenix, a language learning school in Cuernavaca, Mexico, features oral language learning and a creative teaching technique to help language students to learn Spanish both effectively and quickly. (RK)

  4. Learning about primates' learning, language, and cognition

    Science.gov (United States)

    Rumbaugh, Duane M.

    1992-01-01

    Results are presented of many years of research on the methods of teaching primates the language and cognitive skills which were long considered to be unteachable to particular species of primates. It was found that chimpanzee subjects could not only learn a number of 'stock sentences' but to use them in variations and several combinations for the purpose of solving various problems. Apes placed in different rooms could be taught to communicate via computer, and collaborate with each other on doing specific tasks. Contrary to expectations, young rhesus monkeys proved to be able to learn as much as the chimpanzee species.

  5. Experiential Learning - Learning Combined with Action

    Directory of Open Access Journals (Sweden)

    Karmen Špilek Štumberger

    2000-12-01

    Full Text Available The author is introducing the experiential learning method which is, in her opinion, one of the best methods for educating adults. She is also emphasizing the importance of teachers' qualification for implementing the method: they have to experience it themselves first. A teacher's role is not classical any more; rather, he or she becomes a co-ordinator. The au thor is also describing some cases of applying the method. Her conclusion is the following: experiential learning has become so crucial because of dynamic changes in the society and a growing need for flexibility and transforming the existing knowledge.

  6. Welding. Student Learning Guide.

    Science.gov (United States)

    Palm Beach County Board of Public Instruction, West Palm Beach, FL.

    This student learning guide contains 30 modules for completing a course in welding. It is designed especially for use in secondary schools in Palm Beach County, Florida. Each module covers one task, and consists of a purpose, performance objective, enabling objectives, learning activities keyed to resources, information sheets, student self-check…

  7. Learning through Discussions

    Science.gov (United States)

    Ellis, Robert A.; Calvo, Rafael; Levy, David; Tan, Kelvin

    2004-01-01

    Students studying a third-year e-commerce subject experienced face-to-face and online discussions as an important part of their learning experience. The quality of the students' experiences of learning through those discussions is investigated in this study. This study uses qualitative approaches to investigate the variation in the students'…

  8. Sustainable Learning Organizations

    Science.gov (United States)

    Velazquez, Luis E.; Esquer, Javier; Munguia, Nora E.; Moure-Eraso, Rafael

    2011-01-01

    Purpose: The purpose of this paper is to debate how companies may better become a sustainable learning organization by offering the most used and insightful concepts of sustainability. Design/methodology/approach: Through literature review, learning organization and sustainability perspectives are explored and compared. Findings: Learning…

  9. Are Learning Organizations Pragmatic?

    Science.gov (United States)

    Cavaleri, Steven A.

    2008-01-01

    Purpose: The purpose of this paper is to evaluate the future prospects of the popular concept known as the learning organization; to trace the influence of philosophical pragmatism on the learning organization and to consider its potential impact on the future; and to emphasize how pragmatic theories have shaped the development of Deming's total…

  10. Rethinking lessons learned processes

    NARCIS (Netherlands)

    Buttler, T.; Lukosch, S.G.; Kolfschoten, G.L.; Verbraeck, A.

    2012-01-01

    Lessons learned are one way to retain experience and knowledge in project-based organizations, helping them to prevent reinventin,g the wheel or to repeat past mistakes. However, there are several challenges that make these lessonts learned processes a challenging endeavor. These include capturing

  11. SMashup Personal Learning Environments

    NARCIS (Netherlands)

    Chatti, Mohamed; Jarke, Matthias; Wang, Zhaohui; Specht, Marcus

    2009-01-01

    Chatti, M. A., Jarke, M., Wang, Z., & Specht, M. (2009). SMashup Personal Learning Environments. In F. Wild, M. Kalz, M. Palmér & D. Müller (Eds.), Proceedings of 2nd Workshop Mash-Up Personal Learning Environments (MUPPLE'09). Workshop in conjunction with 4th European Conference on Technology

  12. Learning multimodal latent attributes.

    Science.gov (United States)

    Fu, Yanwei; Hospedales, Timothy M; Xiang, Tao; Gong, Shaogang

    2014-02-01

    The rapid development of social media sharing has created a huge demand for automatic media classification and annotation techniques. Attribute learning has emerged as a promising paradigm for bridging the semantic gap and addressing data sparsity via transferring attribute knowledge in object recognition and relatively simple action classification. In this paper, we address the task of attribute learning for understanding multimedia data with sparse and incomplete labels. In particular, we focus on videos of social group activities, which are particularly challenging and topical examples of this task because of their multimodal content and complex and unstructured nature relative to the density of annotations. To solve this problem, we 1) introduce a concept of semilatent attribute space, expressing user-defined and latent attributes in a unified framework, and 2) propose a novel scalable probabilistic topic model for learning multimodal semilatent attributes, which dramatically reduces requirements for an exhaustive accurate attribute ontology and expensive annotation effort. We show that our framework is able to exploit latent attributes to outperform contemporary approaches for addressing a variety of realistic multimedia sparse data learning tasks including: multitask learning, learning with label noise, N-shot transfer learning, and importantly zero-shot learning.

  13. Towards effective learning strategies

    NARCIS (Netherlands)

    Bergstra, Anouk Simone

    2015-01-01

    To become self-regulative in learning, students should be able to deploy various learning strategies in a flexible way. For this, they require specific knowledge and skills, referred to as metacognition. Metacognition is a complex concept that is difficult for teachers to teach to their students.

  14. Participation in adult learning

    DEFF Research Database (Denmark)

    Desjardins, Richard

    2010-01-01

    This entry presents an internationally comparative overview of adult learning patterns. Emphasis is placed on who is participating in adult learning and the observed unequal chances to participate. The entry covers three overarching questions that are central to participation research: a) What...

  15. scikit-learn cookbook

    CERN Document Server

    Hauck, Trent

    2014-01-01

    If you're a data scientist already familiar with Python but not Scikit-Learn, or are familiar with other programming languages like R and want to take the plunge with the gold standard of Python machine learning libraries, then this is the book for you.

  16. Towards Strategic Language Learning

    NARCIS (Netherlands)

    Oostdam, R.; Rijlaarsdam, Gert

    1995-01-01

    Towards Strategic Language Learning is the result of extensive research in the relationship between mother tongue education and foreign language learning. As language skills that are taught during native language lessons are applied in foreign language performance as well, it is vital that curricula

  17. Mobile Informal Learning

    NARCIS (Netherlands)

    Börner, Dirk; Glahn, Christian; Specht, Marcus

    2009-01-01

    Börner, D., Glahn, C., & Specht, M. (2009). Mobile Informal Learning. Presentation for the Education in the Wild: contextual and location-based mobile learning in action workshop at the STELLAR Alpine Rendez-Vous 2009. November, 30-December, 3, 2009, Garmisch-Partenkirchen, Germany.

  18. Human Learning and Memory

    Science.gov (United States)

    Lieberman, David A.

    2012-01-01

    This innovative textbook is the first to integrate learning and memory, behaviour, and cognition. It focuses on fascinating human research in both memory and learning (while also bringing in important animal studies) and brings the reader up to date with the latest developments in the subject. Students are encouraged to think critically: key…

  19. The Sign Learning Theory

    African Journals Online (AJOL)

    KING OF DAWN

    The Sign Learning Theory. Although a blend of both Gestalt psychology and behaviourism, the sign learning theory is actually a drift from the behaviourist perspective with an attempt to explain certain phenomena commonly seen in behaviour which could not be satisfactorily accounted for by stimulus-response paradigms.

  20. The Reception Learning Paradigm.

    Science.gov (United States)

    Novak, Joseph D.

    1979-01-01

    Presented is a paradigm for science education research. The paradigm advances the reception learning theory, where regularities to be learned are presented explicitly to the learner. A tool for the study of knowledge production in science education, the Gowin "V," is presented. (RE)

  1. Designing Creative Learning Environments

    Directory of Open Access Journals (Sweden)

    Thomas Cochrane

    2015-05-01

    Full Text Available Designing creative learning environments involves not only facilitating student creativity, but also modeling creative pedagogical practice. In this paper we explore the implementation of a framework for designing creative learning environments using mobile social media as a catalyst for redefining both lecturer pedagogical practice, as well as redesigning the curriculum around student generated m-portfolios.

  2. Design for Learning.

    Science.gov (United States)

    Martin, Frank Edgerton

    2003-01-01

    Describes how Richard Macias, a landscape architect and the university planner at San Jose State University, has learned to push the boundaries of how landscape architects coordinate the many disciplines involved in managing a modern campus that must constantly adapt to change. Offers lessons learned over the course of a career spanning the…

  3. Intercultural Learning across Contexts

    Science.gov (United States)

    Vasbø, Kristin Beate

    2013-01-01

    International youth work in Europe (i.e. non-formal learning) demands a renewal of the prominent intercultural theory and framework in the youth field in order to cope with contemporary questions concerning pluralism and global challenges. This article provides a new theoretical framework for intercultural learning that departs from a complex,…

  4. Learning in cobweb experiments

    NARCIS (Netherlands)

    Hommes, C.H.; Sonnemans, J.H.; Tuinstra, J.; van de Velden, H.

    2007-01-01

    Different theories of expectation formation and learning usually yield different outcomes for realized market prices in dynamic models. The purpose of this paper is to investigate expectation formation and learning in a controlled experimental environment. Subjects are asked to predict the next

  5. "Inventive" Learning Stations

    Science.gov (United States)

    Jarrett, Olga

    2010-01-01

    Learning stations can be used for myriad purposes--to teach concepts, integrate subject matter, build interest, and allow for inquiry--the possibilities are limited only by the imagination of the teacher and the supplies available. In this article, the author shares suggestions and a checklist for setting up successful learning stations. In…

  6. Learning and Cognition

    Science.gov (United States)

    Gr ver Aukrust, Vibeke, Ed.

    2011-01-01

    This collection of 58 articles from the recently-published third edition of the International Encyclopedia of Education focuses on learning, memory, attention, problem solving, concept formation, and language. Learning and cognition is the foundation of cognitive psychology and encompasses many topics including attention, memory, categorization,…

  7. Action Learning and Leadership.

    Science.gov (United States)

    Marquardt, Michael J.

    2000-01-01

    Today's leaders perform the following roles: systems thinker, change agent, innovator, servant, polychronic coordinator, teacher-mentor, and visionary. The elements of action learning (real problems, teams, reflective inquiry, commitment to action, focus on learning) contribute to the development of these critical skills. (Author/SK)

  8. Leading Professional Learning

    Science.gov (United States)

    Fullan, Michael

    2006-01-01

    If the goal is to fundamentally change the culture inside schools, people need to move beyond the superficiality of professional learning communities and focus on a system of learners. Professional learning communities are in fact about establishing lasting new collaborative cultures. Collaborative cultures are ones that focus on building the…

  9. Learning about System Renewal

    Science.gov (United States)

    Levin, Ben; Fullan, Michael

    2008-01-01

    Our focus in this article is on the lessons learned about effective change from international experience with large-scale reform over the last 20 years. The central lesson now evident is that sustained improvement in student outcomes requires a sustained effort to change teaching and learning practices in thousands and thousands of classrooms, and…

  10. Mobile Learning Platform

    DEFF Research Database (Denmark)

    Annan, Nana Kofi; Ofori-Dwumfou, George; Falch, Morten

    2012-01-01

    This paper presents a study on a one year m-learning pilot project at Central University College in Ghana. This was done through a user trial, where the m-learning tool AD-CONNECT is introduced in 44 courses with a total of 500 students and 22 lecturers at the College. The paper reports on the fi...

  11. Pervasive e-learning

    DEFF Research Database (Denmark)

    Helms, Niels Henrik; Hundebøl, Jesper

    2009-01-01

    The establishment of pervasive learning environments is based on the successful combination and re-configuration of inter-connected sets of activities and contexts. This chapter presents a definition of Pervasive (e) Learning Environments and discusses the pedagogical potentials and challenges in...

  12. Robots Learn Writing

    Directory of Open Access Journals (Sweden)

    Huan Tan

    2012-01-01

    Full Text Available This paper proposes a general method for robots to learn motions and corresponding semantic knowledge simultaneously. A modified ISOMAP algorithm is used to convert the sampled 6D vectors of joint angles into 2D trajectories, and the required movements for writing numbers are learned from this modified ISOMAP-based model. Using this algorithm, the knowledge models are established. Learned motion and knowledge models are stored in a 2D latent space. Gaussian Process (GP method is used to model and represent these models. Practical experiments are carried out on a humanoid robot, named ISAC, to learn the semantic representations of numbers and the movements of writing numbers through imitation and to verify the effectiveness of this framework. This framework is applied into training a humanoid robot, named ISAC. At the learning stage, ISAC not only learns the dynamics of the movement required to write the numbers, but also learns the semantic meaning of the numbers which are related to the writing movements from the same data set. Given speech commands, ISAC recognizes the words and generated corresponding motion trajectories to write the numbers. This imitation learning method is implemented on a cognitive architecture to provide robust cognitive information processing.

  13. Designing Interactive Learning Environments.

    Science.gov (United States)

    Akpinar, Y.; Hartley, J. R.

    1996-01-01

    Describes the design principles of computer-assisted learning (CAL) environments in which the software is interactive yet adaptable to different styles of learning and teaching, illustrated with a mathematics application. Following implementation, initial evaluation data taken from students showed marked performance improvements, and indicated how…

  14. Learning to Be

    DEFF Research Database (Denmark)

    Hansen, Finn Thorbjørn

    2002-01-01

    På baggrund af en nylig OECD-report om kompetencer for Lifelong Learning samt Eus memorandum for Lifelong Learning peges der på behovet for en mere filosofisk og eksistentiel tilgang til dette begreb. Med henvisning til bl.a. filosofihistorikeren Pierre Hadot og eksistensfilosoffen Gabriel Marcel...

  15. Learning from Tokyo urbanism

    DEFF Research Database (Denmark)

    Greve, Anni

    2013-01-01

    This article takes up the challenge of demonstrating that ‘we’ can learn from Tokyo about the intrinsic importance of in-between realms to a cosmopolitan culture: the urban sanctuaries. It has four sections. The first section encircles a location from where to learn from Tokyo as well as an angle...

  16. Learning that Opens Doors

    Science.gov (United States)

    Hayes, John

    2011-01-01

    To maximise people's chances to reach their potential and so build a more cohesive and just society, one must acknowledge that learning is not only for the young; one must know that it's a lifelong activity. And one must also value and support the role that informal learning plays in transferring skills and knowledge. The author launched a review…

  17. Learning Curve? Which One?

    Directory of Open Access Journals (Sweden)

    Paulo Prochno

    2004-07-01

    Full Text Available Learning curves have been studied for a long time. These studies provided strong support to the hypothesis that, as organizations produce more of a product, unit costs of production decrease at a decreasing rate (see Argote, 1999 for a comprehensive review of learning curve studies. But the organizational mechanisms that lead to these results are still underexplored. We know some drivers of learning curves (ADLER; CLARK, 1991; LAPRE et al., 2000, but we still lack a more detailed view of the organizational processes behind those curves. Through an ethnographic study, I bring a comprehensive account of the first year of operations of a new automotive plant, describing what was taking place on in the assembly area during the most relevant shifts of the learning curve. The emphasis is then on how learning occurs in that setting. My analysis suggests that the overall learning curve is in fact the result of an integration process that puts together several individual ongoing learning curves in different areas throughout the organization. In the end, I propose a model to understand the evolution of these learning processes and their supporting organizational mechanisms.

  18. Allergy, living and learning

    DEFF Research Database (Denmark)

    Chivato, T; Valovirta, E; Dahl, R

    2012-01-01

    Allergy Living and Learning (ALL) is a European initiative designed to increase knowledge and understanding of people living with allergies in order to improve respiratory allergy care.......Allergy Living and Learning (ALL) is a European initiative designed to increase knowledge and understanding of people living with allergies in order to improve respiratory allergy care....

  19. Integrated Learning Management Systems

    Science.gov (United States)

    Clark, Sharon; Cossarin, Mary; Doxsee, Harry; Schwartz, Linda

    2004-01-01

    Four integrated learning management packages were reviewed: "CentraOne", "IntraLearn", "Lyceum", and "Silicon Chalk". These products provide different combinations of synchronous and asynchronous tools. The current report examines the products in relation to their specific value for distance educators and students.

  20. The Reinforcement Learning Competitions

    NARCIS (Netherlands)

    Whiteson, S.; Tanner, B.; White, A.

    2010-01-01

    This article reports on the reinforcement learning competitions, which have been held annually since 2006. In these events, researchers from around the world developed reinforcement learning agents to compete in domains of various complexity and difficulty. We focus on the 2008 competition, which

  1. Hypnosis and Language Learning.

    Science.gov (United States)

    Hammerman, Myrna Lynn

    A thorough investiqation is attempted of efforts to apply hypnosis and suggestive learning techniques to education in general and specifically to second language learning. Hypnosis is discussed in terms of its dangers, its definition, and its application. Included in this discussion is a comparison of auto- and hetero-hypnosis, an overview of the…

  2. Significant Learning, Significant Advising

    Science.gov (United States)

    Kelley, Bruce

    2008-01-01

    The acknowledgment that advisees are learners and advisors are teachers may be the most powerful philosophical change in advising in 30 years. This article builds generally on the growing momentum to view academic advising as an extension of student learning, and specifically as an expansion of "Advising as Learning" in which Hemwall and Trachte…

  3. Reinforcement and learning

    NARCIS (Netherlands)

    Servedio, M.R.; Sæther, S.A.; Sætre, G.-P.

    2009-01-01

    Evidence has been accumulating to support the process of reinforcement as a potential mechanism in speciation. In many species, mate choice decisions are influenced by cultural factors, including learned mating preferences (sexual imprinting) or learned mate attraction signals (e.g., bird song). It

  4. Learning-Walk Continuum

    Science.gov (United States)

    Finch, Peter Dallas

    2010-01-01

    The continuum of learning walks can be viewed in stages with various dimensions including frequency, participants, purpose and the presence of an instructional framework within which the instructional practice is viewed. Steps in the continuum progress as the learning walks are conducted more frequently. One way to ensure this is accomplished is…

  5. Machine learning with R

    CERN Document Server

    Lantz, Brett

    2015-01-01

    Perhaps you already know a bit about machine learning but have never used R, or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.

  6. Metaphysics and Learning

    Science.gov (United States)

    Verran, Helen

    2007-01-01

    Is it possible to learn and simultaneously articulate the metaphysical basis of that learning? In my contribution to the forum I tell of how I came to recognise that bilingual Yoruba children could articulate the contrasting metaphysical framings of Yoruba and English numbering. The story introduces an arena I call "ontics" that recognises the…

  7. Learning by design

    NARCIS (Netherlands)

    de Jong, Anthonius J.M.; Wild, Fridolin; Lefrere, Paul; Scott, Peter

    2013-01-01

    One way of engaging students in science-based learning uses contextual collaborative assignments in which students create solutions for socio-technical problems together with other students. The Science Created by You (SCY) project delivers learning environments (‘missions’) that offer students

  8. Phonological Concept Learning

    Science.gov (United States)

    Moreton, Elliott; Pater, Joe; Pertsova, Katya

    2017-01-01

    Linguistic and non-linguistic pattern learning have been studied separately, but we argue for a comparative approach. Analogous inductive problems arise in phonological and visual pattern learning. Evidence from three experiments shows that human learners can solve them in analogous ways, and that human performance in both cases can be captured by…

  9. Enterprise E-Learning.

    Science.gov (United States)

    Gold, Martha

    2003-01-01

    Part 1 of a five-part series of case studies on how some large organizations are using and measuring enterprise-wide electronic learning profiles Braxton's efforts to move from 95% classroom-based training in 1999 to a blend of live and e-learning, resulting in substantial cost savings. (JOW)

  10. Problem-based learning

    NARCIS (Netherlands)

    Loyens, Sofie; Kirschner, Paul A.; Paas, Fred

    2010-01-01

    Loyens, S. M. M., Kirschner, P. A., & Paas, F. (2011). Problem-based learning. In S. Graham (Editor-in-Chief), A. Bus, S. Major, & L. Swanson (Associate Editors), APA educational psychology handbook: Vol. 3. Application to learning and teaching (pp. 403-425). Washington, DC: American Psychological

  11. Pervasive e-learning

    DEFF Research Database (Denmark)

    Helms, Niels Henrik; Hundebøl, Jesper

    2009-01-01

    The establishment of pervasive learning environments is based on the successful combination and re-configuration of inter-connected sets of activities and contexts. This chapter presents a definition of Pervasive (e) Learning Environments and discusses the pedagogical potentials and challenges...

  12. Work based learning

    OpenAIRE

    Adams, David M.

    2014-01-01

    Entry submitted for publication in The SAGE Encyclopedia of Action Research. Provides a full definition of Work based learning, including origins, historical context, significant characteristics, the relationship between work based learning and action research and their shared foundations, and future prospects.

  13. What Are Learning Disabilities?

    Science.gov (United States)

    ... the lines. 9 Apraxia of speech. Sometimes called verbal apraxia, this disorder involves problems with speaking. People with ... http://www.nidcd.nih.gov/health/voice/Pages/apraxia.aspx [top] Learning ... (n.d.). Non-verbal learning disorders . Retrieved June 15, 2012, from http:// ...

  14. Preschool Children Can Learn to Transfer: Learning to Learn and Learning from Example.

    Science.gov (United States)

    Brown, Ann L.; Kane, Mary Jo

    1988-01-01

    Seven experiments with a total of 423 three-five year olds assessed preschool children's ability to learn and transfer across problems that share a common underlying structure but differ in surface manifestations. Results are discussed in terms of explanation- or analysis-based models of both machine and human learning. (TJH)

  15. Learning Space Service Design

    Science.gov (United States)

    Felix, Elliot

    2011-01-01

    Much progress has been made in creating informal learning spaces that incorporate technology and flexibly support a variety of activities. This progress has been principally in designing the right combination of furniture, technology, and space. However, colleges and universities do not design services within learning spaces with nearly the same…

  16. Fostering teachers' team learning

    NARCIS (Netherlands)

    Bouwmans, Machiel; Runhaar, Piety; Wesselink, Renate; Mulder, Martin

    2017-01-01

    The implementation of educational innovations by teachers seems to benefit from a team approach and team learning. The study's goal is to examine to what extent transformational leadership is associated with team learning, and to investigate the mediating roles of participative decision-making,

  17. Juggling Balls and Learning

    Science.gov (United States)

    Warren, Andrew

    2013-01-01

    How do you change a teacher’s mentality from seeing children as "just vases to be filled", to seeing them as "fires to be lit"? It seemed to the author that more consideration was being given to the learning process than to the learning emotions, that the feelings of the learner were being largely ignored. This seemed to be a serious omission, so…

  18. Learning Systems Design.

    Science.gov (United States)

    Nelson, Harold G.

    1994-01-01

    Discusses the need to learn how to design learning systems involving the synthesis of systems thinking and design actions. Design intelligence is considered, based on theories of multiple intelligence; new models of the information age that require systems design are discussed; and the roles of symbolic analysts and symbolic synthesists are…

  19. Towards Smart City Learning

    DEFF Research Database (Denmark)

    Rehm, Matthias; Stan, Catalin; Wøldike, Niels Peter

    2015-01-01

    , the concept of smart city learning is exploited to situate learning about geometric shapes in concrete buildings and thus make them more accessible for younger children. In close collaboration with a local school a game for 3rd graders was developed and tested on a field trip and in class. A mixed measures...

  20. Machine Learning in Medicine.

    Science.gov (United States)

    Deo, Rahul C

    2015-11-17

    Spurred by advances in processing power, memory, storage, and an unprecedented wealth of data, computers are being asked to tackle increasingly complex learning tasks, often with astonishing success. Computers have now mastered a popular variant of poker, learned the laws of physics from experimental data, and become experts in video games - tasks that would have been deemed impossible not too long ago. In parallel, the number of companies centered on applying complex data analysis to varying industries has exploded, and it is thus unsurprising that some analytic companies are turning attention to problems in health care. The purpose of this review is to explore what problems in medicine might benefit from such learning approaches and use examples from the literature to introduce basic concepts in machine learning. It is important to note that seemingly large enough medical data sets and adequate learning algorithms have been available for many decades, and yet, although there are thousands of papers applying machine learning algorithms to medical data, very few have contributed meaningfully to clinical care. This lack of impact stands in stark contrast to the enormous relevance of machine learning to many other industries. Thus, part of my effort will be to identify what obstacles there may be to changing the practice of medicine through statistical learning approaches, and discuss how these might be overcome. © 2015 American Heart Association, Inc.