Turner, Kagan; Agogino, Adrian K.; Wolpert, David H.; Clancy, Daniel (Technical Monitor)
In this paper we focus on the problem of designing a collective of autonomous agents that individually learn sequences of actions such that the resultant sequence of joint actions achieves a predetermined global objective. We are particularly interested in instances of this problem where centralized control is either impossible or impractical. For single agent systems in similar domains, machine learning methods (e.g., reinforcement learners) have been successfully used. However, applying such solutions directly to multi-agent systems often proves problematic, as agents may work at cross-purposes, or have difficulty in evaluating their contribution to achievement of the global objective, or both. Accordingly, the crucial design step in multiagent systems centers on determining the private objectives of each agent so that as the agents strive for those objectives, the system reaches a good global solution. In this work we consider a version of this problem involving multiple autonomous agents in a grid world. We use concepts from collective intelligence to design goals for the agents that are 'aligned' with the global goal, and are 'learnable' in that agents can readily see how their behavior affects their utility. We show that reinforcement learning agents using those goals outperform both 'natural' extensions of single agent algorithms and global reinforcement, learning solutions based on 'team games'.
Collins, Anne L.; Greenfield, Venuz Y.; Bye, Jeffrey K.; Linker, Kay E.; Wang, Alice S.; Wassum, Kate M.
Prolonged mesolimbic dopamine concentration changes have been detected during spatial navigation, but little is known about the conditions that engender this signaling profile or how it develops with learning. To address this, we monitored dopamine concentration changes in the nucleus accumbens core of rats throughout acquisition and performance of an instrumental action sequence task. Prolonged dopamine concentration changes were detected that ramped up as rats executed each action sequence and declined after earned reward collection. With learning, dopamine concentration began to rise increasingly earlier in the execution of the sequence and ultimately backpropagated away from stereotyped sequence actions, becoming only transiently elevated by the most distal and unexpected reward predictor. Action sequence-related dopamine signaling was reactivated in well-trained rats if they became disengaged in the task and in response to an unexpected change in the value, but not identity of the earned reward. Throughout training and test, dopamine signaling correlated with sequence performance. These results suggest that action sequences can engender a prolonged mode of dopamine signaling in the nucleus accumbens core and that such signaling relates to elements of the motivation underlying sequence execution and is dynamic with learning, overtraining and violations in reward expectation. PMID:26869075
Kinnebrew, John S.; Biswas, Gautam
Our learning-by-teaching environment, Betty's Brain, captures a wealth of data on students' learning interactions as they teach a virtual agent. This paper extends an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs sequence mining techniques to…
Full Text Available An important characteristic of human language is compositionality. We can efficiently express a wide variety of real-world situations, events, and behaviors by compositionally constructing the meaning of a complex expression from a finite number of elements. Previous studies have analyzed how machine-learning models, particularly neural networks, can learn from experience to represent compositional relationships between language and robot actions with the aim of understanding the symbol grounding structure and achieving intelligent communicative agents. Such studies have mainly dealt with the words (nouns, adjectives, and verbs that directly refer to real-world matters. In addition to these words, the current study deals with logic words, such as “not,” “and,” and “or” simultaneously. These words are not directly referring to the real world, but are logical operators that contribute to the construction of meaning in sentences. In human–robot communication, these words may be used often. The current study builds a recurrent neural network model with long short-term memory units and trains it to learn to translate sentences including logic words into robot actions. We investigate what kind of compositional representations, which mediate sentences and robot actions, emerge as the network's internal states via the learning process. Analysis after learning shows that referential words are merged with visual information and the robot's own current state, and the logical words are represented by the model in accordance with their functions as logical operators. Words such as “true,” “false,” and “not” work as non-linear transformations to encode orthogonal phrases into the same area in a memory cell state space. The word “and,” which required a robot to lift up both its hands, worked as if it was a universal quantifier. The word “or,” which required action generation that looked apparently random, was represented as an
Kemény, Ferenc; Meier, Beat
While sequence learning research models complex phenomena, previous studies have mostly focused on unimodal sequences. The goal of the current experiment is to put implicit sequence learning into a multimodal context: to test whether it can operate across different modalities. We used the Task Sequence Learning paradigm to test whether sequence learning varies across modalities, and whether participants are able to learn multimodal sequences. Our results show that implicit sequence learning is very similar regardless of the source modality. However, the presence of correlated task and response sequences was required for learning to take place. The experiment provides new evidence for implicit sequence learning of abstract conceptual representations. In general, the results suggest that correlated sequences are necessary for implicit sequence learning to occur. Moreover, they show that elements from different modalities can be automatically integrated into one unitary multimodal sequence. Copyright © 2015 Elsevier B.V. All rights reserved.
Shah, Ashvin; Gurney, Kevin N.
Animals are able to discover the minimal number of actions that achieves an outcome (the minimal action sequence). In most accounts of this, actions are associated with a measure of behavior that is higher for actions that lead to the outcome with a shorter action sequence, and learning mechanisms find the actions associated with the highest measure. In this sense, previous accounts focus on more than the simple binary signal of “was the outcome achieved?”; they focus on “how well was the outcome achieved?” However, such mechanisms may not govern all types of behavioral development. In particular, in the process of action discovery (Redgrave and Gurney, 2006), actions are reinforced if they simply lead to a salient outcome because biological reinforcement signals occur too quickly to evaluate the consequences of an action beyond an indication of the outcome's occurrence. Thus, action discovery mechanisms focus on the simple evaluation of “was the outcome achieved?” and not “how well was the outcome achieved?” Notwithstanding this impoverishment of information, can the process of action discovery find the minimal action sequence? We address this question by implementing computational mechanisms, referred to in this paper as no-cost learning rules, in which each action that leads to the outcome is associated with the same measure of behavior. No-cost rules focus on “was the outcome achieved?” and are consistent with action discovery. No-cost rules discover the minimal action sequence in simulated tasks and execute it for a substantial amount of time. Extensive training, however, results in extraneous actions, suggesting that a separate process (which has been proposed in action discovery) must attenuate learning if no-cost rules participate in behavioral development. We describe how no-cost rules develop behavior, what happens when attenuation is disrupted, and relate the new mechanisms to wider computational and biological context. PMID:25506326
Corley, Aileen; Thorne, Ann
Action learning is based on the premise that action and learning are inextricably entwined and it is this potential, to enable action, which has contributed to the growth of action learning within education and management development programmes. However has this growth in action learning lead to an evolution or a dilution of Revan's classical…
Marquardt, Michael J.
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…
Gnadt, William; Grossberg, Stephen
How do reactive and planned behaviors interact in real time? How are sequences of such behaviors released at appropriate times during autonomous navigation to realize valued goals? Controllers for both animals and mobile robots, or animats, need reactive mechanisms for exploration, and learned plans to reach goal objects once an environment becomes familiar. The SOVEREIGN (Self-Organizing, Vision, Expectation, Recognition, Emotion, Intelligent, Goal-oriented Navigation) animat model embodies these capabilities, and is tested in a 3D virtual reality environment. SOVEREIGN includes several interacting subsystems which model complementary properties of cortical What and Where processing streams and which clarify similarities between mechanisms for navigation and arm movement control. As the animat explores an environment, visual inputs are processed by networks that are sensitive to visual form and motion in the What and Where streams, respectively. Position-invariant and size-invariant recognition categories are learned by real-time incremental learning in the What stream. Estimates of target position relative to the animat are computed in the Where stream, and can activate approach movements toward the target. Motion cues from animat locomotion can elicit head-orienting movements to bring a new target into view. Approach and orienting movements are alternately performed during animat navigation. Cumulative estimates of each movement are derived from interacting proprioceptive and visual cues. Movement sequences are stored within a motor working memory. Sequences of visual categories are stored in a sensory working memory. These working memories trigger learning of sensory and motor sequence categories, or plans, which together control planned movements. Predictively effective chunk combinations are selectively enhanced via reinforcement learning when the animat is rewarded. Selected planning chunks effect a gradual transition from variable reactive exploratory
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...
Brink, Tove; Madsen, Svend Ole
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....
Rosman, Benjamin S
Full Text Available The computational complexity of learning in sequential decision problems grows exponentially with the number of actions available to the agent at each state. We present a method for accelerating this process by learning action priors that express...
Jung, Minju; Hwang, Jungsik; Tani, Jun
It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.
Nielsen, Kurt Aagaard; Svensson, Lennart
The authors suggest routines and educational structures that could improve a succesfull learning and education of action research.......The authors suggest routines and educational structures that could improve a succesfull learning and education of action research....
Annemieke van den Berg
Full Text Available Context: This critical reflection is about the positive effects for educational and research settings of participation in a two-day programme entitled ‘Using participatory action research and appreciative inquiry to research healthcare practice’. Aims: To reflect on the journey of positive developments in research and education that started with participation in this programme. Using Caring Conversations (Dewar, 2011 as a reflective framework of questions, this article discusses the journey in order to encourage others to consider the approach of appreciative inquiry to bring to life the concept of co-creation in research and education. Conclusions and implications for practice: Participation in this programme has led to the implementation of a variety of actions in educational and research settings. Central to all these actions is an appreciative approach to co-creation as a counterpart to today’s prevailing problem-based viewpoint. A possible factor behind these developments was the power of vulnerability experienced during the programme, a shared process of transformational learning. Implications for practice: This critical reflection: Provides an invitation to shift from a problem-based focus to a positive revolution Provides an appreciative reflective story about the power of vulnerability as an inspiration for others to move out of their comfort zone and seek to discover their own exceptionality Supports a shift from a facilitator-led to a co-creation approach in doing research and teaching with older adults
Monroy, Claire; Meyer, Marlene; Gerson, Sarah; Hunnius, Sabine
Sensitivity to the regularities and structure contained within sequential, goal-directed actions is an important building block for generating expectations about the actions we observe. Until now, research on statistical learning for actions has solely focused on individual action sequences, but many actions in daily life involve multiple actors in various interaction contexts. The current study is the first to investigate the role of statistical learning in tracking regularities between actions performed by different actors, and whether the social context characterizing their interaction influences learning. That is, are observers more likely to track regularities across actors if they are perceived as acting jointly as opposed to in parallel? We tested adults and toddlers to explore whether social context guides statistical learning and-if so-whether it does so from early in development. In a between-subjects eye-tracking experiment, participants were primed with a social context cue between two actors who either shared a goal of playing together ('Joint' condition) or stated the intention to act alone ('Parallel' condition). In subsequent videos, the actors performed sequential actions in which, for certain action pairs, the first actor's action reliably predicted the second actor's action. We analyzed predictive eye movements to upcoming actions as a measure of learning, and found that both adults and toddlers learned the statistical regularities across actors when their actions caused an effect. Further, adults with high statistical learning performance were sensitive to social context: those who observed actors with a shared goal were more likely to correctly predict upcoming actions. In contrast, there was no effect of social context in the toddler group, regardless of learning performance. These findings shed light on how adults and toddlers perceive statistical regularities across actors depending on the nature of the observed social situation and the
Imagine an ordinary action sequence, such as making a peanut butter sandwich. You first reach for two bread slices, grasp your peanut butter jar, open the jar, reach for a knife, insert it into your jar… and so forth. Even the simplest actions contain a complex stream of information from movements,
Clarke, Jean; Thorpe, Richard; Anderson, Lisa; Gold, Jeff
Purpose: The purpose of this paper is to argue that action learning (AL) may provide a means of successfully developing small to medium-sized enterprises (SMEs). Design/methodology/approach: The literature around SME learning suggests a number of processes are important for SME learning which similarity, it is argued, are encompassed in AL. AL may…
Full Text Available Robot learning from demonstration is a method which enables robots to learn in a similar way as humans. In this paper, a framework that enables robots to learn from multiple human demonstrations via kinesthetic teaching is presented. The subject of learning is a high-level sequence of actions, as well as the low-level trajectories necessary to be followed by the robot to perform the object manipulation task. The multiple human demonstrations are recorded and only the most similar demonstrations are selected for robot learning. The high-level learning module identifies the sequence of actions of the demonstrated task. Using Dynamic Time Warping (DTW and Gaussian Mixture Model (GMM, the model of demonstrated trajectories is learned. The learned trajectory is generated by Gaussian mixture regression (GMR from the learned Gaussian mixture model. In online working phase, the sequence of actions is identified and experimental results show that the robot performs the learned task successfully.
If you're new to ActionScript 3.0, or want to enhance your skill set, this bestselling book is the ideal guide. Designers, developers, and programmers alike will find Learning ActionScript 3.0 invaluable for navigating ActionScript 3.0's learning curve. You'll learn the language by getting a clear look at essential topics such as logic, event handling, displaying content, classes, and much more. Updated for Flash Professional CS5, this revised and expanded edition delivers hands-on exercises and full-color code samples to help you increase your abilities as you progress through the book. Top
Baby, Sanmohan; Krüger, Volker; Kragic, Danica
and scale, the use of the object can provide a strong invariant for the detection of motion primitives. In this paper we propose an unsupervised learning approach for action primitives that makes use of the human movements as well as the object state changes. We group actions according to the changes......Action representation is a key issue in imitation learning for humanoids. With the recent finding of mirror neurons there has been a growing interest in expressing actions as a combination meaningful subparts called primitives. Primitives could be thought of as an alphabet for the human actions....... In this paper we observe that human actions and objects can be seen as being intertwined: we can interpret actions from the way the body parts are moving, but as well from how their effect on the involved object. While human movements can look vastly different even under minor changes in location, orientation...
Boydell, Tom; Blantern, Chris
In this paper we propose that all knowledge is made through social processes and is political (of the people involved). If one invests in a relational or historical ontology (a philosophical choice) there are implications for the way action learning is practiced. We illuminate some of these "relational practices". We purport that action learning…
Press, Clare; Heyes, Cecilia; Kilner, James M
Despite nearly two decades of research on mirror neurons, there is still much debate about what they do. The most enduring hypothesis is that they enable 'action understanding'. However, recent critical reviews have failed to find compelling evidence in favour of this view. Instead, these authors argue that mirror neurons are produced by associative learning and therefore that they cannot contribute to action understanding. The present opinion piece suggests that this argument is flawed. We argue that mirror neurons may both develop through associative learning and contribute to inferences about the actions of others.
Monroy, Claire D; Gerson, Sarah A; Domínguez-Martínez, Estefanía; Kaduk, Katharina; Hunnius, Sabine; Reid, Vincent
Infants are sensitive to structure and patterns within continuous streams of sensory input. This sensitivity relies on statistical learning, the ability to detect predictable regularities in spatial and temporal sequences. Recent evidence has shown that infants can detect statistical regularities in action sequences they observe, but little is known about the neural process that give rise to this ability. In the current experiment, we combined electroencephalography (EEG) with eye-tracking to identify electrophysiological markers that indicate whether 8-11-month-old infants detect violations to learned regularities in action sequences, and to relate these markers to behavioral measures of anticipation during learning. In a learning phase, infants observed an actor performing a sequence featuring two deterministic pairs embedded within an otherwise random sequence. Thus, the first action of each pair was predictive of what would occur next. One of the pairs caused an action-effect, whereas the second did not. In a subsequent test phase, infants observed another sequence that included deviant pairs, violating the previously observed action pairs. Event-related potential (ERP) responses were analyzed and compared between the deviant and the original action pairs. Findings reveal that infants demonstrated a greater Negative central (Nc) ERP response to the deviant actions for the pair that caused the action-effect, which was consistent with their visual anticipations during the learning phase. Findings are discussed in terms of the neural and behavioral processes underlying perception and learning of structured action sequences. Copyright © 2017 Elsevier Ltd. All rights reserved.
Monroy, Claire D; Gerson, Sarah A; Hunnius, Sabine
Humans are sensitive to the statistical regularities in action sequences carried out by others. In the present eyetracking study, we investigated whether this sensitivity can support the prediction of upcoming actions when observing unfamiliar action sequences. In two between-subjects conditions, we examined whether observers would be more sensitive to statistical regularities in sequences performed by a human agent versus self-propelled 'ghost' events. Secondly, we investigated whether regularities are learned better when they are associated with contingent effects. Both implicit and explicit measures of learning were compared between agent and ghost conditions. Implicit learning was measured via predictive eye movements to upcoming actions or events, and explicit learning was measured via both uninstructed reproduction of the action sequences and verbal reports of the regularities. The findings revealed that participants, regardless of condition, readily learned the regularities and made correct predictive eye movements to upcoming events during online observation. However, different patterns of explicit-learning outcomes emerged following observation: Participants were most likely to re-create the sequence regularities and to verbally report them when they had observed an actor create a contingent effect. These results suggest that the shift from implicit predictions to explicit knowledge of what has been learned is facilitated when observers perceive another agent's actions and when these actions cause effects. These findings are discussed with respect to the potential role of the motor system in modulating how statistical regularities are learned and used to modify behavior.
In the present action learning implementation, twelve action learning sets were conducted over eight years. The action learning sets consisted of students involved in undergraduate engineering research thesis work. The concurrent study accompanying this initiative investigated the influence of the action learning environment on student approaches to learning and any accompanying academic, learning and personal benefits realised. The influence of preferred learning styles on set function and s...
In the present action learning implementation, twelve action learning sets were conducted over eight years. The action learning sets consisted of students involved in undergraduate engineering research thesis work. The concurrent study accompanying this initiative investigated the influence of the action learning environment on student approaches…
Press, Clare; Heyes, Cecilia; Kilner, James M.
Despite nearly two decades of research on mirror neurons, there is still much debate about what they do. The most enduring hypothesis is that they enable ‘action understanding’. However, recent critical reviews have failed to find compelling evidence in favour of this view. Instead, these authors argue that mirror neurons are produced by associative learning and therefore that they cannot contribute to action understanding. The present opinion piece suggests that this argument is flawed. We a...
Full Text Available In the present action learning implementation, twelve action learning sets were conducted over eight years. The action learning sets consisted of students involved in undergraduate engineering research thesis work. The concurrent study accompanying this initiative, investigated the influence of the action learning environment on student approaches to learning and any accompanying academic, learning and personal benefits realised. The influence of preferred learning styles on set function and student adoption of the action learning process were also examined. The action learning environment implemented had a measurable significant positive effect on student academic performance, their ability to cope with the stresses associated with conducting a research thesis, the depth of learning, the development of autonomous learners and student perception of the research thesis experience. The present study acts as an addendum to a smaller scale implementation of this action learning approach, applied to supervision of third and fourth year research projects and theses, published in 2010.
Full Text Available What are the memory-related consequences of learning actions (such as "apply the patch" by enactment during study, as compared to action observation? Theories converge in postulating that enactment encoding increases item-specific processing, but not the processing of relational information. Typically, in the laboratory enactment encoding is studied for lists of unrelated single actions in which one action execution has no overarching purpose or relation with other actions. In contrast, real-life actions are usually carried out with the intention to achieve such a purpose. When actions are embedded in action sequences, relational information provides efficient retrieval cues. We contrasted memory for single actions with memory for action sequences in three experiments. We found more reliance on relational processing for action-sequences than single actions. To what degree can this relational information be used after enactment versus after the observation of an actor? We found indicators of superior relational processing after observation than enactment in ordered pair recall (Experiment 1A and in emerging subjective organization of repeated recall protocols (recall runs 2-3, Experiment 2. An indicator of superior item-specific processing after enactment compared to observation was recognition (Experiment 1B, Experiment 2. Similar net recall suggests that observation can be as good a learning strategy as enactment. We discuss possible reasons why these findings only partly converge with previous research and theorizing.
An action learning approach to help managers enhance learning capacity involved a performance management seminar, work by action learning sets, implementation of a new performance management instrument with mentoring by action learning facilitators, and evaluation. Survey responses from 392 participants revealed satisfaction with managerial…
Choi, Julia T; Jensen, Peter; Nielsen, Jens Bo
walking. In addition, we determined how age (i.e., healthy young adults vs. children) and biomechanical factors (i.e., walking speed) affected the rate and magnitude of locomotor sequence learning. The results showed that healthy young adults (age 24 ± 5 years, N = 20) could learn a specific sequence...... of step lengths over 300 training steps. Younger children (age 6-10 years, N = 8) have lower baseline performance, but their magnitude and rate of sequence learning was the same compared to older children (11-16 years, N = 10) and healthy adults. In addition, learning capacity may be more limited...... to modify step length from one trial to the next. Our sequence learning paradigm is derived from the serial reaction-time (SRT) task that has been used in upper limb studies. Both random and ordered sequences of step lengths were used to measure sequence-specific and sequence non-specific learning during...
Verschoor, Stephan Alexander
By using innovative paradigms, the present thesis provides convincing evidence that action-effect learning, and sensorimotor processes in general play a crucial role in the development of action- perception and production in infancy. This finding was further generalized to sequential action.
Bolander, Thomas; Gierasimczuk, Nina
In this article we study learnability of fully observable, universally applicable action models of dynamic epistemic logic. We introduce a framework for actions seen as sets of transitions between propositional states and we relate them to their dynamic epistemic logic representations as action...... in the limit (inconclusive convergence to the right action model). We show that deterministic actions are finitely identifiable, while arbitrary (non-deterministic) actions require more learning power—they are identifiable in the limit. We then move on to a particular learning method, i.e. learning via update......, which proceeds via restriction of a space of events within a learning-specific action model. We show how this method can be adapted to learn conditional and unconditional deterministic action models. We propose update learning mechanisms for the afore mentioned classes of actions and analyse...
Nielbo, Kristoffer Laigaard; Sørensen, Jesper
recurrent networks were made and the results are presented in this article. The simulations show that non-functional action sequences do indeed increase prediction error, but that context representations, such as abstract goal information, can modulate the error signal considerably. It is also shown...... that the networks are sensitive to boundaries between sequences in both functional and non-functional actions....
Ding, Wenwen; Liu, Kai; Cheng, Fei; Zhang, Jin; Li, YunSong
Human action recognition and analysis is an active research topic in computer vision for many years. This paper presents a method to represent human actions based on trajectories consisting of 3D joint positions. This method first decompose action into a sequence of meaningful atomic actions (actionlets), and then label actionlets with English alphabets according to the Davies-Bouldin index value. Therefore, an action can be represented using a sequence of actionlet symbols, which will preserve the temporal order of occurrence of each of the actionlets. Finally, we employ sequence comparison to classify multiple actions through using string matching algorithms (Needleman-Wunsch). The effectiveness of the proposed method is evaluated on datasets captured by commodity depth cameras. Experiments of the proposed method on three challenging 3D action datasets show promising results.
Full Text Available This paper presents a visual/motor behavior learning approach, based on neural networks. We propose Behavior Chain Model (BCM in order to create a way of behavior learning. Our behavior-based system evolution task is a mobile robot detecting a target and driving/acting towards it. First, the mapping relations between the image feature domain of the object and the robot action domain are derived. Second, a multilayer neural network for offline learning of the mapping relations is used. This learning structure through neural network training process represents a connection between the visual perceptions and motor sequence of actions in order to grip a target. Last, using behavior learning through a noticed action chain, we can predict mobile robot behavior for a variety of similar tasks in similar environment. Prediction results suggest that the methodology is adequate and could be recognized as an idea for designing different mobile robot behaviour assistance.
and MySQL . However, all participants participated from in-lab computers. Results Figure 6 shows the distribution of participants’ raw key presses... Java program to present video of action sequences and collect ratings. The program presented all 12 actions, non-actions, and part-actions
Lustig, Patricia; Rai, Deep Ranjani
This article describes an example of how action learning was used as a framework for an organisational intervention to fundamentally change the organisational culture over a period of time. It also identifies our learning over that period of time and what worked well (and not so well) in an International Non-Governmental Organisation in Nepal.
This account of practice outlines the Oxyme Action Learning Program which was conducted as part of the Management Challenge in my final year of the MSc in Coaching and Behavioral Change at Henley Business School. The central research questions were: (1) how action learning can help to solve wicked problems and (2) what the effect of an action…
Dickenson, Mollie; Burgoyne, John; Pedler, Mike
This paper reports findings from research that set out to explore virtual action learning (VAL) as an emerging variety of action learning (AL). In bringing together geographically dispersed individuals within and across organizations, and possibly across time, VAL has obvious potential in both educational and commercial contexts. Whilst there is…
Bolander, Thomas; Gierasimczuk, Nina
In dynamic epistemic logic, actions are described using action models. In this paper we introduce a framework for studying learnability of action models from observations. We present first results concerning propositional action models. First we check two basic learnability criteria: finite ident...
This paper explores the conduct and outcomes of an action learning activity during a period of intense organisational change in a medium-sized vocational education and training organisation in Victoria, Australia. This organisation was the subject of significant change due to government-driven and statewide amalgamation, downsizing and sector…
Keller, Arielle S.; Sekuler, Robert
We examined short-term memory for sequences of visual stimuli embedded in varying multisensory contexts. In two experiments, subjects judged the structure of the visual sequences while disregarding concurrent, but task-irrelevant auditory sequences. Stimuli were eight-item sequences in which varying luminances and frequencies were presented concurrently and rapidly (at 8 Hz). Subjects judged whether the final four items in a visual sequence identically replicated the first four items. Luminances and frequencies in each sequence were either perceptually correlated (Congruent) or were unrelated to one another (Incongruent). Experiment 1 showed that, despite encouragement to ignore the auditory stream, subjects' categorization of visual sequences was strongly influenced by the accompanying auditory sequences. Moreover, this influence tracked the similarity between a stimulus's separate audio and visual sequences, demonstrating that task-irrelevant auditory sequences underwent a considerable degree of processing. Using a variant of Hebb's repetition design, Experiment 2 compared musically trained subjects and subjects who had little or no musical training on the same task as used in Experiment 1. Test sequences included some that intermittently and randomly recurred, which produced better performance than sequences that were generated anew for each trial. The auditory component of a recurring audiovisual sequence influenced musically trained subjects more than it did other subjects. This result demonstrates that stimulus-selective, task-irrelevant learning of sequences can occur even when such learning is an incidental by-product of the task being performed. PMID:26575193
Keller, Arielle S; Sekuler, Robert
We examined short-term memory for sequences of visual stimuli embedded in varying multisensory contexts. In two experiments, subjects judged the structure of the visual sequences while disregarding concurrent, but task-irrelevant auditory sequences. Stimuli were eight-item sequences in which varying luminances and frequencies were presented concurrently and rapidly (at 8 Hz). Subjects judged whether the final four items in a visual sequence identically replicated the first four items. Luminances and frequencies in each sequence were either perceptually correlated (Congruent) or were unrelated to one another (Incongruent). Experiment 1 showed that, despite encouragement to ignore the auditory stream, subjects' categorization of visual sequences was strongly influenced by the accompanying auditory sequences. Moreover, this influence tracked the similarity between a stimulus's separate audio and visual sequences, demonstrating that task-irrelevant auditory sequences underwent a considerable degree of processing. Using a variant of Hebb's repetition design, Experiment 2 compared musically trained subjects and subjects who had little or no musical training on the same task as used in Experiment 1. Test sequences included some that intermittently and randomly recurred, which produced better performance than sequences that were generated anew for each trial. The auditory component of a recurring audiovisual sequence influenced musically trained subjects more than it did other subjects. This result demonstrates that stimulus-selective, task-irrelevant learning of sequences can occur even when such learning is an incidental by-product of the task being performed.
Nalborczyk, Sarah; Sandelands, Luke
This account examines the action learning process adopted by Emerald Group Publishing Ltd., embedded in the organization through the in-company Emerald Academy. In case study format, the paper emphasizes that in order to align learning with organizational objectives joined up thinking and practice is needed beyond the learning and development…
Nunez, Heilyn Camacho; Aguirre, María
reflections. Through his work Revans was claiming several times that action learning goes further than other training methods and that its central ideas had been misunderstood. (Revans, 1982, p.531) He was claiming the need to develop the whole person in all its dimensions. From this perspective the Alpha...... system of action learning, where you explore your values, should not be taken as a light activity. It is the essence of action learning, where the person can explore all the significant aspects of his complete development which includes these moral, ethical and spiritual aspects.......The aim of this article is to provide a discussion and description of some topics of action learning that are not so commonly discussed in the literature and that I have called ‘the forgotten elements of action learning’. Those elements are dealing with Revans’ moral, spiritual and ethical...
Deroost, Natacha; Coomans, Daphné
We examined the role of sequence awareness in a pure perceptual sequence learning design. Participants had to react to the target's colour that changed according to a perceptual sequence. By varying the mapping of the target's colour onto the response keys, motor responses changed randomly. The effect of sequence awareness on perceptual sequence learning was determined by manipulating the learning instructions (explicit versus implicit) and assessing the amount of sequence awareness after the experiment. In the explicit instruction condition (n = 15), participants were instructed to intentionally search for the colour sequence, whereas in the implicit instruction condition (n = 15), they were left uninformed about the sequenced nature of the task. Sequence awareness after the sequence learning task was tested by means of a questionnaire and the process-dissociation-procedure. The results showed that the instruction manipulation had no effect on the amount of perceptual sequence learning. Based on their report to have actively applied their sequence knowledge during the experiment, participants were subsequently regrouped in a sequence strategy group (n = 14, of which 4 participants from the implicit instruction condition and 10 participants from the explicit instruction condition) and a no-sequence strategy group (n = 16, of which 11 participants from the implicit instruction condition and 5 participants from the explicit instruction condition). Only participants of the sequence strategy group showed reliable perceptual sequence learning and sequence awareness. These results indicate that perceptual sequence learning depends upon the continuous employment of strategic cognitive control processes on sequence knowledge. Sequence awareness is suggested to be a necessary but not sufficient condition for perceptual learning to take place. Copyright © 2018 Elsevier B.V. All rights reserved.
Dezfouli, Amir; Lingawi, Nura W; Balleine, Bernard W
Goal-directed action involves making high-level choices that are implemented using previously acquired action sequences to attain desired goals. Such a hierarchical schema is necessary for goal-directed actions to be scalable to real-life situations, but results in decision-making that is less flexible than when action sequences are unfolded and the decision-maker deliberates step-by-step over the outcome of each individual action. In particular, from this perspective, the offline revaluation of any outcomes that fall within action sequence boundaries will be invisible to the high-level planner resulting in decisions that are insensitive to such changes. Here, within the context of a two-stage decision-making task, we demonstrate that this property can explain the emergence of habits. Next, we show how this hierarchical account explains the insensitivity of over-trained actions to changes in outcome value. Finally, we provide new data that show that, under extended extinction conditions, habitual behaviour can revert to goal-directed control, presumably as a consequence of decomposing action sequences into single actions. This hierarchical view suggests that the development of action sequences and the insensitivity of actions to changes in outcome value are essentially two sides of the same coin, explaining why these two aspects of automatic behaviour involve a shared neural structure. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Dean P. Jones
Full Text Available The exposome is a complement to the genome that includes non-genetic causes of disease. Multiple definitions are available, with salient points being global inclusion of exposures and behaviors, and cumulative integration of associated biologic responses. As such, the concept is both refreshingly simple and dauntingly complex. This article reviews high-resolution metabolomics (HRM as an affordable approach to routinely analyze samples for a broad spectrum of environmental chemicals and biologic responses. HRM has been successfully used in multiple exposome research paradigms and is suitable to implement in a prototype universal exposure surveillance system. Development of such a structure for systematic monitoring of environmental exposures is an important step toward sequencing the exposome because it builds upon successes of exposure science, naturally connects external exposure to body burden and partitions the exposome into workable components. Practical results would be repositories of quantitative data on chemicals according to geography and biology. This would support new opportunities for environmental health analysis and predictive modeling. Complementary approaches to hasten development of exposome theory and associated biologic response networks could include experimental studies with model systems, analysis of archival samples from longitudinal studies with outcome data and study of relatively short-lived animals, such as household pets (dogs and cats and non-human primates (common marmoset. International investment and cooperation to sequence the human exposome will advance scientific knowledge and also provide an important foundation to control adverse environmental exposures to sustain healthy living spaces and improve prediction and management of disease. Keywords: Mass spectrometry, Biomonitoring, Analytical chemistry, Metabolomics, Environmental surveillance
Gold, Jeff; Anderson, Lisa; Clarke, Jean; Thorpe, Richard
This paper considers the work of the Russian social philosopher and cultural theorist, Mikhail Mikhailovich Bakhtin as a source of understanding for those involved in action learning. Drawing upon data gathered over two years during the evaluation of 20 action learning sets in the north of England, we will seek to work with the ideas of Bakhtin to…
Middel, H.G.A.; McNichols, Timothy
The process of implementing collaborative initiatives across disparate members of supply networks is fraught with difficulties. One approach designed to tackle the difficulties of organisational change and interorganisational improvement in practice is 'action learning'. This paper examines the
Yeadon-Lee, Annie; Hall, Roger
There has been increasing criticism of the relevance of the Master of Business Administration (MBA) degree in developing skills and competencies. Action learning, devised to address problem solving in the
Shanks, David R; Rowland, Lee A; Ranger, Mandeep S
A widely employed conceptualization of implicit learning hypothesizes that it makes minimal demands on attentional resources. This conjecture was investigated by comparing learning under single-task and dual-task conditions in the sequential reaction time (SRT) task. Participants learned probabilistic sequences, with dual-task participants additionally having to perform a counting task using stimuli that were targets in the SRT display. Both groups were then tested for sequence knowledge under single-task (Experiments 1 and 2) or dual-task (Experiment 3) conditions. Participants also completed a free generation task (Experiments 2 and 3) under inclusion or exclusion conditions to determine if sequence knowledge was conscious or unconscious in terms of its access to intentional control. The experiments revealed that the secondary task impaired sequence learning and that sequence knowledge was consciously accessible. These findings disconfirm both the notion that implicit learning is able to proceed normally under conditions of divided attention, and that the acquired knowledge is inaccessible to consciousness. A unitary framework for conceptualizing implicit and explicit learning is proposed.
Full Text Available Recognizing the actions of others from visual stimuli is a crucial aspect of human perception that allows individuals to respond to social cues. Humans are able to discriminate between similar actions despite transformations, like changes in viewpoint or actor, that substantially alter the visual appearance of a scene. This ability to generalize across complex transformations is a hallmark of human visual intelligence. Advances in understanding action recognition at the neural level have not always translated into precise accounts of the computational principles underlying what representations of action sequences are constructed by human visual cortex. Here we test the hypothesis that invariant action discrimination might fill this gap. Recently, the study of artificial systems for static object perception has produced models, Convolutional Neural Networks (CNNs, that achieve human level performance in complex discriminative tasks. Within this class, architectures that better support invariant object recognition also produce image representations that better match those implied by human and primate neural data. However, whether these models produce representations of action sequences that support recognition across complex transformations and closely follow neural representations of actions remains unknown. Here we show that spatiotemporal CNNs accurately categorize video stimuli into action classes, and that deliberate model modifications that improve performance on an invariant action recognition task lead to data representations that better match human neural recordings. Our results support our hypothesis that performance on invariant discrimination dictates the neural representations of actions computed in the brain. These results broaden the scope of the invariant recognition framework for understanding visual intelligence from perception of inanimate objects and faces in static images to the study of human perception of action sequences.
Hasselt, H. van; Wiering, M.A.
Quite some research has been done on Reinforcement Learning in continuous environments, but the research on problems where the actions can also be chosen from a continuous space is much more limited. We present a new class of algorithms named Continuous Actor Critic Learning Automaton (CACLA)
Coghlan, David; Coughlan, Paul
The philosophical foundations of action learning research have not received a great deal of attention. In the context of action learning postgraduate and professional programmes in universities, articulation of a philosophy of action learning research seems timely and appropriate. This article explores a philosophy of action learning research,…
Nielbo, Kristoffer Laigaard; Sørensen, Jesper
as sub-categories of non-functional behavior (i.e., actions lacking causal coherence and a necessary integration between subparts). New insights in human action processing can help us explain how cognition might vary depending on the type of behavior processed. Using an event segmentation paradigm, we...... conducted two experiments eliciting differences in participants' response patterns to functional and non-functional actions. Participants consistently segmented non-functional action sequences into smaller units indicating either an attentional shift to the level of gesture analysis or a problem...... of representational integration. Experimental studies of non-functional behavior can strengthen explanations of recurrent features of human action processing, such as ritual and ritualized behavior, as well as indicate potential sources and effects of breakdown of the system....
Meyer, Meredith; Baldwin, Dare
Identification of distinct units within a continuous flow of human action is fundamental to action processing. Such segmentation may rest in part on statistical learning. In a series of four experiments, we examined what types of statistics people can use to segment a continuous stream involving many brief, goal-directed action elements. The results of Experiment 1 showed no evidence for sensitivity to conditional probability, whereas Experiment 2 displayed learning based on joint probability. In Experiment 3, we demonstrated that additional exposure to the input failed to engender sensitivity to conditional probability. However, the results of Experiment 4 showed that a subset of adults-namely, those more successful at identifying actions that had been seen more frequently than comparison sequences-were also successful at learning conditional-probability statistics. These experiments help to clarify the mechanisms subserving processing of intentional action, and they highlight important differences from, as well as similarities to, prior studies of statistical learning in other domains, including language.
Jiang, Zhuolin; Lin, Zhe; Davis, Larry S
A shape-motion prototype-based approach is introduced for action recognition. The approach represents an action as a sequence of prototypes for efficient and flexible action matching in long video sequences. During training, an action prototype tree is learned in a joint shape and motion space via hierarchical K-means clustering and each training sequence is represented as a labeled prototype sequence; then a look-up table of prototype-to-prototype distances is generated. During testing, based on a joint probability model of the actor location and action prototype, the actor is tracked while a frame-to-prototype correspondence is established by maximizing the joint probability, which is efficiently performed by searching the learned prototype tree; then actions are recognized using dynamic prototype sequence matching. Distance measures used for sequence matching are rapidly obtained by look-up table indexing, which is an order of magnitude faster than brute-force computation of frame-to-frame distances. Our approach enables robust action matching in challenging situations (such as moving cameras, dynamic backgrounds) and allows automatic alignment of action sequences. Experimental results demonstrate that our approach achieves recognition rates of 92.86 percent on a large gesture data set (with dynamic backgrounds), 100 percent on the Weizmann action data set, 95.77 percent on the KTH action data set, 88 percent on the UCF sports data set, and 87.27 percent on the CMU action data set.
Jones, Karen; Sambrook, Sally A.; Pittaway, Luke; Henley, Andrew; Norbury, Heather
This paper presents research with small- and medium-sized enterprise (SME) owners who have participated in a leadership development programme. The primary focus of this paper is on learning transfer and factors affecting it, arguing that entrepreneurs must engage in "action" in order to "learn" and that under certain conditions…
van den Bosch, A.; Daelemans, W.; Dagan, I.; Gildea, D.
Symbolic machine-learning classifiers are known to suffer from near-sightedness when performing sequence segmentation (chunking) tasks in natural language processing: without special architectural additions they are oblivious of the decisions they made earlier when making new ones. We introduce a
The ten learning sequences follow on one another. Each picks on a particular aspect from the energy field. The subject notebooks are self-contained and can therefore be used independently. Apart from actual data and energy-related information, the information for the teacher contains: - proposals for teaching - suggestions for further activities - sample solutions for the pupil's sheets - references to the literature and media. The worksheets for the pupils are different; it should be possible to use the learning sequences in all classes of secondary school stage 1. The multicoloured foils for projectors should motivate, on the one hand, and on the other hand should help to check the results of learning. (orig./HP) [de
Seddon, John; Caulkin, Simon
Systems thinking underpins "lean" management and is best understood through action-learning as the ideas are counter-intuitive. The Toyota Production System is just that--a system; the failure to appreciate that starting-place and the advocacy of "tools" leads many to fail to grasp what is, without doubt, a significant…
This is an account of a programmer utilizing the application of action learning to the development of capacities of citizens. The Citizen Leadership for Democratic Governance is designed to equip citizens with the skills to get involved and handle the difficult tasks of governance in their communities in South Africa. After a history of apartheid…
Merkulova, T. V.
This article explores "comparison" as a universal metasubject learning action, a key curricular element envisaged by the Russian Federal State Educational Standards. Representing the modern learner's fundamental pragmatic skill embedding such core capacities as information processing, critical thinking, robust decision-making, and…
Kurashima, Takeshi; Althoff, Tim; Leskovec, Jure
Mobile health applications, including those that track activities such as exercise, sleep, and diet, are becoming widely used. Accurately predicting human actions in the real world is essential for targeted recommendations that could improve our health and for personalization of these applications. However, making such predictions is extremely difficult due to the complexities of human behavior, which consists of a large number of potential actions that vary over time, depend on each other, and are periodic. Previous work has not jointly modeled these dynamics and has largely focused on item consumption patterns instead of broader types of behaviors such as eating, commuting or exercising. In this work, we develop a novel statistical model, called TIPAS, for Time-varying, Interdependent, and Periodic Action Sequences. Our approach is based on personalized, multivariate temporal point processes that model time-varying action propensities through a mixture of Gaussian intensities. Our model captures short-term and long-term periodic interdependencies between actions through Hawkes process-based self-excitations. We evaluate our approach on two activity logging datasets comprising 12 million real-world actions (e.g., eating, sleep, and exercise) taken by 20 thousand users over 17 months. We demonstrate that our approach allows us to make successful predictions of future user actions and their timing. Specifically, TIPAS improves predictions of actions, and their timing, over existing methods across multiple datasets by up to 156%, and up to 37%, respectively. Performance improvements are particularly large for relatively rare and periodic actions such as walking and biking, improving over baselines by up to 256%. This demonstrates that explicit modeling of dependencies and periodicities in real-world behavior enables successful predictions of future actions, with implications for modeling human behavior, app personalization, and targeting of health interventions. PMID
Smith-Stoner, Marilyn; Molle, Mary E
Nurse educators must continually improve their teaching skills through innovation. However, research about the process used by faculty members to transform their teaching methods is limited. This collaborative study uses classroom action research to describe, analyze, and address problems encountered in implementing cooperative learning in two undergraduate nursing courses. After four rounds of action and reflection, the following themes emerged: students did not understand the need for structured cooperative learning; classroom structure and seating arrangement influenced the effectiveness of activities; highly structured activities engaged the students; and short, targeted activities that involved novel content were most effective. These findings indicate that designing specific activities to prepare students for class is critical to cooperative learning. Copyright 2010, SLACK Incorporated.
Green, C S; Bavelier, D
While humans have an incredible capacity to acquire new skills and alter their behavior as a result of experience, enhancements in performance are typically narrowly restricted to the parameters of the training environment, with little evidence of generalization to different, even seemingly highly related, tasks. Such specificity is a major obstacle for the development of many real-world training or rehabilitation paradigms, which necessarily seek to promote more general learning. In contrast to these typical findings, research over the past decade has shown that training on 'action video games' produces learning that transfers well beyond the training task. This has led to substantial interest among those interested in rehabilitation, for instance, after stroke or to treat amblyopia, or training for various precision-demanding jobs, for instance, endoscopic surgery or piloting unmanned aerial drones. Although the predominant focus of the field has been on outlining the breadth of possible action-game-related enhancements, recent work has concentrated on uncovering the mechanisms that underlie these changes, an important first step towards the goal of designing and using video games for more definite purposes. Game playing may not convey an immediate advantage on new tasks (increased performance from the very first trial), but rather the true effect of action video game playing may be to enhance the ability to learn new tasks. Such a mechanism may serve as a signature of training regimens that are likely to produce transfer of learning. Copyright Â© 2012 Elsevier Ltd. All rights reserved.
Green, C.S.; Bavelier, D.
While humans have an incredible capacity to acquire new skills and alter their behavior as a result of experience, enhancements in performance are typically narrowly restricted to the parameters of the training environment, with little evidence of generalization to different, even seemingly highly related, tasks. Such specificity is a major obstacle for the development of many real-world training or rehabilitation paradigms, which necessarily seek to promote more general learning. In contrast to these typical findings, research over the past decade has shown that training on ‘action video games’ produces learning that transfers well beyond the training task. This has led to substantial interest among those interested in rehabilitation, for instance, after stroke or to treat amblyopia, or training for various precision-demanding jobs, for instance, endoscopic surgery or piloting unmanned aerial drones. Although the predominant focus of the field has been on outlining the breadth of possible action-game-related enhancements, recent work has concentrated on uncovering the mechanisms that underlie these changes, an important first step towards the goal of designing and using video games for more definite purposes. Game playing may not convey an immediate advantage on new tasks (increased performance from the very first trial), but rather the true effect of action video game playing may be to enhance the ability to learn new tasks. Such a mechanism may serve as a signature of training regimens that are likely to produce transfer of learning. PMID:22440805
Green, C Shawn; Li, Renjie; Bavelier, Daphne
Action video games have been shown to enhance behavioral performance on a wide variety of perceptual tasks, from those that require effective allocation of attentional resources across the visual scene, to those that demand the successful identification of fleetingly presented stimuli. Importantly, these effects have not only been shown in expert action video game players, but a causative link has been established between action video game play and enhanced processing through training studies. Although an account based solely on attention fails to capture the variety of enhancements observed after action game playing, a number of models of perceptual learning are consistent with the observed results, with behavioral modeling favoring the hypothesis that avid video game players are better able to form templates for, or extract the relevant statistics of, the task at hand. This may suggest that the neural site of learning is in areas where information is integrated and actions are selected; yet changes in low-level sensory areas cannot be ruled out. Copyright © 2009 Cognitive Science Society, Inc.
Full Text Available Enhanced procedural learning has been evidenced in conditions where cognitive control is diminished, including hypnosis, disruption of prefrontal activity and non-optimal time of the day. Another condition depleting the availability of controlled resources is cognitive fatigue. We tested the hypothesis that cognitive fatigue, eventually leading to diminished cognitive control, facilitates procedural sequence learning. In a two-day experiment, twenty-three young healthy adults were administered a serial reaction time task (SRTT following the induction of high or low levels of cognitive fatigue, in a counterbalanced order. Cognitive fatigue was induced using the Time load Dual-back (TloadDback paradigm, a dual working memory task that allows tailoring cognitive load levels to the individual's optimal performance capacity. In line with our hypothesis, reaction times in the SRTT were faster in the high- than in the low-level fatigue condition, and performance improvement showed more of a benefit from the sequential components than from motor. Altogether, our results suggest a paradoxical, facilitating impact of cognitive fatigue on procedural motor sequence learning. We propose that facilitated learning in the high-level fatigue condition stems from a reduction in the cognitive resources devoted to cognitive control processes that normally oppose automatic procedural acquisition mechanisms.
Nielsen, Bjørn Gilbert
. It is proposed that the neural machinery required in such a learning/retrieval mechanism could involve the NMDA receptor, in conjunction with the ability of dendrites to maintain differentially activated regions. In particular, it is suggested that such a parcellation of the dendrite allows the neuron......Differentially activated areas of a dendrite permit the existence of zones with distinct rates of synaptic modification, and such areas can be individually accessed using a reference signal which localizes synaptic plasticity and memory trace retrieval to certain subregions of the dendrite...... to participate in multiple sequences, which can be learned without suffering from the 'wash-out' of synaptic efficacy associated with superimposition of training patterns. This is a biologically plausible solution to the stability-plasticity dilemma of learning in neural networks....
Kamath, Uday Krishna
Sequence classification is an important problem in many real-world applications. Unlike other machine learning data, there are no "explicit" features or signals in sequence data that can help traditional machine learning algorithms learn and predict from the data. Sequence data exhibits inter-relationships in the elements that are…
Wang, C.; Hindriks, K.V.; Babuska, R.
Learning object affordances and manipulation skills is essential for developing cognitive service robots. We propose an active affordance learning approach in continuous state and action spaces without manual discretization of states or exploratory motor primitives. During exploration in the action
Reese, Debbie Denise; Tabachnick, Barbara G.; Kosko, Robert E.
Valid, accessible, reusable methods for instructional video game design and embedded assessment can provide actionable information enhancing individual and collective achievement. Cyberlearning through game-based, metaphor-enhanced learning objects (CyGaMEs) design and embedded assessment quantify player behavior to study knowledge discovery and…
Bong, Hyeon-Cheol; Cho, Yonjoo
Purpose: The purpose of this paper was to explore how the two groups of action learning experts (Korean and non-Korean experts) define success of action learning to see whether there are any cultural differences. To this end, the authors conducted a total of 44 interviews with action learning experts around the world. Research questions guiding…
Gobel, Eric W; Parrish, Todd B; Reber, Paul J
Learning of complex motor skills requires learning of component movements as well as the sequential structure of their order and timing. Using a Serial Interception Sequence Learning (SISL) task, participants learned a sequence of precisely timed interception responses through training with a repeating sequence. Following initial implicit learning of the repeating sequence, functional MRI data were collected during performance of that known sequence and compared with activity evoked during novel sequences of actions, novel timing patterns, or both. Reduced activity was observed during the practiced sequence in a distributed bilateral network including extrastriate occipital, parietal, and premotor cortical regions. These reductions in evoked activity likely reflect improved efficiency in visuospatial processing, spatio-motor integration, motor planning, and motor execution for the trained sequence, which is likely supported by nondeclarative skill learning. In addition, the practiced sequence evoked increased activity in the left ventral striatum and medial prefrontal cortex, while the posterior cingulate was more active during periods of better performance. Many prior studies of perceptual-motor skill learning have found increased activity in motor areas of the frontal cortex (e.g., motor and premotor cortex, SMA) and striatal areas (e.g., the putamen). The change in activity observed here (i.e., decreased activity across a cortical network) may reflect skill learning that is predominantly expressed through more accurate performance rather than decreased reaction time. Copyright © 2011 Elsevier Inc. All rights reserved.
Full Text Available A dense matching algorithm that solves the problem of synchronizing prerecorded human motion sequences, which show different speeds and accelerations, is proposed. The approach is based on minimization of MRF energy and solves the problem by using Dynamic Programming. Additionally, an optimal sequence is automatically selected from the input dataset to be a time-scale pattern for all other sequences. The paper utilizes an action specific model which automatically learns the variability of 3D human postures observed in a set of training sequences. The model is trained using the public CMU motion capture dataset for the walking action, and a mean walking performance is automatically learnt. Additionally, statistics about the observed variability of the postures and motion direction are also computed at each time step. The synchronized motion sequences are used to learn a model of human motion for action recognition and full-body tracking purposes.
Lynch, Brighid; Beukema, Patrick; Verstynen, Timothy
The dual-system model of sequence learning posits that during early learning there is an advantage for encoding sequences in sensory frames; however, it remains unclear whether this advantage extends to long-term consolidation. Using the serial RT task, we set out to distinguish the dynamics of learning sequential orders of visual cues from learning sequential responses. On each day, most participants learned a new mapping between a set of symbolic cues and responses made with one of four fingers, after which they were exposed to trial blocks of either randomly ordered cues or deterministic ordered cues (12-item sequence). Participants were randomly assigned to one of four groups (n = 15 per group): Visual sequences (same sequence of visual cues across training days), Response sequences (same order of key presses across training days), Combined (same serial order of cues and responses on all training days), and a Control group (a novel sequence each training day). Across 5 days of training, sequence-specific measures of response speed and accuracy improved faster in the Visual group than any of the other three groups, despite no group differences in explicit awareness of the sequence. The two groups that were exposed to the same visual sequence across days showed a marginal improvement in response binding that was not found in the other groups. These results indicate that there is an advantage, in terms of rate of consolidation across multiple days of training, for learning sequences of actions in a sensory representational space, rather than as motoric representations.
Katherine R Gamble
Full Text Available Implicit sequence learning involves learning about dependencies in sequences of events without intent to learn or awareness of what has been learned. Sequence learning is related to striatal dopamine levels, striatal activation, and integrity of white matter connections. People with Parkinson’s disease (PD have degeneration of dopamine-producing neurons, leading to dopamine deficiency and therefore striatal deficits, and they have difficulties with sequencing, including complex language comprehension and postural stability. Most research on implicit sequence learning in PD has used motor-based tasks. However, because PD presents with motor deficits, it is difficult to assess whether learning itself is impaired in these tasks. The present study used an implicit sequence learning task with a reduced motor component, the Triplets Learning Task (TLT. People with PD and age- and education-matched healthy older adults completed three sessions (each consisting of 10 blocks of 50 trials of the TLT. Results revealed that the PD group was able to learn the sequence, however, when learning was examined using a Half Blocks analysis (Nemeth et al., 2013, which compared learning in the 1st 25/50 trials of all blocks to that in the 2nd 25/50 trials, the PD group showed significantly less learning than Controls in the 2nd Half Blocks, but not in the 1st. Nemeth et al. hypothesized that the 1st Half Blocks involve recall and reactivation of the sequence learned, thus reflecting hippocampal-dependent learning, while the 2nd Half Blocks involve proceduralized behavior of learned sequences, reflecting striatal-based learning. The present results suggest that the PD group had intact hippocampal-dependent implicit sequence learning, but impaired striatal-dependent learning. Thus, sequencing deficits in PD are likely due to striatal impairments, but other brain systems, such as the hippocampus, may be able to partially compensate for striatal decline to improve
Taber, Jennifer M; Klein, William M P; Ferrer, Rebecca A; Han, Paul K J; Lewis, Katie L; Biesecker, Leslie G; Biesecker, Barbara B
Many variants that could be returned from genome sequencing may be perceived as ambiguous-lacking reliability, credibility, or adequacy. Little is known about how perceived ambiguity influences thoughts about sequencing results. Participants (n = 494) in an NIH genome sequencing study completed a baseline survey before sequencing results were available. We examined how perceived ambiguity regarding sequencing results and individual differences in medical ambiguity aversion and tolerance for uncertainty were associated with cognitions and intentions concerning sequencing results. Perceiving sequencing results as more ambiguous was associated with less favorable cognitions about results and lower intentions to learn and share results. Among participants low in tolerance for uncertainty or optimism, greater perceived ambiguity was associated with lower intentions to learn results for non-medically actionable diseases; medical ambiguity aversion did not moderate any associations. Results are consistent with the phenomenon of "ambiguity aversion" and may influence whether people learn and communicate genomic information.
Du, Yue; Prashad, Shikha; Schoenbrun, Ilana; Clark, Jane E
It is well acknowledged that motor sequences can be learned quickly through online learning. Subsequently, the initial acquisition of a motor sequence is boosted or consolidated by offline learning. However, little is known whether offline learning can drive the fast learning of motor sequences (i.e., initial sequence learning in the first training session). To examine offline learning in the fast learning stage, we asked four groups of young adults to perform the serial reaction time (SRT) task with either a fixed or probabilistic sequence and with or without preliminary knowledge (PK) of the presence of a sequence. The sequence and PK were manipulated to emphasize either procedural (probabilistic sequence; no preliminary knowledge (NPK)) or declarative (fixed sequence; with PK) memory that were found to either facilitate or inhibit offline learning. In the SRT task, there were six learning blocks with a 2 min break between each consecutive block. Throughout the session, stimuli followed the same fixed or probabilistic pattern except in Block 5, in which stimuli appeared in a random order. We found that PK facilitated the learning of a fixed sequence, but not a probabilistic sequence. In addition to overall learning measured by the mean reaction time (RT), we examined the progressive changes in RT within and between blocks (i.e., online and offline learning, respectively). It was found that the two groups who performed the fixed sequence, regardless of PK, showed greater online learning than the other two groups who performed the probabilistic sequence. The groups who performed the probabilistic sequence, regardless of PK, did not display online learning, as indicated by a decline in performance within the learning blocks. However, they did demonstrate remarkably greater offline improvement in RT, which suggests that they are learning the probabilistic sequence offline. These results suggest that in the SRT task, the fast acquisition of a motor sequence is driven
Robertson, Jane; Bell, Diane
Business Driven Action Learning (BDAL), as a learning philosophy that attempts to create real value for business is often used by executive education providers in their management development programmes. As the action learning facilitator, I found that the learning that took place during such a management development programme resulted in…
De Loo, Ivo
Purpose: To highlight the relevance of management control in action learning programs that aim to foster organizational learning. Design/methodology/approach: Literature review plus case study. The latter consists of archival analysis and multiple interviews. Findings: When action learning programs are built around singular learning experiences,…
Action learning (AL) is often viewed as a process that facilitates professional learning through the creation of a positive psychological climate [Marquardt, M. J. 2000. "Action Learning and Leadership." "The Learning Organisation" 7 (5): 233-240; Schein, E. H. 1979. "Personal Change Through Interpersonal…
Nagayoshi, Masato; Murao, Hajime; Tamaki, Hisashi
Reinforcement Learning (RL) attracts much attention as a technique of realizing computational intelligence such as adaptive and autonomous decentralized systems. In general, however, it is not easy to put RL into practical use. This difficulty includes a problem of designing a suitable action space of an agent, i.e., satisfying two requirements in trade-off: (i) to keep the characteristics (or structure) of an original search space as much as possible in order to seek strategies that lie close to the optimal, and (ii) to reduce the search space as much as possible in order to expedite the learning process. In order to design a suitable action space adaptively, we propose switching RL model to mimic a process of an infant's motor development in which gross motor skills develop before fine motor skills. Then, a method for switching controllers is constructed by introducing and referring to the “entropy”. Further, through computational experiments by using robot navigation problems with one and two-dimensional continuous action space, the validity of the proposed method has been confirmed.
Giovani Parente FARIAS
Full Text Available An agent can attempt to achieve multiple goals and each goal can be achieved by applying various different plans. Anticipating failures in agent plan execution is important to enable an agent to develop strategies to avoid or circumvent such failures, allowing the agent to achieve its goal. Plan recognition can be used to infer which plans are being executed from observations of sequences of activities being performed by an agent. Symbolic Plan Recognition is an algorithm that represents knowledge about the agents under observation in the form of a plan library. In this work, we use this symbolic algorithm to find out which plan the agent is performing and we develop a failure prediction system, based on information available in the plan library and in a simplified calendar which manages the goals the agent has to achieve. This failure predictor is able to monitor the sequence of agent actions and detects if an action is taking too long or does not match the plan that the agent was expected to be performing. We have successfully employed this approach in a health-care prototype system.
Younger, Jon; Sørensen, René; Cleemann, Christine
Purpose – The purpose of this paper is to describe how a leading global company used action-learning based leadership development to accelerate strategic culture change. Design/methodology/approach – It describes the need for change, and the methodology and approach by which the initiative, Impact......, generated significant benefits. Findings – The initiative led to financial benefit, as well as measurable gains in customer centricity, collaboration, and innovation. It was also a powerful experience for participants in their journey as commercial leaders. Originality/value – Impact was created using...
Cui, Yuwei; Ahmad, Subutar; Hawkins, Jeff
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.
Fu, Qiufang; Dienes, Zoltan; Shang, Junchen; Fu, Xiaolan
Background It is well documented that East Asians differ from Westerners in conscious perception and attention. However, few studies have explored cultural differences in unconscious processes such as implicit learning. Methodology/Principal Findings The global-local Navon letters were adopted in the serial reaction time (SRT) task, during which Chinese and British participants were instructed to respond to global or local letters, to investigate whether culture influences what people acquire in implicit sequence learning. Our results showed that from the beginning British expressed a greater local bias in perception than Chinese, confirming a cultural difference in perception. Further, over extended exposure, the Chinese learned the target regularity better than the British when the targets were global, indicating a global advantage for Chinese in implicit learning. Moreover, Chinese participants acquired greater unconscious knowledge of an irrelevant regularity than British participants, indicating that the Chinese were more sensitive to contextual regularities than the British. Conclusions/Significance The results suggest that cultural biases can profoundly influence both what people consciously perceive and unconsciously learn. PMID:23940773
Koedijker, J.M.; Oudejans, R.R.D.; Beek, P.J.
Three experiments were conducted to examine proactive and retroactive interference effects in learning two similar sequences of discrete movements. In each experiment, the participants in the experimental group practiced two movement sequences on consecutive days (1 on each day, order
Parisi, German I; Tani, Jun; Weber, Cornelius; Wermter, Stefan
Lifelong learning is fundamental in autonomous robotics for the acquisition and fine-tuning of knowledge through experience. However, conventional deep neural models for action recognition from videos do not account for lifelong learning but rather learn a batch of training data with a predefined number of action classes and samples. Thus, there is the need to develop learning systems with the ability to incrementally process available perceptual cues and to adapt their responses over time. We propose a self-organizing neural architecture for incrementally learning to classify human actions from video sequences. The architecture comprises growing self-organizing networks equipped with recurrent neurons for processing time-varying patterns. We use a set of hierarchically arranged recurrent networks for the unsupervised learning of action representations with increasingly large spatiotemporal receptive fields. Lifelong learning is achieved in terms of prediction-driven neural dynamics in which the growth and the adaptation of the recurrent networks are driven by their capability to reconstruct temporally ordered input sequences. Experimental results on a classification task using two action benchmark datasets show that our model is competitive with state-of-the-art methods for batch learning also when a significant number of sample labels are missing or corrupted during training sessions. Additional experiments show the ability of our model to adapt to non-stationary input avoiding catastrophic interference. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.
Leonard, H. Skipton
Clients and practitioners alike are often confused about the ultimate purpose of action learning (AL). Because of the title of the method, many believe the primary goal of AL is to generate learning. This article clarifies the relationship between action, learning, and solutions. It also provides historical evidence to support the conclusion that…
Guevara, Jose Roberto Q.
Ecologically sound tourism planning and policy require an empowering community participation. The participatory action research model helps a community gain understanding of its social reality, learn how to learn, initiate dialog, and discover new possibilities for addressing its situation. (SK)
The article presents and illustrates the learning journey (LJ)--a new management development approach to inter-organisational learning based on observation, reflection and problem-solving. The LJ involves managers from different organisations and applies key concepts of action learning and systemic organisational development. Made up of…
Tucker, Catlin R.; Wycoff, Tiffany; Green, Jason T.
Blended learning has the power to reinvent education, but transitioning to a blended model is challenging. Blended learning requires a fundamentally new approach to learning as well as a new skillset for both teachers and school leaders. Loaded with research, examples, and resources, "Blended Learning in Action" demonstrates the…
Aspinwall, Kath; Pedler, Mike; Radcliff, Phil
This paper presents a case study based on the evaluation of the two VAL (virtual action learning) sets. We report participants learning both leadership and the VAL process based on the basis of telephone interviews. We conclude that what is learned about leadership is connected with how learning takes place and suggest that the content and process…
Full Text Available Sensory-motor learning is commonly considered as a mapping process, whereby sensory information is transformed into the motor commands that drive actions. However, this directional mapping, from inputs to outputs, is part of a loop; sensory stimuli cause actions and vice versa. Here, we explore whether actions affect the understanding of the sensory input that they cause. Using a visuo-motor task in humans, we demonstrate two types of learning-related behavioral effects. Stimulus-dependent effects reflect stimulus-response learning, while action-dependent effects reflect a distinct learning component, allowing the brain to predict the forthcoming sensory outcome of actions. Together, the stimulus-dependent and the action-dependent learning components allow the brain to construct a complete internal representation of the sensory-motor loop.
The present paper is a review of literature in relation to formulaic sequences and the implications for second language learning. The formulaic sequence is a significant part of our language, and plays an essential role in both first and second language learning. The paper first introduces the definition, classifications, and major features of…
Stoter, Arjan J. R.; Scherder, Erik J. A.; Kamsma, Yvo P. T.; Mulder, Theo
Motor imagery and action-based rehearsal were compared during motor sequence-learning by young adults (M = 25 yr., SD = 3) and aged adults (M = 63 yr., SD = 7). General accuracy of aged adults was lower than that of young adults (F-1,F-28 = 7.37, p = .01) even though working-memory capacity was
For most of the twentieth century, the goal in education was the generation and dissemination of information. With the rise of technology and unlimited access to information, it is the ability to apply knowledge and learn from experience that is the new priority for employee development. Action learning, with its emphasis on action and reflection,…
The present article describes the use of action learning by a group of 30 franchisees to organise themselves and work through a period of upheaval and uncertainty when their parent company faced liquidation. Written from the perspective of one of the franchisees who found herself adopting action learning principles to facilitate the group, it…
This paper reports the historical foundation of Northeastern University's course, LDR 6100: Developing Your Leadership Capability, a partial literature review of action learning (AL) and virtual action learning (VAL), a course methodology of LDR 6100 requiring students to apply leadership perspectives using VAL as instructed by the author,…
Cother, Genevieve; Cother, Robert F.
Business Action Learning Tasmania's (BALT) mission is self-reliant industry development, with diverse companies co-operating to improve their profitability, develop their people and grow the local economy. This is achieved through collaborative action learning, with companies working together on projects of vital importance and sharing the…
This account describes action learning in a small to medium-size enterprise (SME) that operates as a local power utility on an established market that is currently going through a process of radical transformation. The task of the action learning set was to improve the flow of information to employees about the evolving framework in which the…
Walia, Surinder; Marks-Maran, Di
This article examines the use of action learning sets in a leadership module delivered by a university in south east England. An evaluation research study was undertaking using survey method to evaluate student engagement with action learning sets, and their value, impact and sustainability. Data were collected through a questionnaire with a mix of Likert-style and open-ended questions and qualitative and quantitative data analysis was undertaken. Findings show that engagement in the action learning sets was very high. Action learning sets also had a positive impact on the development of leadership knowledge and skills and are highly valued by participants. It is likely that they would be sustainable as the majority would recommend action learning to colleagues and would consider taking another module that used action learning sets. When compared to existing literature on action learning, this study offers new insights as there is little empirical literature on student engagement with action learning sets and even less on value and sustainability. Copyright © 2014 Elsevier Ltd. All rights reserved.
This paper reflects on how action learning sets (ALSs) were used to support organisational change initiatives. It sets the scene with contextualising the inclusion of change projects in a masters programme. Action learning is understood to be a dynamic process where a team meets regularly to help individual members address issues through a highly…
H. P. van Hasselt (Hado); M.A. Wiering; M. van Otterlo
textabstractMany traditional reinforcement-learning algorithms have been designed for problems with small finite state and action spaces. Learning in such discrete problems can been difficult, due to noise and delayed reinforcements. However, many real-world problems have continuous state or action
Five case studies of individual and collective learning projects in India demonstrate that (1) the impetus for civic action arises from local conditions; (2) transformative action requires sustained adult learning; and (3) civil society is a complex concept reflecting diverse priorities and perspectives. (SK)
Full Text Available Skill learning autonomously through interactions with the environment is a crucial ability for intelligent robot. A perception-action integration or sensorimotor cycle, as an important issue in imitation learning, is a natural mechanism without the complex program process. Recently, neurocomputing model and developmental intelligence method are considered as a new trend for implementing the robot skill learning. In this paper, based on research of the human brain neocortex model, we present a skill learning method by perception-action integration strategy from the perspective of hierarchical temporal memory (HTM theory. The sequential sensor data representing a certain skill from a RGB-D camera are received and then encoded as a sequence of Sparse Distributed Representation (SDR vectors. The sequential SDR vectors are treated as the inputs of the perception-action HTM. The HTM learns sequences of SDRs and makes predictions of what the next input SDR will be. It stores the transitions of the current perceived sensor data and next predicted actions. We evaluated the performance of this proposed framework for learning the shaking hands skill on a humanoid NAO robot. The experimental results manifest that the skill learning method designed in this paper is promising.
Cross, Emily S; Kraemer, David J M; Hamilton, Antonia F de C; Kelley, William M; Grafton, Scott T
Human motor skills can be acquired by observation without the benefit of immediate physical practice. The current study tested if physical rehearsal and observational learning share common neural substrates within an action observation network (AON) including premotor and inferior parietal regions, that is, areas activated both for execution and observation of similar actions. Participants trained for 5 days on dance sequences set to music videos. Each day they physically rehearsed one set of dance sequences ("danced"), and passively watched a different set of sequences ("watched"). Functional magnetic resonance imaging was obtained prior to and immediately following the 5 days of training. After training, a subset of the AON showed a degree of common activity for observational and physical learning. Activity in these premotor and parietal regions was sustained during observation of sequences that were danced or watched, but declined for unfamiliar sequences relative to the pretraining scan session. These imaging data demonstrate the emergence of action resonance processes in the human brain based on observational learning without physical practice and identify commonalities in the neural substrates for physical and observational learning.
Sanromà, G.; Patino, L.; Burghouts, G.J.; Schutte, K.; Ferryman, J.
We present a method for the recognition of complex actions. Our method combines automatic learning of simple actions and manual definition of complex actions in a single grammar. Contrary to the general trend in complex action recognition, that consists in dividing recognition into two stages, our
Morris, Richard W; Cyrzon, Chad; Green, Melissa J; Le Pelley, Mike E; Balleine, Bernard W
Learning the causal relation between actions and their outcomes (AO learning) is critical for goal-directed behavior when actions are guided by desire for the outcome. This can be contrasted with habits that are acquired by reinforcement and primed by prevailing stimuli, in which causal learning plays no part. Recently, we demonstrated that goal-directed actions are impaired in schizophrenia; however, whether this deficit exists alongside impairments in habit or reinforcement learning is unknown. The present study distinguished deficits in causal learning from reinforcement learning in schizophrenia. We tested people with schizophrenia (SZ, n = 25) and healthy adults (HA, n = 25) in a vending machine task. Participants learned two action-outcome contingencies (e.g., push left to get a chocolate M&M, push right to get a cracker), and they also learned one contingency was degraded by delivery of noncontingent outcomes (e.g., free M&Ms), as well as changes in value by outcome devaluation. Both groups learned the best action to obtain rewards; however, SZ did not distinguish the more causal action when one AO contingency was degraded. Moreover, action selection in SZ was insensitive to changes in outcome value unless feedback was provided, and this was related to the deficit in AO learning. The failure to encode the causal relation between action and outcome in schizophrenia occurred without any apparent deficit in reinforcement learning. This implies that poor goal-directed behavior in schizophrenia cannot be explained by a more primary deficit in reward learning such as insensitivity to reward value or reward prediction errors.
This paper researches robot soccer action selection based on Q learning . The robot learn to activate particular behavior given their current situation and reward signal. We adopt neural network to implementations of Q learning for their generalization properties and limited computer memory requirements
Bleicher, Robert E.
The field of professional development is moving towards the notion of professional learning, highlighting the active learning role that teachers play in changing their knowledge bases, beliefs and practice. This article builds on this idea and argues for creating professional learning that is guided by a collaborative action research (CAR)…
Robert D. Sutter; Christopher C. Szell
The identification of conservation priorities is one of the leading issues in conservation biology. We present a project of The Nature Conservancy, called Sequencing Conservation Actions, which prioritizes conservation areas and identifies foci for crosscutting strategies at various geographic scales. We use the term âSequencingâ to mean an ordering of actions over...
Yu, Yue; Kushnir, Tamar
This study explores the role of a particular social cue--the "sequence" of demonstrated actions and events--in preschooler's categorization. A demonstrator sorted objects that varied on both a surface feature (color) and a nonobvious property (sound made when shaken). Children saw a sequence of actions in which the nonobvious property…
HolmesParker, Chris; Taylor, Mathew E.; Tumer, Kagan; Agogino, Adrian
Learning in multiagent systems can be slow because agents must learn both how to behave in a complex environment and how to account for the actions of other agents. The inability of an agent to distinguish between the true environmental dynamics and those caused by the stochastic exploratory actions of other agents creates noise in each agent's reward signal. This learning noise can have unforeseen and often undesirable effects on the resultant system performance. We define such noise as exploratory action noise, demonstrate the critical impact it can have on the learning process in multiagent settings, and introduce a reward structure to effectively remove such noise from each agent's reward signal. In particular, we introduce Coordinated Learning without Exploratory Action Noise (CLEAN) rewards and empirically demonstrate their benefits
Luo, Guan; Yang, Shuang; Tian, Guodong; Yuan, Chunfeng; Hu, Weiming; Maybank, Stephen J
In this paper, we address the problem of human action recognition through combining global temporal dynamics and local visual spatio-temporal appearance features. For this purpose, in the global temporal dimension, we propose to model the motion dynamics with robust linear dynamical systems (LDSs) and use the model parameters as motion descriptors. Since LDSs live in a non-Euclidean space and the descriptors are in non-vector form, we propose a shift invariant subspace angles based distance to measure the similarity between LDSs. In the local visual dimension, we construct curved spatio-temporal cuboids along the trajectories of densely sampled feature points and describe them using histograms of oriented gradients (HOG). The distance between motion sequences is computed with the Chi-Squared histogram distance in the bag-of-words framework. Finally we perform classification using the maximum margin distance learning method by combining the global dynamic distances and the local visual distances. We evaluate our approach for action recognition on five short clips data sets, namely Weizmann, KTH, UCF sports, Hollywood2 and UCF50, as well as three long continuous data sets, namely VIRAT, ADL and CRIM13. We show competitive results as compared with current state-of-the-art methods.
Full Text Available This paper expounds action learning for effective change leadership development using the learning-teaching helix as a paradigm for individual’s introspection. Which consists of five phases—Awareness phase (as certain your strengths and weaknesses. Alignment phase (identify your core competence. Action phase (synthesize your work, business and management skills, Adoption phase (becoming a leader and Assurance phase (excel as an educator cum coach. In addition, to succeed, the individual has to plan, strategize, prioritize and integrate. As a holistic manager the individual needs to think, feel and do to evolve from continuous action learning to the cycle of teaching for continuous innovation in organizational performance capabilities.
Frings, Markus; Boenisch, Raoul; Gerwig, Marcus; Diener, Hans-Christoph; Timmann, Dagmar
A possible role of the cerebellum in detecting and recognizing event sequences has been proposed. The present study sought to determine whether patients with cerebellar lesions are impaired in the acquisition and discrimination of sequences of sensory stimuli of different modalities. A group of 26 cerebellar patients and 26 controls matched for…
Van den Berg, Bert; Tattersall, Colin; Janssen, José; Brouns, Francis; Kurvers, Hub; Koper, Rob
Van den Berg, B., Tattersall, C., Janssen, J., Brouns, F., Kurvers, H., & Koper, R. (2006). Swarm-based Sequencing Recommendations in E-learning. International Journal of Computer Science & Applications, III(III), 1-11.
Full Text Available Acquiring knowledge about the relationship between stimulus conditions, one’s own actions, and the resulting consequences or effects, is one prerequisite for intentional action. Previous studies have shown that such contextualized associations between actions and their effects (S-R-E associations can be picked up very quickly. The present study examined how such weakly practiced associations might affect overt behavior during the process of initial learning and during subsequent retrieval, and how these two measures are inter-related. We examined incidental (S-R-E learning in the context of trial-and-error S-R learning and in the context of instruction-based S-R learning. Furthermore, as a control condition, common outcome (CO learning blocks were included in which all responses produced one common sound effect, hence precluding differential (S-R-E learning. Post-learning retrieval of R-E associations was tested by re-using previously produced sound effects as novel imperative stimuli combined with actions that were either compatible or incompatible with the previously encountered R-E mapping. The central result was that the size of the compatibility effect could be predicted by the size of relative response slowing during ongoing learning in the preceding acquisition phase, both in trial-and-error learning and in instruction-based learning. Importantly, this correlation was absent for the common outcome control condition, precluding accounts based on unspecific factors. Instead, the results suggest that differential outcomes are ‘actively’ integrated into action planning and that this takes additional planning time. We speculate that this might be especially true for weakly practiced (S-R-E associations before an initial goal-directed action mode transitions into a more stimulus-based action mode.
Madhavan, Radhika; Millman, Daniel; Tang, Hanlin; Crone, Nathan E.; Lenz, Fredrick A.; Tierney, Travis S.; Madsen, Joseph R.; Kreiman, Gabriel; Anderson, William S.
Learning novel sequences constitutes an example of declarative memory formation, involving conscious recall of temporal events. Performance in sequence learning tasks improves with repetition and involves forming temporal associations over scales of seconds to minutes. To further understand the neural circuits underlying declarative sequence learning over trials, we tracked changes in intracranial field potentials (IFPs) recorded from 1142 electrodes implanted throughout temporal and frontal cortical areas in 14 human subjects, while they learned the temporal-order of multiple sequences of images over trials through repeated recall. We observed an increase in power in the gamma frequency band (30–100 Hz) in the recall phase, particularly in areas within the temporal lobe including the parahippocampal gyrus. The degree of this gamma power enhancement decreased over trials with improved sequence recall. Modulation of gamma power was directly correlated with the improvement in recall performance. When presenting new sequences, gamma power was reset to high values and decreased again after learning. These observations suggest that signals in the gamma frequency band may play a more prominent role during the early steps of the learning process rather than during the maintenance of memory traces. PMID:25653598
Rosman, Benjamin S
Full Text Available behavioural invariances in the domain, by identifying actions to be prioritised in local contexts, invariant to task details. This information has the effect of greatly increasing the speed of solving new problems. We formalise this notion as action priors...
Sharer, Elizabeth A; Mostofsky, Stewart H; Pascual-Leone, Alvaro; Oberman, Lindsay M
In addition to defining impairments in social communication skills, individuals with autism spectrum disorder (ASD) also show impairments in more basic sensory and motor skills. Development of new skills involves integrating information from multiple sensory modalities. This input is then used to form internal models of action that can be accessed when both performing skilled movements, as well as understanding those actions performed by others. Learning skilled gestures is particularly reliant on integration of visual and proprioceptive input. We used a modified serial reaction time task (SRTT) to decompose proprioceptive and visual components and examine whether patterns of implicit motor skill learning differ in ASD participants as compared with healthy controls. While both groups learned the implicit motor sequence during training, healthy controls showed robust generalization whereas ASD participants demonstrated little generalization when visual input was constant. In contrast, no group differences in generalization were observed when proprioceptive input was constant, with both groups showing limited degrees of generalization. The findings suggest, when learning a motor sequence, individuals with ASD tend to rely less on visual feedback than do healthy controls. Visuomotor representations are considered to underlie imitative learning and action understanding and are thereby crucial to social skill and cognitive development. Thus, anomalous patterns of implicit motor learning, with a tendency to discount visual feedback, may be an important contributor in core social communication deficits that characterize ASD. Autism Res 2016, 9: 563-569. © 2015 International Society for Autism Research, Wiley Periodicals, Inc. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.
Traditional approaches for action detection use trimmed data to learn sophisticated action detector models. Although these methods have achieved great success at detecting human actions, we argue that huge information is discarded when ignoring the process, through which this trimmed data is obtained. In this paper, we propose Action Search, a novel approach that mimics the way people annotate activities in video sequences. Using a Recurrent Neural Network, Action Search can efficiently explore a video and determine the time boundaries during which an action occurs. Experiments on the THUMOS14 dataset reveal that our model is not only able to explore the video efficiently but also accurately find human activities, outperforming state-of-the-art methods.
Garcia, Javier; Fernandez, Fernando
In this paper, we consider the important problem of safe exploration in reinforcement learning. While reinforcement learning is well-suited to domains with complex transition dynamics and high-dimensional state-action spaces, an additional challenge is posed by the need for safe and efficient exploration. Traditional exploration techniques are not particularly useful for solving dangerous tasks, where the trial and error process may lead to the selection of actions whose execution in some sta...
Tempelaar, Dirk; Rienties, Bart; Nguyen, Quan
Studies in the field of learning analytics (LA) have shown students’ demographics and learning management system (LMS) data to be effective identifiers of “at risk” performance. However, insights generated by these predictive models may not be suitable for pedagogically informed interventions due to
Tempelaar, Dirk T.; Rienties, Bart; Nguyen, Quan
Studies in the field of learning analytics (LA) have shown students' demographics and learning management system (LMS) data to be effective identifiers of "at risk" performance. However, insights generated by these predictive models may not be suitable for pedagogically informed interventions due to the inability to explain why students…
Lieblein, Geir; Breland, Tor Arvid; Francis, Charles; Ostergaard, Edvin
Purpose: This article examines and evaluates the potential contributions from action learning and action research with stakeholders to higher education in agriculture and food systems. Design/Methodology/Approach: The research is based on our experiences over the past two decades of running PhD courses and an MSc degree programme in Agroecology in…
Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E; Kourtzi, Zoe
Human behavior is guided by our expectations about the future. Often, we make predictions by monitoring how event sequences unfold, even though such sequences may appear incomprehensible. Event structures in the natural environment typically vary in complexity, from simple repetition to complex probabilistic combinations. How do we learn these structures? Here we investigate the dynamics of structure learning by tracking human responses to temporal sequences that change in structure unbeknownst to the participants. Participants were asked to predict the upcoming item following a probabilistic sequence of symbols. Using a Markov process, we created a family of sequences, from simple frequency statistics (e.g., some symbols are more probable than others) to context-based statistics (e.g., symbol probability is contingent on preceding symbols). We demonstrate the dynamics with which individuals adapt to changes in the environment's statistics-that is, they extract the behaviorally relevant structures to make predictions about upcoming events. Further, we show that this structure learning relates to individual decision strategy; faster learning of complex structures relates to selection of the most probable outcome in a given context (maximizing) rather than matching of the exact sequence statistics. Our findings provide evidence for alternate routes to learning of behaviorally relevant statistics that facilitate our ability to predict future events in variable environments.
Conway, Christopher M; Pisoni, David B; Anaya, Esperanza M; Karpicke, Jennifer; Henning, Shirley C
Deaf children with cochlear implants (CIs) represent an intriguing opportunity to study neurocognitive plasticity and reorganization when sound is introduced following a period of auditory deprivation early in development. Although it is common to consider deafness as affecting hearing alone, it may be the case that auditory deprivation leads to more global changes in neurocognitive function. In this paper, we investigate implicit sequence learning abilities in deaf children with CIs using a novel task that measured learning through improvement to immediate serial recall for statistically consistent visual sequences. The results demonstrated two key findings. First, the deaf children with CIs showed disturbances in their visual sequence learning abilities relative to the typically developing normal-hearing children. Second, sequence learning was significantly correlated with a standardized measure of language outcome in the CI children. These findings suggest that a period of auditory deprivation has secondary effects related to general sequencing deficits, and that disturbances in sequence learning may at least partially explain why some deaf children still struggle with language following cochlear implantation. © 2010 Blackwell Publishing Ltd.
In the current climate of economic ‘austerity’, organisational learning has increasingly gained importance, and a need for new ways of transferring learning has been identified. Organisational learning is seen as key to organisational success, ensuring both competitive advantage and organisational longevity. However, in order for organisations to keep pace with change they must not only strive to learn but also pay attention to how they might learn. A dominant view within the field of organis...
Aguilar, Jessica M.; Plante, Elena
Purpose: Two studies examined learning of grammar-like visual sequences to determine whether a general deficit in statistical learning characterizes this population. Furthermore, we tested the hypothesis that difficulty in sustaining attention during the learning task might account for differences in statistical learning. Method: In Study 1,…
Cho, Yonjoo; Egan, Toby
The purpose of this study was (1) to examine the impact of organizational support on employee learning and performance and (2) to elaborate on the context of organizational support for action learning in South Korean organizations. For this inquiry, two central questions were posed: What are employee reactions to organizational support for action…
Wang, Chien-hsing; Ke, Yi-Ting; Wu, Jin-Tong; Hsu, Wen-Hua
This paper briefly reports the outcomes of an action research inquiry on the use of blogs, MS PowerPoint [PPT], and the Internet as learning tools with a science class of sixth graders for project-based learning. Multiple sources of data were essential to triangulate the key findings articulated in this paper. Corresponding to previous studies,…
Full Text Available The article presents a three-year educational action research project on autonomous and reflective learning. Students and teachers, being actively engaged in many learning practices, were both participating in process(es of developing educational and research community. These interrelated processes framed a dynamic space for constructing and reconstructing the participants’ learning cultures. Thanks to linking educational and research aspects of students’ activity and to interpenetration of practice and reflection, action research generates particular conditions for learning cultures’ transformation, from “traditional” toward “new” ones, based on reflectivity, authenticity and empowerment. The dynamism of learning cultures was connected to various and conscious and reflective types of educational participation, which affected autonomy of studying (in its numerous dimensions and types, being in turn a constitutive element of participants’ learning cultures.
Brink, Tove; Madsen, Svend Ole
Purpose: This paper reveals how managers of small- and medium-sized enterprises (SMEs) can utilise their participation in research-based training to enable innovation and growth. Design/methodology/approach: Action research and action learning from a longitudinal study of 10 SME managers...... in the wind turbine industry are conducted to reveal SME managers learning and the impact of the application of learning in the wind turbine industry. Findings: The findings of this study show that SME managers employ a practice-shaped holistic cross-disciplinary approach to learning. This learning approach...... is supported by theory dissemination and collaboration on the business challenges perceived. Open mindedness to new learning by SME managers and to cross-disciplinary collaboration with SME managers by university facilitators/ researchers is required. Research limitations/implications: The research...
Wang, Jue; Cherian, Anoop; Porikli, Fatih
Training of Convolutional Neural Networks (CNNs) on long video sequences is computationally expensive due to the substantial memory requirements and the massive number of parameters that deep architectures demand. Early fusion of video frames is thus a standard technique, in which several consecutive frames are first agglomerated into a compact representation, and then fed into the CNN as an input sample. For this purpose, a summarization approach that represents a set of consecutive RGB fram...
This paper explores the practice of action learning (AL) facilitation in supporting AL set members to address their 'messy' problems through a self-reflexive approach using the concept of 'living theory' [Whitehead, J., and J. McNiff. 2006. "Action Research Living Theory." London: Sage]. The facilitation practice is investigated through…
Stephan Alexander eVerschoor
Full Text Available Ideomotor theories claim that carrying out a movement that produces a perceivable effect creates a bidirectional association between the two, which can be used by action control processes to retrieve the associated action by anticipating its outcome. Indeed, previous implicit-learning studies have shown that practice renders novel but action-contingent stimuli effective retrieval cues of the action they used to follow, suggesting that experiencing sequences of actions and effects creates bidirectional action-effect associations. We investigated whether action-effect associations are also acquired under explicit-learning conditions and whether familiar action-effect relations (such as between a trumpet and a trumpet sound are learned the same way as novel, arbitrary relations are. We also investigated whether these factors affect adults and 4-year-old children equally. Our findings suggest that explicit learning produces the same bidirectional action-effect associations as implicit learning does, that non-arbitrary relations improve performance without affecting learning per se, and that adults and young children show equivalent performance—apart from the common observation that children have greater difficulty to withstand stimulus-induced action tendencies.
Wood, Justin N; Prasad, Aditya; Goldman, Jason G; Wood, Samantha M W
To what extent are newborn brains designed to operate over natural visual input? To address this question, we used a high-throughput controlled-rearing method to examine whether newborn chicks (Gallus gallus) show enhanced learning of natural visual sequences at the onset of vision. We took the same set of images and grouped them into either natural sequences (i.e., sequences showing different viewpoints of the same real-world object) or unnatural sequences (i.e., sequences showing different images of different real-world objects). When raised in virtual worlds containing natural sequences, newborn chicks developed the ability to recognize familiar images of objects. Conversely, when raised in virtual worlds containing unnatural sequences, newborn chicks' object recognition abilities were severely impaired. In fact, the majority of the chicks raised with the unnatural sequences failed to recognize familiar images of objects despite acquiring over 100 h of visual experience with those images. Thus, newborn chicks show enhanced learning of natural visual sequences at the onset of vision. These results indicate that newborn brains are designed to operate over natural visual input.
Ellmer, Eva; Rynne, Steven
The exponential growth in action and adventure sport (e.g. snowboarding, bicycle motorcross (BMX), surfing, parkour) participation over the past two decades has been showcased in world championship events and the inclusion in Olympic programs. Yet, by virtue of their alternative, escapist and/or adventure-based origins, these sports do not fully…
Full Text Available The ability to learn sequential behaviors is a fundamental property of our brains. Yet a long stream of studies including recent experiments investigating motor sequence learning in adult human subjects have produced a number of puzzling and seemingly contradictory results. In particular, when subjects have to learn multiple action sequences, learning is sometimes impaired by proactive and retroactive interference effects. In other situations, however, learning is accelerated as reflected in facilitation and transfer effects. At present it is unclear what the underlying neural mechanism are that give rise to these diverse findings. Here we show that a recently developed recurrent neural network model readily reproduces this diverse set of findings. The self-organizing recurrent neural network (SORN model is a network of recurrently connected threshold units that combines a simplified form of spike-timing dependent plasticity (STDP with homeostatic plasticity mechanisms ensuring network stability, namely intrinsic plasticity (IP and synaptic normalization (SN. When trained on sequence learning tasks modeled after recent experiments we find that it reproduces the full range of interference, facilitation, and transfer effects. We show how these effects are rooted in the network's changing internal representation of the different sequences across learning and how they depend on an interaction of training schedule and task similarity. Furthermore, since learning in the model is based on fundamental neuronal plasticity mechanisms, the model reveals how these plasticity mechanisms are ultimately responsible for the network's sequence learning abilities. In particular, we find that all three plasticity mechanisms are essential for the network to learn effective internal models of the different training sequences. This ability to form effective internal models is also the basis for the observed interference and facilitation effects. This suggests that
Stark-Inbar, Alit; Raza, Meher; Taylor, Jordan A; Ivry, Richard B
In standard taxonomies, motor skills are typically treated as representative of implicit or procedural memory. We examined two emblematic tasks of implicit motor learning, sensorimotor adaptation and sequence learning, asking whether individual differences in learning are correlated between these tasks, as well as how individual differences within each task are related to different performance variables. As a prerequisite, it was essential to establish the reliability of learning measures for each task. Participants were tested twice on a visuomotor adaptation task and on a sequence learning task, either the serial reaction time task or the alternating reaction time task. Learning was evident in all tasks at the group level and reliable at the individual level in visuomotor adaptation and the alternating reaction time task but not in the serial reaction time task. Performance variability was predictive of learning in both domains, yet the relationship was in the opposite direction for adaptation and sequence learning. For the former, faster learning was associated with lower variability, consistent with models of sensorimotor adaptation in which learning rates are sensitive to noise. For the latter, greater learning was associated with higher variability and slower reaction times, factors that may facilitate the spread of activation required to form predictive, sequential associations. Interestingly, learning measures of the different tasks were not correlated. Together, these results oppose a shared process for implicit learning in sensorimotor adaptation and sequence learning and provide insight into the factors that account for individual differences in learning within each task domain. We investigated individual differences in the ability to implicitly learn motor skills. As a prerequisite, we assessed whether individual differences were reliable across test sessions. We found that two commonly used tasks of implicit learning, visuomotor adaptation and the
Zheng, Jingjing; Jiang, Zhuolin; Chellappa, Rama
Discriminative appearance features are effective for recognizing actions in a fixed view, but may not generalize well to a new view. In this paper, we present two effective approaches to learn dictionaries for robust action recognition across views. In the first approach, we learn a set of view-specific dictionaries where each dictionary corresponds to one camera view. These dictionaries are learned simultaneously from the sets of correspondence videos taken at different views with the aim of encouraging each video in the set to have the same sparse representation. In the second approach, we additionally learn a common dictionary shared by different views to model view-shared features. This approach represents the videos in each view using a view-specific dictionary and the common dictionary. More importantly, it encourages the set of videos taken from the different views of the same action to have the similar sparse representations. The learned common dictionary not only has the capability to represent actions from unseen views, but also makes our approach effective in a semi-supervised setting where no correspondence videos exist and only a few labeled videos exist in the target view. The extensive experiments using three public datasets demonstrate that the proposed approach outperforms recently developed approaches for cross-view action recognition.
Catmur, Caroline; Heyes, Cecilia
Imitation is important in the development of social and technological skills throughout the lifespan. Experiments investigating the acquisition and modulation of imitation (and of its proposed neural substrate, the mirror neuron system) have produced evidence that the capacity for imitation depends on associative learning in which connections are formed between sensory and motor representations of actions. However, evidence that the development of imitation depends on associative learning has been found only for non-goal-directed actions. One reason for the lack of research on goal-directed actions is that imitation of such actions is commonly confounded with the tendency to respond in a spatially compatible manner. However, since the most prominent account of mirror neuron function, and hence of imitation, suggests that these cells encode goal-directed actions, it is important to establish whether sensorimotor learning can also modulate imitation of goal-directed actions. Experiment 1 demonstrated that imitation of goal-directed grasping can be measured while controlling for spatial compatibility, and Experiment 2 showed that this imitation effect can be modulated by sensorimotor training. Together these data support the hypothesis that the capacity for behavioural imitation, and the properties of the mirror neuron system, are constructed in the course of development through associative learning.
Scott, Fiona M.; Butler, Jim; Edwards, John
An action learning program was implemented by a manufacturer using lean production practices. Action learning practices were accommodated during times of stability, but abandoned in times of crisis. The meaning of work in this organizational culture excluded all practices, such as reflection, that were not visible and targeted at immediate…
Full Text Available First identified as an issue in 1996, duplication in biological databases introduces redundancy and even leads to inconsistency when contradictory information appears. The amount of data makes purely manual de-duplication impractical, and existing automatic systems cannot detect duplicates as precisely as can experts. Supervised learning has the potential to address such problems by building automatic systems that learn from expert curation to detect duplicates precisely and efficiently. While machine learning is a mature approach in other duplicate detection contexts, it has seen only preliminary application in genomic sequence databases.We developed and evaluated a supervised duplicate detection method based on an expert curated dataset of duplicates, containing over one million pairs across five organisms derived from genomic sequence databases. We selected 22 features to represent distinct attributes of the database records, and developed a binary model and a multi-class model. Both models achieve promising performance; under cross-validation, the binary model had over 90% accuracy in each of the five organisms, while the multi-class model maintains high accuracy and is more robust in generalisation. We performed an ablation study to quantify the impact of different sequence record features, finding that features derived from meta-data, sequence identity, and alignment quality impact performance most strongly. The study demonstrates machine learning can be an effective additional tool for de-duplication of genomic sequence databases. All Data are available as described in the supplementary material.
Chen, Qingyu; Zobel, Justin; Zhang, Xiuzhen; Verspoor, Karin
First identified as an issue in 1996, duplication in biological databases introduces redundancy and even leads to inconsistency when contradictory information appears. The amount of data makes purely manual de-duplication impractical, and existing automatic systems cannot detect duplicates as precisely as can experts. Supervised learning has the potential to address such problems by building automatic systems that learn from expert curation to detect duplicates precisely and efficiently. While machine learning is a mature approach in other duplicate detection contexts, it has seen only preliminary application in genomic sequence databases. We developed and evaluated a supervised duplicate detection method based on an expert curated dataset of duplicates, containing over one million pairs across five organisms derived from genomic sequence databases. We selected 22 features to represent distinct attributes of the database records, and developed a binary model and a multi-class model. Both models achieve promising performance; under cross-validation, the binary model had over 90% accuracy in each of the five organisms, while the multi-class model maintains high accuracy and is more robust in generalisation. We performed an ablation study to quantify the impact of different sequence record features, finding that features derived from meta-data, sequence identity, and alignment quality impact performance most strongly. The study demonstrates machine learning can be an effective additional tool for de-duplication of genomic sequence databases. All Data are available as described in the supplementary material.
Hori, Takayuki; Ohya, Jun; Kurumisawa, Jun
This paper proposes a Tensor Decomposition Based method that can recognize an unknown person's action from a video sequence, where the unknown person is not included in the database (tensor) used for the recognition. The tensor consists of persons, actions and time-series image features. For the observed unknown person's action, one of the actions stored in the tensor is assumed. Using the motion signature obtained from the assumption, the unknown person's actions are synthesized. The actions of one of the persons in the tensor are replaced by the synthesized actions. Then, the core tensor for the replaced tensor is computed. This process is repeated for the actions and persons. For each iteration, the difference between the replaced and original core tensors is computed. The assumption that gives the minimal difference is the action recognition result. For the time-series image features to be stored in the tensor and to be extracted from the observed video sequence, the human body silhouette's contour shape based feature is used. To show the validity of our proposed method, our proposed method is experimentally compared with Nearest Neighbor rule and Principal Component analysis based method. Experiments using 33 persons' seven kinds of action show that our proposed method achieves better recognition accuracies for the seven actions than the other methods.
Gershman, Samuel J.; Pesaran, Bijan; Daw, Nathaniel D.
Humans and animals are endowed with a large number of effectors. Although this enables great behavioral flexibility, it presents an equally formidable reinforcement learning problem of discovering which actions are most valuable, due to the high dimensionality of the action space. An unresolved question is how neural systems for reinforcement learning – such as prediction error signals for action valuation associated with dopamine and the striatum – can cope with this “curse of dimensionality...
Boyd Lara A
Full Text Available Abstract Background Recent work has demonstrated the importance of proprioception for the development of internal representations of the forces encountered during a task. Evidence also exists for a significant role for proprioception in the execution of sequential movements. However, little work has explored the role of proprioceptive sensation during the learning of continuous movement sequences. Here, we report that the repeated segment of a continuous tracking task can be learned despite peripherally altered arm proprioception and severely restricted visual feedback regarding motor output. Methods Healthy adults practiced a continuous tracking task over 2 days. Half of the participants experienced vibration that altered proprioception of shoulder flexion/extension of the active tracking arm (experimental condition and half experienced vibration of the passive resting arm (control condition. Visual feedback was restricted for all participants. Retention testing was conducted on a separate day to assess motor learning. Results Regardless of vibration condition, participants learned the repeated segment demonstrated by significant improvements in accuracy for tracking repeated as compared to random continuous movement sequences. Conclusion These results suggest that with practice, participants were able to use residual afferent information to overcome initial interference of tracking ability related to altered proprioception and restricted visual feedback to learn a continuous motor sequence. Motor learning occurred despite an initial interference of tracking noted during acquisition practice.
Loucks, Jeff; Mutschler, Christina; Meltzoff, Andrew N
Children's imitation of adults plays a prominent role in human cognitive development. However, few studies have investigated how children represent the complex structure of observed actions which underlies their imitation. We integrate theories of action segmentation, memory, and imitation to investigate whether children's event representation is organized according to veridical serial order or a higher level goal structure. Children were randomly assigned to learn novel event sequences either through interactive hands-on experience (Study 1) or via storybook (Study 2). Results demonstrate that children's representation of observed actions is organized according to higher level goals, even at the cost of representing the veridical temporal ordering of the sequence. We argue that prioritizing goal structure enhances event memory, and that this mental organization is a key mechanism of social-cognitive development in real-world, dynamic environments. It supports cultural learning and imitation in ecologically valid settings when social agents are multitasking and not demonstrating one isolated goal at a time. Copyright © 2016 Cognitive Science Society, Inc.
Piater, Justus; Jodogne, Sebastien; Detry, Renaud
and RLJC, our second method learns structural object models for robust object detection and pose estimation by probabilistic inference. To these models, the method associates grasp experiences autonomously learned by trial and error. These experiences form a nonparametric representation of grasp success......We discuss vision as a sensory modality for systems that effect actions in response to perceptions. While the internal representations informed by vision may be arbitrarily complex, we argue that in many cases it is advantageous to link them rather directly to action via learned mappings....... These arguments are illustrated by two examples of our own work. First, our RLVC algorithm performs reinforcement learning directly on the visual input space. To make this very large space manageable, RLVC interleaves the reinforcement learner with a supervised classification algorithm that seeks to split...
Fichtl, Severin; Kraft, Dirk; Krüger, Norbert
The outcome of many complex manipulation ac- tions is contingent on the spatial relationships among pairs of objects, e.g. if an object is “inside” or “on top” of another. Recognising these spatial relationships requires a vision system which can extract appropriate features from the vision input...... that capture and represent the spatial relationships in an easily accessible way. We are interested in learning to predict the success of “means end” actions that manipulate two objects at once, from exploratory actions, and the observed sensorimo- tor contingencies. In this paper, we use relational histogram...... features and illustrate their effect on learning to predict a variety of “means end” actions’ outcomes. The results show that our vision features can make the learning problem significantly easier, leading to increased learning rates and higher maximum performance. This work is in particular important...
Dayarian, Adel; Shraiman, Boris
Recent advances in sequencing and in laboratory evolution experiments have made possible to obtain quantitative data on genetic diversity of populations and on the dynamics of evolution. This dynamics is shaped by the interplay between selection acting on beneficial and deleterious mutations and recombination which reshuffles genotypes. Mounting evidence suggests that natural populations harbor extensive fitness diversity, yet most of the currently available tools for analyzing polymorphism data are based on the neutral theory. Our aim is to develop methods to analyze genomic data for populations in the presence of the above-mentioned factors. We consider different evolutionary regimes - Muller's ratchet, mutation-recombination-selection balance and positive adaption rate - and revisit a number of observables considered in the nearly-neutral theory of evolution. In particular, we examine the coalescent structure in the presence of recombination and calculate quantities such as the distribution of the coalescent times along the genome, the distribution of haplotype block sizes and the correlation between ancestors of different loci along the genome. In addition, we characterize the probability and time of fixation of mutations as a function of their fitness effect.
Wu, Hongjie; Cao, Chengyuan; Xia, Xiaoyan; Lu, Qiang
Prediction of the spatial structure or function of biological macromolecules based on their sequence remains an important challenge in bioinformatics. When modeling biological sequences using traditional sequencing models, characteristics, such as long-range interactions between basic units, the complicated and variable output of labeled structures, and the variable length of biological sequences, usually lead to different solutions on a case-by-case basis. This study proposed the use of bidirectional recurrent neural networks based on long short-term memory or a gated recurrent unit to capture long-range interactions by designing the optional reshape operator to adapt to the diversity of the output labels and implementing a training algorithm to support the training of sequence models capable of processing variable-length sequences. Additionally, the merge and pooling operators enhanced the ability to capture short-range interactions between basic units of biological sequences. The proposed deep-learning model and its training algorithm might be capable of solving currently known biological sequence-modeling problems through the use of a unified framework. We validated our model on one of the most difficult biological sequence-modeling problems currently known, with our results indicating the ability of the model to obtain predictions of protein residue interactions that exceeded the accuracy of current popular approaches by 10% based on multiple benchmarks.
Király, Ildikó; Csibra, Gergely; Gergely, György
The principle of rationality has been invoked to explain that infants expect agents to perform the most efficient means action to attain a goal. It has also been demonstrated that infants take into account the efficiency of observed actions to achieve a goal outcome when deciding whether to reenact a specific behavior or not. It is puzzling, however, that they also tend to imitate an apparently suboptimal unfamiliar action even when they can bring about the same outcome more efficiently by applying a more rational action alternative available to them. We propose that this apparently paradoxical behavior is explained by infants' interpretation of action demonstrations as communicative manifestations of novel and culturally relevant means actions to be acquired, and we present empirical evidence supporting this proposal. In Experiment 1, we found that 14-month-olds reenacted novel arbitrary means actions only following a communicative demonstration. Experiment 2 showed that infants' inclination to reproduce communicatively manifested novel actions is restricted to behaviors they can construe as goal-directed instrumental acts. The study also provides evidence that infants' reenactment of the demonstrated novel actions reflects epistemic motives rather than purely social motives. We argue that ostensive communication enables infants to represent the teleological structure of novel actions even when the causal relations between means and end are cognitively opaque and apparently violate the efficiency expectation derived from the principle of rationality. This new account of imitative learning of novel means shows how the teleological stance and natural pedagogy--two separate cognitive adaptations to interpret instrumental versus communicative actions--are integrated as a system for learning socially constituted instrumental knowledge in humans. Copyright © 2013 Elsevier Inc. All rights reserved.
New product development and commercialization are essential to entrepreneurial growth and international competitiveness. Excellence in this area is strongly supported by individual and organizational learning efforts. By analyzing how Japanese car manufacturer Toyota organizes learning, this paper evaluates the potential of action learning to…
Taber, Jennifer M; Klein, William M P; Ferrer, Rebecca A; Lewis, Katie L; Biesecker, Leslie G; Biesecker, Barbara B
Dispositional optimism and risk perceptions are each associated with health-related behaviors and decisions and other outcomes, but little research has examined how these constructs interact, particularly in consequential health contexts. The predictive validity of risk perceptions for health-related information seeking and intentions may be improved by examining dispositional optimism as a moderator, and by testing alternate types of risk perceptions, such as comparative and experiential risk. Participants (n = 496) had their genomes sequenced as part of a National Institutes of Health pilot cohort study (ClinSeq®). Participants completed a cross-sectional baseline survey of various types of risk perceptions and intentions to learn genome sequencing results for differing disease risks (e.g., medically actionable, nonmedically actionable, carrier status) and to use this information to change their lifestyle/health behaviors. Risk perceptions (absolute, comparative, and experiential) were largely unassociated with intentions to learn sequencing results. Dispositional optimism and comparative risk perceptions interacted, however, such that individuals higher in optimism reported greater intentions to learn all 3 types of sequencing results when comparative risk was perceived to be higher than when it was perceived to be lower. This interaction was inconsistent for experiential risk and absent for absolute risk. Independent of perceived risk, participants high in dispositional optimism reported greater interest in learning risks for nonmedically actionable disease and carrier status, and greater intentions to use genome information to change their lifestyle/health behaviors. The relationship between risk perceptions and intentions may depend on how risk perceptions are assessed and on degree of optimism. (c) 2015 APA, all rights reserved.
Philip J Tully
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.
Full Text Available In this paper, we announce the development of Neural Monkey – an open-source neural machine translation (NMT and general sequence-to-sequence learning system built over the TensorFlow machine learning library. The system provides a high-level API tailored for fast prototyping of complex architectures with multiple sequence encoders and decoders. Models’ overall architecture is specified in easy-to-read configuration files. The long-term goal of the Neural Monkey project is to create and maintain a growing collection of implementations of recently proposed components or methods, and therefore it is designed to be easily extensible. Trained models can be deployed either for batch data processing or as a web service. In the presented paper, we describe the design of the system and introduce the reader to running experiments using Neural Monkey.
Full Text Available A primate study reported the existence of neurons from the dorso-lateral prefrontal cortex which fired prior to executing categorical action sequences. The authors suggested these activities may represent abstract level information. Here, we aimed to find the neurophysiological representation of planning categorical action sequences at the population level in healthy humans. Previous human studies have shown beta-band event-related desynchronization (ERD during action planning in humans. Some of these studies showed different levels of ERD according to different types of action preparation. Especially, the literature suggests that variations in cognitive factors rather than physical factors (force, direction, etc modulate the level of beta-ERD. We hypothesized that the level of beta-band power will differ according to planning of different categorical sequences. We measured magnetoencephalography (MEG from 22 subjects performing 11 four-sequence actions--each consisting of one or two of three simple actions--in 3 categories; 'Paired (ooxx', 'Alternative (oxox' and 'Repetitive (oooo' ('o' and 'x' each denoting one of three simple actions. Time-frequency representations were calculated for each category during the planning period, and the corresponding beta-power time-courses were compared. We found beta-ERD during the planning period for all subjects, mostly in the contralateral fronto-parietal areas shortly after visual cue onset. Power increase (transient rebound followed ERD in 20 out of 22 subjects. Amplitudes differed among categories in 20 subjects for both ERD and transient rebound. In 18 out of 20 subjects 'Repetitive' category showed the largest ERD and rebound. The current result suggests that beta-ERD in the contralateral frontal/motor/parietal areas during planning is differentiated by the category of action sequences.
Maier, Carmen Daniela
In order to secure correct understanding of environmental issues, to promote behavioral change and to encourage environmental action, more and more educational practices support and provide environmental programs. This article explores the design of online learning resources created for teachers...... and students by the GreenLearning environmental education program. The topic is approached from a social semiotic perspective. I conduct a multimodal analysis of the knowledge processes and the knowledge selection types that characterize the GreenLearning environmental education program and its online...
Jurjen van der Helden
Full Text Available Mankind is unique in her ability for observational learning, i.e. the transmission of acquired knowledge and behavioral repertoire through observation of others' actions. In the present study we used electrophysiological measures to investigate brain mechanisms of observational learning. Analysis investigated the possible functional coupling between occipital (alpha and motor (mu rhythms operating in the 10 Hz frequency range for translating "seeing" into "doing". Subjects observed movement sequences consisting of six consecutive left or right hand button presses directed at one of two target-buttons for subsequent imitation. Each movement sequence was presented four times, intervened by short pause intervals for sequence rehearsal. During a control task subjects observed the same movement sequences without a requirement for subsequent reproduction. Although both alpha and mu rhythms desynchronized during the imitation task relative to the control task, modulations in alpha and mu power were found to be largely independent from each other over time, arguing against a functional coupling of alpha and mu generators during observational learning. This independence was furthermore reflected in the absence of coherence between occipital and motor electrodes overlaying alpha and mu generators. Instead, coherence analysis revealed a pair of symmetric fronto-parietal networks, one over the left and one over the right hemisphere, reflecting stronger coherence during observation of movements than during pauses. Individual differences in fronto-parietal coherence were furthermore found to predict imitation accuracy. The properties of these networks, i.e. their fronto-parietal distribution, their ipsilateral organization and their sensitivity to the observation of movements, match closely with the known properties of the mirror neuron system (MNS as studied in the macaque brain. These results indicate a functional dissociation between higher order areas for
Molnar-Szakacs, Istvan; Kaplan, Jonas; Greenfield, Patricia M; Iacoboni, Marco
A fronto-parietal mirror neuron network in the human brain supports the ability to represent and understand observed actions allowing us to successfully interact with others and our environment. Using functional magnetic resonance imaging (fMRI), we wanted to investigate the response of this network in adults during observation of hierarchically organized action sequences of varying complexity that emerge at different developmental stages. We hypothesized that fronto-parietal systems may play a role in coding the hierarchical structure of object-directed actions. The observation of all action sequences recruited a common bilateral network including the fronto-parietal mirror neuron system and occipito-temporal visual motion areas. Activity in mirror neuron areas varied according to the motoric complexity of the observed actions, but not according to the developmental sequence of action structures, possibly due to the fact that our subjects were all adults. These results suggest that the mirror neuron system provides a fairly accurate simulation process of observed actions, mimicking internally the level of motoric complexity. We also discuss the results in terms of the links between mirror neurons, language development and evolution.
Eckstein, E.; Veenhoven, G.; De Loo, I.G.M.
Becoming a 'winning organization' when one currently is an 'ugly ducking' can be a difficult and strenuous task. BAT Niemeyer in the Netherlands succeeded in making such a transformation over the course of four years. Action learning was used, among other methods, to steer part of this
2. To describe the learning environment of typical classrooms in. South African ... a more teacher-centred approach to more constructivist teaching ap- proaches and ... control over their lives within a framework promoted through action research ... cycles of questioning, planning, implementing, collecting data and reflecting ...
Hite, Linda M.
In a college course on diversity in the workplace, students' experiences with conducting a cultural audit of the university as a workplace illustrate the dilemmas that can arise when students conduct action research in a real client system. Despite the inherent problems, the project resulted in significant student learning about the subject and…
Eckstein, Emiel; Veenhoven, Gert; De Loo, Ivo
Becoming a "winning organization" when one currently is an "ugly ducking" can be a difficult and strenuous task. BAT Niemeyer in the Netherlands succeeded in making such a transformation over the course of four years. Action learning was used, among other methods, to steer part of this transformation, in which employee…
Mitchener, Carole P.; Jackson, Wendy M.
In this article, we present a case study of a beginning science teacher's year-long action research project, during which she developed a meaningful grasp of learning from practice. Wendy was a participant in the middle grade science program designed for career changers from science professions who had moved to teaching middle grade science. An…
This paper explores the combination of storytelling and reflective action research as a means to effect change and learning within and across communities and organizations. Taking the complex challenge of "pro-environmental behaviour change" as an example, the paper reflects on the experiences of a pilot project run for the UK government…
Full Text Available This article positions participatory action learning and action research (PALAR as a preferred methodology for community-university partnerships to achieve a holistic outcome that benefits the common interest. Evidence for this claim is illustrated through case studies of two community engagement programs, one in South Africa and the other in Australia. The South African study explains how relationships, reflection and recognition (the three R’s of PALAR are important elements that promote a truly participatory approach to knowledge creation and practical improvement in social circumstances. The Australian study then highlights what can be achieved. It does this by showing the potential for PALAR participants to learn how to design and implement a community engagement program, and how to cascade their own learning into their community to improve educational opportunities. Both studies demonstrate PALAR’s potential to disrupt traditional understandings of the research process, particularly in terms of researcher–participant relationships. At the same time, both studies identify the challenges arising from the theoretical and practical implications of PALAR as an approach to community development. This article is therefore significant for universities and funding organisations engaging in community-based research and development through partnerships, specifically in contexts of disadvantage. Keywords: Participatory action learning and action research, PALAR, community development, community engagement, community partnerships, disadvantaged communities, higher education.
Full Text Available Recognizing human actions in videos is an active topic with broad commercial potentials. Most of the existing action recognition methods are supposed to have the same camera view during both training and testing. And thus performances of these single-view approaches may be severely influenced by the camera movement and variation of viewpoints. In this paper, we address the above problem by utilizing videos simultaneously recorded from multiple views. To this end, we propose a learning framework based on multitask random forest to exploit a discriminative mid-level representation for videos from multiple cameras. In the first step, subvolumes of continuous human-centered figures are extracted from original videos. In the next step, spatiotemporal cuboids sampled from these subvolumes are characterized by multiple low-level descriptors. Then a set of multitask random forests are built upon multiview cuboids sampled at adjacent positions and construct an integrated mid-level representation for multiview subvolumes of one action. Finally, a random forest classifier is employed to predict the action category in terms of the learned representation. Experiments conducted on the multiview IXMAS action dataset illustrate that the proposed method can effectively recognize human actions depicted in multiview videos.
McGill, Ian; Beaty, Liz
Action learning is a process of learning and reflection that happens with the support of a group of colleagues ("set") working with real problems with the intention of getting things done. This guide is for those who want to practice action learning. It can be used to introduce the concepts of action learning to others and as a manual…
Full Text Available BACKGROUND: It is well documented that positive rather than negative moods encourage integrative processing of conscious information. However, the extent to which implicit or unconscious learning can be influenced by affective states remains unclear. METHODOLOGY/PRINCIPAL FINDINGS: A Serial Reaction Time (SRT task with sequence structures requiring integration over past trials was adopted to examine the effect of affective states on implicit learning. Music was used to induce and maintain positive and negative affective states. The present study showed that participants in negative rather than positive states learned less of the regularity. Moreover, the knowledge was shown by a Bayesian analysis to be largely unconscious as participants were poor at recognizing the regularity. CONCLUSIONS/SIGNIFICANCE: The results demonstrated that negative rather than positive affect inhibited implicit learning of complex structures. Our findings help to understand the effects of affective states on unconscious or implicit processing.
Wang, Chien-Hsing; Ke, Yi-Ting; Wu, Jin-Tong; Hsu, Wen-Hua
This paper briefly reports the outcomes of an action research inquiry on the use of blogs, MS PowerPoint [PPT], and the Internet as learning tools with a science class of sixth graders for project-based learning. Multiple sources of data were essential to triangulate the key findings articulated in this paper. Corresponding to previous studies, the incorporation of technology and project-based learning could motivate students in self-directed exploration. The students were excited about the autonomy over what to learn and the use of PPT to express what they learned. Differing from previous studies, the findings pointed to the lack information literacy among students. The students lacked information evaluation skills, note-taking and information synthesis. All these findings imply the importance of teaching students about information literacy and visual literacy when introducing information technology into the classroom. The authors suggest that further research should focus on how to break the culture of "copy-and-paste" by teaching the skills of note-taking and synthesis through inquiry projects for science learning. Also, further research on teacher professional development should focus on using collaboration action research as a framework for re-designing graduate courses for science teachers in order to enhance classroom technology integration.
Little, Daniel Y; Sommer, Friedrich T
Discovering the structure underlying observed data is a recurring problem in machine learning with important applications in neuroscience. It is also a primary function of the brain. When data can be actively collected in the context of a closed action-perception loop, behavior becomes a critical determinant of learning efficiency. Psychologists studying exploration and curiosity in humans and animals have long argued that learning itself is a primary motivator of behavior. However, the theoretical basis of learning-driven behavior is not well understood. Previous computational studies of behavior have largely focused on the control problem of maximizing acquisition of rewards and have treated learning the structure of data as a secondary objective. Here, we study exploration in the absence of external reward feedback. Instead, we take the quality of an agent's learned internal model to be the primary objective. In a simple probabilistic framework, we derive a Bayesian estimate for the amount of information about the environment an agent can expect to receive by taking an action, a measure we term the predicted information gain (PIG). We develop exploration strategies that approximately maximize PIG. One strategy based on value-iteration consistently learns faster than previously developed reward-free exploration strategies across a diverse range of environments. Psychologists believe the evolutionary advantage of learning-driven exploration lies in the generalized utility of an accurate internal model. Consistent with this hypothesis, we demonstrate that agents which learn more efficiently during exploration are later better able to accomplish a range of goal-directed tasks. We will conclude by discussing how our work elucidates the explorative behaviors of animals and humans, its relationship to other computational models of behavior, and its potential application to experimental design, such as in closed-loop neurophysiology studies.
Daniel Ying-Jeh Little
Full Text Available Discovering the structure underlying observed data is a recurring problem in machine learning with important applications in neuroscience. It is also a primary function of the brain. When data can be actively collected in the context of a closed action-perception loop, behavior becomes a critical determinant of learning efficiency. Psychologists studying exploration and curiosity in humans and animals have long argued that learning itself is a primary motivator of behavior. However, the theoretical basis of learning-driven behavior is not well understood. Previous computational studies of behavior have largely focused on the control problem of maximizing acquisition of rewards and have treated learning the structure of data as a secondary objective. Here, we study exploration in the absence of external reward feedback. Instead, we take the quality of an agent's learned internal model to be the primary objective. In a simple probabilistic framework, we derive a Bayesian estimate for the amount of information about the environment an agent can expect to receive by taking an action, a measure we term the predicted information gain (PIG. We develop exploration strategies that approximately maximize PIG. One strategy based on value-iteration consistently learns faster, across a diverse range of environments, than previously developed reward-free exploration strategies. Psychologists believe the evolutionary advantage of learning-driven exploration lies in the generalized utility of an accurate internal model. Consistent with this hypothesis, we demonstrate that agents which learn more efficiently during exploration are later better able to accomplish a range of goal-directed tasks. We will conclude by discussing how our work elucidates the explorative behaviors of animals and humans, its relationship to other computational models of behavior, and its potential application to experimental design, such as in closed-loop neurophysiology studies.
Thompson, Joseph J; McColeman, C M; Stepanova, Ekaterina R; Blair, Mark R
Many theories of complex cognitive-motor skill learning are built on the notion that basic cognitive processes group actions into easy-to-perform sequences. The present work examines predictions derived from laboratory-based studies of motor chunking and motor preparation using data collected from the real-time strategy video game StarCraft 2. We examined 996,163 action sequences in the telemetry data of 3,317 players across seven levels of skill. As predicted, the latency to the first action (thought to be the beginning of a chunked sequence) is delayed relative to the other actions in the group. Other predictions, inspired by the memory drum theory of Henry and Rogers, received only weak support. Copyright © 2017 Cognitive Science Society, Inc.
Tully, Philip J; Lindén, Henrik; Hennig, Matthias H
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...
Gershman, Samuel J; Pesaran, Bijan; Daw, Nathaniel D
Humans and animals are endowed with a large number of effectors. Although this enables great behavioral flexibility, it presents an equally formidable reinforcement learning problem of discovering which actions are most valuable because of the high dimensionality of the action space. An unresolved question is how neural systems for reinforcement learning-such as prediction error signals for action valuation associated with dopamine and the striatum-can cope with this "curse of dimensionality." We propose a reinforcement learning framework that allows for learned action valuations to be decomposed into effector-specific components when appropriate to a task, and test it by studying to what extent human behavior and blood oxygen level-dependent (BOLD) activity can exploit such a decomposition in a multieffector choice task. Subjects made simultaneous decisions with their left and right hands and received separate reward feedback for each hand movement. We found that choice behavior was better described by a learning model that decomposed the values of bimanual movements into separate values for each effector, rather than a traditional model that treated the bimanual actions as unitary with a single value. A decomposition of value into effector-specific components was also observed in value-related BOLD signaling, in the form of lateralized biases in striatal correlates of prediction error and anticipatory value correlates in the intraparietal sulcus. These results suggest that the human brain can use decomposed value representations to "divide and conquer" reinforcement learning over high-dimensional action spaces.
Conclusion The results of this study showed that PWS show improvement in accuracy, reaction time and sequence duration variables from day 1 to day 3. Also, PWS show more substantial number of errors compared to PNS, but this difference was not significant between the two groups. Similar results were obtained for the reaction time. Results of this study demonstrated that PWS show slower sequence duration compared to PNS. Some studies suggested that this could be because people who stutter use a control strategy to reduce the number of errors, although many studies suggested that this may indicate motor learning. According to speech motor skills hypothesis, it can be concluded that people who stutter have limitations in motor speech learning abilities. The findings of the present study could have clinical implication for the treatment of stuttering.
Lasky, Barbara; Tempone, Irene
Action learning techniques are well suited to the teaching of organisation behaviour students because of their flexibility, inclusiveness, openness, and respect for individuals. They are no less useful as a tool for change for vocational teachers, learning, of necessity, to become researchers. Whereas traditional universities have always had a…
This paper reports the historical foundation of Northeastern University's course, LDR 6100: Developing Your Leadership Capability, a partial literature review of action learning (AL) and virtual action learning (VAL), a course methodology of LDR 6100 requiring students to apply leadership perspectives using VAL as instructed by the author, questionnaire and survey results of students who evaluated the effectiveness of their application of leadership theories using VAL and insights believed to have been gained by the author administering VAL. Findings indicate most students thought applying leadership perspectives using AL was better than considering leadership perspectives not using AL. In addition as implemented in LDR 6100, more students evaluated VAL positively than did those who assessed VAL negatively.
Morita, Kenji; Jitsev, Jenia; Morrison, Abigail
Value-based action selection has been suggested to be realized in the corticostriatal local circuits through competition among neural populations. In this article, we review theoretical and experimental studies that have constructed and verified this notion, and provide new perspectives on how the local-circuit selection mechanisms implement reinforcement learning (RL) algorithms and computations beyond them. The striatal neurons are mostly inhibitory, and lateral inhibition among them has been classically proposed to realize "Winner-Take-All (WTA)" selection of the maximum-valued action (i.e., 'max' operation). Although this view has been challenged by the revealed weakness, sparseness, and asymmetry of lateral inhibition, which suggest more complex dynamics, WTA-like competition could still occur on short time scales. Unlike the striatal circuit, the cortical circuit contains recurrent excitation, which may enable retention or temporal integration of information and probabilistic "soft-max" selection. The striatal "max" circuit and the cortical "soft-max" circuit might co-implement an RL algorithm called Q-learning; the cortical circuit might also similarly serve for other algorithms such as SARSA. In these implementations, the cortical circuit presumably sustains activity representing the executed action, which negatively impacts dopamine neurons so that they can calculate reward-prediction-error. Regarding the suggested more complex dynamics of striatal, as well as cortical, circuits on long time scales, which could be viewed as a sequence of short WTA fragments, computational roles remain open: such a sequence might represent (1) sequential state-action-state transitions, constituting replay or simulation of the internal model, (2) a single state/action by the whole trajectory, or (3) probabilistic sampling of state/action. Copyright © 2016. Published by Elsevier B.V.
Brian R. King
Full Text Available Protein sequence data continue to become available at an exponential rate. Annotation of functional and structural attributes of these data lags far behind, with only a small fraction of the data understood and labeled by experimental methods. Classification methods that are based on semi-supervised learning can increase the overall accuracy of classifying partly labeled data in many domains, but very few methods exist that have shown their effect on protein sequence classification. We show how proven methods from text classification can be applied to protein sequence data, as we consider both existing and novel extensions to the basic methods, and demonstrate restrictions and differences that must be considered. We demonstrate comparative results against the transductive support vector machine, and show superior results on the most difficult classification problems. Our results show that large repositories of unlabeled protein sequence data can indeed be used to improve predictive performance, particularly in situations where there are fewer labeled protein sequences available, and/or the data are highly unbalanced in nature.
Aguilar, Jessica M; Plante, Elena
Two studies examined learning of grammar-like visual sequences to determine whether a general deficit in statistical learning characterizes this population. Furthermore, we tested the hypothesis that difficulty in sustaining attention during the learning task might account for differences in statistical learning. In Study 1, adults with normal language (NL) or language-learning disability (LLD) were familiarized with the visual artificial grammar and then tested using items that conformed or deviated from the grammar. In Study 2, a 2nd sample of adults with NL and LLD were presented auditory word pairs with weak semantic associations (e.g., groom + clean) along with the visual learning task. Participants were instructed to attend to visual sequences and to ignore the auditory stimuli. Incidental encoding of these words would indicate reduced attention to the primary task. In Studies 1 and 2, both groups demonstrated learning and generalization of the artificial grammar. In Study 2, neither the NL nor the LLD group appeared to encode the words presented during the learning phase. The results argue against a general deficit in statistical learning for individuals with LLD and demonstrate that both NL and LLD learners can ignore extraneous auditory stimuli during visual learning.
Shahnazian, Danesh; Holroyd, Clay B
Anterior cingulate cortex (ACC) has been the subject of intense debate over the past 2 decades, but its specific computational function remains controversial. Here we present a simple computational model of ACC that incorporates distributed representations across a network of interconnected processing units. Based on the proposal that ACC is concerned with the execution of extended, goal-directed action sequences, we trained a recurrent neural network to predict each successive step of several sequences associated with multiple tasks. In keeping with neurophysiological observations from nonhuman animals, the network yields distributed patterns of activity across ACC neurons that track the progression of each sequence, and in keeping with human neuroimaging data, the network produces discrepancy signals when any step of the sequence deviates from the predicted step. These simulations illustrate a novel approach for investigating ACC function.
Moyer, Joanne M.; Sinclair, A. John; Quinn, Lisa
In recent years, action on sustainability has been highly influential around the globe and many now recognize the importance of individual and social learning for inspiring action and achieving sustainability outcomes. Transformative learning theory has been criticized, however, for insufficient development of the link between learning and action.…
This paper considers the shared characteristics between action learning (AL) and the research methodology constructivist grounded theory (CGT). Mirroring Edmonstone's [2011. "Action Learning and Organisation Development: Overlapping Fields of Practice." "Action Learning: Research and Practice" 8 (2): 93-102] article, which…
Alwassel, Humam; Heilbron, Fabian Caba; Ghanem, Bernard
Traditional approaches for action detection use trimmed data to learn sophisticated action detector models. Although these methods have achieved great success at detecting human actions, we argue that huge information is discarded when ignoring
Full Text Available How are sequences of events that are temporarily stored in a cognitive working memory unitized, or chunked, through learning? Such sequential learning is needed by the brain in order to enable language, spatial understanding, and motor skills to develop. In particular, how does the brain learn categories, or list chunks, that become selectively tuned to different temporal sequences of items in lists of variable length as they are stored in working memory, and how does this learning process occur in real time? The present article introduces a neural model that simulates learning of such list chunks. In this model, sequences of items are temporarily stored in an Item-and-Order, or competitive queuing, working memory before learning categorizes them using a categorization network, called a Masking Field, which is a self-similar, multiple-scale, recurrent on-center off-surround network that can weigh the evidence for variable-length sequences of items as they are stored in the working memory through time. A Masking Field hereby activates the learned list chunks that represent the most predictive item groupings at any time, while suppressing less predictive chunks. In a network with a given number of input items, all possible ordered sets of these item sequences, up to a fixed length, can be learned with unsupervised or supervised learning. The self-similar multiple-scale properties of Masking Fields interacting with an Item-and-Order working memory provide a natural explanation of George Miller's Magical Number Seven and Nelson Cowan's Magical Number Four. The article explains why linguistic, spatial, and action event sequences may all be stored by Item-and-Order working memories that obey similar design principles, and thus how the current results may apply across modalities. Item-and-Order properties may readily be extended to Item-Order-Rank working memories in which the same item can be stored in multiple list positions, or ranks, as in the list
Fujimoto, M Stanley; Suvorov, Anton; Jensen, Nicholas O; Clement, Mark J; Bybee, Seth M
Accurate detection of homologous relationships of biological sequences (DNA or amino acid) amongst organisms is an important and often difficult task that is essential to various evolutionary studies, ranging from building phylogenies to predicting functional gene annotations. There are many existing heuristic tools, most commonly based on bidirectional BLAST searches that are used to identify homologous genes and combine them into two fundamentally distinct classes: orthologs and paralogs. Due to only using heuristic filtering based on significance score cutoffs and having no cluster post-processing tools available, these methods can often produce multiple clusters constituting unrelated (non-homologous) sequences. Therefore sequencing data extracted from incomplete genome/transcriptome assemblies originated from low coverage sequencing or produced by de novo processes without a reference genome are susceptible to high false positive rates of homology detection. In this paper we develop biologically informative features that can be extracted from multiple sequence alignments of putative homologous genes (orthologs and paralogs) and further utilized in context of guided experimentation to verify false positive outcomes. We demonstrate that our machine learning method trained on both known homology clusters obtained from OrthoDB and randomly generated sequence alignments (non-homologs), successfully determines apparent false positives inferred by heuristic algorithms especially among proteomes recovered from low-coverage RNA-seq data. Almost ~42 % and ~25 % of predicted putative homologies by InParanoid and HaMStR respectively were classified as false positives on experimental data set. Our process increases the quality of output from other clustering algorithms by providing a novel post-processing method that is both fast and efficient at removing low quality clusters of putative homologous genes recovered by heuristic-based approaches.
Full Text Available The module described and evaluated here was created in response to perceived learning difficulties in diagnostic test design and interpretation for students in third-year Clinical Microbiology. Previously, the activities in lectures and laboratory classes in the module fell into the lower cognitive operations of “knowledge” and “understanding.” The new approach was to exchange part of the traditional activities with elements of interactive learning, where students had the opportunity to engage in deep learning using a variety of learning styles. The effectiveness of the new curriculum was assessed by means of on-course student assessment throughout the module, a final exam, an anonymous questionnaire on student evaluation of the different activities and a focus group of volunteers. Although the new curriculum enabled a major part of the student cohort to achieve higher pass grades (p < 0.001, it did not meet the requirements of the weaker students, and the proportion of the students failing the module remained at 34%. The action research applied here provided a number of valuable suggestions from students on how to improve future curricula from their perspective. Most importantly, an interactive online program that facilitated flexibility in the learning space for the different reagents and their interaction in diagnostic tests was proposed. The methods applied to improve and assess a curriculum refresh by involving students as partners in the process, as well as the outcomes, are discussed.
Ariel, Ellen; Owens, Leigh
The module described and evaluated here was created in response to perceived learning difficulties in diagnostic test design and interpretation for students in third-year Clinical Microbiology. Previously, the activities in lectures and laboratory classes in the module fell into the lower cognitive operations of "knowledge" and "understanding." The new approach was to exchange part of the traditional activities with elements of interactive learning, where students had the opportunity to engage in deep learning using a variety of learning styles. The effectiveness of the new curriculum was assessed by means of on-course student assessment throughout the module, a final exam, an anonymous questionnaire on student evaluation of the different activities and a focus group of volunteers. Although the new curriculum enabled a major part of the student cohort to achieve higher pass grades (p < 0.001), it did not meet the requirements of the weaker students, and the proportion of the students failing the module remained at 34%. The action research applied here provided a number of valuable suggestions from students on how to improve future curricula from their perspective. Most importantly, an interactive online program that facilitated flexibility in the learning space for the different reagents and their interaction in diagnostic tests was proposed. The methods applied to improve and assess a curriculum refresh by involving students as partners in the process, as well as the outcomes, are discussed. Journal of Microbiology & Biology Education.
Full Text Available A motor component is pre-requisite to any communicative act as one must inherently move to communicate. To learn to make a communicative act, the brain must be able to dynamically associate arbitrary percepts to the neural substrate underlying the pre-requisite motor activity. We aimed to investigate whether brain regions involved in complex gestures (ventral pre-motor cortex, Brodmann Area 44 were involved in mediating association between novel abstract auditory stimuli and novel gestural movements. In a functional resonance imaging (fMRI study we asked participants to learn associations between previously unrelated novel sounds and meaningless gestures inside the scanner. We use functional connectivity analysis to eliminate the often present confound of 'strategic covert naming' when dealing with BA44 and to rule out effects of non-specific reductions in signal. Brodmann Area 44, a region incorporating Broca's region showed strong, bilateral, negative correlation of BOLD (blood oxygen level dependent response with learning of sound-action associations during data acquisition. Left-inferior-parietal-lobule (l-IPL and bilateral loci in and around visual area V5, right-orbital-frontal-gyrus, right-hippocampus, left-para-hippocampus, right-head-of-caudate, right-insula and left-lingual-gyrus also showed decreases in BOLD response with learning. Concurrent with these decreases in BOLD response, an increasing connectivity between areas of the imaged network as well as the right-middle-frontal-gyrus with rising learning performance was revealed by a psychophysiological interaction (PPI analysis. The increasing connectivity therefore occurs within an increasingly energy efficient network as learning proceeds. Strongest learning related connectivity between regions was found when analysing BA44 and l-IPL seeds. The results clearly show that BA44 and l-IPL is dynamically involved in linking gesture and sound and therefore provides evidence that one of
Wrzeszczynski, Kazimierz O; Frank, Mayu O; Koyama, Takahiko; Rhrissorrakrai, Kahn; Robine, Nicolas; Utro, Filippo; Emde, Anne-Katrin; Chen, Bo-Juen; Arora, Kanika; Shah, Minita; Vacic, Vladimir; Norel, Raquel; Bilal, Erhan; Bergmann, Ewa A; Moore Vogel, Julia L; Bruce, Jeffrey N; Lassman, Andrew B; Canoll, Peter; Grommes, Christian; Harvey, Steve; Parida, Laxmi; Michelini, Vanessa V; Zody, Michael C; Jobanputra, Vaidehi; Royyuru, Ajay K; Darnell, Robert B
To analyze a glioblastoma tumor specimen with 3 different platforms and compare potentially actionable calls from each. Tumor DNA was analyzed by a commercial targeted panel. In addition, tumor-normal DNA was analyzed by whole-genome sequencing (WGS) and tumor RNA was analyzed by RNA sequencing (RNA-seq). The WGS and RNA-seq data were analyzed by a team of bioinformaticians and cancer oncologists, and separately by IBM Watson Genomic Analytics (WGA), an automated system for prioritizing somatic variants and identifying drugs. More variants were identified by WGS/RNA analysis than by targeted panels. WGA completed a comparable analysis in a fraction of the time required by the human analysts. The development of an effective human-machine interface in the analysis of deep cancer genomic datasets may provide potentially clinically actionable calls for individual patients in a more timely and efficient manner than currently possible. NCT02725684.
Mandrikas, Achilleas; Stavrou, Dimitrios; Skordoulis, Constantine
In this paper a teaching-learning sequence (TLS) introducing pre-service elementary teachers (PET) to weather map reading, with emphasis on wind assignment, is presented. The TLS includes activities about recognition of wind symbols, assignment of wind direction and wind speed on a weather map and identification of wind characteristics in a weather forecast. Sixty PET capabilities and difficulties in understanding weather maps were investigated, using inquiry-based learning activities. The results show that most PET became more capable of reading weather maps and assigning wind direction and speed on them. Our results also show that PET could be guided to understand meteorology concepts useful in everyday life and in teaching their future students.
Full Text Available During the bleaching process the pulp is treated with chemical reagents that can be retained in the pulp and interfere in the action of the optical brighteners. Different bleaching sequences can produce pulps at the same brightness but with different potential to whiteness increase when treated with optical brighteners. The objective of this study was to evaluate the influence of the bleaching sequence on the efficiency of disulphonated and tetrasulphonated optical brighteners. Eucalyptus kraft pulp was bleached using four different bleaching sequences. For each pulp three brightness targets were aimeds. For each bleaching sequence mathematical model was generated for predicting the final pulp whiteness according to the initial brightness and the optical brightener charge applied. The presence of organochlorine residues in the pulp reduced the effectiveness of the optical brighteners. Therefore, bleaching sequences that use low chlorine dioxide charge favors for greater gains in whiteness with the application of optical brighteners. The replacement of the final chlorine dioxide bleaching stage with a hydrogen peroxide one in the sequence increased the efficiency of the optical brightening agents.
Jardim, David; Nunes, Luís.; Dias, Miguel
In our daily activities we perform prediction or anticipation when interacting with other humans or with objects. Prediction of human activity made by computers has several potential applications: surveillance systems, human computer interfaces, sports video analysis, human-robot-collaboration, games and health-care. We propose a system capable of recognizing and predicting human actions using supervised classifiers trained with automatically labeled data evaluated in our human activity RGB-D dataset (recorded with a Kinect sensor) and using only the position of the main skeleton joints to extract features. Using conditional random fields (CRFs) to model the sequential nature of actions in a sequence has been used before, but where other approaches try to predict an outcome or anticipate ahead in time (seconds), we try to predict what will be the next action of a subject. Our results show an activity prediction accuracy of 89.9% using an automatically labeled dataset.
Bers, Marina U.
This paper presents Project InterActions, a series of 5-week workshops in which very young learners (4- to 7-year-old children) and their parents come together to build and program a personally meaningful robotic project in the context of a multigenerational robotics-based community of practice. The goal of these family workshops is to teach both parents and children about the mechanical and programming aspects involved in robotics, as well as to initiate them in a learning trajectory with and about technology. Results from this project address different ways in which parents and children learn together and provide insights into how to develop educational interventions that would educate parents, as well as children, in new domains of knowledge and skills such as robotics and new technologies.
Guisasola, Jenaro; Zuza, Kristina; Ametller, Jaume; Gutierrez-Berraondo, José
In this paper we put forward a proposal for the design and evaluation of teaching and learning sequences in upper secondary school and university. We will connect our proposal with relevant contributions on the design of teaching sequences, ground it on the design-based research methodology, and discuss how teaching and learning sequences designed…
Full Text Available In a previous fMRI study we found significant differences in BOLD responses for congruent and incongruent semantic audio-visual action sequences (whole-body actions and speech actions in bilateral pSTS, left SMA, left IFG, and IPL (Meyer, Greenlee, & Wuerger, JOCN, 2011. Here, we present results from a 128-channel ERP study that examined the time-course of these interactions using a one-back task. ERPs in response to congruent and incongruent audio-visual actions were compared to identify regions and latencies of differences. Responses to congruent and incongruent stimuli differed between 240–280 ms, 340–420 ms, and 460–660 ms after stimulus onset. A dipole analysis revealed that the difference around 250 ms can be partly explained by a modulation of sources in the vicinity of the superior temporal area, while the responses after 400 ms are consistent with sources in inferior frontal areas. Our results are in line with a model that postulates early recognition of congruent audiovisual actions in the pSTS, perhaps as a sensory memory buffer, and a later role of the IFG, perhaps in a generative capacity, in reconciling incongruent signals.
McKinstry, Jeffrey L; Edelman, Gerald M
Animal behavior often involves a temporally ordered sequence of actions learned from experience. Here we describe simulations of interconnected networks of spiking neurons that learn to generate patterns of activity in correct temporal order. The simulation consists of large-scale networks of thousands of excitatory and inhibitory neurons that exhibit short-term synaptic plasticity and spike-timing dependent synaptic plasticity. The neural architecture within each area is arranged to evoke winner-take-all (WTA) patterns of neural activity that persist for tens of milliseconds. In order to generate and switch between consecutive firing patterns in correct temporal order, a reentrant exchange of signals between these areas was necessary. To demonstrate the capacity of this arrangement, we used the simulation to train a brain-based device responding to visual input by autonomously generating temporal sequences of motor actions.
Flynn, Emma; Whiten, Andrew
Children can learn how to use complex objects by watching others, yet the relative importance of different elements they may observe, such as the interactions of the individual parts of the apparatus, a model's movements, and desirable outcomes, remains unclear. In total, 140 3-year-olds and 140 5-year-olds participated in a study where they observed a video showing tools being used to extract a reward item from a complex puzzle box. Conditions varied according to the elements that could be seen in the video: (a) the whole display, including the model's hands, the tools, and the box; (b) the tools and the box but not the model's hands; (c) the model's hands and the tools but not the box; (d) only the end state with the box opened; and (e) no demonstration. Children's later attempts at the task were coded to establish whether they imitated the hierarchically organized sequence of the model's actions, the action details, and/or the outcome. Children's successful retrieval of the reward from the box and the replication of hierarchical sequence information were reduced in all but the whole display condition. Only once children had attempted the task and witnessed a second demonstration did the display focused on the tools and box prove to be better for hierarchical sequence information than the display focused on the tools and hands only. Copyright © 2013 Elsevier Inc. All rights reserved.
Funamizu, Akihiro; Ito, Makoto; Doya, Kenji; Kanzaki, Ryohei; Takahashi, Hirokazu
The estimation of reward outcomes for action candidates is essential for decision making. In this study, we examined whether and how the uncertainty in reward outcome estimation affects the action choice and learning rate. We designed a choice task in which rats selected either the left-poking or right-poking hole and received a reward of a food pellet stochastically. The reward probabilities of the left and right holes were chosen from six settings (high, 100% vs. 66%; mid, 66% vs. 33%; low, 33% vs. 0% for the left vs. right holes, and the opposites) in every 20-549 trials. We used Bayesian Q-learning models to estimate the time course of the probability distribution of action values and tested if they better explain the behaviors of rats than standard Q-learning models that estimate only the mean of action values. Model comparison by cross-validation revealed that a Bayesian Q-learning model with an asymmetric update for reward and non-reward outcomes fit the choice time course of the rats best. In the action-choice equation of the Bayesian Q-learning model, the estimated coefficient for the variance of action value was positive, meaning that rats were uncertainty seeking. Further analysis of the Bayesian Q-learning model suggested that the uncertainty facilitated the effective learning rate. These results suggest that the rats consider uncertainty in action-value estimation and that they have an uncertainty-seeking action policy and uncertainty-dependent modulation of the effective learning rate. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.
Thacker, M. S.; Freshour, P.; McDonald, W.
Valuable experience in environmental remediation was gained at Sandia National Laboratories/New Mexico (Sandia) by concurrently conducting Voluntary Corrective Actions (VCAs) at three Solid Waste Management Units (SWMUs). Sandia combined the planning, implementation, and reporting phases of three VCAs with the goal of realizing significant savings in both cost and schedule. The lessons learned through this process have been successfully implemented within the Sandia Environmental Restoration (ER) Project and could be utilized at other locations with multiple ER sites. All lessons learned resulted from successful teaming with the New Mexico Environment Department (NMED) Hazardous Waste Bureau (HWB), Sandia management, a Sandia risk assessment team, and Sandia waste management personnel. Specific lessons learned included the following: (1) potential efficiencies can be exploited by reprioritization and rescheduling of activities; (2) cost and schedule reductions can be realized by combining similar work at contiguous sites into a single effort; (3) working with regulators to develop preliminary remediation goals (PRGs) and gain regulatory acceptance for VCA planning prior to project initiation results in significant time savings throughout the remediation and permit modification processes; (4) effective and thoughtful contingency planning removes uncertainties and defrays costs so that projects can be completed without interruption; (5) timely collection of waste characterization samples allows efficient disposal of waste streams, and (6) concurrent reporting of VCA activities results in significant savings in time for the authors and reviewers
De Loo, I.G.M.
Action learning has been proposed as both a problem-solving and organizational learning approach when organizations are faced with complex, unfamiliar problems for which no clear-cut solutions exist. Certainly when action learning participants are not intrinsically motivated to tackle these problems
Donnenberg, O.; De Loo, I.G.M.
Action learning programmes are supposed to result in both personal and organizational development. However, organizational development can be negligible because, as the term implies, a connection must be secured between what has been learned by action learning participants and other members of an
Bulf, Hermann; de Hevia, Maria Dolores; Gariboldi, Valeria; Macchi Cassia, Viola
A wealth of studies show that human adults map ordered information onto a directional spatial continuum. We asked whether mapping ordinal information into a directional space constitutes an early predisposition, already functional prior to the acquisition of symbolic knowledge and language. While it is known that preverbal infants represent numerical order along a left-to-right spatial continuum, no studies have investigated yet whether infants, like adults, organize any kind of ordinal information onto a directional space. We investigated whether 7-month-olds' ability to learn high-order rule-like patterns from visual sequences of geometric shapes was affected by the spatial orientation of the sequences (left-to-right vs. right-to-left). Results showed that infants readily learn rule-like patterns when visual sequences were presented from left to right, but not when presented from right to left. This result provides evidence that spatial orientation critically determines preverbal infants' ability to perceive and learn ordered information in visual sequences, opening to the idea that a left-to-right spatially organized mental representation of ordered dimensions might be rooted in biologically-determined constraints on human brain development.
Queral, C.; Mena Rosell, L.; Jimenez Varas, G.
The Fukushima accident has shown the need for tools and methodologies able to analyze human activities and / or capabilities of portable systems that has given the Spanish plants as a result of the stress tests . In this work we have applied the methodology of integrated safety analysis developed by the CSN , to SBO sequences with LOCA stamp. The aim is to show a methodology for testing the performances of the Emergency Operating Procedures and Guides Severe Accident Management. The simulations were performed with the tool SCAIS coupled to MAAP . The results show that there are human activities that may be beneficial in certain sequences but harmful in others. This type of problem is already known and referred to in the GGAS . However, FSR shows a practical way to check human actions cannot be obtained with other methods.
Karim, Helmet T; Huppert, Theodore J; Erickson, Kirk I; Wollam, Mariegold E; Sparto, Patrick J; Sejdić, Ervin; VanSwearingen, Jessie M
Previous studies have shown the functional neural circuitry differences before and after an explicitly learned motor sequence task, but have not assessed these changes during the process of motor skill learning. Functional magnetic resonance imaging activity was measured while participants (n=13) were asked to tap their fingers to visually presented sequences in blocks that were either the same sequence repeated (learning block) or random sequences (control block). Motor learning was associated with a decrease in brain activity during learning compared to control. Lower brain activation was noted in the posterior parietal association area and bilateral thalamus during the later periods of learning (not during the control). Compared to the control condition, we found the task-related motor learning was associated with decreased connectivity between the putamen and left inferior frontal gyrus and left middle cingulate brain regions. Motor learning was associated with changes in network activity, spatial extent, and connectivity. Copyright © 2016 Elsevier B.V. All rights reserved.
Shanahan, Phiala E.; Trewartha, Daniel; Detmold, William
Numerical lattice quantum chromodynamics studies of the strong interaction are important in many aspects of particle and nuclear physics. Such studies require significant computing resources to undertake. A number of proposed methods promise improved efficiency of lattice calculations, and access to regions of parameter space that are currently computationally intractable, via multi-scale action-matching approaches that necessitate parametric regression of generated lattice datasets. The applicability of machine learning to this regression task is investigated, with deep neural networks found to provide an efficient solution even in cases where approaches such as principal component analysis fail. The high information content and complex symmetries inherent in lattice QCD datasets require custom neural network layers to be introduced and present opportunities for further development.
Aline eMoussard; Emmanuel eBigand; Emmanuel eBigand; Isabelle ePeretz; Isabelle ePeretz; Isabelle ePeretz; Sylvie eBelleville; Sylvie eBelleville
Strong links between music and motor functions suggest that music could represent an interesting aid for motor learning. The present study aims for the first time to test the potential of music to assist in the learning of sequences of gestures in normal and pathological aging. Participants with mild Alzheimer's disease (AD) and healthy older adults (Controls) learned sequences of meaningless gestures that were either accompanied by music or a metronome. We also manipulated the learning proce...
Moussard, Aline; Bigand, Emmanuel; Belleville, Sylvie; Peretz, Isabelle
Strong links between music and motor functions suggest that music could represent an interesting aid for motor learning. The present study aims for the first time to test the potential of music to assist in the learning of sequences of gestures in normal and pathological aging. Participants with mild Alzheimer’s disease (AD) and healthy older adults (controls) learned sequences of meaningless gestures that were either accompanied by music or a metronome. We also manipulated the learning proce...
Smith, Sue; Smith, Laurie
In this paper we evaluate action learning for leaders of social enterprises and charities. Based on ethnographic research including participant observation, facilitator reflective diary notes and in-depth, qualitative interviews with participants of two action learning sets undertaken over eight months, analysed using Wenger et al.’s (2011) value creation framework, we show how the current and future value of action learning is perceived by the participants. We seek to give a deeper understan...
Todd, Juanita; Provost, Alexander; Whitson, Lisa; Mullens, Daniel
This paper features two studies confirming a lasting impact of first learning on how subsequent experience is weighted in early relevance-filtering processes. In both studies participants were exposed to sequences of sound that contained a regular pattern on two different timescales. Regular patterning in sound is readily detected by the auditory system and used to form "prediction models" that define the most likely properties of sound to be encountered in a given context. The presence and strength of these prediction models is inferred from changes in automatically elicited components of auditory evoked potentials. Both studies employed sound sequences that contained both a local and longer-term pattern. The local pattern was defined by a regular repeating pure tone occasionally interrupted by a rare deviating tone (p=0.125) that was physically different (a 30msvs. 60ms duration difference in one condition and a 1000Hz vs. 1500Hz frequency difference in the other). The longer-term pattern was defined by the rate at which the two tones alternated probabilities (i.e., the tone that was first rare became common and the tone that was first common became rare). There was no task related to the tones and participants were asked to ignore them while focussing attention on a movie with subtitles. Auditory-evoked potentials revealed long lasting modulatory influences based on whether the tone was initially encountered as rare and unpredictable or common and predictable. The results are interpreted as evidence that probability (or indeed predictability) assigns a differential information-value to the two tones that in turn affects the extent to which prediction models are updated and imposed. These effects are exposed for both common and rare occurrences of the tones. The studies contribute to a body of work that reveals that probabilistic information is not faithfully represented in these early evoked potentials and instead exposes that predictability (or conversely
Takács, Ádám; Shilon, Yuval; Janacsek, Karolina; Kóbor, Andrea; Tremblay, Antoine; Németh, Dezső; Ullman, Michael T
Procedural memory, which is rooted in the basal ganglia, plays an important role in the implicit learning of motor and cognitive skills. Few studies have examined procedural learning in either Tourette syndrome (TS) or Attention Deficit Hyperactivity Disorder (ADHD), despite basal ganglia abnormalities in both of these neurodevelopmental disorders. We aimed to assess procedural learning in children with TS (n=13), ADHD (n=22), and comorbid TS-ADHD (n=20), as well as in typically developing children (n=21). Procedural learning was measured with a well-studied implicit probabilistic sequence learning task, the alternating serial reaction time task. All four groups showed evidence of sequence learning, and moreover did not differ from each other in sequence learning. This result, from the first study to examine procedural memory across TS, ADHD and comorbid TS-ADHD, is consistent with previous findings of intact procedural learning of sequences in both TS and ADHD. In contrast, some studies have found impaired procedural learning of non-sequential probabilistic categories in TS. This suggests that sequence learning may be spared in TS and ADHD, while at least some other forms of learning in procedural memory are impaired, at least in TS. Our findings indicate that disorders associated with basal ganglia abnormalities do not necessarily show procedural learning deficits, and provide a possible path for more effective diagnostic tools, and educational and training programs. Copyright © 2017 Elsevier Inc. All rights reserved.
Herrera, Juan Sebastian
Research in geoscience education addressing students' conceptions of geological subjects has concentrated in topics such as geological time, plate tectonics, and problem solving in the field, mostly in K-12 and entry level college scenarios. Science education research addressing learning of sedimentary systems in advance undergraduates is rather limited. Therefore, this dissertation contributed to filling that research gap and explored students' narratives when explaining geological processes associated with the interaction between sediment deposition and sea level fluctuations. The purpose of the present study was to identify the common conceptions and alternative conceptions held by students when learning the basics of the sub discipline known as sequence stratigraphy - which concepts students were familiar and easily identified, and which ones they had more difficulty with. In addition, we mapped the cognitive models that underlie those conceptions by analyzing students' gestures and conceptual metaphors used in their explanations. This research also investigated the interaction between geoscientific visual displays and student gesturing in a specific learning context. In this research, an in-depth assessment of 27 students' ideas of the basic principles of sequence stratigraphy was completed. Participants were enrolled in advanced undergraduate stratigraphy courses at three research-intensive universities in Midwest U.S. Data collection methods included semi-structured interviews, spatial visualization tests, and lab assignments. Results indicated that students poorly integrated temporal and spatial scales in their sequence stratigraphic models, and that many alternative conceptions were more deeply rooted than others, especially those related to eustasy and base level. In order to better understand the depth of these conceptions, we aligned the analysis of gesture with the theory of conceptual metaphor to recognize the use of mental models known as image
Ejaz, N.; Khan, U. A.; Martínez-del-Amor, M. A.; Sparenberg, H.
Automatic understanding and interpretation of movies can be used in a variety of ways to semantically manage the massive volumes of movies data. "Action Movie Franchises" dataset is a collection of twenty Hollywood action movies from five famous franchises with ground truth annotations at shot and beat level of each movie. In this dataset, the annotations are provided for eleven semantic beat categories. In this work, we propose a deep learning based method to classify shots and beat-events on this dataset. The training dataset for each of the eleven beat categories is developed and then a Convolution Neural Network is trained. After finding the shot boundaries, key frames are extracted for each shot and then three classification labels are assigned to each key frame. The classification labels for each of the key frames in a particular shot are then used to assign a unique label to each shot. A simple sliding window based method is then used to group adjacent shots having the same label in order to find a particular beat event. The results of beat event classification are presented based on criteria of precision, recall, and F-measure. The results are compared with the existing technique and significant improvements are recorded.
Vollmer, Anna-Lisa; Mühlig, Manuel; Steil, Jochen J; Pitsch, Karola; Fritsch, Jannik; Rohlfing, Katharina J; Wrede, Britta
Robot learning by imitation requires the detection of a tutor's action demonstration and its relevant parts. Current approaches implicitly assume a unidirectional transfer of knowledge from tutor to learner. The presented work challenges this predominant assumption based on an extensive user study with an autonomously interacting robot. We show that by providing feedback, a robot learner influences the human tutor's movement demonstrations in the process of action learning. We argue that the robot's feedback strongly shapes how tutors signal what is relevant to an action and thus advocate a paradigm shift in robot action learning research toward truly interactive systems learning in and benefiting from interaction.
Raman spectra have been examined to clarify the polymorphic forms of DNA, A, B, and Z forms. From an analysis the authors found that the guanine ring breathing vibration is sensitive to its local conformation. Examination of nine crystals of guanosine residues in which the local conformations are well established revealed that a guanosine residue with a C3'endo-anti gives a strong line at 666+-2 cm/sup -1/, O4'endo-anti at 682 cm/sup -1/, C1'exo-anti at 673 cm/sup -1/, C2'endo-anti at 677 cm/sup -1/ and syn-forms around 625 cm/sup -1/. Using this characteristic line, they were able to obtain the local conformations of guanosine moieties in poly(dG-dC). Such a sequence derived variation is suggested to be recognized by sequence specific proteins such as restriction enzymes. The authors found a correlation between sequence dependent DNA conformation and a mode of action of restriction enzymes. The cutting mode of restriction enzymes is classified into three groups. The classification of whether the products have blunt ends, two-base-long cohesive ends, or four-base-long cohesive ends depends primarily on the substrate, not on the enzyme. It is suggested that sequence dependent DNA conformation causes such a classification by the use of the Calladine-Dickerson analysis. In the recognition of restriction enzymes, the methyl group in a certain sequence is considered to play an important role by changing the local conformation of DNA
Clark, Gillian M; Lum, Jarrad A G
A core claim of the procedural deficit hypothesis of specific language impairment (SLI) is that the disorder is associated with poor implicit sequence learning. This study investigated whether implicit sequence learning problems in SLI are present for first-order conditional (FOC) and higher order conditional (HOC) sequences. Twenty-five children with SLI and 27 age-matched, nonlanguage-impaired children completed 2 serial reaction time tasks. On 1 version, the sequence to be implicitly learnt comprised a FOC sequence and on the other a HOC sequence. Results showed that the SLI group learned the HOC sequence (η p ² = .285, p = .005) but not the FOC sequence (η p ² = .099, p = .118). The control group learned both sequences (FOC η p ² = .497, HOC η p 2= .465, ps < .001). The SLI group's difficulty learning the FOC sequence is consistent with the procedural deficit hypothesis. However, the study provides new evidence that multiple mechanisms may underpin the learning of FOC and HOC sequences. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Malmberg, Jonna; Järvenoja, Hanna; Järvelä, Sanna
This study uses log file traces to examine differences between high-and low-achieving students' strategic actions in varying learning situations. In addition, this study illustrates, in detail, what strategic and self-regulated learning constitutes in practice. The study investigates the learning patterns that emerge in learning situations…
Bunlon, Frédérique; Marshall, Peter J.; Quandt, Lorna C.; Bouquet, Cedric A.
According to the ideomotor theory, actions are represented in terms of their perceptual effects, offering a solution for the correspondence problem of imitation (how to translate the observed action into a corresponding motor output). This effect-based coding of action is assumed to be acquired through action-effect learning. Accordingly, performing an action leads to the integration of the perceptual codes of the action effects with the motor commands that brought them about. While ideomotor theory is invoked to account for imitation, the influence of action-effect learning on imitative behavior remains unexplored. In two experiments, imitative performance was measured in a reaction time task following a phase of action-effect acquisition. During action-effect acquisition, participants freely executed a finger movement (index or little finger lifting), and then observed a similar (compatible learning) or a different (incompatible learning) movement. In Experiment 1, finger movements of left and right hands were presented as action-effects during acquisition. In Experiment 2, only right-hand finger movements were presented during action-effect acquisition and in the imitation task the observed hands were oriented orthogonally to participants’ hands in order to avoid spatial congruency effects. Experiments 1 and 2 showed that imitative performance was improved after compatible learning, compared to incompatible learning. In Experiment 2, although action-effect learning involved perception of finger movements of right hand only, imitative capabilities of right- and left-hand finger movements were equally affected. These results indicate that an observed movement stimulus processed as the effect of an action can later prime execution of that action, confirming the ideomotor approach to imitation. We further discuss these findings in relation to previous studies of action-effect learning and in the framework of current ideomotor approaches to imitation. PMID:25793755
Sakreida, Katrin; Higuchi, Satomi; Di Dio, Cinzia; Ziessler, Michael; Turgeon, Martine; Roberts, Neil; Vogt, Stefan
Imitation learning involves the acquisition of novel motor patterns based on action observation (AO). We used event-related functional magnetic resonance imaging to study the imitation learning of spatial sequences and rhythms during AO, motor imagery (MI), and imitative execution in nonmusicians and musicians. While both tasks engaged the fronto-parietal mirror circuit, the spatial sequence task recruited posterior parietal and dorsal premotor regions more strongly. The rhythm task involved an additional network for auditory working memory. This partial dissociation supports the concept of task-specific mirror mechanisms. Two regions of cognitive control were identified: 1) dorsolateral prefrontal cortex (DLPFC) was found to be more strongly activated during MI of novel spatial sequences, which allowed us to extend the 2-level model of imitation learning by Buccino et al. (2004) to spatial sequences. 2) During imitative execution of both tasks, the posterior medial frontal cortex was robustly activated, along with the DLPFC, which suggests that both regions are involved in the cognitive control of imitation learning. The musicians' selective behavioral advantage for rhythm imitation was reflected cortically in enhanced sensory-motor processing during AO and by the absence of practice-related activation differences in DLPFC during rhythm execution. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: firstname.lastname@example.org.
Boonyuen Saranya; Charungkaittikul Suwithida; Ratana-ubol Archanya
Ethical leadership is now increasingly focused in leadership development. The main purpose of this study is to explore two methods of adult learning, action learning and transformative learning, and to use the methods to enhance ethical leadership. Building ethical leadership requires an approach that focuses on personal values, beliefs, or frames of references, which is transformative learning. Transformative learning requires a series of meetings to conduct critical discourse and to follow ...
Bleske, Barry E; Remington, Tami L; Wells, Trisha D; Dorsch, Michael P; Guthrie, Sally K; Stumpf, Janice L; Alaniz, Marissa C; Ellingrod, Vicki L; Tingen, Jeffrey M
To compare the effectiveness of team-based learning (TBL) to that of traditional lectures on learning outcomes in a therapeutics course sequence. A revised TBL curriculum was implemented in a therapeutic course sequence. Multiple choice and essay questions identical to those used to test third-year students (P3) taught using a traditional lecture format were administered to the second-year pharmacy students (P2) taught using the new TBL format. One hundred thirty-one multiple-choice questions were evaluated; 79 tested recall of knowledge and 52 tested higher level, application of knowledge. For the recall questions, students taught through traditional lectures scored significantly higher compared to the TBL students (88%±12% vs. 82%±16%, p=0.01). For the questions assessing application of knowledge, no differences were seen between teaching pedagogies (81%±16% vs. 77%±20%, p=0.24). Scores on essay questions and the number of students who achieved 100% were also similar between groups. Transition to a TBL format from a traditional lecture-based pedagogy allowed P2 students to perform at a similar level as students with an additional year of pharmacy education on application of knowledge type questions. However, P3 students outperformed P2 students regarding recall type questions and overall. Further assessment of long-term learning outcomes is needed to determine if TBL produces more persistent learning and improved application in clinical settings.
Antonio Exposito; Juan Antonio Quiroga; Javier Hortal; John-Einar Hulsund
Full text of publication follows: Nowadays, simulation-based human reliability analysis (HRA) methods seem to provide a new direction for the development of advanced methodologies to study operator actions effect during accident sequences. Due to this, the Spanish Nuclear Safety Council (CSN) started a working group which has, among other objectives, to develop such simulation-based HRA methodology. As a result of its activities, a new methodology, named Integrated Safety Assessment (ISA), has been developed and is currently being incorporated into licensing activities at CSN. One of the key aspects of this approach is the incorporation of the capability to simulate operator actions, expanding the ISA methodology scopes to make HRA studies. For this reason, CSN is involved in several activities oriented to develop a new tool, which must be able to incorporate operator actions in conventional thermohydraulic (TH) simulations. One of them is the collaboration project between CSN, Halden Reactor Project (HRP) and the Department of Energy Systems (DSE) of the Polytechnic University of Madrid that started in 2003. The basic aim of the project is to develop a software tool that consists of a closed-loop plant/operator simulator, a thermal hydraulic (TH) code for simulating the plant transient and the procedures processor to give the information related with operator actions to the TH code, both coupled by a data communication system which allows the information exchange. For the plant simulation we have a plant transient simulator code (TRETA/TIZONA for PWR/BWR NPPs respectively), developed by the CSN, with PWR/BWR full scope models. The functionality of these thermalhydraulic codes has been expanded, allowing control the overall information flow between coupled codes, simulating the TH transient and determining when the operator actions must be considered. In the other hand, we have the COPMA-III code, a computerized procedure system able to manage XML operational
Verstynen, Timothy; Phillips, Jeff; Braun, Emily; Workman, Brett; Schunn, Christian; Schneider, Walter
Many everyday skills are learned by binding otherwise independent actions into a unified sequence of responses across days or weeks of practice. Here we looked at how the dynamics of action planning and response binding change across such long timescales. Subjects (N = 23) were trained on a bimanual version of the serial reaction time task (32-item sequence) for two weeks (10 days total). Response times and accuracy both showed improvement with time, but appeared to be learned at different rates. Changes in response speed across training were associated with dynamic changes in response time variability, with faster learners expanding their variability during the early training days and then contracting response variability late in training. Using a novel measure of response chunking, we found that individual responses became temporally correlated across trials and asymptoted to set sizes of approximately 7 bound responses at the end of the first week of training. Finally, we used a state-space model of the response planning process to look at how predictive (i.e., response anticipation) and error-corrective (i.e., post-error slowing) processes correlated with learning rates for speed, accuracy and chunking. This analysis yielded non-monotonic association patterns between the state-space model parameters and learning rates, suggesting that different parts of the response planning process are relevant at different stages of long-term learning. These findings highlight the dynamic modulation of response speed, variability, accuracy and chunking as multiple movements become bound together into a larger set of responses during sequence learning.
Yorks, Lyle; Dilworth, Robert L.; Marquardt, Michael J.; Marsick, Victoria; O'Neil, Judy
Action learning is receiving increasing attention from human resource development (HRD) practitioners and the HRD management literature. Action learning has been characterized as follows: (1) working in small groups to take action on meaningful problems while seeking to learn from having taken the specified action lies at the foundation of action…
Kiilo, Tatjana; Kutsar, Dagmar
Based on appreciative inquiry and threshold concepts from an intercultural learning perspective, the article makes insights into the constructivist social learning practice of Estonian language learning amongst Russian-speaking teachers in Estonia. The application of educational action research methodology, more specifically that of Bridget…
Warwick, Rob; McCray, Janet; Board, Douglas
This paper considers the logic of practice of the French sociologist Pierre Bourdieu in relation to critical action learning: in particular "habitus" which is co-created with field and the interplay amongst the two in the form of misrecognition and risk. We draw on interviews with participants who have experienced action learning as part…
This account relates my experiences as facilitator of an action learning set on a DBA cohort comprising international students and myself. It outlines the reasons for my selection as facilitator and describes my initial expectations and assumptions of action learning. I chart the difficulty in separating the 'what' of my own research from the…
This paper reflects upon a sub-optimal action learning application with a strategic business re-design project. The objective of the project was to improve the long-term business performance of a subsidiary business and build the strategic plan. Action learning was introduced to aid the group in expanding their view of the real problems…
Kellie, Jean; Henderson, Eileen; Milsom, Brian; Crawley, Hayley
This account of practice reports on an action learning initiative designed and implemented in partnership between a regional NHS Acute Trust and a UK Business School. The central initiative was the implementation of an action learning programme entitled "Leading change in tissue viability best practice: a development programme for Link Nurse…
Borragán, Guillermo; Urbain, Charline; Schmitz, Rémy; Mary, Alison; Peigneux, Philippe
That post-training sleep supports the consolidation of sequential motor skills remains debated. Performance improvement and sensitivity to proactive interference are both putative measures of long-term memory consolidation. We tested sleep-dependent memory consolidation for visuo-motor sequence learning using a proactive interference paradigm. Thirty-three young adults were trained on sequence A on Day 1, then had Regular Sleep (RS) or were Sleep Deprived (SD) on the night after learning. After two recovery nights, they were tested on the same sequence A, then had to learn a novel, potentially competing sequence B. We hypothesized that proactive interference effects on sequence B due to the prior learning of sequence A would be higher in the RS condition, considering that proactive interference is an indirect marker of the robustness of sequence A, which should be better consolidated over post-training sleep. Results highlighted sleep-dependent improvement for sequence A, with faster RTs overnight for RS participants only. Moreover, the beneficial impact of sleep was specific to the consolidation of motor but not sequential skills. Proactive interference effects on learning a new material at Day 4 were similar between RS and SD participants. These results suggest that post-training sleep contributes to optimizing motor but not sequential components of performance in visuo-motor sequence learning. Copyright © 2015 Elsevier Inc. All rights reserved.
Kinnebrew, John S.; Loretz, Kirk M.; Biswas, Gautam
Computer-based learning environments can produce a wealth of data on student learning interactions. This paper presents an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs a novel combination of sequence mining techniques to identify deferentially…
Jimenez, Luis; Vazquez, Gustavo A.
Sequence learning and contextual cueing explore different forms of implicit learning, arising from practice with a structured serial task, or with a search task with informative contexts. We assess whether these two learning effects arise simultaneously when both remain implicit. Experiments 1 and 2 confirm that a cueing effect can be observed…
Cormas, Peter C.
Preservice teachers (N = 27) in two sections of a sequenced, methodological and process integrated mathematics/science course solved a levers problem with three similar learning processes and a problem-solving approach, and identified a problem-solving approach through one different learning process. Similar learning processes used included:…
Sarah Nadine Meissner
Full Text Available Although implicit motor sequence learning is rather well understood in young adults, effects of aging on this kind of learning are controversial. There is first evidence that working memory (WM might play a role in implicit motor sequence learning in young adults as well as in adults above the age of 65. However the knowledge about the development of these processes across the adult life span is rather limited. As the average age of our population continues to rise, a better understanding of age-related changes in motor sequence learning and potentially mediating cognitive processes takes on increasing significance. Therefore, we investigated aging effects on implicit motor sequence learning and WM. Sixty adults (18-71 years completed verbal and visuospatial n-back tasks and were trained on a serial reaction time task. Randomly varying trials served as control condition. To further assess consolidation indicated by off-line improvement and reduced susceptibility to interference, reaction times (RTs were determined 1 h after initial learning. Young and older but not middle-aged adults showed motor sequence learning. Nine out of 20 older adults (compared to one young/one middle-aged exhibited some evidence of sequence awareness. After 1 h, young and middle-aged adults showed off-line improvement. However, RT facilitation was not specific to sequence trials. Importantly, susceptibility to interference was reduced in young and older adults indicating the occurrence of consolidation. Although WM performance declined in older participants when load was high, it was not significantly related to sequence learning. The data reveal a decline in motor sequence learning in middle-aged but not in older adults. The use of explicit learning strategies in older adults might account for the latter result.
Full Text Available Ethical leadership is now increasingly focused in leadership development. The main purpose of this study is to explore two methods of adult learning, action learning and transformative learning, and to use the methods to enhance ethical leadership. Building ethical leadership requires an approach that focuses on personal values, beliefs, or frames of references, which is transformative learning. Transformative learning requires a series of meetings to conduct critical discourse and to follow up the learning of learners. By organizing such action learning, human resource developers can optimize their time and effort more effectively. The authors have created a comprehensive model to integrate the two learning approaches in a general way that focuses not only on ethical leadership, but also on all kinds of behavioral transformation in the workplace in the hotel business or even other types of business.
Kirsch, Louise P; Cross, Emily S
The way in which we perceive others in action is biased by one's prior experience with an observed action. For example, we can have auditory, visual, or motor experience with actions we observe others perform. How action experience via 1, 2, or all 3 of these modalities shapes action perception remains unclear. Here, we combine pre- and post-training functional magnetic resonance imaging measures with a dance training manipulation to address how building experience (from auditory to audiovisual to audiovisual plus motor) with a complex action shapes subsequent action perception. Results indicate that layering experience across these 3 modalities activates a number of sensorimotor cortical regions associated with the action observation network (AON) in such a way that the more modalities through which one experiences an action, the greater the response is within these AON regions during action perception. Moreover, a correlation between left premotor activity and participants' scores for reproducing an action suggests that the better an observer can perform an observed action, the stronger the neural response is. The findings suggest that the number of modalities through which an observer experiences an action impacts AON activity additively, and that premotor cortical activity might serve as an index of embodiment during action observation. © The Author 2015. Published by Oxford University Press.
Desantis, Andrea; Haggard, Patrick
To form a coherent representation of the objects around us, the brain must group the different sensory features composing these objects. Here, we investigated whether actions contribute in this grouping process. In particular, we assessed whether action-outcome learning and prediction contribute to audiovisual temporal binding. Participants were presented with two audiovisual pairs: one pair was triggered by a left action, and the other by a right action. In a later test phase, the audio and visual components of these pairs were presented at different onset times. Participants judged whether they were simultaneous or not. To assess the role of action-outcome prediction on audiovisual simultaneity, each action triggered either the same audiovisual pair as in the learning phase ('predicted' pair), or the pair that had previously been associated with the other action ('unpredicted' pair). We found the time window within which auditory and visual events appeared simultaneous increased for predicted compared to unpredicted pairs. However, no change in audiovisual simultaneity was observed when audiovisual pairs followed visual cues, rather than voluntary actions. This suggests that only action-outcome learning promotes temporal grouping of audio and visual effects. In a second experiment we observed that changes in audiovisual simultaneity do not only depend on our ability to predict what outcomes our actions generate, but also on learning the delay between the action and the multisensory outcome. When participants learned that the delay between action and audiovisual pair was variable, the window of audiovisual simultaneity for predicted pairs increased, relative to a fixed action-outcome pair delay. This suggests that participants learn action-based predictions of audiovisual outcome, and adapt their temporal perception of outcome events based on such predictions. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Gómez, Jaime; Vélez-Torres, Francisco; Rueda-Armengot, Carlos
This book examines education in entrepreneurship through an action-learning environment that employs various education tools, technology tools and pedagogical methods being implemented into university curriculums around the world. Entrepreneurship in all of its aspects, connotations, and applications has undoubtedly become a major force for new and sustainable wealth creation in both emerging and developed economies. This notion has been encouraging universities to incorporate entrepreneurship-related competencies into the curriculums of almost all subjects, as researchers, educators, and administrators alike acknowledge that students must be fully engaged and prepared to thrive in a society increasingly defined by innovation. In this context, the primary challenge consists in how to inspire or work beyond the mental limits in the classroom; to determine which learning platforms are required or useful to unlock and stimulate creativity and eliminate the human aversion to failure. Featuring contributions and c...
Full Text Available Physical and psychosocial rehabilitation following spinal cord injury (SCI leans heavily on learning and practicing new skills. However, despite research relating motor sequence learning to spinal cord activity and clinical observations of impeded skill-learning after SCI, implicit procedural learning following spinal cord damage has not been examined.To test the hypothesis that spinal cord injury (SCI in the absence of concomitant brain injury is associated with a specific implicit motor sequence learning deficit that cannot be explained by depression or impairments in other cognitive measures.Ten participants with SCI in T1-T11, unharmed upper limb motor and sensory functioning, and no concomitant brain injury were compared to ten matched control participants on measures derived from the serial reaction time (SRT task, which was used to assess implicit motor sequence learning. Explicit generation of the SRT sequence, depression, and additional measures of learning, memory, and intelligence were included to explore the source and specificity of potential learning deficits.There was no between-group difference in baseline reaction time, indicating that potential differences between the learning curves of the two groups could not be attributed to an overall reduction in response speed in the SCI group. Unlike controls, the SCI group showed no decline in reaction time over the first six blocks of the SRT task and no advantage for the initially presented sequence over the novel interference sequence. Meanwhile, no group differences were found in explicit learning, depression, or any additional cognitive measures.The dissociation between impaired implicit learning and intact declarative memory represents novel empirical evidence of a specific implicit procedural learning deficit following SCI, with broad implications for rehabilitation and adjustment.
Höper, Dirk; Finke, Stefan; Freuling, Conrad M; Hoffmann, Bernd; Beer, Martin
The main task of the individual project number four"Whole genome sequencing, virus-host adaptation, and molecular epidemiological analyses of lyssaviruses "within the network" Lyssaviruses--a potential re-emerging public health threat" is to provide high quality complete genome sequences from lyssaviruses. These sequences are analysed in-depth with regard to the diversity of the viral populations as to both quasi-species and so-called defective interfering RNAs. Moreover, the sequence data will facilitate further epidemiological analyses, will provide insight into the evolution of lyssaviruses and will be the basis for the design of novel nucleic acid based diagnostics. The first results presented here indicate that not only high quality full-length lyssavirus genome sequences can be generated, but indeed efficient analysis of the viral population gets feasible.
The paper reviews teacher candidates' use of action research and the Professional Learning Community (PLC) concept to support their work in their pre-student teaching field experience. In this research study, teacher candidates are involved in a professional development school relationship that uses action research and PLCs to support candidate…
Murray, James M; Escola, G Sean
Sparse, sequential patterns of neural activity have been observed in numerous brain areas during timekeeping and motor sequence tasks. Inspired by such observations, we construct a model of the striatum, an all-inhibitory circuit where sequential activity patterns are prominent, addressing the following key challenges: (i) obtaining control over temporal rescaling of the sequence speed, with the ability to generalize to new speeds; (ii) facilitating flexible expression of distinct sequences via selective activation, concatenation, and recycling of specific subsequences; and (iii) enabling the biologically plausible learning of sequences, consistent with the decoupling of learning and execution suggested by lesion studies showing that cortical circuits are necessary for learning, but that subcortical circuits are sufficient to drive learned behaviors. The same mechanisms that we describe can also be applied to circuits with both excitatory and inhibitory populations, and hence may underlie general features of sequential neural activity pattern generation in the brain.
de León, Lourdes
This chapter examines Mayan children's initiatives in creating their own learning environments in collaboration with others as they engage in culturally relevant endeavors of family and community life. To this end, I carry out a fine-grained ethnographic and linguistic analysis of the interactional emergence of learning ecologies. Erickson defines learning ecology as a socioecological system where participants mutually influence one another through verbal and nonverbal actions, as well as through other forms of semiotic communication (2010, 254). In analyzing learning ecologies, I adopt a "theory of action" approach, taking into account multimodal communication (e.g., talk, gesture, gaze, body positioning), participants' sociospatial organization, embodied action, objects, tools, and other culturally relevant materials brought together to build action (Goodwin, 2000, 2013; Hutchins, 1995). I use microethnographic analysis (Erickson, 1992) to bring to the surface central aspects of children's agentive roles in learning through "cooperative actions" (Goodwin, 2013) and "hands-on" experience (Ingold, 2007) the skills of competent members of their community. I examine three distinct Learning Ecologies created by children's initiatives among the Mayan children that I observed: (i) children requesting guidance to collaborate in a task, (ii) older children working on their own initiative with subsequent monitoring and correction from competent members, and (iii) children with near competence in a task with occasional monitoring and no guidance. I argue that these findings enrich and add power to models of family- and community-based learning such as Learning by Observing and Pitching In (Rogoff, 2014). © 2015 Elsevier Inc. All rights reserved.
Roseberry, Sarah; Hirsh-Pasek, Kathy; Parish-Morris, Julia; Golinkoff, Roberta Michnick
The availability of educational programming aimed at infants and toddlers is increasing, yet the effect of video on language acquisition remains unclear. Three studies of 96 children aged 30–42 months investigated their ability to learn verbs from video. Study 1 asked whether children could learn verbs from video when supported by live social interaction. Study 2 tested whether children could learn verbs from video alone. Study 3 clarified whether the benefits of social interaction remained w...
Kamiyama, Keiko S; Okanoya, Kazuo
The purpose of the present study was to determine whether and how single finger tapping in synchrony with sound sequences contributed to the auditory processing of them. The participants learned two unfamiliar sound sequences via different methods. In the tapping condition, they learned an auditory sequence while they tapped in synchrony with each sound onset. In the no tapping condition, they learned another sequence while they kept pressing a key until the sequence ended. After these learning sessions, we presented the two melodies again and recorded event-related potentials (ERPs). During the ERP recordings, 10% of the tones within each melody deviated from the original tones. An analysis of the grand average ERPs showed that deviant stimuli elicited a significant P300 in the tapping but not in the no-tapping condition. In addition, the significance of the P300 effect in the tapping condition increased as the participants showed highly synchronized tapping behavior during the learning sessions. These results indicated that single finger tapping promoted the conscious detection and evaluation of deviants within the learned sequences. The effect was related to individuals' musical ability to coordinate their finger movements along with external auditory events.
Langner, Robert; Sternkopf, Melanie A; Kellermann, Tanja S; Grefkes, Christian; Kurth, Florian; Schneider, Frank; Zilles, Karl; Eickhoff, Simon B
The neurobiological organization of action-oriented working memory is not well understood. To elucidate the neural correlates of translating visuo-spatial stimulus sequences into delayed (memory-guided) sequential actions, we measured brain activity using functional magnetic resonance imaging while participants encoded sequences of four to seven dots appearing on fingers of a left or right schematic hand. After variable delays, sequences were to be reproduced with the corresponding fingers. Recall became less accurate with longer sequences and was initiated faster after long delays. Across both hands, encoding and recall activated bilateral prefrontal, premotor, superior and inferior parietal regions as well as the basal ganglia, whereas hand-specific activity was found (albeit to a lesser degree during encoding) in contralateral premotor, sensorimotor, and superior parietal cortex. Activation differences after long versus short delays were restricted to motor-related regions, indicating that rehearsal during long delays might have facilitated the conversion of the memorandum into concrete motor programs at recall. Furthermore, basal ganglia activity during encoding selectively predicted correct recall. Taken together, the results suggest that to-be-reproduced visuo-spatial sequences are encoded as prospective action representations (motor intentions), possibly in addition to retrospective sensory codes. Overall, our study supports and extends multi-component models of working memory, highlighting the notion that sensory input can be coded in multiple ways depending on what the memorandum is to be used for. Copyright © 2013 Wiley Periodicals, Inc.
In 2007, the Federal Railroad Administration (FRA) launched : C3RS, the Confidential Close Call Reporting System, as a : demonstration project to learn how to facilitate the effective : reporting and implementation of corrective actions, and assess t...
Ghirardi, Marco; Marchetti, Fabio; Pettinari, Claudio; Regis, Alberto; Roletto, Ezio
A novel didactic sequence is proposed for the teaching of chemical equilibrium. This teaching sequence takes into account the historical and epistemological evolution of the concept, the alternative conceptions and learning difficulties highlighted by teaching science and research in education, and the need to focus on both the students'…
Martin, Michael W.; Shen, Yuzhong
This paper explores the distinction between operative and resultant actions in games, and proposes that the learning space created by a serious game is a function of these actions. Further, it suggests a possible relationship between these actions and the forms of cognitive load imposed upon the game player. Association of specific types of cognitive load with respective forms of actions in game mechanics also presents some heuristics for integrating learning content into serious games. Research indicates that different balances of these types of actions are more suitable for novice or experienced learners. By examining these relationships, we can develop a few basic principles of game design which have an increased potential to promote positive learning outcomes.
Friedrich, Johannes; Urbanczik, Robert; Senn, Walter
Population coding is widely regarded as a key mechanism for achieving reliable behavioral decisions. We previously introduced reinforcement learning for population-based decision making by spiking neurons. Here we generalize population reinforcement learning to spike-based plasticity rules that take account of the postsynaptic neural code. We consider spike/no-spike, spike count and spike latency codes. The multi-valued and continuous-valued features in the postsynaptic code allow for a generalization of binary decision making to multi-valued decision making and continuous-valued action selection. We show that code-specific learning rules speed up learning both for the discrete classification and the continuous regression tasks. The suggested learning rules also speed up with increasing population size as opposed to standard reinforcement learning rules. Continuous action selection is further shown to explain realistic learning speeds in the Morris water maze. Finally, we introduce the concept of action perturbation as opposed to the classical weight- or node-perturbation as an exploration mechanism underlying reinforcement learning. Exploration in the action space greatly increases the speed of learning as compared to exploration in the neuron or weight space.
Fu, Yuchen; Liu, Quan; Ling, Xionghong; Cui, Zhiming
Reinforcement learning (RL) is one kind of interactive learning methods. Its main characteristics are "trial and error" and "related reward." A hierarchical reinforcement learning method based on action subrewards is proposed to solve the problem of "curse of dimensionality," which means that the states space will grow exponentially in the number of features and low convergence speed. The method can reduce state spaces greatly and choose actions with favorable purpose and efficiency so as to optimize reward function and enhance convergence speed. Apply it to the online learning in Tetris game, and the experiment result shows that the convergence speed of this algorithm can be enhanced evidently based on the new method which combines hierarchical reinforcement learning algorithm and action subrewards. The "curse of dimensionality" problem is also solved to a certain extent with hierarchical method. All the performance with different parameters is compared and analyzed as well.
Ren, Huamin; Kanhabua, Nattiya; Møgelmose, Andreas
transfer learning being a promising approach, it is still an open question how to adapt the model learned from the source dataset to the target dataset. One big challenge is to prevent the impact of category bias on classification performance. Dataset bias exists when two images from the same category...
This paper examines how Cooperative learning (CL) and democracy can be examined in relation to one another. CL supports a social constructivist view of students learning together to form knowledge through direct interaction. The overriding benefits of CL are that that it is an effective strategy for maximising both social and academic learning…
Teixeira-Poit, Stephanie M.; Cameron, Abigail E.; Schulman, Michael D.
How can instructors use experiential learning strategies to enhance student understanding of research ethics and responsible research conduct? In this article, the authors review literature on using experiential learning to teach research ethics and responsible research conduct. They present a three-step exercise for teaching research ethics and…
Scheer, Andrea; Noweski, Christine; Meinel, Christoph
In an ever changing society of the 21st century, there is a demand to equip students with meta competences going beyond cognitive knowledge. Education, therefore, needs a transition from transferring knowledge to developing individual potentials with the help of constructivist learning. Advantages of constructivist learning, and criteria for its…
Roseberry, Sarah; Hirsh-Pasek, Kathy; Parish-Morris, Julia; Golinkoff, Roberta M.
The availability of educational programming aimed at infants and toddlers is increasing, yet the effect of video on language acquisition remains unclear. Three studies of 96 children aged 30-42 months investigated their ability to learn verbs from video. Study 1 asked whether children could learn verbs from video when supported by live social…
Ostergaard, Edvin; Lieblein, Geir; Breland, Tor Arvid; Francis, Charles
Preparing students for a complex and dynamic future is a challenge for educators. This article explores three crucial issues related to agroecological education and learning: (1) the phenomenological foundation for learning agroecology in higher education; (2) the process of students' interactions with a wide range of various learners within and…
Full Text Available We investigated the influence of attentional demands on sequence-specific learning by means of the serial reaction time (SRT task (Nissen & Bullemer, 1987 in young (age 18-25 and aged (age 55-75 adults. Participants had to respond as fast as possible to a stimulus presented in one of four horizontal locations by pressing a key corresponding to the spatial position of the stimulus. During the training phase sequential blocks were accompanied by (1 no secondary task (single, (2 a secondary tone counting task (dual tone, or (3 a secondary shape counting task (dual shape. Both secondary tasks were administered to investigate whether low and high interference tasks interact with implicit learning and age. The testing phase, under baseline single condition, was implemented to assess differences in sequence-specific learning between young and aged adults. Results indicate that (1 aged subjects show less sequence learning compared to young adults, (2 young participants show similar implicit learning effects under both single and dual task conditions when we account for explicit awareness, and (3 aged adults demonstrate reduced learning when the primary task is accompanied with a secondary task, even when explicit awareness is included as a covariate in the analysis. These findings point to implicit learning deficits under dual task conditions that can be related to cognitive aging, demonstrating the need for sufficient cognitive resources while performing a sequence learning task.
Whitfield, Jason A.; Goberman, Alexander M.
Purpose: The aim of the current investigation was to examine speech motor sequence learning in neurologically healthy younger adults, neurologically healthy older adults, and individuals with Parkinson disease (PD) over a 2-day period. Method: A sequential nonword repetition task was used to examine learning over 2 days. Participants practiced a…
Hsu, Hsinjen Julie; Bishop, Dorothy V M
This study tested the procedural deficit hypothesis of specific language impairment (SLI) by comparing children's performance in two motor procedural learning tasks and an implicit verbal sequence learning task. Participants were 7- to 11-year-old children with SLI (n = 48), typically developing age-matched children (n = 20) and younger typically developing children matched for receptive grammar (n = 28). In a serial reaction time task, the children with SLI performed at the same level as the grammar-matched children, but poorer than age-matched controls in learning motor sequences. When tested with a motor procedural learning task that did not involve learning sequential relationships between discrete elements (i.e. pursuit rotor), the children with SLI performed comparably with age-matched children and better than younger grammar-matched controls. In addition, poor implicit learning of word sequences in a verbal memory task (the Hebb effect) was found in the children with SLI. Together, these findings suggest that SLI might be characterized by deficits in learning sequence-specific information, rather than generally weak procedural learning. © 2014 The Authors. Developmental Science Published by John Wiley & Sons Ltd.
Stephan, Marianne A.; Meier, Beat; Zaugg, Sabine Weber; Kaelin-Lang, Alain
It is still unclear, whether patients with Parkinson's disease (PD) are impaired in the incidental learning of different motor sequences in short succession, although such a deficit might greatly impact their daily life. The aim of this study was thus to clarify the relation between disease parameters of PD and incidental motor learning of two…
Young, Sarah; Nixon, Eileen; Hinge, Denise; McFadyen, Jan; Wright, Vanessa; Lambert, Pauline; Pilkington, Carolyn; Newsome, Christine
This paper will discuss the process of action learning and the outcomes of using action learning as a tool to achieve a more strategic function from Nurse Consultant posts. It is documented that one of the most challenging aspect of Nurse Consultant roles, in terms of leadership, is the strategic contribution they make at a senior corporate Trust level, often across organizations and local health economies. A facilitated action learning set was established in Brighton, England, to support the strategic leadership development of eight nurse consultant posts across two NHS Trusts. Benefits to patient care, with regard to patient pathways and cross-organizational working, have been evident outcomes associated with the nurse consultant posts involved in the action learning set. Commitment by organizational nurse leaders is essential to address the challenges facing nurse consultants to implement change at strategic levels. The use of facilitated action learning had been a successful tool in developing the strategic skills of Nurse Consultant posts within this setting. Action learning sets may be successfully applied to a range of senior nursing posts with a strategic remit and may assist post holders in achieving better outcomes pertinent to their roles.
Helden, J. van der; Schie, H.T. van; Rombouts, C.
Mankind is unique in her ability for observational learning, i.e. the transmission of acquired knowledge and behavioral repertoire through observation of others' actions. In the present study we used electrophysiological measures to investigate brain mechanisms of observational learning. Analysis
van der Helden, J.; van Schie, Hein T.; Rombouts, Christiaan
Mankind is unique in her ability for observational learning, i.e. the transmission of acquired knowledge and behavioral repertoire through observation of others' actions. In the present study we used electrophysiological measures to investigate brain mechanisms of observational learning. Analysis
Zhou, Jian; Troyanskaya, Olga G
Identifying functional effects of noncoding variants is a major challenge in human genetics. To predict the noncoding-variant effects de novo from sequence, we developed a deep learning-based algorithmic framework, DeepSEA (http://deepsea.princeton.edu/), that directly learns a regulatory sequence code from large-scale chromatin-profiling data, enabling prediction of chromatin effects of sequence alterations with single-nucleotide sensitivity. We further used this capability to improve prioritization of functional variants including expression quantitative trait loci (eQTLs) and disease-associated variants.
Kawulich, Barbara B.
This manuscript shares lessons learned from conducting an action evaluation of the use of multimedia case studies in Management Information Systems (MIS) courses. Three undergraduate MIS classes took part in the study. The purpose for using case studies in these classes was to teach students about the role of MIS in business. An action evaluation…
Mills, Jane; Gibbon, David; Ingram, Julie; Reed, Matt; Short, Christopher; Dwyer, Janet
The paper explored key factors that might lead to successful agri-environmental social learning and collective action in order to deliver landscape-scale resource management within agri-environment schemes. Using the theory of collective action as an analytical framework the paper examined findings from in-depth interviews with 20 members of two…
Liljeholm, Mimi; Molloy, Ciara J; O'Doherty, John P
Two distinct strategies have been suggested to support action selection in humans and other animals on the basis of experiential learning: a goal-directed strategy that generates decisions based on the value and causal antecedents of action outcomes, and a habitual strategy that relies on the automatic elicitation of actions by environmental stimuli. In the present study, we investigated whether a similar dichotomy exists for actions that are acquired vicariously, through observation of other individuals rather than through direct experience, and assessed whether these strategies are mediated by distinct brain regions. We scanned participants with functional magnetic resonance imaging while they performed an observational learning task designed to encourage either goal-directed encoding of the consequences of observed actions, or a mapping of observed actions to conditional discriminative cues. Activity in different parts of the action observation network discriminated between the two conditions during observational learning and correlated with the degree of insensitivity to outcome devaluation in subsequent performance. Our findings suggest that, in striking parallel to experiential learning, neural systems mediating the observational acquisition of actions may be dissociated into distinct components: a goal-directed, outcome-sensitive component and a less flexible stimulus-response component.
Boudett, Kathryn Parker, Ed.; Steele, Jennifer L., Ed.
What does it look like when a school uses data wisely? "Data Wise in Action", a new companion and sequel to the bestselling "Data Wise", tells the stories of eight very different schools following the Data Wise process of using assessment results to improve teaching and learning. "Data Wise in Action" highlights the…
Asmolov, V.G.; Khakh, O.Ya.; Shashkov, M.G.
The problem of beyond-design accidents at nuclear stations will not be solved unless a safety culture becomes a basic characteristic of all lines of activity. Only then can the danger of accidents as an objective feature of nuclear stations be eliminated by purposive skilled and responsible activities of those implementing safety. Nuclear-station safety is provided by the following interacting and complementary lines of activity: (1) the design and construction of nuclear stations by properly qualified design and building organizations; (2) monitoring and supervision of safety by special state bodies; (3) control of the station by the exploiting organization; and (4) scientific examination of safety within the above framework and by independent organizations. The distribution of the responsibilities, powers, and right in these lines should be defined by a law on atomic energy, but there is not such law in Russian. The beyond-design accident problem is a key one in nuclear station safety, as it clear from the serious experience with accidents and numerous probabilistic studies. There are four features of the state of this topic in Russia that are of major significance for managing accidents: the lack of an atomic energy law, the inadequacy of the technical standards, the lack of a verified program package for nuclear-station designs in order to calculate the beyond-design accidents and analyze risks, and a lack of approach by designers to such accidents on the basis of international recommendations. This paper gives a brief description of three-forming points in the scientific activity: the general concept of nuclear-station safety, methods of analyzing and providing accident management, and the sequence of actions developed by specialists at this institute in recent years
Brawn, Timothy P; Fenn, Kimberly M; Nusbaum, Howard C; Margoliash, Daniel
Sleep is widely believed to play a critical role in memory consolidation. Sleep-dependent consolidation has been studied extensively in humans using an explicit motor-sequence learning paradigm. In this task, performance has been reported to remain stable across wakefulness and improve significantly after sleep, making motor-sequence learning the definitive example of sleep-dependent enhancement. Recent work, however, has shown that enhancement disappears when the task is modified to reduce task-related inhibition that develops over a training session, thus questioning whether sleep actively consolidates motor learning. Here we use the same motor-sequence task to demonstrate sleep-dependent consolidation for motor-sequence learning and explain the discrepancies in results across studies. We show that when training begins in the morning, motor-sequence performance deteriorates across wakefulness and recovers after sleep, whereas performance remains stable across both sleep and subsequent waking with evening training. This pattern of results challenges an influential model of memory consolidation defined by a time-dependent stabilization phase and a sleep-dependent enhancement phase. Moreover, the present results support a new account of the behavioral effects of waking and sleep on explicit motor-sequence learning that is consistent across a wide range of tasks. These observations indicate that current theories of memory consolidation that have been formulated to explain sleep-dependent performance enhancements are insufficient to explain the range of behavioral changes associated with sleep.
Lagisz, Malgorzata; Mercer, Alison R; de Mouzon, Charlotte; Santos, Luana L S; Nakagawa, Shinichi
Octopamine- and dopamine-based neuromodulatory systems play a critical role in learning and learning-related behaviour in insects. To further our understanding of these systems and resulting phenotypes, we quantified DNA sequence variations at six loci coding octopamine-and dopamine-receptors and their association with aversive and appetitive learning traits in a population of honeybees. We identified 79 polymorphic sequence markers (mostly SNPs and a few insertions/deletions) located within or close to six candidate genes. Intriguingly, we found that levels of sequence variation in the protein-coding regions studied were low, indicating that sequence variation in the coding regions of receptor genes critical to learning and memory is strongly selected against. Non-coding and upstream regions of the same genes, however, were less conserved and sequence variations in these regions were weakly associated with between-individual differences in learning-related traits. While these associations do not directly imply a specific molecular mechanism, they suggest that the cross-talk between dopamine and octopamine signalling pathways may influence olfactory learning and memory in the honeybee.
Gabrielsson, Jonas; Tell, Joakim; Politis, Diamanto
Recent calls to close the rigour-relevance gap in business school education have suggested incorporating principles and ideas from action learning in small business management education. In this paper we discuss how business simulation exercises can be used as a platform to trigger students' learning by providing them with a platform where they…
Edmonstone, John; Robson, Jean
This account of practice describes the introduction of an accredited postgraduate management qualification which used action learning as a major contribution to a blended learning approach in a fragile cross-border setting on the edge of Europe. Conventional management education has frequently been challenged on the grounds of relevance, efficacy…
This article explores learning opportunities offered by students' written reflections as they learn through writing an action research proposal. From tapping into students' reported struggles, I analysed data using three stages of qualitative data analysis: data reduction, data display, and conclusion drawing (Miles and Huberman 1994). It emerged…
Milano, Chloe; Lawless, Aileen; Eades, Elaine
This account explores the role of action learning during and after an educational programme. We focus on the final stage of a master's programme and the insider research that is a key feature in many UK universities. Researching within one's own organization should lead to individual and organizational learning. However, there is relatively little…
Calvert, Megan; Sheen, Younghee
The creation, implementation, and evaluation of language learning tasks remain a challenge for many teachers, especially those with limited experience with using tasks in their teaching. This action-research study reports on one teacher's experience of developing, implementing, critically reflecting on, and modifying a language learning task…
Smith, Janice Witt; Clark, Gloria
This research study looks at the implementation of an action research project within a blended learning human resource management class in employee and labor relations. The internal and external environment created conditions that converged in the Perfect Storm and resulted in an almost disastrous learning experience for faculty and students. What…
Macy, M.W.; Flache, A.
We are grateful for the opportunity that Bendor, Diermeier, and Ting (hereafter BDT) have provided to address important questions about the empirical content of learning theoretic solutions to the collective action problem. They discuss two well-known classes of adaptive models— stochastic learning
Cooper, Jeffrey C; Dunne, Simon; Furey, Teresa; O'Doherty, John P
The dorsal striatum plays a key role in the learning and expression of instrumental reward associations that are acquired through direct experience. However, not all learning about instrumental actions require direct experience. Instead, humans and other animals are also capable of acquiring instrumental actions by observing the experiences of others. In this study, we investigated the extent to which human dorsal striatum is involved in observational as well as experiential instrumental reward learning. Human participants were scanned with fMRI while they observed a confederate over a live video performing an instrumental conditioning task to obtain liquid juice rewards. Participants also performed a similar instrumental task for their own rewards. Using a computational model-based analysis, we found reward prediction errors in the dorsal striatum not only during the experiential learning condition but also during observational learning. These results suggest a key role for the dorsal striatum in learning instrumental associations, even when those associations are acquired purely by observing others.
classroom environment have to change as the curriculum changes. Objectives. 1. To modify ... South African schools in terms of the dimensions assessed by the. CLES. 3. ...... middle school. Learning Environments Research: An International.
Ariel, Ellen; Owens, Leigh
The module described and evaluated here was created in response to perceived learning difficulties in diagnostic test design and interpretation for students in third-year Clinical Microbiology. Previously, the activities in lectures and laboratory classes in the module fell into the lower cognitive operations of “knowledge” and “understanding.” The new approach was to exchange part of the traditional activities with elements of interactive learning, where students had the opportunity to engag...
The paper centre on an Action Research project undertaken in India for enabling the female students empowered through Internet use. The paper will discuss the design elements of Internet training for the first time users with limited Internet access based on Blooms Digital Taxonomy of Learning...... Domains.The paper also illustrates the identity formation of students, through learning to use Internet, using wengers social theory of learning with the empirical data....
Daikoku, Tatsuya; Yatomi, Yutaka; Yumoto, Masato
In our previous study (Daikoku, Yatomi, & Yumoto, 2014), we demonstrated that the N1m response could be a marker for the statistical learning process of pitch sequence, in which each tone was ordered by a Markov stochastic model. The aim of the present study was to investigate how the statistical learning of music- and language-like auditory sequences is reflected in the N1m responses based on the assumption that both language and music share domain generality. By using vowel sounds generated by a formant synthesizer, we devised music- and language-like auditory sequences in which higher-ordered transitional rules were embedded according to a Markov stochastic model by controlling fundamental (F0) and/or formant frequencies (F1-F2). In each sequence, F0 and/or F1-F2 were spectrally shifted in the last one-third of the tone sequence. Neuromagnetic responses to the tone sequences were recorded from 14 right-handed normal volunteers. In the music- and language-like sequences with pitch change, the N1m responses to the tones that appeared with higher transitional probability were significantly decreased compared with the responses to the tones that appeared with lower transitional probability within the first two-thirds of each sequence. Moreover, the amplitude difference was even retained within the last one-third of the sequence after the spectral shifts. However, in the language-like sequence without pitch change, no significant difference could be detected. The pitch change may facilitate the statistical learning in language and music. Statistically acquired knowledge may be appropriated to process altered auditory sequences with spectral shifts. The relative processing of spectral sequences may be a domain-general auditory mechanism that is innate to humans. Copyright © 2014 Elsevier Inc. All rights reserved.
Tzvi, Elinor; Bauhaus, Leon J; Kessler, Till U; Liebrand, Matthias; Wöstmann, Malte; Krämer, Ulrike M
Cross-frequency coupling is suggested to serve transfer of information between wide-spread neuronal assemblies and has been shown to underlie many cognitive functions including learning and memory. In previous work, we found that alpha (8-13 Hz) - gamma (30-48 Hz) phase amplitude coupling (αγPAC) is decreased during sequence learning in bilateral frontal cortex and right parietal cortex. We interpreted this to reflect decreased demands for visuo-motor mapping once the sequence has been encoded. In the present study, we put this hypothesis to the test by adding a "simple" condition to the standard serial reaction time task (SRTT) with minimal needs for visuo-motor mapping. The standard SRTT in our paradigm entailed a perceptual sequence allowing for implicit learning of a sequence of colors with randomly assigned motor responses. Sequence learning in this case was thus not associated with reduced demands for visuo-motor mapping. Analysis of oscillatory power revealed a learning-related alpha decrease pointing to a stronger recruitment of occipito-parietal areas when encoding the perceptual sequence. Replicating our previous findings but in contrast to our hypothesis, αγPAC was decreased in sequence compared to random trials over right frontal and parietal cortex. It also tended to be smaller compared to trials requiring a simple motor sequence. We additionally analyzed αγPAC in resting-state data of a separate cohort. PAC in electrodes over right parietal cortex was significantly stronger compared to sequence trials and tended to be higher compared to simple and random trials of the SRTT data. We suggest that αγPAC in right parietal cortex reflects a "default-mode" brain state, which gets perturbed to allow for encoding of visual regularities into memory. Copyright © 2018 Elsevier Inc. All rights reserved.
Boiling water reactor severe accident sequence studies are being carried out using Browns Ferry Unit 1 as the model plant. Four accident studies were completed, resulting in recommendations for improvements in system design, emergency procedures, and operator training. Computer code improvements were an important by-product
Shahib, Ali Al-; Gilbert, David; Breitling, Rainer
Much work has been done to identify species-specific proteins in sequenced genomes and hence to determine their function. We assumed that such proteins have specific physico-chemical properties that will discriminate them from proteins in other species. In this paper, we examine the validity of this
Chang, Acer Y-C; Schwartzman, David J; VanRullen, Rufin; Kanai, Ryota; Seth, Anil K
A novel neural signature of active visual processing has recently been described in the form of the "perceptual echo", in which the cross-correlation between a sequence of randomly fluctuating luminance values and occipital electrophysiological signals exhibits a long-lasting periodic (∼100 ms cycle) reverberation of the input stimulus (VanRullen and Macdonald, 2012). As yet, however, the mechanisms underlying the perceptual echo and its function remain unknown. Reasoning that natural visual signals often contain temporally predictable, though nonperiodic features, we hypothesized that the perceptual echo may reflect a periodic process associated with regularity learning. To test this hypothesis, we presented subjects with successive repetitions of a rapid nonperiodic luminance sequence, and examined the effects on the perceptual echo, finding that echo amplitude linearly increased with the number of presentations of a given luminance sequence. These data suggest that the perceptual echo reflects a neural signature of regularity learning.Furthermore, when a set of repeated sequences was followed by a sequence with inverted luminance polarities, the echo amplitude decreased to the same level evoked by a novel stimulus sequence. Crucially, when the original stimulus sequence was re-presented, the echo amplitude returned to a level consistent with the number of presentations of this sequence, indicating that the visual system retained sequence-specific information, for many seconds, even in the presence of intervening visual input. Altogether, our results reveal a previously undiscovered regularity learning mechanism within the human visual system, reflected by the perceptual echo. SIGNIFICANCE STATEMENT How the brain encodes and learns fast-changing but nonperiodic visual input remains unknown, even though such visual input characterizes natural scenes. We investigated whether the phenomenon of "perceptual echo" might index such learning. The perceptual echo is a
The 'action observation network' (AON), which is thought to translate observed actions into motor codes required for their execution, is biologically tuned: it responds more to observation of human, than non-human, movement. This biological specificity has been taken to support the hypothesis that the AON underlies various social functions, such as theory of mind and action understanding, and that, when it is active during observation of non-human agents like humanoid robots, it is a sign of ascription of human mental states to these agents. This review will outline evidence for biological tuning in the AON, examining the features which generate it, and concluding that there is evidence for tuning to both the form and kinematic profile of observed movements, and little evidence for tuning to belief about stimulus identity. It will propose that a likely reason for biological tuning is that human actions, relative to non-biological movements, have been observed more frequently while executing corresponding actions. If the associative hypothesis of the AON is correct, and the network indeed supports social functioning, sensorimotor experience with non-human agents may help us to predict, and therefore interpret, their movements. Copyright © 2011 Elsevier Ltd. All rights reserved.
McNamara, Martin S; Fealy, Gerard M; Casey, Mary; O'Connor, Tom; Patton, Declan; Doyle, Louise; Quinlan, Christina
To evaluate mentoring, coaching and action learning interventions used to develop nurses' and midwives' clinical leadership competencies and to describe the programme participants' experiences of the interventions. Mentoring, coaching and action learning are effective interventions in clinical leadership development and were used in a new national clinical leadership development programme, introduced in Ireland in 2011. An evaluation of the programme focused on how participants experienced the interventions. A qualitative design, using multiple data sources and multiple data collection methods. Methods used to generate data on participant experiences of individual interventions included focus groups, individual interviews and nonparticipant observation. Seventy participants, including 50 programme participants and those providing the interventions, contributed to the data collection. Mentoring, coaching and action learning were positively experienced by participants and contributed to the development of clinical leadership competencies, as attested to by the programme participants and intervention facilitators. The use of interventions that are action-oriented and focused on service development, such as mentoring, coaching and action learning, should be supported in clinical leadership development programmes. Being quite different to short attendance courses, these interventions require longer-term commitment on the part of both individuals and their organisations. In using mentoring, coaching and action learning interventions, the focus should be on each participant's current role and everyday practice and on helping the participant to develop and demonstrate clinical leadership skills in these contexts. © 2014 John Wiley & Sons Ltd.
Paulus, Markus; Hunnius, Sabine; Bekkering, Harold
Social transmission of knowledge is one of the reasons for human evolutionary success, and it has been suggested that already human infants possess eminent social learning abilities. However, nothing is known about the neurocognitive mechanisms that subserve infants' acquisition of novel action knowledge through the observation of other people's actions and their consequences in the physical world. In an electroencephalogram study on social learning in infancy, we demonstrate that 9-month-old infants represent the environmental effects of others' actions in their own motor system, although they never achieved these effects themselves before. The results provide first insights into the neurocognitive basis of human infants' unique ability for social learning of novel action knowledge.
Reviewed by Patrick J. Fahy
Full Text Available Action learning, as defined in this book, is “a process of reflecting on one’s work and beliefs in the supportive/ confrontational environment of one’s peers for the purpose of gaining new insights and resolving real business and community problems in real time” (p. 11. The claims made for action learning are impressive. Action learning: * Allows participants (who work in groups called sets to answer the question, “What is an honest man, and what do I need to do to become one?” (p. viii. * Is more than learning by doing, action learning “has the potential for putting control of lifelong learning directly in the hands of learners, in ways that alter their perceptions, amplify self-efficacy, and re-connect these individuals to spontaneous curiosity and confidence in the exercise of their own good judgment” (p. xi. * Is a “sleeping giant in the catalogue of individual and organizational change strategies” (p. xi. * Is believed to address the five most important needs facing organizations today: 1 problem-solving; 2 organizational learning; 3 leadership development; 4 professional growth; and 5 career development (p. xiii.
Archibald, Lisa M D; Joanisse, Marc F
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.
Frese, Michael; Keith, Nina
Every organization is confronted with errors. Most errors are corrected easily, but some may lead to negative consequences. Organizations often focus on error prevention as a single strategy for dealing with errors. Our review suggests that error prevention needs to be supplemented by error management--an approach directed at effectively dealing with errors after they have occurred, with the goal of minimizing negative and maximizing positive error consequences (examples of the latter are learning and innovations). After defining errors and related concepts, we review research on error-related processes affected by error management (error detection, damage control). Empirical evidence on positive effects of error management in individuals and organizations is then discussed, along with emotional, motivational, cognitive, and behavioral pathways of these effects. Learning from errors is central, but like other positive consequences, learning occurs under certain circumstances--one being the development of a mind-set of acceptance of human error.
Verhagen, H.J.; Van der Pol, C.; Glasius, A.; Winnubst, M.
Projects using innovative concepts in coastal defence -like ComCoast- can benefit greatly from participatory action. It can lead to innovative solutions with a broad societal support base, as is shown in the plan for water storage in the Overdiepse polder and the inundation compensation scheme for
Savic, Branislav; Cazzoli, Dario; Müri, René; Meier, Beat
Neurostimulation of the dorsolateral prefrontal cortex (DLPFC) can modulate performance in cognitive tasks. In a recent study, however, transcranial direct current stimulation (tDCS) of the DLPFC did not affect implicit task sequence learning and consolidation in a paradigm that involved bimanual responses. Because bimanual performance increases the coupling between homologous cortical areas of the hemispheres and left and right DLPFC were stimulated separately the null findings may have been due to the bimanual setup. The aim of the present study was to test the effect of neuro-stimulation on sequence learning in a uni-manual setup. For this purpose two experiments were conducted. In Experiment 1, the DLPFC was stimulated with tDCS. In Experiment 2 the DLPFC was stimulated with transcranial magnetic stimulation (TMS). In both experiments, consolidation was measured 24 hours later. The results showed that sequence learning was present in all conditions and sessions, but it was not influenced by stimulation. Likewise, consolidation of sequence learning was robust across sessions, but it was not influenced by stimulation. These results replicate and extend previous findings. They indicate that established tDCS and TMS protocols on the DLPFC do not influence implicit task sequence learning and consolidation.
Schuck, Nicolas W; Frensch, Peter A; Schjeide, Brit-Maren M; Schröder, Julia; Bertram, Lars; Li, Shu-Chen
The striatum and medial temporal lobe play important roles in implicit and explicit memory, respectively. Furthermore, recent studies have linked striatal dopamine modulation to both implicit as well as explicit sequence learning and suggested a potential role of the striatum in the emergence of explicit memory during sequence learning. With respect to aging, previous findings indicated that implicit memory is less impaired than explicit memory in older adults and that genetic effects on cognition are magnified by aging. To understand the links between these findings, we investigated effects of aging and genotypes relevant for striatal dopamine on the implicit and explicit components of sequence learning. Reaction time (RT) and error data from 80 younger (20-30 years) and 70 older adults (60-71 years) during a serial reaction time task showed that age differences in learning-related reduction of RTs emerged gradually over the course of learning. Verbal recall and measures derived from the process-dissociation procedure revealed that younger adults acquired more explicit memory about the sequence than older adults, potentially causing age differences in RT gains in later stages of learning. Of specific interest, polymorphisms of the dopamine- and cAMP-regulated neuronal phosphoprotein (DARPP-32, rs907094) and dopamine transporter (DAT, VNTR) genes showed interactive effects on overall RTs and verbal recall of the sequence in older but not in younger adults. Together our findings show that variations in genotypes relevant for dopamine functions are associated more with aging-related impairments in the explicit than the implicit component of sequence learning, providing support for theories emphasizing the role of dopaminergic modulation in cognitive aging and the magnification of genetic effects in human aging. © 2013 Elsevier Ltd. All rights reserved.
Noguchi, Fumiko; Guevara, Jose Roberto; Yorozu, Rika
This handbook identifies principles and policy mechanisms to advance community-based learning for sustainable development based on the commitments endorsed by the participants of the "Kominkan-CLC International Conference on Education for Sustainable Development," which took place in Okayama City, Japan, in October 2014. To inform…
Stewart, Trae, Ed.; Webster, Nicole, Ed.
Interest in and research on civic engagement and service-learning have increased exponentially. In this rapid growth, efforts have been made to institutionalize pedagogies of engagement across both K-12 and higher education. As a result, increased positive attention has been complemented equally by well-founded critiques complicating experiential…
Nasrollahi, Kamal; Guerrero, Sergio Escalera; Rasti, Pejman
with results of a state-of- the-art deep learning-based super-resolution algorithm, through an alpha-blending approach. The experimental results obtained on down-sampled version of a large subset of Hoolywood2 benchmark database show the importance of the proposed system in increasing the recognition rate...
Weber, Peter; Lehr, Christian; Gersch, Martin
Virtual collaboration continues to gain in significance and is attracting attention also as virtual collaborative learning (VCL) in education. This paper addresses aspects of VCL that we identified as critical in a series of courses named "Net Economy": (1) technical infrastructure, (2) motivation and collaboration, and (3) assessment…
The primary focus was to assist South African teachers to become reflective practitioners in their daily mathematics classroom teaching. The study involved a combination of quantitative and qualitative research methods. Quantitative data were collected using the Constructivist Learning Environment Survey (CLES) to ...
program aimed at improving leadership, critical thinking , problem solving and decisionmaking skills. Participants in this rigorous, inresidence...problem • Skill Development • Urgent and complex problems requiring unique systems thinking • Groups charged with implementing the solution as...most pressing organi zational issues: problem solving, organizational learning, team building, leadership development, and professional growth and
This account of practice explores the concept of resistance in action learning. Resistance is conceptualized as an attempt of self-protection that is manifested in action learners' struggles with their sense of self-efficacy and their social Self. These struggles are an inherent part of the action learning process and may elicit defensive…
Boak, George; Watt, Peter; Gold, Jeff; Devins, David; Garvey, Robert
This paper contributes to an understanding of the processes by which organisational actors learn how to affect positive and sustainable social change in their local region through action learning, action research and appreciative inquiry. The paper is based on a critically reflective account of key findings from an ongoing action research project,…
Otsuka, Sachio; Saiki, Jun
Prior studies have shown that visual statistical learning (VSL) enhances familiarity (a type of memory) of sequences. How do statistical regularities influence the processing of each triplet element and inserted distractors that disrupt the regularity? Given that increased attention to triplets induced by VSL and inhibition of unattended triplets, we predicted that VSL would promote memory for each triplet constituent, and degrade memory for inserted stimuli. Across the first two experiments, we found that objects from structured sequences were more likely to be remembered than objects from random sequences, and that letters (Experiment 1) or objects (Experiment 2) inserted into structured sequences were less likely to be remembered than those inserted into random sequences. In the subsequent two experiments, we examined an alternative account for our results, whereby the difference in memory for inserted items between structured and random conditions is due to individuation of items within random sequences. Our findings replicated even when control letters (Experiment 3A) or objects (Experiment 3B) were presented before or after, rather than inserted into, random sequences. Our findings suggest that statistical learning enhances memory for each item in a regular set and impairs memory for items that disrupt the regularity. Copyright © 2015 Elsevier B.V. All rights reserved.
Kuppuraj, Sengottuvel; Duta, Mihaela; Thompson, Paul; Bishop, Dorothy
Statistical learning has been proposed as a key mechanism in language learning. Our main goal was to examine whether adults are capable of simultaneously extracting statistical dependencies in a task where stimuli include a range of structures amenable to statistical learning within a single paradigm. We devised an online statistical learning task using real word auditory-picture sequences that vary in two dimensions: (i) predictability and (ii) adjacency of dependent elements. This task was followed by an offline recall task to probe learning of each sequence type. We registered three hypotheses with specific predictions. First, adults would extract regular patterns from continuous stream (effect of grammaticality). Second, within grammatical conditions, they would show differential speeding up for each condition as a factor of statistical complexity of the condition and exposure. Third, our novel approach to measure online statistical learning would be reliable in showing individual differences in statistical learning ability. Further, we explored the relation between statistical learning and a measure of verbal short-term memory (STM). Forty-two participants were tested and retested after an interval of at least 3 days on our novel statistical learning task. We analysed the reaction time data using a novel regression discontinuity approach. Consistent with prediction, participants showed a grammaticality effect, agreeing with the predicted order of difficulty for learning different statistical structures. Furthermore, a learning index from the task showed acceptable test-retest reliability ( r = 0.67). However, STM did not correlate with statistical learning. We discuss the findings noting the benefits of online measures in tracking the learning process.
Viczko, Jeremy; Sergeeva, Valya; Ray, Laura B.; Owen, Adrian M.; Fogel, Stuart M.
Sleep facilitates the consolidation (i.e., enhancement) of simple, explicit (i.e., conscious) motor sequence learning (MSL). MSL can be dissociated into egocentric (i.e., motor) or allocentric (i.e., spatial) frames of reference. The consolidation of the allocentric memory representation is sleep-dependent, whereas the egocentric consolidation…
Christopoulos, George I; King-Casas, Brooks
In social environments, it is crucial that decision-makers take account of the impact of their actions not only for oneself, but also on other social agents. Previous work has identified neural signals in the striatum encoding value-based prediction errors for outcomes to oneself; also, recent work suggests that neural activity in prefrontal cortex may similarly encode value-based prediction errors related to outcomes to others. However, prior work also indicates that social valuations are not isomorphic, with social value orientations of decision-makers ranging on a cooperative to competitive continuum; this variation has not been examined within social learning environments. Here, we combine a computational model of learning with functional neuroimaging to examine how individual differences in orientation impact neural mechanisms underlying 'other-value' learning. Across four experimental conditions, reinforcement learning signals for other-value were identified in medial prefrontal cortex, and were distinct from self-value learning signals identified in striatum. Critically, the magnitude and direction of the other-value learning signal depended strongly on an individual's cooperative or competitive orientation toward others. These data indicate that social decisions are guided by a social orientation-dependent learning system that is computationally similar but anatomically distinct from self-value learning. The sensitivity of the medial prefrontal learning signal to social preferences suggests a mechanism linking such preferences to biases in social actions and highlights the importance of incorporating heterogeneous social predispositions in neurocomputational models of social behavior. Published by Elsevier Inc.
Guisasola, Jenaro; Zuza, Kristina; Ametller, Jaume; Gutierrez-Berraondo, José
In this paper we put forward a proposal for the design and evaluation of teaching and learning sequences in upper secondary school and university. We will connect our proposal with relevant contributions on the design of teaching sequences, ground it on the design-based research methodology, and discuss how teaching and learning sequences designed according to our proposal relate to learning progressions. An iterative methodology for evaluating and redesigning the teaching and learning sequence (TLS) is presented. The proposed assessment strategy focuses on three aspects: (a) evaluation of the activities of the TLS, (b) evaluation of learning achieved by students in relation to the intended objectives, and (c) a document for gathering the difficulties found when implementing the TLS to serve as a guide to teachers. Discussion of this guide with external teachers provides feedback used for the TLS redesign. The context of our implementation and evaluation is an innovative calculus-based physics course for first-year engineering and science degree students at the University of the Basque Country.
Petrick, Ronald; Kraft, Dirk; Mourao, Kira
We describe an approach to integrated robot control, high-level planning, and action effect learning that attempts to overcome the representational difficulties that exist between these diverse areas. Our approach combines ideas from robot vision, knowledgelevel planning, and connectionist machine......-level action specifications, suitable for planning, from a robot’s interactions with the world. We present a detailed overview of our approach and show how it supports the learning of certain aspects of a high-level lepresentation from low-level world state information....... learning, and focuses on the representational needs of these components.We also make use of a simple representational unit called an instantiated state transition fragment (ISTF) and a related structure called an object-action complex (OAC). The goal of this work is a general approach for inducing high...
Keysers, Christian; Gazzola, Valeria
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 neurons in the presence of direct or indirect re-afference (e.g. seeing/hearing one's own actions) predicts the emergence of mirror neurons with predictive properties. In this framework, we analyse how mirror neurons become a dynamic system that performs active inferences about the actions of others and allows joint actions despite sensorimotor delays. We explore how this system performs a projection of the self onto others, with egocentric biases to contribute to mind-reading. Finally, we argue that Hebbian learning predicts mirror-like neurons for sensations and emotions and review evidence for the presence of such vicarious activations outside the motor system.
Gardner, Tom; Aglinskas, Aidas; Cross, Emily S
Watching other people move elicits engagement of a collection of sensorimotor brain regions collectively termed the Action Observation Network (AON). An extensive literature documents more robust AON responses when observing or executing familiar compared to unfamiliar actions, as well as a positive correlation between amplitude of AON response and an observer's familiarity with an observed or executed movement. On the other hand, emerging evidence shows patterns of AON activity counter to these findings, whereby in some circumstances, unfamiliar actions lead to greater AON engagement than familiar actions. In an attempt to reconcile these conflicting findings, some have proposed that the relationship between AON response amplitude and action familiarity is nonlinear in nature. In the present study, we used an elaborate guitar training intervention to probe the relationship between movement familiarity and AON engagement during action execution and action observation tasks. Participants underwent fMRI scanning while executing one set of guitar sequences with a scanner-compatible bass guitar and observing a second set of sequences. Participants then acquired further physical practice or observational experience with half of these stimuli outside the scanner across 3 days. Participants then returned for an identical scanning session, wherein they executed and observed equal numbers of familiar (trained) and unfamiliar (untrained) guitar sequences. Via region of interest analyses, we extracted activity within AON regions engaged during both scanning sessions, and then fit linear, quadratic and cubic regression models to these data. The data best support the cubic regression models, suggesting that the response profile within key sensorimotor brain regions associated with the AON respond to action familiarity in a nonlinear manner. Moreover, by probing the subjective nature of the prediction error signal, we show results consistent with a predictive coding account of
Full Text Available A growing body of evidence suggests that the midbrain dopamine system plays a key role in reinforcement learning and disruption of the midbrain dopamine system in Parkinson's disease (PD may lead to deficits on tasks that require learning from feedback. We examined how changes in dopamine levels (‘ON’ and ‘OFF’ their dopamine medication affect sequence learning from stochastic positive and negative feedback using Bayesian reinforcement learning models. We found deficits in sequence learning in patients with PD when they were ‘ON’ and ‘OFF’ medication relative to healthy controls, but smaller differences between patients ‘OFF’ and ‘ON’. The deficits were mainly due to decreased learning from positive feedback, although across all participant groups learning was more strongly associated with positive than negative feedback in our task. The learning in our task is likely mediated by the relatively depleted dorsal striatum and not the relatively intact ventral striatum. Therefore, the changes we see in our task may be due to a strong loss of phasic dopamine signals in the dorsal striatum in PD.
Seo, Moonsang; Beigi, Mazda; Jahanshahi, Marjan; Averbeck, Bruno B.
A growing body of evidence suggests that the midbrain dopamine system plays a key role in reinforcement learning and disruption of the midbrain dopamine system in Parkinson's disease (PD) may lead to deficits on tasks that require learning from feedback. We examined how changes in dopamine levels (“ON” and “OFF” their dopamine medication) affect sequence learning from stochastic positive and negative feedback using Bayesian reinforcement learning models. We found deficits in sequence learning in patients with PD when they were “ON” and “OFF” medication relative to healthy controls, but smaller differences between patients “OFF” and “ON”. The deficits were mainly due to decreased learning from positive feedback, although across all participant groups learning was more strongly associated with positive than negative feedback in our task. The learning in our task is likely mediated by the relatively depleted dorsal striatum and not the relatively intact ventral striatum. Therefore, the changes we see in our task may be due to a strong loss of phasic dopamine signals in the dorsal striatum in PD. PMID:20740077
Qian, Li; Wu, Song; Pu, Nan; Xu, Shulin; Xiao, Guoqiang
Human action recognition is an important and challenging task in computer vision research, due to the variations in human motion performance, interpersonal differences and recording settings. In this paper, we propose a novel multi-task learning framework with group information (MTL-GI) for accurate and efficient human action recognition. Specifically, we firstly obtain group information through calculating the mutual information according to the latent relationship between Gaussian components and action categories, and clustering similar action categories into the same group by affinity propagation clustering. Additionally, in order to explore the relationships of related tasks, we incorporate group information into multi-task learning. Experimental results evaluated on two popular benchmarks (UCF50 and HMDB51 datasets) demonstrate the superiority of our proposed MTL-GI framework.
Khany, Reza; Amiri, Majid
Theoretical developments in second or foreign language motivation research have led to a better understanding of the convoluted nature of motivation in the process of language acquisition. Among these theories, action control theory has recently shown a good deal of explanatory power in second language learning contexts and in the presence of…
MacIntyre, Peter D.; Blackie, Rebecca A.
The present study examines the relative ability of variables from three motivational frameworks to predict four non-linguistic outcomes of language learning. The study examines Action Control Theory with its measures of (1) hesitation, (2) volatility and (3) rumination. The study also examined Pintrich's expectancy-value model that uses measures…
Full Text Available Strong links between music and motor functions suggest that music could represent an interesting aid for motor learning. The present study aims for the first time to test the potential of music to assist in the learning of sequences of gestures in normal and pathological aging. Participants with mild Alzheimer's disease (AD and healthy older adults (Controls learned sequences of meaningless gestures that were either accompanied by music or a metronome. We also manipulated the learning procedure such that participants had to imitate the gestures to-be-memorized in synchrony with the experimenter or after the experimenter during encoding. Results show different patterns of performance for the two groups. Overall, musical accompaniment had no impact on the Controls' performance, but improved those of AD participants. Conversely, synchronization of gestures during learning helped Controls but seemed to interfere with retention in AD. We discuss these findings regarding their relevance for a better understanding of auditory-motor memory, and we propose recommendations to maximize the mnemonic effect of music for motor sequence learning for dementia care.
Moussard, Aline; Bigand, Emmanuel; Belleville, Sylvie; Peretz, Isabelle
Strong links between music and motor functions suggest that music could represent an interesting aid for motor learning. The present study aims for the first time to test the potential of music to assist in the learning of sequences of gestures in normal and pathological aging. Participants with mild Alzheimer’s disease (AD) and healthy older adults (controls) learned sequences of meaningless gestures that were either accompanied by music or a metronome. We also manipulated the learning procedure such that participants had to imitate the gestures to-be-memorized in synchrony with the experimenter or after the experimenter during encoding. Results show different patterns of performance for the two groups. Overall, musical accompaniment had no impact on the controls’ performance but improved those of AD participants. Conversely, synchronization of gestures during learning helped controls but seemed to interfere with retention in AD. We discuss these findings regarding their relevance for a better understanding of auditory–motor memory, and we propose recommendations to maximize the mnemonic effect of music for motor sequence learning for dementia care. PMID:24860476
Moussard, Aline; Bigand, Emmanuel; Belleville, Sylvie; Peretz, Isabelle
Strong links between music and motor functions suggest that music could represent an interesting aid for motor learning. The present study aims for the first time to test the potential of music to assist in the learning of sequences of gestures in normal and pathological aging. Participants with mild Alzheimer's disease (AD) and healthy older adults (controls) learned sequences of meaningless gestures that were either accompanied by music or a metronome. We also manipulated the learning procedure such that participants had to imitate the gestures to-be-memorized in synchrony with the experimenter or after the experimenter during encoding. Results show different patterns of performance for the two groups. Overall, musical accompaniment had no impact on the controls' performance but improved those of AD participants. Conversely, synchronization of gestures during learning helped controls but seemed to interfere with retention in AD. We discuss these findings regarding their relevance for a better understanding of auditory-motor memory, and we propose recommendations to maximize the mnemonic effect of music for motor sequence learning for dementia care.
Tamosiunaite, Minija; Asfour, Tamim; Wörgötter, Florentin
Reinforcement learning methods can be used in robotics applications especially for specific target-oriented problems, for example the reward-based recalibration of goal directed actions. To this end still relatively large and continuous state-action spaces need to be efficiently handled. The goal of this paper is, thus, to develop a novel, rather simple method which uses reinforcement learning with function approximation in conjunction with different reward-strategies for solving such problems. For the testing of our method, we use a four degree-of-freedom reaching problem in 3D-space simulated by a two-joint robot arm system with two DOF each. Function approximation is based on 4D, overlapping kernels (receptive fields) and the state-action space contains about 10,000 of these. Different types of reward structures are being compared, for example, reward-on- touching-only against reward-on-approach. Furthermore, forbidden joint configurations are punished. A continuous action space is used. In spite of a rather large number of states and the continuous action space these reward/punishment strategies allow the system to find a good solution usually within about 20 trials. The efficiency of our method demonstrated in this test scenario suggests that it might be possible to use it on a real robot for problems where mixed rewards can be defined in situations where other types of learning might be difficult.
Hibbard, Lisa; Sung, Shannon; Wells, Breche´
Flipped learning has come to the forefront in education. It maximizes learning by moving content delivery online, where learning can be self-paced, allowing for class time to focus on student-centered active learning. This five-year cross-sectional study assessed student performance in a college general chemistry for majors sequence taught by a…
Why is design based action research method important in the world of robot technology and learning? The article explores how action research and interaction-driven design can be used in development of educational robot technological tools. The actual case is the development of “Fraction Battle......” which is about learning fractions in primary school. The technology is based on robot technology. An outdoor digital playground is taken into to the classroom and then redesigned. The article argues for interaction design takes precedence to technology or goal driven design for development...... of educational tools....
This report describes work funded under the DARPA Planning and Scheduling Initiative that led to the development of SOCAP (System for Operations Crisis Action Planning). In particular, it describes lessons learned in applying SIPE-2, the underlying AI planning technology within SOCAP, to the domain of military operations deliberate and crisis action planning. SOCAP was demonstrated at the U.S. Central Command and at the Pentagon in early 1992. A more detailed report about the lessons learned is currently being prepared. This report was presented during one of the panel discussions on 'The Relevance of Scheduling to AI Planning Systems.'
Jenkins, Emrys R; Mabbett, Gaynor M; Surridge, Andrea G; Warring, Joanna; Gwynn, Elizabeth D
As nurse lecturers we investigated practice development and action learning approaches aimed at enabling postregistration bachelor's- and master's-level nursing students (Community Health Studies, Nursing in the Home) to advance practice in the context of policy and professional developments. A patchwork text was used to assess summatively what students achieved (practice change/development) and how this was informed critically, via an extended epistemology. First-person inquiry supplemented by cooperative inquiry postcourse completion (including reflective discussions with 16 students and 16 practice mentors) were used to assist coresearcher constructions of meaning. A relational, tripartite approach to learning and assessment (students', teachers', and practice mentors' collective contributions) depends on continuing reflective attention. Action learning enhances interrelation of experience with dialectic thinking. The patchwork text functions to promote creative writing, evaluative thinking, and praxis development. Role modeling by all, being genuine and not just "talking" genuine, is challenging yet crucial if people are to function as mutual resources for learning.
Norqvist, Lars; Leffler, Eva
This article offers insights into the practices of a non-formal education programme for youth provided by the European Union (EU). It takes a qualitative approach and is based on a case study of the European Voluntary Service (EVS). Data were collected during individual and focus group interviews with learners (the EVS volunteers), decision takers and trainers, with the aim of deriving an understanding of learning in non-formal education. The research questions concerned learning, the recognition of learning and perspectives of usefulness. The study also examined the Youthpass documentation tool as a key to understanding the recognition of learning and to determine whether the learning was useful for learners (the volunteers). The findings and analysis offer several interpretations of learning, and the recognition of learning, which take place in non-formal education. The findings also revealed that it is complicated to divide learning into formal and non- formal categories; instead, non-formal education is useful for individual learners when both formal and non-formal educational contexts are integrated. As a consequence, the division of formal and non-formal (and possibly even informal) learning creates a gap which works against the development of flexible and interconnected education with ubiquitous learning and mobility within and across formal and non-formal education. This development is not in the best interests of learners, especially when seeking useful learning and education for youth (what the authors term "youthful" for youth in action).
Taschereau-Dumouchel, Vincent; Hétu, Sébastien; Michon, Pierre-Emmanuel; Vachon-Presseau, Etienne; Massicotte, Elsa; De Beaumont, Louis; Fecteau, Shirley; Poirier, Judes; Mercier, Catherine; Chagnon, Yvon C.; Jackson, Philip L.
Motor representations in the human mirror neuron system are tuned to respond to specific observed actions. This ability is widely believed to be influenced by genetic factors, but no study has reported a genetic variant affecting this system so far. One possibility is that genetic variants might interact with visuomotor associative learning to configure the system to respond to novel observed actions. In this perspective, we conducted a candidate gene study on the Brain-derived neurotrophic factor (BDNF) Val66Met polymorphism, a genetic variant linked to motor learning in regions of the mirror neuron system, and tested the effect of this polymorphism on motor facilitation and visuomotor associative learning. In a single-pulse TMS study carried on 16 Met (Val/Met and Met/Met) and 16 Val/Val participants selected from a large pool of healthy volunteers, Met participants showed significantly less muscle-specific corticospinal sensitivity during action observation, as well as reduced visuomotor associative learning, compared to Val homozygotes. These results are the first evidence of a genetic variant tuning sensitivity to action observation and bring to light the importance of considering the intricate relation between genetics and associative learning in order to further understand the origin and function of the human mirror neuron system. PMID:27703276
Adult Learning, 2012
This article presents the Belem Framework for Action. This framework focuses on harnessing the power and potential of adult learning and education for a viable future. This framework begins with a preamble on adult education and towards lifelong learning.
Keysers, C.; Gazzola, Valeria
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 neurons in the presence of direct or indirect re-afference (e.g. seeing/hearing one's own actions) predicts the emergence of mirror neurons with predictive properties. In this framework, we analyse ...
Windridge, David; Felsberg, Michael; Shaukat, Affan
Perception-action (P-A) learning is an approach to cognitive system building that seeks to reduce the complexity associated with conventional environment-representation/action-planning approaches. Instead, actions are directly mapped onto the perceptual transitions that they bring about, eliminating the need for intermediate representation and significantly reducing training requirements. We here set out a very general learning framework for cognitive systems in which online learning of the P-A mapping may be conducted within a symbolic processing context, so that complex contextual reasoning can influence the P-A mapping. In utilizing a variational calculus approach to define a suitable objective function, the P-A mapping can be treated as an online learning problem via gradient descent using partial derivatives. Our central theoretical result is to demonstrate top-down modulation of low-level perceptual confidences via the Jacobian of the higher levels of a subsumptive P-A hierarchy. Thus, the separation of the Jacobian as a multiplying factor between levels within the objective function naturally enables the integration of abstract symbolic manipulation in the form of fuzzy deductive logic into the P-A mapping learning. We experimentally demonstrate that the resulting framework achieves significantly better accuracy than using P-A learning without top-down modulation. We also demonstrate that it permits novel forms of context-dependent multilevel P-A mapping, applying the mechanism in the context of an intelligent driver assistance system.
such as emergent learning , experiential learning , and sense-making. It then ties these theories and concepts together into an emergency learning ...edition, loc. 3409–3414. 107 David Kolb , Experiential Learning : Experience as the Source of Learning and Development (Englewood Cliffs, NJ: Prentice...shows us that our theory needs developing again. And the process continues. Fundamental in the Kolb model is the role of action in any learning
Maurício, Paulo; Valente, Bianor; Chagas, Isabel
In this work, we present a teaching-learning sequence on colour intended to a pre-service elementary teacher programme informed by History and Philosophy of Science. Working in a socio-constructivist framework, we made an excursion on the history of colour. Our excursion through history of colour, as well as the reported misconception on colour…
Ghirardi, Marco; Marchetti, Fabio; Pettinari, Claudio; Regis, Alberto; Roletto, Ezio
A didactic sequence is proposed for the teaching of chemical equilibrium law. In this approach, we have avoided the kinetic derivation and the thermodynamic justification of the equilibrium constant. The equilibrium constant expression is established empirically by a trial-and-error approach. Additionally, students learn to use the criterion of…
Spyrtou, Anna; Lavonen, Jari; Zoupidis, Anastasios; Loukomies, Anni; Pnevmatikos, Dimitris; Juuti, Kalle; Kariotoglou, Petros
In the present paper, we report on the idea of exchanging educational innovations across European countries aiming to shed light on the following question: how feasible and useful is it to transfer an innovation across different national educational settings? The innovation, in this case, Inquiry-Based Teaching Learning Sequences, is recognized as…
Slone, Lauren Krogh; Johnson, Scott P
Past research suggests that infants have powerful statistical learning abilities; however, studies of infants' visual statistical learning offer differing accounts of the developmental trajectory of and constraints on this learning. To elucidate this issue, the current study tested the hypothesis that young infants' segmentation of visual sequences depends on redundant statistical cues to segmentation. A sample of 20 2-month-olds and 20 5-month-olds observed a continuous sequence of looming shapes in which unit boundaries were defined by both transitional probability and co-occurrence frequency. Following habituation, only 5-month-olds showed evidence of statistically segmenting the sequence, looking longer to a statistically improbable shape pair than to a probable pair. These results reaffirm the power of statistical learning in infants as young as 5 months but also suggest considerable development of statistical segmentation ability between 2 and 5 months of age. Moreover, the results do not support the idea that infants' ability to segment visual sequences based on transitional probabilities and/or co-occurrence frequencies is functional at the onset of visual experience, as has been suggested previously. Rather, this type of statistical segmentation appears to be constrained by the developmental state of the learner. Factors contributing to the development of statistical segmentation ability during early infancy, including memory and attention, are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.
Stavrou, D.; Duit, R.; Komorek, M.
A teaching and learning sequence aimed at introducing upper secondary school students to the interplay between chance and determinism in nonlinear systems is presented. Three experiments concerning nonlinear systems (deterministic chaos, self-organization and fractals) and one experiment concerning linear systems are introduced. Thirty upper…
Chan, John S Y; Wu, Qiaofeng; Liang, Danxia; Yan, Jin H
Finger sequence learning requires visuospatial working memory (WM). However, the dynamics between age, WM training, and motor skill acquisition are unclear. Therefore, we examined how visuospatial WM training improves finger movement sequential accuracy in younger (n=26, 21.1±1.37years) and older adults (n=22, 70.6±4.01years). After performing a finger sequence learning exercise and numerical and spatial WM tasks, participants in each age group were randomly assigned to either the experimental (EX) or control (CO) groups. For one hour daily over a 10-day period, the EX group practiced an adaptive n-back spatial task while those in the CO group practiced a non-adaptive version. As a result of WM practice, the EX participants increased their accuracy in the spatial n-back tasks, while accuracy remained unimproved in the numerical n-back tasks. In all groups, reaction times (RT) became shorter in most numerical and spatial n-back tasks. The learners in the EX group - but not in the CO group - showed improvements in their retention of finger sequences. The findings support our hypothesis that computerized visuospatial WM training improves finger sequence learning both in younger and in older adults. We discuss the theoretical implications and clinical relevance of this research for motor learning and functional rehabilitation. Copyright © 2015 Elsevier B.V. All rights reserved.
Abadi, Shiran; Yan, Winston X; Amar, David; Mayrose, Itay
The adaptation of the CRISPR-Cas9 system as a genome editing technique has generated much excitement in recent years owing to its ability to manipulate targeted genes and genomic regions that are complementary to a programmed single guide RNA (sgRNA). However, the efficacy of a specific sgRNA is not uniquely defined by exact sequence homology to the target site, thus unintended off-targets might additionally be cleaved. Current methods for sgRNA design are mainly concerned with predicting off-targets for a given sgRNA using basic sequence features and employ elementary rules for ranking possible sgRNAs. Here, we introduce CRISTA (CRISPR Target Assessment), a novel algorithm within the machine learning framework that determines the propensity of a genomic site to be cleaved by a given sgRNA. We show that the predictions made with CRISTA are more accurate than other available methodologies. We further demonstrate that the occurrence of bulges is not a rare phenomenon and should be accounted for in the prediction process. Beyond predicting cleavage efficiencies, the learning process provides inferences regarding patterns that underlie the mechanism of action of the CRISPR-Cas9 system. We discover that attributes that describe the spatial structure and rigidity of the entire genomic site as well as those surrounding the PAM region are a major component of the prediction capabilities.
Full Text Available The adaptation of the CRISPR-Cas9 system as a genome editing technique has generated much excitement in recent years owing to its ability to manipulate targeted genes and genomic regions that are complementary to a programmed single guide RNA (sgRNA. However, the efficacy of a specific sgRNA is not uniquely defined by exact sequence homology to the target site, thus unintended off-targets might additionally be cleaved. Current methods for sgRNA design are mainly concerned with predicting off-targets for a given sgRNA using basic sequence features and employ elementary rules for ranking possible sgRNAs. Here, we introduce CRISTA (CRISPR Target Assessment, a novel algorithm within the machine learning framework that determines the propensity of a genomic site to be cleaved by a given sgRNA. We show that the predictions made with CRISTA are more accurate than other available methodologies. We further demonstrate that the occurrence of bulges is not a rare phenomenon and should be accounted for in the prediction process. Beyond predicting cleavage efficiencies, the learning process provides inferences regarding patterns that underlie the mechanism of action of the CRISPR-Cas9 system. We discover that attributes that describe the spatial structure and rigidity of the entire genomic site as well as those surrounding the PAM region are a major component of the prediction capabilities.
Eva Edman Stålbrandt
Full Text Available The aims of this paper are to develop knowledge about scaffolding when students in Swedish schools use digital educational material and to investigate what the main focus is in teachers' interventions during a Learning Design Sequence (LDS, based on a socio-cultural perspective. The results indicate that scaffolding were most common in the primary transformation unit and the most frequent type was procedural scaffolding, although all types of scaffolds; conceptual, metacognitive, procedural, strategic, affective and technical scaffolding occurred in all parts of a learning design sequence. In this study most of the teachers and students, think that using digital educational material requires more and other forms of scaffolding and concerning teacher interventions teachers interact both supportively and restrictively according to students' learning process. Reasons for that are connected to the content of the intervention and whether teachers intervene together with the students or not.
Brook, Cheryl; Christy, Gill
The question addressed in this paper is whether action learning as a management development technique can be more effective in promoting ethical decision-making than more traditional approaches. Recent examples of moral failures which have emerged in both corporate and public sector organisations in the UK during recent years have prompted a…
Conklin, James; Cohen-Schneider, Rochelle; Linkewich, Beth; Legault, Emma
This paper reports on a study of how action learning facilitates the movement of knowledge between social contexts. The study involved a community organization that provides educational services related to aphasia and members of a complex continuing care (CCC) practice that received training from the agency. People with aphasia (PWA) (a disability…
Muskett, Judith A.; Village, Andrew
Rural clergy often lack colleagues and may struggle with isolation, especially if over-extended in multi-parish benefices. Theory suggests that this sense of isolation could be addressed by launching clergy action learning sets, which have the potential to establish a peer support network through the formation of social capital as a by-product of…
This Account of Practice describes the introduction and development of action learning within a level 5 module of "Communications at Work" delivered as part of a Business & Technology Education Council (BTEC) Professional Certificate in Management (CMS) between 2005/2006 and 2009/2010. This will commence with a personal narrative and…
Cross, E.S.; Kraemer, D.J.M.; Hamilton, A.F.D.C.; Kelley, W.M.; Grafton, S.T.
Human motor skills can be acquired by observation without the benefit of immediate physical practice. The current study tested if physical rehearsal and observational learning share common neural substrates within an action observation network (AON) including premotor and inferior parietal regions,
Donovan, Paul Jeffrey
"Undiscussables" are topics associated with threat or embarrassment that are avoided by groups, where that avoidance is also not discussed. Their deleterious effect on executive groups has been a point of discussion for several decades. More recently critical action learning (AL) has brought a welcome focus to power relations within AL…
Simões, L.F.; Schut, M.C.; Haasdijk, E.W.
An important design goal in Learning Classifier Systems (LCS) is to equally reinforce those classifiers which cause the level of reward supplied by the environment. In this paper, we propose a new method for action set formation in LCS. When applied to a Zeroth Level Classifier System with Memory
Elbert, Norb; Cumiskey, Kevin J.
This paper describes an action learning simulation designed for a Professional Golf Management (PGM) program housed in a College of Business of a public university. The PGA Golf Management University Program, a 4.5- to 5-year college curriculum for aspiring PGA Professionals is offered at 19 PGA accredited universities nationwide. The program…
Erlhagen, W.; Mukovskiy, A.; Bicho, E.; Panin, G.; Kiss, C.; Knoll, A.; Schie, H.T. van; Bekkering, H.
We report results of an interdisciplinary project which aims at endowing a real robot system with the capacity for learning by goal-directed imitation. The control architecture is biologically inspired as it reflects recent experimental findings in action observation/execution studies. We test its
Anderson, Lisa; Gold, Jeff
In this paper we consider the construction of narrative identity and particularly how managers of small businesses may construct new narrative identities within the activity of the action learning situation. We build on recent work to suggest that the "world" of managers can be explored through a consideration of Vygotsky's socio-cultural theory…
Scott-Ladd, Brenda; Chan, Christopher C. A.
This article reports on a study investigating strategies that students can use to develop skills in managing team learning. Two groups of second-year management students participated in a semester-long action research project over two semesters. The students were educated on team development, team processes and conflict management and how to…
Kamath, Shyam; Agrawal, Jagdish; Krickx, Guido
This paper discusses the theoretical foundations and implementation challenges and outcomes of a unique "hands-on" global consulting program that is integrated into an international EMBA program for mid-career and senior American and European managers. It details the challenges for the integration of experiential action learning, double-loop…
Purpose This is an attempt to write an account of action learning that is as close to the ground on which it was practised as the author can make it. In that sense, the reader can read what follows below as a kind of autoethnography, a "representation as relationship" as Gergen and Gergen (2002, p. 11) call it. This is because in the opportunity of telling a story about his practice as an action learning facilitator, the author hopes to evoke that which is more akin to the contactful environment of quality action learning than any amount of abstract theorising. Design/methodology/approach This is an example of "narrative inquiry", best judged, according to Sparkes (2002), in terms of the ability of such accounts to "contribute to sociological understanding in ways that, amongst others are self-knowing, self-respecting, self-sacrificing and self-luminous". Findings As the author re-tells this partial account, he has a sense of the massive wider structures around him, but all he can see in his dim lamp is the fleeting glimpse of the local strata. The author traces his hand along the seams, not intending to dig them out, but simply to witness them, or even, in a spirit of yearning, to give them a witnessing of themselves. Originality/value To the author, this is about portraying what action learning feels like, rather than thinks like, for his own and for the benefit of other practitioners.
Burns, Heather L.
This study used action research methodology to examine the development of sustainability leadership in a graduate leadership course. The research investigated the impact of this leadership course, which was designed using transformative learning theory with attention to integrating thematic content, multiple and nondominant perspectives, a…
Khalid, Md. Saifuddin; Nyvang, Tom
This chapter examines barriers and methods to identify barriers to educational technology in a rural technical vocational education and training institute in Bangladesh. It also examines how the application of participatory learning and action methods can provide information for barrier research ...
Heimbauer, Lisa A; Conway, Christopher M; Christiansen, Morten H; Beran, Michael J; Owren, Michael J
Humans and nonhuman primates can learn about the organization of stimuli in the environment using implicit sequential pattern learning capabilities. However, most previous artificial grammar learning studies with nonhuman primates have involved relatively simple grammars and short input sequences. The goal in the current experiments was to assess the learning capabilities of monkeys on an artificial grammar-learning task that was more complex than most others previously used with nonhumans. Three experiments were conducted using a joystick-based, symmetrical-response serial reaction time task in which two monkeys were exposed to grammar-generated sequences at sequence lengths of four in Experiment 1, six in Experiment 2, and eight in Experiment 3. Over time, the monkeys came to respond faster to the sequences generated from the artificial grammar compared to random versions. In a subsequent generalization phase, subjects generalized their knowledge to novel sequences, responding significantly faster to novel instances of sequences produced using the familiar grammar compared to those constructed using an unfamiliar grammar. These results reveal that rhesus monkeys can learn and generalize the statistical structure inherent in an artificial grammar that is as complex as some used with humans, for sequences up to eight items long. These findings are discussed in relation to whether or not rhesus macaques and other primate species possess implicit sequence learning abilities that are similar to those that humans draw upon to learn natural language grammar.
Vogt, Stefan; Buccino, Giovanni; Wohlschläger, Afra M; Canessa, Nicola; Shah, N Jon; Zilles, Karl; Eickhoff, Simon B; Freund, Hans-Joachim; Rizzolatti, Giacomo; Fink, Gereon R
In this event-related fMRI study, we demonstrate the effects of a single session of practising configural hand actions (guitar chords) on cortical activations during observation, motor preparation and imitative execution. During the observation of non-practised actions, the mirror neuron system (MNS), consisting of inferior parietal and ventral premotor areas, was more strongly activated than for the practised actions. This finding indicates a strong role of the MNS in the early stages of imitation learning. In addition, the left dorsolateral prefrontal cortex (DLPFC) was selectively involved during observation and motor preparation of the non-practised chords. This finding confirms Buccino et al.'s [Buccino, G., Vogt, S., Ritzl, A., Fink, G.R., Zilles, K., Freund, H.-J., Rizzolatti, G., 2004a. Neural circuits underlying imitation learning of hand actions: an event-related fMRI study. Neuron 42, 323-334] model of imitation learning: for actions that are not yet part of the observer's motor repertoire, DLPFC engages in operations of selection and combination of existing, elementary representations in the MNS. The pattern of prefrontal activations further supports Shallice's [Shallice, T., 2004. The fractionation of supervisory control. In: Gazzaniga, M.S. (Ed.), The Cognitive Neurosciences, Third edition. MIT Press, Cambridge, MA, pp. 943-956] proposal of a dominant role of the left DLPFC in modulating lower level systems and of a dominant role of the right DLPFC in monitoring operations.
Hall, Matthew L; Eigsti, Inge-Marie; Bortfeld, Heather; Lillo-Martin, Diane
Developmental psychology plays a central role in shaping evidence-based best practices for prelingually deaf children. The Auditory Scaffolding Hypothesis (Conway et al., 2009) asserts that a lack of auditory stimulation in deaf children leads to impoverished implicit sequence learning abilities, measured via an artificial grammar learning (AGL) task. However, prior research is confounded by a lack of both auditory and language input. The current study examines implicit learning in deaf children who were (Deaf native signers) or were not (oral cochlear implant users) exposed to language from birth, and in hearing children, using both AGL and Serial Reaction Time (SRT) tasks. Neither deaf nor hearing children across the three groups show evidence of implicit learning on the AGL task, but all three groups show robust implicit learning on the SRT task. These findings argue against the Auditory Scaffolding Hypothesis, and suggest that implicit sequence learning may be resilient to both auditory and language deprivation, within the tested limits. A video abstract of this article can be viewed at: https://youtu.be/EeqfQqlVHLI [Correction added on 07 August 2017, after first online publication: The video abstract link was added.]. © 2017 John Wiley & Sons Ltd.
Uehara, Shintaro; Mawase, Firas; Celnik, Pablo
Humans can acquire knowledge of new motor behavior via different forms of learning. The two forms most commonly studied have been the development of internal models based on sensory-prediction errors (error-based learning) and success-based feedback (reinforcement learning). Human behavioral studies suggest these are distinct learning processes, though the neurophysiological mechanisms that are involved have not been characterized. Here, we evaluated physiological markers from the cerebellum and the primary motor cortex (M1) using noninvasive brain stimulations while healthy participants trained finger-reaching tasks. We manipulated the extent to which subjects rely on error-based or reinforcement by providing either vector or binary feedback about task performance. Our results demonstrated a double dissociation where learning the task mainly via error-based mechanisms leads to cerebellar plasticity modifications but not long-term potentiation (LTP)-like plasticity changes in M1; while learning a similar action via reinforcement mechanisms elicited M1 LTP-like plasticity but not cerebellar plasticity changes. Our findings indicate that learning complex motor behavior is mediated by the interplay of different forms of learning, weighing distinct neural mechanisms in M1 and the cerebellum. Our study provides insights for designing effective interventions to enhance human motor learning. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: email@example.com.
Teng, Haotian; Cao, Minh Duc; Hall, Michael B; Duarte, Tania; Wang, Sheng; Coin, Lachlan J M
Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology that offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex electrical signal is challenging. Here, we report Chiron, the first deep learning model to achieve end-to-end basecalling and directly translate the raw signal to DNA sequence without the error-prone segmentation step. Trained with only a small set of 4,000 reads, we show that our model provides state-of-the-art basecalling accuracy, even on previously unseen species. Chiron achieves basecalling speeds of more than 2,000 bases per second using desktop computer graphics processing units.
Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology that offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex electrical signal is challenging. Here, we report Chiron, the first deep learning model to achieve end-to-end basecalling and directly translate the raw signal to DNA sequence without the error-prone segmentation step. Trained with only a small set of 4,000 reads, we show that our model provides state-of-the-art basecalling accuracy, even on previously unseen species. Chiron achieves basecalling speeds of more than 2,000 bases per second using desktop computer graphics processing units.
Eleftheriadis, Stefanos; Rudovic, Ognjen; Pantic, Maja
Automated analysis of facial expressions can benefit many domains, from marketing to clinical diagnosis of neurodevelopmental disorders. Facial expressions are typically encoded as a combination of facial muscle activations, i.e., action units. Depending on context, these action units co-occur in specific patterns, and rarely in isolation. Yet, most existing methods for automatic action unit detection fail to exploit dependencies among them, and the corresponding facial features. To address this, we propose a novel multi-conditional latent variable model for simultaneous fusion of facial features and joint action unit detection. Specifically, the proposed model performs feature fusion in a generative fashion via a low-dimensional shared subspace, while simultaneously performing action unit detection using a discriminative classification approach. We show that by combining the merits of both approaches, the proposed methodology outperforms existing purely discriminative/generative methods for the target task. To reduce the number of parameters, and avoid overfitting, a novel Bayesian learning approach based on Monte Carlo sampling is proposed, to integrate out the shared subspace. We validate the proposed method on posed and spontaneous data from three publicly available datasets (CK+, DISFA and Shoulder-pain), and show that both feature fusion and joint learning of action units leads to improved performance compared to the state-of-the-art methods for the task.
Limongelli, Carla; Sciarrone, Filippo; Temperini, Marco; Vaste, Giulia
LS-Lab provides automatic support to comparison/evaluation of the Learning Object Sequences produced by different Curriculum Sequencing Algorithms. Through this framework a teacher can verify the correspondence between the behaviour of different sequencing algorithms and her pedagogical preferences. In fact the teacher can compare algorithms…
Full Text Available The human visual system can acquire the statistical structures in temporal sequences of object feature changes, such as changes in shape, color, and its combination. Here we investigate whether the statistical learning for spatial position and shape changes operates separately or not. It is known that the visual system processes these two types of information separately; the spatial information is processed in the parietal cortex, whereas object shapes and colors are detected in the temporal pathway, and, after that, we perceive bound information in the two streams. We examined whether the statistical learning operates before or after binding the shape and the spatial information by using the “re-paired triplet” paradigm proposed by Turk-Browne, Isola, Scholl, and Treat (2008. The result showed that observers acquired combined sequences of shape and position changes, but no statistical information in individual sequence was obtained. This finding suggests that the visual statistical learning works after binding the temporal sequences of shapes and spatial structures and would operate in the higher-order visual system; this is consistent with recent ERP (Abla & Okanoya, 2009 and fMRI (Turk-Browne, Scholl, Chun, & Johnson, 2009 studies.
Carlos Alexandre dos Santos Batista
Full Text Available After more than two decades of justifications on the insertion of Modern and Contemporary Physics in the high school Education, the current challenge regards to how this content can be inserted in the classroom in an interesting and innovative way. Recent research reveals that despite a significant accumulation of recent academic research, whose purpose is to assist teachers pedagogically, few are grounded and proposed theoretically seeking to investigate how this integration happens. In this sense, we present a teaching-learning sequence on the topic of radioactivity, forged in the theoretical and methodological assumptions of Design-Based Research and a Teaching-Learning Sequence that, when implemented in public schools in the south of Bahia, produced the relevant knowledge to be shared with the community on teaching physics. Forged in our assumptions, the proposal allows teachers and researchers to understand questions about how, when and why, in fact, the inclusion of Modern and Contemporary Physics can occur in a non-traditional way. Therefore, the importance of this proposal is revealed to the high school of physics as it translates its ability to transform the theoretical demands on the curriculum and methodological innovation in the practical interventions in the classroom. We add that the availability of the necessary sources to find lesson plans, quizzes, texts, videos of teaching-learning sequence, shows the contribution of this work for teachers and researchers, in particular, to improve the scientific learning of students in the Basic Education.
Full Text Available This article focuses on the biographical dimension of the processes of developing political awareness and the significance for consistency in political action. It is based on a single case study which was developed within an oral history project in the 1980s. A new reconstruction of a worker's narrative about his refusal to serve in the army and subsequent flight during the National-Socialist period shows how personal desires for change and institutionalized political patterns of interpretation and action are intertwined. The protagonist could cope with times of extremely restricted latitude for action, as was the case in the Nazi era, acquiring personal learning or crisis management skills as long as there was hope for future emancipation and social integration. In the postwar period the dissipation of this perspective lead to a reduction in his individual ability to take political action. URN: http://nbn-resolving.de/urn:nbn:de:0114-fqs1102118
Full Text Available This paper describes an action research study during which a flexible or hybrid approach to delivering an Information and Communication Technology competency course is implemented in the preparation of student teachers. The course incorporates Web-based course-content delivery, face-to-face classroom meetings to satisfy the need for human interaction, a variety of assessment methods, as well as recognition of prior learning. The objectives are to accommodate learning diversity, make learning focused and achievable for each learner, allow for intervention if the learning outcomes are not met, and focus on and guide the learning process, i.e. teach learners how to learn. This paper reports on the perspectives and experiences of two groups of first year learners, namely student teachers who attended a hybrid ICT course and first year learners who attended an e-learning ICT course. It was found that the success rate of the hybrid mode ICT course was significantly higher than that of the similar e-learning ICT course. The hybrid mode ICT course also enabled the learners to become self-directed to a higher degree.
Casado, Pilar; Martín-Loeches, Manuel; León, Inmaculada; Hernández-Gutiérrez, David; Espuny, Javier; Muñoz, Francisco; Jiménez-Ortega, Laura; Fondevila, Sabela; de Vega, Manuel
This study aims to extend the embodied cognition approach to syntactic processing. The hypothesis is that the brain resources to plan and perform motor sequences are also involved in syntactic processing. To test this hypothesis, Event-Related brain Potentials (ERPs) were recorded while participants read sentences with embedded relative clauses, judging for their acceptability (half of the sentences contained a subject-verb morphosyntactic disagreement). The sentences, previously divided into three segments, were self-administered segment-by-segment in two different sequential manners: linear or non-linear. Linear self-administration consisted of successively pressing three buttons with three consecutive fingers in the right hand, while non-linear self-administration implied the substitution of the finger in the middle position by the right foot. Our aim was to test whether syntactic processing could be affected by the manner the sentences were self-administered. Main results revealed that the ERPs LAN component vanished whereas the P600 component increased in response to incorrect verbs, for non-linear relative to linear self-administration. The LAN and P600 components reflect early and late syntactic processing, respectively. Our results convey evidence that language syntactic processing and performing non-linguistic motor sequences may share resources in the human brain. Copyright © 2017 Elsevier Ltd. All rights reserved.
Zhang, Wen; Zhu, Xiaopeng; Fu, Yu; Tsuji, Junko; Weng, Zhiping
Alternative splicing is the critical process in a single gene coding, which removes introns and joins exons, and splicing branchpoints are indicators for the alternative splicing. Wet experiments have identified a great number of human splicing branchpoints, but many branchpoints are still unknown. In order to guide wet experiments, we develop computational methods to predict human splicing branchpoints. Considering the fact that an intron may have multiple branchpoints, we transform the branchpoint prediction as the multi-label learning problem, and attempt to predict branchpoint sites from intron sequences. First, we investigate a variety of intron sequence-derived features, such as sparse profile, dinucleotide profile, position weight matrix profile, Markov motif profile and polypyrimidine tract profile. Second, we consider several multi-label learning methods: partial least squares regression, canonical correlation analysis and regularized canonical correlation analysis, and use them as the basic classification engines. Third, we propose two ensemble learning schemes which integrate different features and different classifiers to build ensemble learning systems for the branchpoint prediction. One is the genetic algorithm-based weighted average ensemble method; the other is the logistic regression-based ensemble method. In the computational experiments, two ensemble learning methods outperform benchmark branchpoint prediction methods, and can produce high-accuracy results on the benchmark dataset.
Full Text Available This paper examines how to leverage the design studio learning environment throughout long-term Digital Design education in order to support students to progress from tactical, well-defined, device-centric routine design, to confidently design sustainable solutions for strategic, complex, problems for a wide range of devices and platforms in the digital space. We present a framework derived from literature on design, creativity, and theories on learning that: (a implements a theory of formal learning sequences as a user-centered design process in the studio; and (b describes design challenge progressions in the design studio environment modeled in seven dimensions. The framework can be used as a tool for designing, evaluating, and communicating course progressions within – and between series of – design studio courses. This approach is evaluated by implementing a formal learning sequence framework in a series of design studio courses that progress in an undergraduate design-oriented Informatics program. Reflections from students, teachers, and external clients indicate high student motivation and learning goal achievement, high teacher satisfaction and skill development, and high satisfaction among external clients.
Panda, Priyadarshini; Srinivasa, Narayan
A fundamental challenge in machine learning today is to build a model that can learn from few examples. Here, we describe a reservoir based spiking neural model for learning to recognize actions with a limited number of labeled videos. First, we propose a novel encoding, inspired by how microsaccades influence visual perception, to extract spike information from raw video data while preserving the temporal correlation across different frames. Using this encoding, we show that the reservoir generalizes its rich dynamical activity toward signature action/movements enabling it to learn from few training examples. We evaluate our approach on the UCF-101 dataset. Our experiments demonstrate that our proposed reservoir achieves 81.3/87% Top-1/Top-5 accuracy, respectively, on the 101-class data while requiring just 8 video examples per class for training. Our results establish a new benchmark for action recognition from limited video examples for spiking neural models while yielding competitive accuracy with respect to state-of-the-art non-spiking neural models. PMID:29551962
This dissertation study investigates what happens when students participate in an afterschool science club designed around action-oriented science instruction, a set of curriculum design principles based on social justice pedagogy. Comprised of three manuscripts written for journal publication, the dissertation includes 1) Negotiating community-based action-oriented science teaching and learning: Articulating curriculum design principles, 2) Middle school girls' socio-scientific participation pathways in an afterschool science club, and 3) Laughing and learning together: Productive science learning spaces for middle school girls. By investigating how action-oriented science design principles get negotiated, female identity development in and with science, and the role of everyday social interactions as students do productive science, this research fills gaps in the understanding of how social justice pedagogy gets enacted and negotiated among multiple stakeholders including students, teachers, and community members along what identity development looks like across social and scientific activity. This study will be of interest to educators thinking about how to enact social justice pedagogy in science learning spaces and those interested in identity development in science.
Vinera, Jennifer; Kermen, Florence; Sacquet, Joëlle; Didier, Anne; Mandairon, Nathalie; Richard, Marion
Noradrenaline contributes to olfactory-guided behaviors but its role in olfactory learning during adulthood is poorly documented. We investigated its implication in olfactory associative and perceptual learning using local infusion of mixed a1-ß adrenergic receptor antagonist (labetalol) in the adult mouse olfactory bulb. We reported that…
Biddle, Elyce Anne; Keane, Paul R.
Action Learning is a problem-solving process that is used in various industries to address difficult problems. This project applied Action Learning to a leading problem in agricultural safety. Tractor overturns are the leading cause of fatal injury to farmworkers. This cause of injury is preventable using rollover protective structures (ROPS), protective equipment that functions as a roll bar structure to protect the operator in the event of an overturn. For agricultural tractors manufactured after 1976 and employee operated, Occupational Safety and Health Administration (OSHA) regulation requires employers to equip them with ROPS and seat belts. By the mid-1980s, US tractor manufacturers began adding ROPS on all farm tractors over 20 horsepower sold in the United States (http://www.nasdonline.org/document/113/d001656/rollover-protection-for-farm-tractor-operators.html). However, many older tractors remain in use without ROPS, putting tractor operators at continued risk for traumatic injury and fatality. For many older tractor models ROPS are available for retrofit, but for a variety of reasons, tractor owners have not chosen to retrofit those ROPS. The National Institute for Occupational Safety and Health (NIOSH) attempted various means to ameliorate this occupational safety risk, including the manufacture of a low-cost ROPS for self-assembly. Other approaches address barriers to adoption. An Action Learning approach to increasing adoption of ROPS was followed in Virginia and New York, with mixed results. Virginia took action to increase the manufacturing and adoption of ROPS, but New York saw problems that would be insurmountable. Increased focus on team composition might be needed to establish effective Action Learning teams to address this problem. PMID:22994641
Full Text Available Many generalization results in learning theory are established under the assumption that samples are independent and identically distributed (i.i.d.. However, numerous learning tasks in practical applications involve the time-dependent data. In this paper, we propose a theoretical framework to analyze the generalization performance of the empirical risk minimization (ERM principle for sequences of time-dependent samples (TDS. In particular, we first present the generalization bound of ERM principle for TDS. By introducing some auxiliary quantities, we also give a further analysis of the generalization properties and the asymptotical behaviors of ERM principle for TDS.
Carlo Ponzo, Felice; Ditommaso, Rocco; Nigro, Antonella; Nigro, Domenico S.; Iacovino, Chiara
After the Mw 6.0 mainshock of August 24, 2016 at 03.36 a.m. (local time), with the epicenter located between the towns of Accumoli (province of Rieti), Amatrice (province of Rieti) and Arquata del Tronto (province of Ascoli Piceno), several activities were started in order to perform some preliminary evaluations on the characteristics of the recent seismic sequence in the areas affected by the earthquake. Ambient vibration acquisitions have been performed using two three-directional velocimetric synchronized stations, with a natural frequency equal to 0.5Hz and a digitizer resolution of equal to 24bit. The activities are continuing after the events of the seismic sequence of October 26 and October 30, 2016. In this paper, in order to compare recorded and code provision values in terms of peak (PGA, PGV and PGD), spectral and integral (Housner Intensity) seismic parameters, several preliminary analyses have been performed on accelerometric time-histories acquired by three near fault station of the RAN (Italian Accelerometric Network): Amatrice station (station code AMT), Norcia station (station code NRC) and Castelsantangelo sul Nera station (station code CNE). Several comparisons between the elastic response spectra derived from accelerometric recordings and the elastic demand spectra provided by the Italian seismic code (NTC 2008) have been performed. Preliminary results retrieved from these analyses highlight several apparent difference between experimental data and conventional code provision. Then, the ongoing seismic sequence appears compatible with the historical seismicity in terms of integral parameters, but not in terms of peak and spectral values. It seems appropriate to reconsider the necessity to revise the simplified design approach based on the conventional spectral values. Acknowledgements This study was partially funded by the Italian Department of Civil Protection within the project DPC-RELUIS 2016 - RS4 ''Seismic observatory of structures and
Jesús de la Fuente
Full Text Available Action-Emotion Style (AES is an affective-motivational construct that describes the achievement motivation that is characteristic of students in their interaction with stressful situations. Using elements from the Type-A Behavior Pattern (TABP, characteristics of competitiveness and overwork occur in different combinations with emotions of impatience and hostility, leading to a classification containing five categories of action-emotion style (Type B, Impatient-hostile type, Medium type, Competitive-Overworking type and Type A. The objective of the present research is to establish how characteristics of action-emotion style relate to learning approach (deep and surface approaches and to coping strategies (emotion-focused and problem-focused. The sample was composed of 225 students from the Psychology degree program. Pearson correlation analyses, ANOVAs and MANOVAs were used. Results showed that competitiveness-overwork characteristics have a significant positive association with the deep approach and with problem-focused strategies, while impatience-hostility is thus related to surface approach and emotion-focused strategies. The level of action-emotion style had a significant main effect. The results verified our hypotheses with reference to the relationships between action-emotion style, learning approaches and coping strategies.
This qualitative case study explored a third grade bilingual teacher's transformative language ideologies through participating in a collaborative action research project. By merging language ideologies theory, Cultural Historical Activity Theory (CHAT), and action research, I was able to identify the analytic focus of this study. I analyzed how one teacher and I, the researcher, collaboratively reflected on classroom language practices during the video analysis meetings and focus groups. Further, I analyzed twelve videos that we coded together to see the changes in the teacher's language practices over time. My unit of analysis was the discourse practice mediated by additive language ideologies. Throughout the collaborative action research process, we both critically reflected on the classroom language use. We also developed a critical consciousness about the participatory shifts and learning of focal English Learner (EL) students. Finally, the teacher made changes to her classroom language practices. The results of this study will contribute to the literacy education research field for theoretical, methodological, and practical insights. The integration of language ideologies, CHAT, and action research can help educational practitioners, researchers, and policy makers understand the importance of transforming teachers' language ideologies in designing additive learning contexts for ELs. From a methodological perspective, the transformative language ideologies through researcher and teacher collaborated video analysis process provide a unique contribution to the language ideologies in education literature, with analytic triangulation. As a practical implication, this study suggests action research can be one of the teacher education tools to help the teachers transform language ideologies for EL education.
Maddison, Charlotte; Strang, Gus
The aim of this study was to investigate if by participating in action learning sets, Graduate Entry Pre-registration Nursing (GEN) students were able to engage in collaborative and deliberative learning. A single focus group interview involving eleven participants was used to collect data. Data analysis identified five themes; collaborative learning; reflection; learning through case study and problem-solving; communication, and rejection of codified learning. The themes are discussed and further analysed in the context of collaborative and deliberative learning. The evidence from this small scale study suggests that action learning sets do provide an environment where collaborative and deliberative learning can occur. However, students perceived some of them, particularly during year one, to be too 'teacher lead', which stifled learning. Copyright © 2017 Elsevier Ltd. All rights reserved.
Ma, Eddie Y T; Ratnasingham, Sujeevan; Kremer, Stefan C
This study presents a machine learning method that increases the number of identified bases in Sanger Sequencing. The system post-processes a KB basecalled chromatogram. It selects a recoverable subset of N-labels in the KB-called chromatogram to replace with basecalls (A,C,G,T). An N-label correction is defined given an additional read of the same sequence, and a human finished sequence. Corrections are added to the dataset when an alignment determines the additional read and human agree on the identity of the N-label. KB must also rate the replacement with quality value of in the additional read. Corrections are only available during system training. Developing the system, nearly 850,000 N-labels are obtained from Barcode of Life Datasystems, the premier database of genetic markers called DNA Barcodes. Increasing the number of correct bases improves reference sequence reliability, increases sequence identification accuracy, and assures analysis correctness. Keeping with barcoding standards, our system maintains an error rate of percent. Our system only applies corrections when it estimates low rate of error. Tested on this data, our automation selects and recovers: 79 percent of N-labels from COI (animal barcode); 80 percent from matK and rbcL (plant barcodes); and 58 percent from non-protein-coding sequences (across eukaryotes).
Rosenthal, Clive R; Andrews, Samantha K; Antoniades, Chrystalina A; Kennard, Christopher; Soto, David
Human primary visual cortex (V1) has long been associated with learning simple low-level visual discriminations  and is classically considered outside of neural systems that support high-level cognitive behavior in contexts that differ from the original conditions of learning, such as recognition memory [2, 3]. Here, we used a novel fMRI-based dichoptic masking protocol-designed to induce activity in V1, without modulation from visual awareness-to test whether human V1 is implicated in human observers rapidly learning and then later (15-20 min) recognizing a non-conscious and complex (second-order) visuospatial sequence. Learning was associated with a change in V1 activity, as part of a temporo-occipital and basal ganglia network, which is at variance with the cortico-cerebellar network identified in prior studies of "implicit" sequence learning that involved motor responses and visible stimuli (e.g., ). Recognition memory was associated with V1 activity, as part of a temporo-occipital network involving the hippocampus, under conditions that were not imputable to mechanisms associated with conscious retrieval. Notably, the V1 responses during learning and recognition separately predicted non-conscious recognition memory, and functional coupling between V1 and the hippocampus was enhanced for old retrieval cues. The results provide a basis for novel hypotheses about the signals that can drive recognition memory, because these data (1) identify human V1 with a memory network that can code complex associative serial visuospatial information and support later non-conscious recognition memory-guided behavior (cf. ) and (2) align with mouse models of experience-dependent V1 plasticity in learning and memory . Copyright © 2016 Elsevier Ltd. All rights reserved.
Huang, Furong; Anandkumar, Animashree
Unsupervised text embeddings extraction is crucial for text understanding in machine learning. Word2Vec and its variants have received substantial success in mapping words with similar syntactic or semantic meaning to vectors close to each other. However, extracting context-aware word-sequence embedding remains a challenging task. Training over large corpus is difficult as labels are difficult to get. More importantly, it is challenging for pre-trained models to obtain word-...
Muhei-aldin, Othman; VanSwearingen, Jessie; Karim, Helmet; Huppert, Theodore; Sparto, Patrick J; Erickson, Kirk I; Sejdić, Ervin
Understanding complex brain networks using functional magnetic resonance imaging (fMRI) is of great interest to clinical and scientific communities. To utilize advanced analysis methods such as graph theory for these investigations, the stationarity of fMRI time series needs to be understood as it has important implications on the choice of appropriate approaches for the analysis of complex brain networks. In this paper, we investigated the stationarity of fMRI time series acquired from twelve healthy participants while they performed a motor (foot tapping sequence) learning task. Since prior studies have documented that learning is associated with systematic changes in brain activation, a sequence learning task is an optimal paradigm to assess the degree of non-stationarity in fMRI time-series in clinically relevant brain areas. We predicted that brain regions involved in a "learning network" would demonstrate non-stationarity and may violate assumptions associated with some advanced analysis approaches. Six blocks of learning, and six control blocks of a foot tapping sequence were performed in a fixed order. The reverse arrangement test was utilized to investigate the time series stationarity. Our analysis showed some non-stationary signals with a time varying first moment as a major source of non-stationarity. We also demonstrated a decreased number of non-stationarities in the third block as a result of priming and repetition. Most of the current literature does not examine stationarity prior to processing. The implication of our findings is that future investigations analyzing complex brain networks should utilize approaches robust to non-stationarities, as graph-theoretical approaches can be sensitive to non-stationarities present in data. Copyright © 2014 Elsevier B.V. All rights reserved.
Lee, Ernest Y; Fulan, Benjamin M; Wong, Gerard C L; Ferguson, Andrew L
There are some ∼1,100 known antimicrobial peptides (AMPs), which permeabilize microbial membranes but have diverse sequences. Here, we develop a support vector machine (SVM)-based classifier to investigate ⍺-helical AMPs and the interrelated nature of their functional commonality and sequence homology. SVM is used to search the undiscovered peptide sequence space and identify Pareto-optimal candidates that simultaneously maximize the distance σ from the SVM hyperplane (thus maximize its "antimicrobialness") and its ⍺-helicity, but minimize mutational distance to known AMPs. By calibrating SVM machine learning results with killing assays and small-angle X-ray scattering (SAXS), we find that the SVM metric σ correlates not with a peptide's minimum inhibitory concentration (MIC), but rather its ability to generate negative Gaussian membrane curvature. This surprising result provides a topological basis for membrane activity common to AMPs. Moreover, we highlight an important distinction between the maximal recognizability of a sequence to a trained AMP classifier (its ability to generate membrane curvature) and its maximal antimicrobial efficacy. As mutational distances are increased from known AMPs, we find AMP-like sequences that are increasingly difficult for nature to discover via simple mutation. Using the sequence map as a discovery tool, we find a unexpectedly diverse taxonomy of sequences that are just as membrane-active as known AMPs, but with a broad range of primary functions distinct from AMP functions, including endogenous neuropeptides, viral fusion proteins, topogenic peptides, and amyloids. The SVM classifier is useful as a general detector of membrane activity in peptide sequences.
Christiansen, Morten H; Arnon, Inbal
The ability to convey our thoughts using an infinite number of linguistic expressions is one of the hallmarks of human language. Understanding the nature of the psychological mechanisms and representations that give rise to this unique productivity is a fundamental goal for the cognitive sciences. A long-standing hypothesis is that single words and rules form the basic building blocks of linguistic productivity, with multiword sequences being treated as units only in peripheral cases such as idioms. The new millennium, however, has seen a shift toward construing multiword linguistic units not as linguistic rarities, but as important building blocks for language acquisition and processing. This shift-which originated within theoretical approaches that emphasize language learning and use-has far-reaching implications for theories of language representation, processing, and acquisition. Incorporating multiword units as integral building blocks blurs the distinction between grammar and lexicon; calls for models of production and comprehension that can accommodate and give rise to the effect of multiword information on processing; and highlights the importance of such units to learning. In this special topic, we bring together cutting-edge work on multiword sequences in theoretical linguistics, first-language acquisition, psycholinguistics, computational modeling, and second-language learning to present a comprehensive overview of the prominence and importance of such units in language, their possible role in explaining differences between first- and second-language learning, and the challenges the combined findings pose for theories of language. Copyright © 2017 Cognitive Science Society, Inc.
Gofer-Levi, Moran; Silberg, Tamar; Brezner, Amichai; Vakil, Eli
Skill learning (SL) is learning as a result of repeated exposure and practice, which encompasses independent explicit (response to instructions) and implicit (response to hidden regularities) processes. Little is known about the effects of developmental disorders, such as Cerebral Palsy (CP), on the ability to acquire new skills. We compared performance of CP and typically developing (TD) children and adolescents in completing the serial reaction time (SRT) task, which is a motor sequence learning task, and examined the impact of various factors on this performance as indicative of the ability to acquire motor skills. While both groups improved in performance, participants with CP were significantly slower than TD controls and did not learn the implicit sequence. Our results indicate that SL in children and adolescents with CP is qualitatively and quantitatively different than that of their peers. Understanding the unique aspects of SL in children and adolescents with CP might help plan appropriate and efficient interventions. Copyright © 2013 Elsevier Ltd. All rights reserved.
Yamamoto, Kota; Tsutsui, Seijiro; Yamamoto, Yuji
In this article we report the results of a study conducted to investigate the learning dynamics of three-ball juggling from the perspective of frequency locking. Based on the Farey sequence, we predicted that four stable coordination patterns, corresponding to dwell ratios of 0.83, 0.75, 0.67, and 0.50, would appear in the learning process. We examined the learning process in terms of task performance, taking into account individual differences in the amount of learning. We observed that the participants acquired individual-specific coordination patterns in a relatively early stage of learning, and that those coordination patterns were preserved in subsequent learning, even though performance in terms of number of successful consecutive throws increased substantially. This increase appeared to be related to a reduction in spatial variability of the juggling movements. Finally, the observed coordination patterns were in agreement with the predicted patterns, with the proviso that the pattern corresponding to a dwell ratio of 0.50 was not realized and only a hint of evidence was found for the dwell ratio of 0.67. This implies that the dwell ratios of 0.83 and 0.75 in particular exhibited a stable coordination structure due to strong frequency locking between the temporal variables of juggling. Copyright © 2015 Elsevier B.V. All rights reserved.
Tanaka, Toshihiro; Isfort, Peter; Braunschweig, Till; Westphal, Saskia; Woitok, Anna; Penzkofer, Tobias; Bruners, Philipp; Kichikawa, Kimihiko; Schmitz-Rode, Thomas; Mahnken, Andreas H.
Purpose. To evaluate the effects of particle size and course of action of superselective bland transcatheter arterial embolization (TAE) on the efficacy of radiofrequency ablation (RFA). Methods. Twenty pigs were divided into five groups: group 1a, 40-μm bland TAE before RFA; group 1b, 40-μm bland TAE after RFA; group 2a, 250-μm bland TAE before RFA; group 2b, 250-μm bland TAE after RFA and group 3, RFA alone. A total of 40 treatments were performed with a combined CT and angiography system. The sizes of the treated zones were measured from contrast-enhanced CTs on days 1 and 28. Animals were humanely killed, and the treated zones were examined pathologically. Results. There were no complications during procedures and follow-up. The short-axis diameter of the ablation zone in group 1a (mean ± standard deviation, 3.19 ± 0.39 cm) was significantly larger than in group 1b (2.44 ± 0.52 cm; P = 0.021), group 2a (2.51 ± 0.32 cm; P = 0.048), group 2b (2.19 ± 0.44 cm; P = 0.02), and group 3 (1.91 ± 0.55 cm; P 3 ). At histology, 40-μm microspheres were observed to occlude smaller and more distal arteries than 250-μm microspheres. Conclusion. Bland TAE is more effective before RFA than postablation embolization. The use of very small 40-μm microspheres enhances the efficacy of RFA more than the use of larger particles.
Freundlieb, Nils; Ridder, Volker; Dobel, Christian; Enriquez-Geppert, Stefanie; Baumgaertner, Annette; Zwitserlood, Pienie; Gerloff, Christian; Hummel, Friedhelm C; Liuzzi, Gianpiero
Despite a growing number of studies, the neurophysiology of adult vocabulary acquisition is still poorly understood. One reason is that paradigms that can easily be combined with neuroscientfic methods are rare. Here, we tested the efficiency of two paradigms for vocabulary (re-) acquisition, and compared the learning of novel words for actions and objects. Cortical networks involved in adult native-language word processing are widespread, with differences postulated between words for objects and actions. Words and what they stand for are supposed to be grounded in perceptual and sensorimotor brain circuits depending on their meaning. If there are specific brain representations for different word categories, we hypothesized behavioural differences in the learning of action-related and object-related words. Paradigm A, with the learning of novel words for body-related actions spread out over a number of days, revealed fast learning of these new action words, and stable retention up to 4 weeks after training. The single-session Paradigm B employed objects and actions. Performance during acquisition did not differ between action-related and object-related words (time*word category: p = 0.01), but the translation rate was clearly better for object-related (79%) than for action-related words (53%, p = 0.002). Both paradigms yielded robust associative learning of novel action-related words, as previously demonstrated for object-related words. Translation success differed for action- and object-related words, which may indicate different neural mechanisms. The paradigms tested here are well suited to investigate such differences with neuroscientific means. Given the stable retention and minimal requirements for conscious effort, these learning paradigms are promising for vocabulary re-learning in brain-lesioned people. In combination with neuroimaging, neuro-stimulation or pharmacological intervention, they may well advance the understanding of language learning
Full Text Available Cortical excitability may be subject to changes through training and learning. Motor training can increase cortical excitability in motor cortex, and facilitation of motor cortical excitability has been shown to be positively correlated with improvements in performance in simple motor tasks. Thus cortical excitability may tentatively be considered as a marker of learning and use-dependent plasticity. Previous studies focused on changes in cortical excitability brought about by learning processes, however, the relation between native levels of cortical excitability on the one hand and brain activation and behavioral parameters on the other is as yet unknown. In the present study we investigated the role of differential native motor cortical excitability for learning a motor sequencing task with regard to post-training changes in excitability, behavioral performance and involvement of brain regions. Our motor task required our participants to reproduce and improvise over a pre-learned motor sequence. Over both task conditions, participants with low cortical excitability (CElo showed significantly higher BOLD activation in task-relevant brain regions than participants with high cortical excitability (CEhi. In contrast, CElo and CEhi groups did not exhibit differences in percentage of correct responses and improvisation level. Moreover, cortical excitability did not change significantly after learning and training in either group, with the exception of a significant decrease in facilitatory excitability in the CEhi group. The present data suggest that the native, unmanipulated level of cortical excitability is related to brain activation intensity, but not to performance quality. The higher BOLD mean signal intensity during the motor task might reflect a compensatory mechanism in CElo participants.
Green, C Shawn; Pouget, Alexandre; Bavelier, Daphne
Action video game play benefits performance in an array of sensory, perceptual, and attentional tasks that go well beyond the specifics of game play [1-9]. That a training regimen may induce improvements in so many different skills is notable because the majority of studies on training-induced learning report improvements on the trained task but limited transfer to other, even closely related, tasks (, but see also [11-13]). Here we ask whether improved probabilistic inference may explain such broad transfer. By using a visual perceptual decision making task [14, 15], the present study shows for the first time that action video game experience does indeed improve probabilistic inference. A neural model of this task  establishes how changing a single parameter, namely the strength of the connections between the neural layer providing the momentary evidence and the layer integrating the evidence over time, captures improvements in action-gamers behavior. These results were established in a visual, but also in a novel auditory, task, indicating generalization across modalities. Thus, improved probabilistic inference provides a general mechanism for why action video game playing enhances performance in a wide variety of tasks. In addition, this mechanism may serve as a signature of training regimens that are likely to produce transfer of learning. Copyright © 2010 Elsevier Ltd. All rights reserved.
Shimizu, Renee E; Wu, Allan D; Samra, Jasmine K; Knowlton, Barbara J
The cerebellum has been shown to be important for skill learning, including the learning of motor sequences. We investigated whether cerebellar transcranial direct current stimulation (tDCS) would enhance learning of fine motor sequences. Because the ability to generalize or transfer to novel task variations or circumstances is a crucial goal of real world training, we also examined the effect of tDCS on performance of novel sequences after training. In Study 1, participants received either anodal, cathodal or sham stimulation while simultaneously practising three eight-element key press sequences in a non-repeating, interleaved order. Immediately after sequence practice with concurrent tDCS, a transfer session was given in which participants practised three interleaved novel sequences. No stimulation was given during transfer. An inhibitory effect of cathodal tDCS was found during practice, such that the rate of learning was slowed in comparison to the anodal and sham groups. In Study 2, participants received anodal or sham stimulation and a 24 h delay was added between the practice and transfer sessions to reduce mental fatigue. Although this consolidation period benefitted subsequent transfer for both tDCS groups, anodal tDCS enhanced transfer performance. Together, these studies demonstrate polarity-specific effects on fine motor sequence learning and generalization.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).
Wong, Ka Chun
Protein-DNA bindings are essential activities. Understanding them forms the basis for further deciphering of biological and genetic systems. In particular, the protein-DNA bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) play a central role in gene transcription. Comprehensive TF-TFBS binding sequence pairs have been found in a recent study. However, they are in one-to-one mappings which cannot fully reflect the many-to-many mappings within the bindings. An evolutionary algorithm is proposed to learn generalized representations (many-to-many mappings) from the TF-TFBS binding sequence pairs (one-to-one mappings). The generalized pairs are shown to be more meaningful than the original TF-TFBS binding sequence pairs. Some representative examples have been analyzed in this study. In particular, it shows that the TF-TFBS binding sequence pairs are not presumably in one-to-one mappings. They can also exhibit many-to-many mappings. The proposed method can help us extract such many-to-many information from the one-to-one TF-TFBS binding sequence pairs found in the previous study, providing further knowledge in understanding the bindings between TFs and TFBSs. © 2011 Springer-Verlag.
Wong, Ka Chun; Peng, Chengbin; Wong, Manhon; Leung, Kwongsak
Protein-DNA bindings are essential activities. Understanding them forms the basis for further deciphering of biological and genetic systems. In particular, the protein-DNA bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) play a central role in gene transcription. Comprehensive TF-TFBS binding sequence pairs have been found in a recent study. However, they are in one-to-one mappings which cannot fully reflect the many-to-many mappings within the bindings. An evolutionary algorithm is proposed to learn generalized representations (many-to-many mappings) from the TF-TFBS binding sequence pairs (one-to-one mappings). The generalized pairs are shown to be more meaningful than the original TF-TFBS binding sequence pairs. Some representative examples have been analyzed in this study. In particular, it shows that the TF-TFBS binding sequence pairs are not presumably in one-to-one mappings. They can also exhibit many-to-many mappings. The proposed method can help us extract such many-to-many information from the one-to-one TF-TFBS binding sequence pairs found in the previous study, providing further knowledge in understanding the bindings between TFs and TFBSs. © 2011 Springer-Verlag.
AKMAN, İbrahim; TURHAN, Çiğdem
The growing popularity of the social networking siteshas presented new options for the development of learning and teachingenvironments to provide informal learning. In this study, the usage of socialnetworking sites for the purpose of learning and teaching has been analyzedusing the extended Theory of Reasoned Action (TRA) model. A survey has beenconducted to analyze the behavior in regard to the acceptance of social mediafor learning and teaching and the results were systematically analyzed...
Maria Carolina Coelho Chimenti
Full Text Available The present article is based on a field research that aimed to provide educational subsidies for the use of digital technologies in teaching and learning process of English language, in two classes of the fifth grade from the elementary school, at the public school located in Campinas, São Paulo, Brazil. Based on the perspective of childhood pedagogy, which conceives the child as the protagonist and also (reproductive of knowledge, activities were carried with YouTube videos, online games, music, and many other learning objects. Likewise, observations, interviews and questionnaires were made with teachers and students involved in the research. Based on the action research, we analyzed aspects related to the contribution of some digital resources in teaching and learning of English at elementary school and we obtained many elements that allowed us to know the importance of learning a foreign language in the childhood nowadays, mainly English, and how new technologies can make learning more contextualized, meaningful, motivating children for language learning in a context in which they can be (criative.
Basu, Amrita; McFarlane, Hewlet G; Kopchick, John J
Growth hormone (GH) has a significant influence on cognitive performance in humans and other mammals. To understand the influence of altered GH action on cognition, we assessed spatial learning and memory using a Barnes maze (BM) comparing twelve-month old, male, bovine GH (bGH) and GH receptor antagonist (GHA) transgenic mice and their corresponding wild type (WT) littermates. During the acquisition training period in the BM, bGH mice showed increased latency, traveled longer path lengths and made more errors to reach the target than WT mice, indicating significantly poorer learning. Short-term memory (STM) and long-term memory (LTM) trials showed significantly suppressed memory retention in bGH mice when compared to the WT group. Conversely, GHA mice showed significantly better learning parameters (latency, path length and errors) and increased use of an efficient search strategy than WT mice. Our study indicates a negative impact of GH excess and a beneficial effect of the inhibition of GH action on spatial learning and memory and, therefore, cognitive performance in male mice. Further research to elucidate GH's role in brain function will facilitate identifying therapeutic applications of GH or GHA for neuropathological and neurodegenerative conditions. Copyright © 2017 Elsevier Inc. All rights reserved.
The influence of an intermittent long-time exposure to a concentration of 150 ppm carbon monoxide on the ability to learn conditioned reflexes was investigated with Wistar rats. Half the 80 rats employed and divided into intelligence groups were exposed to this concentration at night five times for 8 hr weekly. The carboxyhemoglobin level in the blood of these animals increased to 7-13 percent. After an adequate interval for CO elimination, the rats exposed and the control animals were trained to develop a conditioned flight reflex. At a later date, the results were ascertained. With regard to the progress in learning this action, the CO-exposed animals showed a significant reduction in performance (longer learning time, more frequent deficient behavior, and inclination for stupor and anxious denial).
Xie, Jing; Lu, Xiongxiong; Wu, Xue; Lin, Xiaoyi; Zhang, Chao; Huang, Xiaofang; Chang, Zhili; Wang, Xinjing; Wen, Chenlei; Tang, Xiaomei; Shi, Minmin; Zhan, Qian; Chen, Hao; Deng, Xiaxing; Peng, Chenghong; Li, Hongwei; Fang, Yuan; Shao, Yang; Shen, Baiyong
Targeted therapies including monoclonal antibodies and small molecule inhibitors have dramatically changed the treatment of cancer over past 10 years. Their therapeutic advantages are more tumor specific and with less side effects. For precisely tailoring available targeted therapies to each individual or a subset of cancer patients, next-generation sequencing (NGS) has been utilized as a promising diagnosis tool with its advantages of accuracy, sensitivity, and high throughput. We developed and validated a NGS-based cancer genomic diagnosis targeting 115 prognosis and therapeutics relevant genes on multiple specimen including blood, tumor tissue, and body fluid from 10 patients with different cancer types. The sequencing data was then analyzed by the clinical-applicable analytical pipelines developed in house. We have assessed analytical sensitivity, specificity, and accuracy of the NGS-based molecular diagnosis. Also, our developed analytical pipelines were capable of detecting base substitutions, indels, and gene copy number variations (CNVs). For instance, several actionable mutations of EGFR,PIK3CA,TP53, and KRAS have been detected for indicating drug susceptibility and resistance in the cases of lung cancer. Our study has shown that NGS-based molecular diagnosis is more sensitive and comprehensive to detect genomic alterations in cancer, and supports a direct clinical use for guiding targeted therapy.
Lange-Küttner, Christiane; Averbeck, Bruno B; Hirsch, Silvia V; Wießner, Isabel; Lamba, Nishtha
We know that stochastic feedback impairs children's associative stimulus-response (S-R) learning (Crone et al., 2004a; Eppinger et al., 2009), but the impact of stochastic feedback on sequence learning that involves deductive reasoning has not been not tested so far. In the current study, 8- to 11-year-old children (N = 171) learned a sequence of four left and right button presses, LLRR, RRLL, LRLR, RLRL, LRRL, and RLLR, which needed to be deduced from feedback because no directional cues were given. One group of children experienced consistent feedback only (deterministic feedback, 100% correct). In this condition, green feedback on the screen indicated that the children had been right when they were right, and red feedback indicated that the children had been wrong when they were wrong. Another group of children experienced inconsistent feedback (stochastic feedback, 85% correct, 15% false), where in some trials, green feedback on the screen could signal that children were right when in fact they were wrong, and red feedback could indicate that they were wrong when in fact they had been right. Independently of age, children's sequence learning in the stochastic condition was initially much lower than in the deterministic condition, but increased gradually and improved with practice. Responses toward positive vs. negative feedback varied with age. Children were increasingly able to understand that they could have been wrong when feedback indicated they were right (self-reflection), but they remained unable to understand that they could have been right when feedback indicated they were wrong (self-assertion).
Full Text Available We know that stochastic feedback impairs children’s associative stimulus-response (S-R learning (Crone, Jennigs, & Van der Molen, 2004a; Eppinger, Mock, & Kray, 2009, but the impact of stochastic feedback on sequence learning that involves deductive reasoning has not been not tested so far. In the current study, 8- to 11-year-old children (N = 171 learned a sequence of four left and right button presses, LLRR, RRLL, LRLR, RLRL, LRRL and RLLR, that needed to be deduced from feedback because no directional cues were given. One group of children experienced consistent feedback only (deterministic feedback, 100% correct. In this condition, green feedback on the screen indicated that the children had been right when they were right, and red feedback indicated that the children had been wrong when they were wrong. Another group of children experienced inconsistent feedback (stochastic feedback, 85% correct, 15% false, where in some trials, green feedback on the screen could signal that children were right when in fact they were wrong, and red feedback could indicate that they were wrong when in fact they had been right. Independently of age, children’s sequence learning in the stochastic condition was initially much lower than in the deterministic condition, but increased gradually and improved with practice. Responses towards positive vs. negative feedback varied with age. Children were increasingly able to understand that they could have been wrong when feedback indicated they were right (self-reflection, but they remained unable to understand that they could have been right when feedback indicated they were wrong (self-assertion.
Full Text Available The objectives of this research were to study: 1 the former and present conditions, problem, expectations, possible alternative solutions to solve problems, achieve expectations and the choices made in formulating an action plan for development of learning activity. 2 the results of both expected and unexpected changes from individual, group and organization, also the new knowledge created from learning by doing processes with participatory action research. The 17 participants consist of administrators, teachers, school committee and 5 stakeholders. Such as administrative officer, caretaker, community leader and representative alumni. Research instruments included an observation form, in-depth interview, and document examination. The research finding were as follows: Srijanwittaya general buddhist scripture school lack of equipment for teaching and learning and modern teaching aids. Teachers have not been development for 21st century learning skills. These were the cause of: bored lesson, low student achievement and school has not passed the third quality evaluation by the office for National Education Standards and Quality Assessment (Public Organization Researcher focus on solving problem by 4 projects were Follows: 1 promotion and development of teacher project 2 developing school environment project. 3 encourage collaboration for school development project and 4 improving manage potential for school based management project. After improving found that Srijanwittaya general buddhist scripture school, Loei province passed the quality evaluation and higher students achievement. Moreover, researcher and participants were learnt from research practice such as knowledge and experience. The new knowledge had 3 characteristics as follows: 1 new knowledge on participatory performance of school context 2 new knowledge by 5 steps of participle learning principal and 3 new knowledge by lesson learned visualizing from “SRIJAN Model”.
Cornelis, Claudia; de Picker, Livia J.; de Boer, Peter; Dumont, Glenn; Coppens, Violette; Morsel, Anne; Janssens, Luc; Timmers, Maarten; Sabbe, Bernard G. C.; Morrens, Manuel; Hulstijn, Wouter
Although there still is conflicting evidence whether schizophrenia is a neurodegenerative disease, cognitive changes in schizophrenia resemble those observed during normal aging. In contrast to extensively demonstrated deficits in explicit learning, it remains unclear whether implicit sequence
Learning in and by organisations has been of great interest to practitioners and academics for a number of years now. However, publications on empirical research are few, especially in the context of product innovation.This thesis reports on research which was aimed at (a) effective managerial
Gatti, R; Tettamanti, A; Gough, P M; Riboldi, E; Marinoni, L; Buccino, G
Both motor imagery and action observation have been shown to play a role in learning or re-learning complex motor tasks. According to a well accepted view they share a common neurophysiological basis in the mirror neuron system. Neurons within this system discharge when individuals perform a specific action and when they look at another individual performing the same or a motorically related action. In the present paper, after a short review of literature on the role of action observation and motor imagery in motor learning, we report the results of a kinematics study where we directly compared motor imagery and action observation in learning a novel complex motor task. This involved movement of the right hand and foot in the same angular direction (in-phase movement), while at the same time moving the left hand and foot in an opposite angular direction (anti-phase movement), all at a frequency of 1Hz. Motor learning was assessed through kinematics recording of wrists and ankles. The results showed that action observation is better than motor imagery as a strategy for learning a novel complex motor task, at least in the fast early phase of motor learning. We forward that these results may have important implications in educational activities, sport training and neurorehabilitation. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Full Text Available In this event-related FMRI study we investigated the effect of five days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the FMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45 and the medial prefrontal regions (centered on BA 8/32. Importantly, and central to this study, the inclusion of a naive preference FMRI baseline measurement allowed us to conclude that these FMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax in unsupervised AGL paradigms with proper learning designs.
Folia, Vasiliki; Petersson, Karl Magnus
In this event-related fMRI study we investigated the effect of 5 days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL) paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the fMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45) and the medial prefrontal regions (centered on BA 8/32). Importantly, and central to this study, the inclusion of a naive preference fMRI baseline measurement allowed us to conclude that these fMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax) in unsupervised AGL paradigms with proper learning designs.
Werner-Lin, Allison; Zaspel, Lori; Carlson, Mae; Mueller, Rebecca; Walser, Sarah A; Desai, Ria; Bernhardt, Barbara A
Clinical genome and exome sequencing (CGES) may identify variants leading to targeted management of existing conditions. Yet, CGES often fails to identify pathogenic diagnostic variants and introduces uncertainties by detecting variants of uncertain significance (VUS) and secondary findings. This study investigated how families understand findings and adjust their perspectives on CGES. As part of NIH's Clinical Sequencing Exploratory Research Consortium, children were recruited from clinics at the Children's Hospital of Pennsylvania (CHOP) and offered exome sequencing. Primary pathogenic and possibly pathogenic, and some secondary findings were returned. Investigators digitally recorded results disclosure sessions and conducted 3-month follow up interviews with 10 adolescents and a parent. An interdisciplinary team coded all transcripts. Participants were initially disappointed with findings, yet reactions evolved within disclosure sessions and at 3-month interviews toward acceptance and satisfaction. Families erroneously expected, and prepared extensively, to learn about risk for common conditions. During disclosure sessions, parents and adolescents varied in how they monitored and responded to each others reactions. Several misinterpreted, or overestimated, the utility of findings to attribute meaning and achieve closure for the CGES experience. Participants perceived testing as an opportunity to improve disease management despite results that did not introduce new treatments or diagnoses. Future research may examine whether families experience cognitive dissonance regarding discrepancies between expectations and findings, and how protective buffering minimizes the burden of disappointment on loved ones. As CGES is increasingly integrated into clinical care providers must contend with tempering family expectations and interpretations of findings while managing complex medical care. © 2018 Wiley Periodicals, Inc.
Luchi, Kelly Cristina Gaviao; Montrezor, Luís Henrique; Marcondes, Fernanda K
The aim of this study was to evaluate the effect of an educational game that is used for teaching the mechanisms of the action potentials in cell membranes. The game was composed of pieces representing the intracellular and extracellular environments, ions, ion channels, and the Na + -K + -ATPase pump. During the game activity, the students arranged the pieces to demonstrate how the ions move through the membrane in a resting state and during an action potential, linking the ion movement with a graph of the action potential. To test the effect of the game activity on student understanding, first-year dental students were given the game to play at different times in a series of classes teaching resting membrane potential and action potentials. In all experiments, students who played the game performed better in assessments. According to 98% of the students, the game supported the learning process. The data confirm the students' perception, indicating that the educational game improved their understanding about action potentials. Copyright © 2017 the American Physiological Society.
Sun, Tanlin; Zhou, Bo; Lai, Luhua; Pei, Jianfeng
Protein-protein interactions (PPIs) are critical for many biological processes. It is therefore important to develop accurate high-throughput methods for identifying PPI to better understand protein function, disease occurrence, and therapy design. Though various computational methods for predicting PPI have been developed, their robustness for prediction with external datasets is unknown. Deep-learning algorithms have achieved successful results in diverse areas, but their effectiveness for PPI prediction has not been tested. We used a stacked autoencoder, a type of deep-learning algorithm, to study the sequence-based PPI prediction. The best model achieved an average accuracy of 97.19% with 10-fold cross-validation. The prediction accuracies for various external datasets ranged from 87.99% to 99.21%, which are superior to those achieved with previous methods. To our knowledge, this research is the first to apply a deep-learning algorithm to sequence-based PPI prediction, and the results demonstrate its potential in this field.
Kaphingst, Kimberly A; Ivanovich, Jennifer; Lyons, Sarah; Biesecker, Barbara; Dresser, Rebecca; Elrick, Ashley; Matsen, Cindy; Goodman, Melody
The growing importance of genome sequencing means that patients will increasingly face decisions regarding what results they would like to learn. The present study examined psychological and clinical factors that might affect these preferences. 1,080 women diagnosed with breast cancer at age 40 or younger completed an online survey. We assessed their interest in learning various types of genome sequencing results: risk of preventable disease or unpreventable disease, cancer treatment response, uncertain meaning, risk to relatives' health, and ancestry/physical traits. Multivariable logistic regression was used to examine whether being "very" interested in each result type was associated with clinical factors: BRCA1/2 mutation status, prior genetic testing, family history of breast cancer, and psychological factors: cancer recurrence worry, genetic risk worry, future orientation, health information orientation, and genome sequencing knowledge. The proportion of respondents who were very interested in learning each type of result ranged from 16% to 77%. In all multivariable models, those who were very interested in learning a result type had significantly higher knowledge about sequencing benefits, greater genetic risks worry, and stronger health information orientation compared to those with less interest (p-values psychological factors. Shared decision-making approaches that increase knowledge about genome sequencing and incorporate patient preferences for health information and learning about genetic risks may help support patients' informed choices about learning different types of sequencing results. © Society of Behavioral Medicine 2018.
Angrist, M; Jamal, L
With the proliferation of affordable large-scale human genomic data come profound and vexing questions about management of such data and their clinical uncertainty. These issues challenge the view that genomic research on human beings can (or should) be fully segregated from clinical genomics, either conceptually or practically. Here, we argue that the sharp distinction between clinical care and research is especially problematic in the context of large-scale genomic sequencing of people with suspected genetic conditions. Core goals of both enterprises (e.g. understanding genotype-phenotype relationships; generating an evidence base for genomic medicine) are more likely to be realized at a population scale if both those ordering and those undergoing sequencing for diagnostic reasons are routinely and longitudinally studied. Rather than relying on expensive and lengthy randomized clinical trials and meta-analyses, we propose leveraging nascent clinical-research hybrid frameworks into a broader, more permanent instantiation of exploratory medical sequencing. Such an investment could enlighten stakeholders about the real-life challenges posed by whole-genome sequencing, such as establishing the clinical actionability of genetic variants, returning 'off-target' results to families, developing effective service delivery models and monitoring long-term outcomes. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Lehmann, Uta; Gilson, Lucy
Health policy and systems research (HPSR) is centrally concerned with people, their relationships and the actions and practices they can implement towards better health systems. These concerns suggest that HPS researchers must work in direct engagement with the practitioners and practice central to the inquiry, acknowledging their tacit knowledge and drawing it into generating new insights into health system functioning. Social science perspectives are of particular importance in this field because health policies and health systems are themselves social and political constructs. However, how can social science methodologies such as action research and narrative and appreciative enquiry enable such research, and how can methodologies from different disciplines be woven together to construct and make meaning of evidence for 'this' field? This article seeks to present 'methodological musings' on these points, to prompt wider discussion on the practice of HPSR. It draws on one long-term collaborative action learning research project being undertaken in Cape Town, South Africa. The District Innovation and Action Learning for Health System Development project is an action research partnership between two South African academic institutions and two health authorities focused, ultimately, on strengthening governance in primary health care.Drawing on this experience, the article considers three interrelated issues: The diversity and complexities of practitioner and research actors involved in co-producing HPSR; The nature of co-production and the importance of providing space to grapple across different systems of meaning;The character of evidence and data in co-production. There is much to be learnt from research traditions outside the health sector, but HPSR must work out its own practices--through collaboration and innovation among researchers and practitioners. In this article, we provide one set of experiences to prompt wider reflection and stimulate engagement on the
We are here today to discuss two related issues, lessons learned from the recent Cerro Grande fire, and, on a broader note, actions needed to mitigate current hazardous forest conditions in the interior West...
Buchanan, John J
The primary goal of this chapter is to merge together the visual perception perspective of observational learning and the coordination dynamics theory of pattern formation in perception and action. Emphasis is placed on identifying movement features that constrain and inform action-perception and action-production processes. Two sources of visual information are examined, relative motion direction and relative phase. The visual perception perspective states that the topological features of relative motion between limbs and joints remains invariant across an actor's motion and therefore are available for pickup by an observer. Relative phase has been put forth as an informational variable that links perception to action within the coordination dynamics theory. A primary assumption of the coordination dynamics approach is that environmental information is meaningful only in terms of the behavior it modifies. Across a series of single limb tasks and bimanual tasks it is shown that the relative motion and relative phase between limbs and joints is picked up through visual processes and supports observational learning of motor skills. Moreover, internal estimations of motor skill proficiency and competency are linked to the informational content found in relative motion and relative phase. Thus, the chapter links action to perception and vice versa and also links cognitive evaluations to the coordination dynamics that support action-perception and action-production processes.
Allah Bux Sargano
Full Text Available Human activity recognition (HAR is an important research area in the fields of human perception and computer vision due to its wide range of applications. These applications include: intelligent video surveillance, ambient assisted living, human computer interaction, human-robot interaction, entertainment, and intelligent driving. Recently, with the emergence and successful deployment of deep learning techniques for image classification, researchers have migrated from traditional handcrafting to deep learning techniques for HAR. However, handcrafted representation-based approaches are still widely used due to some bottlenecks such as computational complexity of deep learning techniques for activity recognition. However, approaches based on handcrafted representation are not able to handle complex scenarios due to their limitations and incapability; therefore, resorting to deep learning-based techniques is a natural option. This review paper presents a comprehensive survey of both handcrafted and learning-based action representations, offering comparison, analysis, and discussions on these approaches. In addition to this, the well-known public datasets available for experimentations and important applications of HAR are also presented to provide further insight into the field. This is the first review paper of its kind which presents all these aspects of HAR in a single review article with comprehensive coverage of each part. Finally, the paper is concluded with important discussions and research directions in the domain of HAR.
Full Text Available How do communities and group-based efforts create, learn and evolve? This paper argues that communities are dynamic, continuously creating connections through cyclical learning processes, regardless of how tight or loosely formulated group based efforts are (Hall et al. 2012. Learning cycles or epicycles processes are relevant for action-based investigation within organizational and social structures. The question of behaviors across boundaries or groups maybe influenced by their positioning within a larger adaptive system, including the type of focus, determined goals and the type of connections that have been developed over time (longitudinally. These types of community or group efforts can be described as autopoietic systems, which operate within larger adaptive societal webs (Nousala 2014. The learning methodologies involved in investigating these types of dynamic phenomena need themselves to be dynamic. These methods can be viewed through longitudinal cycles, (which are essentially feedback loops that include extensive reflective time lines, integration before repetition exposing these epicycles at work. The continuous recording of various processes through epicycles (which are the basis for learning cycles provide a means to "qualitatively measuring" change, which would normally go unseen (Hall et. al 2012; Hall et al. 2005; Nousala and Hall 2008; Wenger and Synder 2000; Garduno et al. 2015.
Hentschel, Maren; Lange-Kuttner, Christiane; Averbeck, Bruno B.
The study investigated sequence learning from stochastic feedback in boys with Autistic Spectrum Disorder (ASD) and typically developed (TD) boys. We asked boys with ASD from Nigeria and the UK as well as age- and gender-matched controls (also males only) to deduce a sequence of four left and right button presses, LLRR, RRLL, LRLR, RLRL, LRRL and…
Schmitz, Rémy; Pasquali, Antoine; Cleeremans, Axel; Peigneux, Philippe
It has been proposed that the right hemisphere (RH) is better suited to acquire novel material whereas the left hemisphere (LH) is more able to process well-routinized information. Here, we ask whether this potential dissociation also manifests itself in an implicit learning task. Using a lateralized version of the serial reaction time task (SRT), we tested whether participants trained in a divided visual field condition primarily stimulating the RH would learn the implicit regularities embedded in sequential material faster than participants in a condition favoring LH processing. In the first study, half of participants were presented sequences in the left (vs. right) visual field, and had to respond using their ipsilateral hand (unimanual condition), hence making visuo-motor processing possible within the same hemisphere. Results showed successful implicit sequence learning, as indicated by increased reaction time for a transfer sequence in both hemispheric conditions and lack of conscious knowledge in a generation task. There was, however, no evidence of interhemispheric differences. In the second study, we hypothesized that a bimanual response version of the lateralized SRT, which requires interhemispheric communication and increases computational and cognitive processing loads, would favor RH-dependent visuospatial/attentional processes. In this bimanual condition, our results revealed a much higher transfer effect in the RH than in the LH condition, suggesting higher RH sensitivity to the processing of novel sequential material. This LH/RH difference was interpreted within the framework of the Novelty-Routinization model [Goldberg, E., & Costa, L. D. (1981). Hemisphere differences in the acquisition and use of descriptive systems. Brain and Language, 14(1), 144-173] and interhemispheric interactions in attentional processing [Banich, M. T. (1998). The missing link: the role of interhemispheric interaction in attentional processing. Brain and Cognition, 36
Starosta, Sarah; Stüttgen, Maik C; Güntürkün, Onur
While the subject of learning has attracted immense interest from both behavioral and neural scientists, only relatively few investigators have observed single-neuron activity while animals are acquiring an operantly conditioned response, or when that response is extinguished. But even in these cases, observation periods usually encompass only a single stage of learning, i.e. acquisition or extinction, but not both (exceptions include protocols employing reversal learning; see Bingman et al.(1) for an example). However, acquisition and extinction entail different learning mechanisms and are therefore expected to be accompanied by different types and/or loci of neural plasticity. Accordingly, we developed a behavioral paradigm which institutes three stages of learning in a single behavioral session and which is well suited for the simultaneous recording of single neurons' action potentials. Animals are trained on a single-interval forced choice task which requires mapping each of two possible choice responses to the presentation of different novel visual stimuli (acquisition). After having reached a predefined performance criterion, one of the two choice responses is no longer reinforced (extinction). Following a certain decrement in performance level, correct responses are reinforced again (reacquisition). By using a new set of stimuli in every session, animals can undergo the acquisition-extinction-reacquisition process repeatedly. Because all three stages of learning occur in a single behavioral session, the paradigm is ideal for the simultaneous observation of the spiking output of multiple single neurons. We use pigeons as model systems, but the task can easily be adapted to any other species capable of conditioned discrimination learning.
Savinainen, Antti; Mäkynen, Asko; Nieminen, Pasi; Viiri, Jouni
This paper presents a research-based teaching-learning sequence (TLS) that focuses on the notion of interaction in teaching Newton's third law (N3 law) which is, as earlier studies have shown, a challenging topic for students to learn. The TLS made systematic use of a visual representation tool--an interaction diagram (ID)--highlighting…
Marzia De Lucia
Full Text Available We propose and validate a multivariate classification algorithm for characterizing changes in human intracranial electroencephalographic data (iEEG after learning motor sequences. The algorithm is based on a Hidden Markov Model (HMM that captures spatio-temporal properties of the iEEG at the level of single trials. Continuous intracranial iEEG was acquired during two sessions (one before and one after a night of sleep in two patients with depth electrodes implanted in several brain areas. They performed a visuomotor sequence (serial reaction time task, SRTT using the fingers of their non-dominant hand. Our results show that the decoding algorithm correctly classified single iEEG trials from the trained sequence as belonging to either the initial training phase (day 1, before sleep or a later consolidated phase (day 2, after sleep, whereas it failed to do so for trials belonging to a control condition (pseudo-random sequence. Accurate single-trial classification was achieved by taking advantage of the distributed pattern of neural activity. However, across all the contacts the hippocampus contributed most significantly to the classification accuracy for both patients, and one fronto-striatal contact for one patient. Together, these human intracranial findings demonstrate that a multivariate decoding approach can detect learning-related changes at the level of single-trial iEEG. Because it allows an unbiased identification of brain sites contributing to a behavioral effect (or experimental condition at the level of single subject, this approach could be usefully applied to assess the neural correlates of other complex cognitive functions in patients implanted with multiple electrodes.
Stavrou, D; Duit, R; Komorek, M
A teaching and learning sequence aimed at introducing upper secondary school students to the interplay between chance and determinism in nonlinear systems is presented. Three experiments concerning nonlinear systems (deterministic chaos, self-organization and fractals) and one experiment concerning linear systems are introduced. Thirty upper secondary students' capabilities and difficulties in understanding the scientific point of view were investigated, using a teaching experiment design. The results show that most students were capable of sound explanations concerning the interplay of chance and determinism in nonlinear systems
Full Text Available Research on the evolutionary basis of the human language faculty has proposed the mirror neuron system as a link between motor processing and speech development. Consequently, most work has focussed on the left inferior frontal cortex, in particular Broca's region, and the left inferior parietal cortex. However, the direct link between planning of hand motor and speech actions remains to be elucidated. Thus, the present study investigated whether sequencing of hand motor actions vs. speech motor actions has a common neural denominator. For the hand motor task, 25 subjects performed single, repeated, or sequenced button presses with either the left or right hand. The speech task was in analogy; the same subjects produced the syllable "po" once or repeatedly, or a sequence of different syllables (po-pi-po. Speech motor vs. hand motor effectors resulted in increased perisylvian activation including Broca's region (left area 44 and areas medially adjacent to left area 45. In contrast, common activation for sequenced vs. repeated production of button presses and syllables revealed the effector-independent involvement of left area 7A in the superior parietal lobule (SPL in sequencing. These data demonstrate that sequencing of vocal gestures, an important precondition for ordered utterances and ultimately human speech, shares area 7A, rather than inferior parietal regions, as a common cortical module with hand motor sequencing. Interestingly, area 7A has previously also been shown to be involved in the observation of hand and non-hand actions. In combination with the literature, the present data thus suggest a distinction between area 44, which is specifically recruited for (cognitive aspects of speech, and SPL area 7A for general aspects of motor sequencing. In sum, the study demonstrates a yet little considered role of the superior parietal lobule in the origins of speech, and may be discussed in the light of embodiment of speech and language in the
Ligozat, Florence; Lundqvist, Eva; Amade-Escot, Chantal
One strand of comparative didactics aims at discussing the relationships between the theoretical constructions developed within subject didactics and how these can contribute to research about teaching and learning. This article explores the relationships between categories for analysing joint actions of teacher and students (didactic contract,…
Traeger, James; Norgate, Carolyn
This is an account of practice. It explores the meeting point between action learning and action research, as a way of doing capacity building in organisational development (OD) in the NHS in the UK. The authors were part of a short cooperative inquiry (Heron, J. 1996. "Co-operative Inquiry: Research into the Human Condition." London:…
West, Eva; Wallin, Anita
Learning abstract concepts such as sound often involves an ontological shift because to conceptualize sound transmission as a process of motion demands abandoning sound transmission as a transfer of matter. Thus, for students to be able to grasp and use a generalized model of sound transmission poses great challenges for them. This study involved 199 students aged 10-14. Their views about sound transmission were investigated before and after teaching by comparing their written answers about sound transfer in different media. The teaching was built on a research-based teaching-learning sequence (TLS), which was developed within a framework of design research. The analysis involved interpreting students' underlying theories of sound transmission, including the different conceptual categories that were found in their answers. The results indicated a shift in students' understandings from the use of a theory of matter before the intervention to embracing a theory of process afterwards. The described pattern was found in all groups of students irrespective of age. Thus, teaching about sound and sound transmission is fruitful already at the ages of 10-11. However, the older the students, the more advanced is their understanding of the process of motion. In conclusion, the use of a TLS about sound, hearing and auditory health promotes students' conceptualization of sound transmission as a process in all grades. The results also imply some crucial points in teaching and learning about the scientific content of sound.
Ahn, Sangkyu; Yune, Young Gill; Ahn, Hyungjoon; Kim, Byungjik; Lee, Jinho [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)
On September 30, 2011, the Task Force completed its review and presented the public with the findings and recommendations in the CNSC Fukushima Task Force Report. The Task Force made 13 recommendations to further enhance the safety of nuclear power plants in Canada. After that, the CNSC established the CNSC Staffs Action Plan based on the Fukushima Task Force's recommendations. In Canada, 19 nuclear power reactor units are currently producing electric power, and all of them are pressurized heavy water-reactor (PHWR) types. Also, considering 2 power reactor units in Korea, Wolsung unit 1 and 2, are the same reactor type, the analysis of the CNSC Staffs Action Plan will be of benefit to determining recommendations of Korea to address lessons learned from the Fukushima Daiichi nuclear power plant. Therefore, the CNSC Staffs Action Plan was introduced and analyzed in this study. From the results of the above analysis, it is recognized that the strengthening of defense in depth, emergency preparedness and the regulatory oversight of nuclear power plants in Canada were emphasized and much similar to practices of other countries. Public consultation process establishing the CNSC Staffs action plan has been carried out several times, in order to ensure regulatory transparency, by the CNSC staffs, and this is comparable with other countries. It is expected that the detail analysis results of the above plan will be helpful to enhance the safety of domestic operating nuclear power plants.
Wu, Jianxin; Zhang, Yu; Lin, Weiyao
High dimensional representations such as Fisher vectors (FV) and vectors of locally aggregated descriptors (VLAD) have shown state-of-the-art accuracy for action recognition in videos. The high dimensionality, on the other hand, also causes computational difficulties when scaling up to large-scale video data. This paper makes three lines of contributions to learning to recognize actions using high dimensional representations. First, we reviewed several existing techniques that improve upon FV or VLAD in image classification, and performed extensive empirical evaluations to assess their applicability for action recognition. Our analyses of these empirical results show that normality and bimodality are essential to achieve high accuracy. Second, we proposed a new pooling strategy for VLAD and three simple, efficient, and effective transformations for both FV and VLAD. Both proposed methods have shown higher accuracy than the original FV/VLAD method in extensive evaluations. Third, we proposed and evaluated new feature selection and compression methods for the FV and VLAD representations. This strategy uses only 4% of the storage of the original representation, but achieves comparable or even higher accuracy. Based on these contributions, we recommend a set of good practices for action recognition in videos for practitioners in this field.
Patterson, Tamatha A.; Grundel, Ralph
Conservation Action Planning (CAP) is an adaptive management planning process refined by The Nature Conservancy (TNC) and embraced worldwide as the Open Standards for the Practice of Conservation. The CAP process facilitates open, multi-institutional collaboration on a common conservation agenda through organized actions and quantified results. While specifically designed for conservation efforts, the framework is adaptable and flexible to multiple scales and can be used for any collaborative planning effort. The CAP framework addresses inception; design and development of goals, measures, and strategies; and plan implementation and evaluation. The specific components of the CAP include defining the project scope and conservation targets; assessing the ecological viability; ascertaining threats and surrounding situation; identifying opportunities and designing strategies for action; and implementing actions and monitoring results. In 2007, TNC and a multidisciplinary graduate student team from the University of Michigan's School of Natural Resources and Environment initiated a CAP for the St. Marys River, the connecting channel between Lake Superior and Lake Huron, and its local watershed. The students not only gained experience in conservation planning, but also learned lessons that notably benefited the CAP process and were valuable for any successful collaborative effort—a dedicated core team improved product quality, accelerated the timeline, and provided necessary support for ongoing efforts; an academic approach in preparation for engagement in the planning process brought applicable scientific research to the forefront, enhanced workshop facilitation, and improved stakeholder participation; and early and continuous interactions with regional stakeholders improved cooperation and built a supportive network for collaboration.
The ten learning sequences follow on one another. Each picks on a particular aspect from the energy field. The subject notebooks are self-contained and can therefore be used independently. Apart from actual data and energy-related information, the information for the teacher contains: - proposals for teaching - suggestions for further activities - sample solutions for the pupil's sheets - references to the literature and media. The worksheets for the pupils are different; it should be possible to use the learning sequences in all classes of secondary school stage 1. The multicoloured foils for projectors should motivate, on the one hand, and on the other hand should help to check the results of learning.
Chersi, Fabian; Ferro, Marcello; Pezzulo, Giovanni; Pirrelli, Vito
A growing body of evidence in cognitive psychology and neuroscience suggests a deep interconnection between sensory-motor and language systems in the brain. Based on recent neurophysiological findings on the anatomo-functional organization of the fronto-parietal network, we present a computational model showing that language processing may have reused or co-developed organizing principles, functionality, and learning mechanisms typical of premotor circuit. The proposed model combines principles of Hebbian topological self-organization and prediction learning. Trained on sequences of either motor or linguistic units, the network develops independent neuronal chains, formed by dedicated nodes encoding only context-specific stimuli. Moreover, neurons responding to the same stimulus or class of stimuli tend to cluster together to form topologically connected areas similar to those observed in the brain cortex. Simulations support a unitary explanatory framework reconciling neurophysiological motor data with established behavioral evidence on lexical acquisition, access, and recall. Copyright © 2014 Cognitive Science Society, Inc.
Lavine, Marc H.; Roussin, Christopher J.
The authors describe a semester-long action-learning project where undergraduate or graduate management students learn about ethics, responsibility, and organizational behavior by examining the policy of their college or university that addresses academic integrity. Working in teams, students adopt a stakeholder management approach as they make…
Penney, Wendy; Meyer, Julienne; Cash, Penny; Clinnick, Lisa; Martin, Louise
The implementation of action learning workshops in three nursing homes in rural Victoria, Australia has been critical in the re-visioning of how care can be enhanced for residents. The workshops were designed with the intent of improving quality of care for residents by providing health care staff with opportunities to learn together and effect…
Brook, Cheryl; Milner, Christopher
This account reports on some experiences of facilitating action learning with international business students. Interest in international student learning and the international student experience is significant and increasing with a considerable range of literature on the subject. Some of this literature is concerned with the perceived…
Keim-Malpass, Jessica; Kitzmiller, Rebecca R; Skeeles-Worley, Angela; Lindberg, Curt; Clark, Matthew T; Tai, Robert; Calland, James Forrest; Sullivan, Kevin; Randall Moorman, J; Anderson, Ruth A
In the intensive care unit, clinicians monitor a diverse array of data inputs to detect early signs of impending clinical demise or improvement. Continuous predictive analytics monitoring synthesizes data from a variety of inputs into a risk estimate that clinicians can observe in a streaming environment. For this to be useful, clinicians must engage with the data in a way that makes sense for their clinical workflow in the context of a learning health system (LHS). This article describes the processes needed to evoke clinical action after initiation of continuous predictive analytics monitoring in an LHS. Copyright © 2018 Elsevier Inc. All rights reserved.
Gozli, Davood G; Bavelier, Daphne; Pratt, Jay
Research on the impact of action video game playing has revealed performance advantages on a wide range of perceptual and cognitive tasks. It is not known, however, if playing such games confers similar advantages in sensorimotor learning. To address this issue, the present study used a manual motion-tracking task that allowed for a sensitive measure of both accuracy and improvement over time. When the target motion pattern was consistent over trials, gamers improved with a faster rate and eventually outperformed non-gamers. Performance between the two groups, however, did not differ initially. When the target motion was inconsistent, changing on every trial, results revealed no difference between gamers and non-gamers. Together, our findings suggest that video game playing confers no reliable benefit in sensorimotor control, but it does enhance sensorimotor learning, enabling superior performance in tasks with consistent and predictable structure. Copyright © 2014. Published by Elsevier B.V.
Full Text Available This paper discusses the application of project-based learning (PBL to improve student’ psychomotor skills and concept understanding, as well as knowing what PBL contribution to the improvement of student’ psychomotor skills in chemistry learning. The study was conducted in three cycles. Each cycle consisted of planning, implementation, observation, and reflection steps. One set of data consists of student’ psychomotor skills assesment, student’ conceptual understanding and questionnaire responses were obtained from the action research. Learning process was performed in the eleventh grade students included 37 students (10 males and 27 females and 3 collaborators. The successful research was indicated by 85% of students achieve the mastery learning on concept understanding and well on psychomotor aspects. Data collection was performed using documentation method by questionnaire, observations, and tests. Data was analyzed quantitatively and qualitatively. The results show that all aspects of the psychomotor assessed include sets, mechanical response, complex response, adaptation, and origination were in high category. At the end of the lesson, the project assigned to students were evaluated jointly between teachers and students. The project results in the form of a series of distillation apparatus is applied to separate the natural compounds.
Ravik, Monika; Havnes, Anton; Bjørk, Ida Torunn
To explore, describe and compare learning actions that nursing students used during peripheral vein cannulation training on a latex arm or each other's arms in a clinical skills centre. Simulation-based training is thought to enhance learning and transfer of learning from simulation to the clinical setting and is commonly recommended in nursing education. What students actually are doing during simulation-based training is, however, less explored. The analysis of learning actions used during simulation-based training could contribute to development and improvement of simulation as a learning strategy in nursing education. A qualitative explorative and descriptive research design, involving content analysis of video recordings, was used. Video-supported observation of nine nursing students practicing vein cannulation was conducted in a clinical skills centre in late 2012. The students engaged in various learning actions. Students training on a latex arm used a considerably higher number of learning actions relative to those training on each other's arms. In both groups, students' learning actions consisted mainly of seeking and giving support. The teacher provided students training on each other's arms with detailed feedback regarding insertion of the cannula into the vein, while those training on a latex arm received sparse feedback from the teacher and fellow students. The teacher played an important role in facilitating nursing students' practical skill learning during simulation. The provision of support from both teachers and students should be emphasised to ensure that nursing students' learning needs are met. This study suggest that student nurses may be differently and inadequately prepared in peripheral vein cannulation in two simulation modalities used in the academic setting; training on a latex arm and on each other's arms. © 2017 John Wiley & Sons Ltd.
Benjamin G Schultz
Full Text Available Implicit learning (IL occurs unconsciously and without intention. Perceptual fluency is the ease of processing elicited by previous exposure to a stimulus. It has been assumed that perceptual fluency is associated with IL. However, the role of perceptual fluency following IL has not been investigated in temporal pattern learning. Two experiments by Schultz, Stevens, Keller, and Tillmann demonstrated the IL of auditory temporal patterns using a serial reaction-time task and a generation task based on the process dissociation procedure. The generation task demonstrated that learning was implicit in both experiments via motor fluency, that is, the inability to suppress learned information. With the aim to disentangle conscious and unconscious processes, we analyze unreported recognition data associated with the Schultz et al. experiments using the sequence identification measurement model. The model assumes that perceptual fluency reflects unconscious processes and IL. For Experiment 1, the model indicated that conscious and unconscious processes contributed to recognition of temporal patterns, but that unconscious processes had a greater influence on recognition than conscious processes. In the model implementation of Experiment 2, there was equal contribution of conscious and unconscious processes in the recognition of temporal patterns. As Schultz et al. demonstrated IL in both experiments using a generation task, and the conditions reported here in Experiments 1 and 2 were identical, two explanations are offered for the discrepancy in model and behavioral results based on the two tasks: 1 perceptual fluency may not be necessary to infer IL, or 2 conscious control over implicitly learned information may vary as a function of perceptual fluency and motor fluency.
Dignath, David; Janczyk, Markus
According to the ideomotor principle, behavior is controlled via a retrieval of the sensory consequences that will follow from the respective movement ("action-effects"). These consequences include not only what will happen, but also when something will happen. In fact, recollecting the temporal duration between response and effect takes time and prolongs the initiation of the response. We investigated the associative structure of action-effect learning with delayed effects and asked whether participants acquire integrated action-time-effect episodes that comprise a compound of all three elements or whether they acquire separate traces that connect actions to the time until an effect occurs and actions to the effects that follow them. In three experiments, results showed that participants retrieve temporal intervals that follow from their actions even when the identity of the effect could not be learned. Furthermore, retrieval of temporal intervals in isolation was not inferior to retrieval of temporal intervals that were consistently followed by predictable action-effects. More specifically, when tested under extinction, retrieval of action-time and action-identity associations seems to compete against each other, similar to overshadowing effects reported for stimulus-response conditioning. Together, these results suggest that people anticipate when the consequences of their action will occur, independently from what the consequences will be.
Kobza, Stefan; Bellebaum, Christian
Learning of stimulus-response-outcome associations is driven by outcome prediction errors (PEs). Previous studies have shown larger PE-dependent activity in the striatum for learning from own as compared to observed actions and the following outcomes despite comparable learning rates. We hypothesised that this finding relates primarily to a stronger integration of action and outcome information in active learners. Using functional magnetic resonance imaging, we investigated brain activations related to action-dependent PEs, reflecting the deviation between action values and obtained outcomes, and action-independent PEs, reflecting the deviation between subjective values of response-preceding cues and obtained outcomes. To this end, 16 active and 15 observational learners engaged in a probabilistic learning card-guessing paradigm. On each trial, active learners saw one out of five cues and pressed either a left or right response button to receive feedback (monetary win or loss). Each observational learner observed exactly those cues, responses and outcomes of one active learner. Learning performance was assessed in active test trials without feedback and did not differ between groups. For both types of PEs, activations were found in the globus pallidus, putamen, cerebellum, and insula in active learners. However, only for action-dependent PEs, activations in these structures and the anterior cingulate were increased in active relative to observational learners. Thus, PE-related activity in the reward system is not generally enhanced in active relative to observational learning but only for action-dependent PEs. For the cerebellum, additional activations were found across groups for cue-related uncertainty, thereby emphasising the cerebellum's role in stimulus-outcome learning. Copyright © 2014 Elsevier Ltd. All rights reserved.
Full Text Available The coming interaction between a growing electrified vehicle fleet and the desired growth in renewable energy provides new insights into the economic dispatch (ED problem. This paper presents an economic dispatch model that considers electric vehicle charging, battery exchange stations, and wind farms. This ED model is a high-dimensional, non-linear, and stochastic problem and its solution requires powerful methods. A new finite action-set learning automata (FALA-based approach that has the ability to adapt to a stochastic environment is proposed. The feasibility of the proposed approach is demonstrated in a modified IEEE 30 bus system. It is compared with continuous action-set learning automata and particle swarm optimization-based approaches in terms of convergence characteristics, computational efficiency, and solution quality. Simulation results show that the proposed FALA-based approach was indeed capable of more efficiently obtaining the approximately optimal solution. In addition, by using an optimal dispatch schedule for the interaction between electric vehicle stations and power systems, it is possible to reduce the gap between demand and power generation at different times of the day.
Full Text Available The contribution of music education to the holistic development of the young learner is uncontested. However, in South Africa, the vast majority of Reception Year (Grade R teachers do not have the required competences to teach music in ways that optimally enhance the holistic growth of their learners, as this aspect has been largely neglected during their pre-service and in-service training. In this paper, we report on a year-long intervention aimed at enabling three Grade R non-music specialist teachers at one urban township school in the Eastern Cape to create music-based learning opportunities for their learners. We employed a participatory action learning and action research (PALAR approach to the inquiry, which combines research with development. Our findings indicate that after a series of collaborative interactions, the participants started to explore and tap into their own musical competences. They revisited notions of the self as (ill-equipped, (unconfident, (incompetent and (independent music teachers, and began to assume autonomy and agency with regard to effective music education in the Grade R classroom. We consequently argue that under-qualified in-service teachers can be enabled to improve their practice through research interventions that stimulate maximum participant involvement, such as PALAR.
Sun, Shichang; Liu, Hongbo; Meng, Jiana; Chen, C L Philip; Yang, Yu
Sequence transfer learning is of interest in both academia and industry with the emergence of numerous new text domains from Twitter and other social media tools. In this paper, we put forward the data-sensitive granularity for transfer learning, and then, a novel substructural regularization transfer learning model (STLM) is proposed to preserve target domain features at substructural granularity in the light of the condition of labeled data set size. Our model is underpinned by hidden Markov model and regularization theory, where the substructural representation can be integrated as a penalty after measuring the dissimilarity of substructures between target domain and STLM with relative entropy. STLM can achieve the competing goals of preserving the target domain substructure and utilizing the observations from both the target and source domains simultaneously. The estimation of STLM is very efficient since an analytical solution can be derived as a necessary and sufficient condition. The relative usability of substructures to act as regularization parameters and the time complexity of STLM are also analyzed and discussed. Comprehensive experiments of part-of-speech tagging with both Brown and Twitter corpora fully justify that our model can make improvements on all the combinations of source and target domains.
Jurtz, Vanessa Isabell; Johansen, Alexander Rosenberg; Nielsen, Morten; Almagro Armenteros, Jose Juan; Nielsen, Henrik; Sønderby, Casper Kaae; Winther, Ole; Sønderby, Søren Kaae
Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data, new algorithms for training deep models and easy to use libraries for implementation and training of neural networks are the drivers of this development. The use of deep learning has been especially successful in image recognition; and the development of tools, applications and code examples are in most cases centered within this field rather than within biology. Here, we aim to further the development of deep learning methods within biology by providing application examples and ready to apply and adapt code templates. Given such examples, we illustrate how architectures consisting of convolutional and long short-term memory neural networks can relatively easily be designed and trained to state-of-the-art performance on three biological sequence problems: prediction of subcellular localization, protein secondary structure and the binding of peptides to MHC Class II molecules. All implementations and datasets are available online to the scientific community at https://github.com/vanessajurtz/lasagne4bio. firstname.lastname@example.org. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: email@example.com
Vlcek, D; Podstavkova, S; Dubovsky, J [Komenskeho Univ., Bratislava (Czechoslovakia). Prirodovedecka Fakulta
The effect was investigated of single and combined actions of alkylnitrosourea derivatives (N-methyl-N-nitrosourea and N-ethyl-N-nitrosourea) and UV-radiation on the survival of cells of Chlamydomonas reinhardtii algae in dependence on the sequence of application of mutagens and on the given conditions of cultivation following mutagen activity. In particular, the single phases were investigated of the total lethal effect, i.e., the death of cells before division and their death after division. The most pronounced changes in dependence on the sequence of application of mutagens and on the given conditions of cultivation were noted in cell death before division. In dependence on the sequence of application of mutagens, the effect of the combined action on the survival of cells changed from an additive (alkylnitrosourea + UV-radiation) to a protective effect (UV-radiation + alkylnitrosourea).
Rowell, Lonnie L.; Polush, Elena Yu; Riel, Margaret; Bruewer, Aaron
The purpose of this study was to identify distinguishing characteristics of action research within the Action Research Special Interest Group of the American Educational Research Association. The authors sought to delineate the foundational framework endorsed by this community. The study was conducted during January-April 2012 and employed an…
John W Krakauer
Full Text Available Generalization of motor learning refers to our ability to apply what has been learned in one context to other contexts. When generalization is beneficial, it is termed transfer, and when it is detrimental, it is termed interference. Insight into the mechanism of generalization may be acquired from understanding why training transfers in some contexts but not others. However, identifying relevant contextual cues has proven surprisingly difficult, perhaps because the search has mainly been for cues that are explicit. We hypothesized instead that a relevant contextual cue is an implicit memory of action with a particular body part. To test this hypothesis we considered a task in which participants learned to control motion of a cursor under visuomotor rotation in two contexts: by moving their hand through motion of their shoulder and elbow, or through motion of their wrist. Use of these contextual cues led to three observations: First, in naive participants, learning in the wrist context was much faster than in the arm context. Second, generalization was asymmetric so that arm training benefited subsequent wrist training, but not vice versa. Third, in people who had prior wrist training, generalization from the arm to the wrist was blocked. That is, prior wrist training appeared to prevent both the interference and transfer that subsequent arm training should have caused. To explain the data, we posited that the learner collected statistics of contextual history: all upper arm movements also move the hand, but occasionally we move our hands without moving the upper arm. In a Bayesian framework, history of limb segment use strongly affects parameter uncertainty, which is a measure of the covariance of the contextual cues. This simple Bayesian prior dictated a generalization pattern that largely reproduced all three findings. For motor learning, generalization depends on context, which is determined by the statistics of how we have previously used
Full Text Available Background and context: The Royal College of Midwives is engaged in a long-term twinning partnership with the Uganda Private Midwives Association. Uganda is one of the poorest countries in the world and only 27% of women and newborns have their needs met (UNFPA, 2014. A well-skilled, competent midwifery workforce is required to meet these needs yet Ugandan student midwives often receive poor-quality clinical education. The Ugandan Nurses and Midwives Council approached the Royal College of Midwives for assistance in designing a system of mentorship for Ugandan midwifery to address this gap. The project was funded by UK-Aid through the Tropical Health and Education Trust. Aims of the project: MOMENTUM was a 20-month action research project that aimed to develop and pilot a model of mentorship for student midwives in Uganda. This article focuses on one workstream relating to practice development, a twinning project that used workbased learning and appreciative inquiry, embedded in an action research approach, to facilitate practice development. Conclusions: This project added to the body of knowledge about midwifery twinning for building capacity in mentorship, research, and cross-cultural competence. MOMENTUM created a powerful community of practice that was enabling, fulfilling and transformative. Replication of this would require funding, management capacity and sufficient lead time for participatory planning and piloting. MOMENTUM’s audit tool was a bespoke design for this pilot project and so may not be transferable to other settings without further development, testing and validation. Implications for practice: •\tTwinning, action research, appreciative enquiry and workbased learning can be effective in enabling practice development •\tThe impact of midwifery twinning on leadership development requires further investigation, together with greater evidence on the reciprocal impact of twinning on the sending country
Davis, Kierrynn; Brownie, Sonya; Doran, Frances; Evans, Sue; Hutchinson, Marie; Mozolic-Staunton, Beth; Provost, Stephen; van Aken, Rosalie
The worldwide academic workforce is ageing. At the same time, health and human services workforces are expanding. The preparation of educators to fill gaps in expertise and to position the health sciences for future growth is an urgent need. The findings from a recent action learning project that aimed to enhance the professional growth and development of higher degree researcher student supervisors in a School of Health and Human Sciences are presented. Seven early career researchers and the facilitator met for two hours every two to three weeks over 4 months between April and July 2010, in a rural and regional university in New South Wales, Australia. The processes initiated were a combination of experiential knowledge, referral to relevant published reports, use of an effective supervision checklist, and critical conversations. Learning outcomes centered on higher degree management and supervision pedagogy, communities of practice, knowledge translation, and the establishment of a research culture. The contextual barriers and implications of the methodology and learning outcomes for the professional development of health and human science practitioners, researchers and educators is also discussed. © 2012 Blackwell Publishing Asia Pty Ltd.
Love, Peter E D; Smith, Jim; Teo, Pauline
Error management theory is drawn upon to examine how a project-based organization, which took the form of a program alliance, was able to change its established error prevention mindset to one that enacted a learning mindfulness that provided an avenue to curtail its action errors. The program alliance was required to unlearn its existing routines and beliefs to accommodate the practices required to embrace error management. As a result of establishing an error management culture the program alliance was able to create a collective mindfulness that nurtured learning and supported innovation. The findings provide a much-needed context to demonstrate the relevance of error management theory to effectively address rework and safety problems in construction projects. The robust theoretical underpinning that is grounded in practice and presented in this paper provides a mechanism to engender learning from errors, which can be utilized by construction organizations to improve the productivity and performance of their projects. Copyright © 2018 Elsevier Ltd. All rights reserved.
Full Text Available First year accounting has generally been perceived as one of the more challenging first year business courses for university students. Various Classroom Assessment Techniques (CATs have been proposed to attempt to enrich and enhance student learning, with these studies generally positioning students as learners alone. This paper uses an educational case study approach and examines the implementation of the IGCRA (individual, group, classroom reflective action technique, a Classroom Assessment Technique, on first year accounting students’ learning performance. Building on theoretical frameworks in the areas of cognitive learning, social development, and dialogical learning, the technique uses reports to promote reflection on both learning and teaching. IGCRA was found to promote feedback on the effectiveness of student, as well as teacher satisfaction. Moreover, the results indicated formative feedback can assist to improve the learning and learning environment for a large group of first year accounting students. Clear guidelines for its implementation are provided in the paper.
Chen, H Carrie; O'Sullivan, Patricia; Teherani, Arianne; Fogh, Shannon; Kobashi, Brent; ten Cate, Olle
Learning in the clinical workplace can appear to rely on opportunistic teaching. The cognitive apprenticeship model describes assigning tasks based on learner rather than just workplace needs. This study aimed to determine how excellent clinical teachers select clinical learning experiences to support the workplace participation and development of different level learners. Using a constructivist grounded theory approach, we conducted semi-structured interviews with medical school faculty identified as excellent clinical teachers teaching multiple levels of learners. We explored their approach to teach different level learners and their perceived role in promoting learner development. We performed thematic analysis of the interview transcripts using open and axial coding. We interviewed 19 clinical teachers and identified three themes related to their teaching approach: sequencing of learning experiences, selection of learning activities and teacher responsibilities. All teachers used sequencing as a teaching strategy by varying content, complexity and expectations by learner level. The teachers initially selected learning activities based on learner level and adjusted for individual competencies over time. They identified teacher responsibilities for learner education and patient safety, and used sequencing to promote both. Excellent clinical teachers described strategies for matching available learning opportunities to learners' developmental levels to safely engage learners and improve learning in the clinical workplace.
Panda, Priyadarshini; Roy, Kaushik
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.
Staels, Eva; Van den Broeck, Wim
Recently, a general implicit sequence learning deficit was proposed as an underlying cause of dyslexia. This new hypothesis was investigated in the present study by including a number of methodological improvements, for example, the inclusion of appropriate control conditions. The second goal of the study was to explore the role of attentional functioning in implicit and explicit learning tasks. In a 2 × 2 within-subjects design 4 tasks were administered in 30 dyslexic and 38 control children: an implicit and explicit serial reaction time (RT) task and an implicit and explicit contextual cueing task. Attentional functioning was also administered. The entire learning curves of all tasks were analyzed using latent growth curve modeling in order to compare performances between groups and to examine the role of attentional functioning on the learning curves. The amount of implicit learning was similar for both groups. However, the dyslexic group showed slower RTs throughout the entire task. This group difference reduced and became nonsignificant after controlling for attentional functioning. Both implicit learning tasks, but none of the explicit learning tasks, were significantly affected by attentional functioning. Dyslexic children do not suffer from a specific implicit sequence learning deficit. The slower RTs of the dyslexic children throughout the entire implicit sequence learning process are caused by their comorbid attention problems and overall slowness. A key finding of the present study is that, in contrast to what was assumed for a long time, implicit learning relies on attentional resources, perhaps even more than explicit learning does. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Guitart-Masip, Marc; Economides, Marcos; Huys, Quentin J M; Frank, Michael J; Chowdhury, Rumana; Duzel, Emrah; Dayan, Peter; Dolan, Raymond J
Decision-making involves two fundamental axes of control namely valence, spanning reward and punishment, and action, spanning invigoration and inhibition. We recently exploited a go/no-go task whose contingencies explicitly decouple valence and action to show that these axes are inextricably coupled during learning. This results in a disadvantage in learning to go to avoid punishment and in learning to no-go to obtain a reward. The neuromodulators dopamine and serotonin are likely to play a role in these asymmetries: Dopamine signals anticipation of future rewards and is also involved in an invigoration of motor responses leading to reward, but it also arbitrates between different forms of control. Conversely, serotonin is implicated in motor inhibition and punishment processing. To investigate the role of dopamine and serotonin in the interaction between action and valence during learning.Methods We combined computational modeling with pharmacological manipulation in 90 healthy human volunteers, using levodopa and citalopram to affect dopamine and serotonin, respectively. We found that, after administration of levodopa,action learning was less affected by outcome valence when compared with the placebo and citalopram groups. This highlights in this context a predominant effect of levodopa in controlling the balance between different forms of control.Citalopram had distinct effects, increasing participants'tendency to perform active responses independent of outcome valence, consistent with a role in decreasing motor inhibition. Our findings highlight the rich complexities of the roles played by dopamine and serotonin during instrumental learning.
Full Text Available Motivational salience plays an important role in shaping human behavior, but recent studies demonstrate that human performance is not uniformly improved by motivation. Instead, action has been shown to dominate valence in motivated tasks, and it is particularly difficult for humans to learn the inhibition of an action to obtain a reward, but the neural mechanism behind this behavioral specificity is yet unclear. In all mammals, including humans, the monoamine neurotransmitter dopamine is particularly important in the neural manifestation of appetitively motivated behavior, and the human dopamine system is subject to considerable genetic variability. The well-studied TaqIA restriction fragment length polymorphism (rs1800497 has previously been shown to affect striatal dopamine metabolism. In this study we investigated a potential effect of this genetic variation on motivated action/inhibition learning. Two independent cohorts consisting of 87 and 95 healthy participants, respectively, were tested using the previously described valenced go/no-go learning paradigm in which participants learned the reward-associated no-go condition significantly worse than all other conditions. This effect was modulated by the TaqIA polymorphism, with carriers of the A1 allele showing a diminished learning-related performance enhancement in the rewarded no-go condition compared to the A2 homozygotes. This result highlights a modulatory role for genetic variability of the dopaminergic system in individual learning differences of action-valence interaction.
Catherine Campbell on "Finishing and Special Motifs: Lessons learned from CRISPR analysis using next-generation draft sequences" at the 2012 Sequencing, Finishing, Analysis in the Future Meeting held June 5-7, 2012 in Santa Fe, New Mexico.
Facial action unit (AU) recognition has been applied in a wild range of fields, and has attracted great attention in the past two decades. Most existing works on AU recognition assumed that the complete label assignment for each training image is available, which is often not the case in practice. Labeling AU is expensive and time consuming process. Moreover, due to the AU ambiguity and subjective difference, some AUs are difficult to label reliably and confidently. Many AU recognition works try to train the classifier for each AU independently, which is of high computation cost and ignores the dependency among different AUs. In this work, we formulate AU recognition under incomplete data as a multi-label learning with missing labels (MLML) problem. Most existing MLML methods usually employ the same features for all classes. However, we find this setting is unreasonable in AU recognition, as the occurrence of different AUs produce changes of skin surface displacement or face appearance in different face regions. If using the shared features for all AUs, much noise will be involved due to the occurrence of other AUs. Consequently, the changes of the specific AUs cannot be clearly highlighted, leading to the performance degradation. Instead, we propose to extract the most discriminative features for each AU individually, which are learned by the supervised learning method. The learned features are further embedded into the instance-level label smoothness term of our model, which also includes the label consistency and the class-level label smoothness. Both a global solution using st-cut and an approximated solution using conjugate gradient (CG) descent are provided. Experiments on both posed and spontaneous facial expression databases demonstrate the superiority of the proposed method in comparison with several state-of-the-art works.
Li, Yongqiang; Wu, Baoyuan; Ghanem, Bernard; Zhao, Yongping; Yao, Hongxun; Ji, Qiang
Facial action unit (AU) recognition has been applied in a wild range of fields, and has attracted great attention in the past two decades. Most existing works on AU recognition assumed that the complete label assignment for each training image is available, which is often not the case in practice. Labeling AU is expensive and time consuming process. Moreover, due to the AU ambiguity and subjective difference, some AUs are difficult to label reliably and confidently. Many AU recognition works try to train the classifier for each AU independently, which is of high computation cost and ignores the dependency among different AUs. In this work, we formulate AU recognition under incomplete data as a multi-label learning with missing labels (MLML) problem. Most existing MLML methods usually employ the same features for all classes. However, we find this setting is unreasonable in AU recognition, as the occurrence of different AUs produce changes of skin surface displacement or face appearance in different face regions. If using the shared features for all AUs, much noise will be involved due to the occurrence of other AUs. Consequently, the changes of the specific AUs cannot be clearly highlighted, leading to the performance degradation. Instead, we propose to extract the most discriminative features for each AU individually, which are learned by the supervised learning method. The learned features are further embedded into the instance-level label smoothness term of our model, which also includes the label consistency and the class-level label smoothness. Both a global solution using st-cut and an approximated solution using conjugate gradient (CG) descent are provided. Experiments on both posed and spontaneous facial expression databases demonstrate the superiority of the proposed method in comparison with several state-of-the-art works.
Zhang, Yile; Wong, Yau Shu; Deng, Jian; Anton, Cristina; Gabos, Stephan; Zhang, Weiping; Huang, Dorothy Yu; Jin, Can
Real Time Cell Analysis (RTCA) technology is used to monitor cellular changes continuously over the entire exposure period. Combining with different testing concentrations, the profiles have potential in probing the mode of action (MOA) of the testing substances. In this paper, we present machine learning approaches for MOA assessment. Computational tools based on artificial neural network (ANN) and support vector machine (SVM) are developed to analyze the time-concentration response curves (TCRCs) of human cell lines responding to tested chemicals. The techniques are capable of learning data from given TCRCs with known MOA information and then making MOA classification for the unknown toxicity. A novel data processing step based on wavelet transform is introduced to extract important features from the original TCRC data. From the dose response curves, time interval leading to higher classification success rate can be selected as input to enhance the performance of the machine learning algorithm. This is particularly helpful when handling cases with limited and imbalanced data. The validation of the proposed method is demonstrated by the supervised learning algorithm applied to the exposure data of HepG2 cell line to 63 chemicals with 11 concentrations in each test case. Classification success rate in the range of 85 to 95 % are obtained using SVM for MOA classification with two clusters to cases up to four clusters. Wavelet transform is capable of capturing important features of TCRCs for MOA classification. The proposed SVM scheme incorporated with wavelet transform has a great potential for large scale MOA classification and high-through output chemical screening.
Pieraccioni, Fabio; Bonaccorsi, Elena; Gioncada, Anna
Some volcanic processes occur at pressures and temperatures very different from daily experience. Such extreme conditions, unreproducible in the classroom, can lead children to build concepts about volcanic phenomena very different from the reality (Greca & Moreira, 2000; Dove, 1998). The didactic goals of this learning sequence concern the relationships between the viscosity of magmas and types of erupted materials and their consequences on volcano shapes, to favour pupils' comprehension of what a volcano is. Viscosity and its temperature dependence can be easily experimented in class with analogue materials at room temperature (Baker et al., 2004). Our research aims are to observe the development of the thought of pupils of middle schools on volcanic phenomena; this allowed to put in evidence the benefits of this approach and to give suggestions to avoid possible critical points. We have experimented a hands-on learning sequence about volcanoes in four third classes of Tuscan middle schools, for an amount of 95 pupils, 48 females and 47 males. Sharing the principles of constructivism, we think useful that pupils start from their own direct experience for understanding natural phenomena not directly observable. Therefore, we start from the experiences and knowledge of children to build a inquiry-based itinerary (Minner et al., 2010; Pieraccioni et al., 2016). The learning sequence begins with a practical activity in which we employ common and well-known materials to introduce the concept of viscosity in order to relate various kinds of magma to the shape of volcanoes. One of the benefits of this approach is to overcome the problems of introducing complex concepts such as acidity of magmas or silica content, far from the pupils' experience and knowledge. These concepts are often used in Italian middle school textbooks to describe and classify volcanoes. The result is a list of names to learn by heart. On the contrary, by using oil, ketchup, peanut butter or honey
Tanaka, Kanji; Watanabe, Katsumi
The present study examined whether sequence learning led to more accurate and shorter performance time if people who are learning a sequence start over from the beginning when they make an error (i.e., practice the whole sequence) or only from the point of error (i.e., practice a part of the sequence). We used a visuomotor sequence learning paradigm with a trial-and-error procedure. In Experiment 1, we found fewer errors, and shorter performance time for those who restarted their performance from the beginning of the sequence as compared to those who restarted from the point at which an error occurred, indicating better learning of spatial and motor representations of the sequence. This might be because the learned elements were repeated when the next performance started over from the beginning. In subsequent experiments, we increased the occasions for the repetitions of learned elements by modulating the number of fresh start points in the sequence after errors. The results showed that fewer fresh start points were likely to lead to fewer errors and shorter performance time, indicating that the repetitions of learned elements enabled participants to develop stronger spatial and motor representations of the sequence. Thus, a single or two fresh start points in the sequence (i.e., starting over only from the beginning or from the beginning or midpoint of the sequence after errors) is likely to lead to more accurate and faster performance. Copyright © 2016 Elsevier B.V. All rights reserved.
Hayashi, Hatsuo; Igarashi, Jun
Spike-timing-dependent synaptic plasticity (STDP) is a simple and effective learning rule for sequence learning. However, synapses being subject to STDP rules are readily influenced in noisy circumstances because synaptic conductances are modified by pre- and postsynaptic spikes elicited within a few tens of milliseconds, regardless of whether those spikes convey information or not. Noisy firing existing everywhere in the brain may induce irrelevant enhancement of synaptic connections through STDP rules and would result in uncertain memory encoding and obscure memory patterns. We will here show that the LTD windows of the STDP rules enable robust sequence learning amid background noise in cooperation with a large signal transmission delay between neurons and a theta rhythm, using a network model of the entorhinal cortex layer II with entorhinal-hippocampal loop connections. The important element of the present model for robust sequence learning amid background noise is the symmetric STDP rule having LTD windows on both sides of the LTP window, in addition to the loop connections having a large signal transmission delay and the theta rhythm pacing activities of stellate cells. Above all, the LTD window in the range of positive spike-timing is important to prevent influences of noise with the progress of sequence learning.
Massing, Matthias; Blandin, Yannick; Panzer, Stefan
An experiment investigated the influence of eye movements on learning a simple motor sequence task when the visual display was magnified. The task was to reproduce a 1300 ms spatial-temporal pattern of elbow flexions and extensions. The spatial-temporal pattern was displayed in front of the participants. Participants were randomly assigned to four groups differing on eye movements (free to use their eyes/instructed to fixate) and the visual display (small/magnified). All participants had to perform a pre-test, an acquisition phase, a delayed retention test, and a transfer test. The results indicated that participants in each practice condition increased their performance during acquisition. The participants who were permitted to use their eyes in the magnified visual display outperformed those who were instructed to fixate on the magnified visual display. When a small visual display was used, the instruction to fixate induced no performance decrements compared to participants who were permitted to use their eyes during acquisition. The findings demonstrated that a spatial-temporal pattern can be learned without eye movements, but being permitting to use eye movements facilitates the response production when the visual angle is increased. Copyright © 2015 Elsevier B.V. All rights reserved.
Kelle, Pido I.; Ratterman, Christian; Gibbs, Cecil
This slide presentation reviews the Constellation Program Problem Reporting, Analysis and Corrective Action Process and System (Cx PRACA). The goal of the Cx PRACA is to incorporate Lessons learned from the Shuttle, ISS, and Orbiter programs by creating a single tool for managing the PRACA process, that clearly defines the scope of PRACA applicability and what must be reported, and defines the ownership and responsibility for managing the PRACA process including disposition approval authority. CxP PRACA is a process, supported by a single information gathering data module which will be integrated with a single CxP Information System, providing interoperability, import and export capability making the CxP PRACA a more effective and user friendly technical and management tool.
Fukushima nuclear accident was caused by loss of all AC power sources (SBO) and loss of ultimate heat sink (LUHS) at Fukushima Daiichi Nuclear Power Plants (NPPs) hit by the Great East Japan Earthquake. This article reviewed outline of Fukushima nuclear accident progression when on year had passed since and referred to lessons learned from accident and countermeasure plan to prevent severe accident in SBO and LUHS events by earthquake and tsunami as future action. This countermeasure would be taken to (1) prevent serious flooding in case a tsunami overwhelms the breakwater, with improving water tightness of rooms for emergency diesel generator, batteries and power centers, (2) enhance emergency power supply and cooling function with mobile electricity generator, high pressure fire pump car and alternate water supply source, (3) mitigate environmental effects caused by core damage with installing containment filtered venting, and (4) enforce emergency preparedness in case of severe accident. Definite countermeasure plan for Kashiwazaki-Kariwa NPPs was enumerated. (T. Tanaka)
Leggat, Sandra G; Balding, Cathy; Schiftan, Dan
To determine whether a formal mentoring programme assists nurse practitioner candidates to develop competence in the clinical leadership competencies required in their advanced practice roles. Nurse practitioner candidates are required to show evidence of defined clinical leadership competencies when they apply for endorsement within the Australian health care system. Aiming to assist the candidates with the development or enhancement of these leadership skills, 18 nurse practitioner candidates participated in a mentoring programme that matched them with senior nurse mentors. A pre-postlongitudinal intervention study. Eighteen nurse practitioner candidates and 17 senior nurses participated in a voluntary mentoring programme that incorporated coaching and action learning over 18 months in 2012 and 2013. Participants completed a pen and paper questionnaire to document baseline measures of self-reported leadership practices prior to commencement of the programme and again at the end of the programme. The mentors and the nurse practitioner candidates qualitatively evaluated the programme as successful and quantitative data illustrated significant improvement in self-reported leadership practices among the nurse practitioner candidates. In particular, the nurse practitioner candidates reported greater competence in the transformational aspects of leadership, which is directly related to the nurse practitioner candidate clinical leadership standard. A formal, structured mentoring programme based on principles of action learning was successful in assisting Australian advanced practice nurses enhance their clinical leadership skills in preparation for formal endorsement as a nurse practitioner and for success in their advanced practice role. Mentoring can assist nurses to transition to new roles and develop knowledge and skills in clinical leadership essential for advanced practice roles. Nurse managers should make greater use of mentoring programmes to support nurses in
Sullivan, Sarah; Gnesdilow, Dana; Puntambekar, Sadhana; Kim, Jee-Seon
Physical and virtual experimentation are thought to have different affordances for supporting students' learning. Research investigating the use of physical and virtual experiments to support students' learning has identified a variety of, sometimes conflicting, outcomes. Unanswered questions remain about how physical and virtual experiments may impact students' learning and for which contexts and content areas they may be most effective. Using a quasi-experimental design, we examined eighth grade students' (N = 100) learning of physics concepts related to pulleys depending on the sequence of physical and virtual labs they engaged in. Five classes of students were assigned to either the: physical first condition (PF) (n = 55), where students performed a physical pulley experiment and then performed the same experiment virtually, or virtual first condition (VF) (n = 45), with the opposite sequence. Repeated measures ANOVA's were conducted to examine how physical and virtual labs impacted students' learning of specific physics concepts. While we did not find clear-cut support that one sequence was better, we did find evidence that participating in virtual experiments may be more beneficial for learning certain physics concepts, such as work and mechanical advantage. Our findings support the idea that if time or physical materials are limited, using virtual experiments may help students understand work and mechanical advantage.
Baldassarre, Gianluca; Mannella, Francesco; Fiore, Vincenzo G; Redgrave, Peter; Gurney, Kevin; Mirolli, Marco
Reinforcement (trial-and-error) learning in animals is driven by a multitude of processes. Most animals have evolved several sophisticated systems of 'extrinsic motivations' (EMs) that guide them to acquire behaviours allowing them to maintain their bodies, defend against threat, and reproduce. Animals have also evolved various systems of 'intrinsic motivations' (IMs) that allow them to acquire actions in the absence of extrinsic rewards. These actions are used later to pursue such rewards when they become available. Intrinsic motivations have been studied in Psychology for many decades and their biological substrates are now being elucidated by neuroscientists. In the last two decades, investigators in computational modelling, robotics and machine learning have proposed various mechanisms that capture certain aspects of IMs. However, we still lack models of IMs that attempt to integrate all key aspects of intrinsically motivated learning and behaviour while taking into account the relevant neurobiological constraints. This paper proposes a bio-constrained system-level model that contributes a major step towards this integration. The model focusses on three processes related to IMs and on the neural mechanisms underlying them: (a) the acquisition of action-outcome associations (internal models of the agent-environment interaction) driven by phasic dopamine signals caused by sudden, unexpected changes in the environment; (b) the transient focussing of visual gaze and actions on salient portions of the environment; (c) the subsequent recall of actions to pursue extrinsic rewards based on goal-directed reactivation of the representations of their outcomes. The tests of the model, including a series of selective lesions, show how the focussing processes lead to a faster learning of action-outcome associations, and how these associations can be recruited for accomplishing goal-directed behaviours. The model, together with the background knowledge reviewed in the paper
Participatory diagnosis of soil fertility problems and subsequent experimentation was carried out at Kibwezi Division, Makweni district, using Participatory learning and Action Research (PLAR) methodologies. results of the soil analysis showed that nitrogen (N), phosphorus (P) and carbon (C) were the most limiting nutrients to the crop production. Farmers were excited to learn how to identify deficiency symptoms of N and P by looking at plant leaves. Farmers also identified and implemented practical options under rain-fed and irrigated conditions for solving the soil fertility problems such as use of manure, fertilisers or a combination of both. Fertiliser application at the rate of 40N + 40P 2 O 5 ha -1 and 60N + 60P 2 O 5 ha -1 produced significantly yield responses under rain-fed conditions. However, application of 20 t ha -1 and 40 t ha -1 of farm yard manure had no effect on grain yield of maize. Maize gross margins were positive with increasing fertilizer application. Similarly, fresh yields of Chili showed marked yield increasing with increasing fertility conditions. In contrast, onions and tomatoes showed a corresponding smaller yield increase with fertility improvement. Chili, onions and tomatoes had positive gross margins as nutrient application was increased indicating that benefit was higher with increasing fertiliser inputs. The PLAR methodology provided farmers with knowledge and skills that helped them to change their attitude towards soil fertility improvement interventions
Harmsen, Wouter J; Bussmann, Johannes B J; Selles, Ruud W; Hurkmans, Henri L P; Ribbers, Gerard M
Mirror therapy is a priming technique to improve motor function of the affected arm after stroke. To investigate whether a mirror therapy-based action observation (AO) protocol contributes to motor learning of the affected arm after stroke. A total of 37 participants in the chronic stage after stroke were randomly allocated to the AO or control observation (CO) group. Participants were instructed to perform an upper-arm reaching task as fast and as fluently as possible. All participants trained the upper-arm reaching task with their affected arm alternated with either AO or CO. Participants in the AO group observed mirrored video tapes of reaching movements performed by their unaffected arm, whereas participants in the CO group observed static photographs of landscapes. The experimental condition effect was investigated by evaluating the primary outcome measure: movement time (in seconds) of the reaching movement, measured by accelerometry. Movement time decreased significantly in both groups: 18.3% in the AO and 9.1% in the CO group. Decrease in movement time was significantly more in the AO compared with the CO group (mean difference = 0.14 s; 95% confidence interval = 0.02, 0.26; P = .026). The present study showed that a mirror therapy-based AO protocol contributes to motor learning after stroke. © The Author(s) 2014.
Molenaar, Inge; Chiu, Ming Ming
Extending past research showing that regulative activities (metacognitive and relational) can aid learning, this study tests whether sequences of cognitive, metacognitive and relational activities affect subsequent cognition. Scaffolded by a computer avatar, 54 primary school students (working in 18 groups of 3) discussed writing a report about a…
The purpose of this study was to investigate the effects of CBI lesson sequence type and cognitive style of field dependence on learning from Computer-Based Cooperative Instruction (CBCI) in WEB on the dependent measures, achievement, reading comprehension and reading rate. Eighty-seven college undergraduate students were randomly assigned to…
Arriassecq, Irene; Greca, Ileana Maria
This paper discusses some topics that stem from recent contributions made by the History, the Philosophy, and the Didactics of Science. We consider these topics relevant to the introduction of the Special Relativity Theory (SRT) in high school within a contextualized approach. We offer an outline of a teaching-learning sequence dealing with the…
Stein, Faith S.; And Others
Recent advances have been made in facilitating implementation of Ausubel's advance organizer strategy. One reason Ausubel's approach has not been widely adopted is its lack of specificity about how to relate what is to be learned to what has already been assimilated within the cognitive structure. The use of subsumptive sequencing, coordinate…
McCray, Janet; Warwick, Rob; Palmer, Adam
This paper aims to explore the influence of one cycle of a learning set experience in a postgraduate medical leadership development programme. It does so from two perspectives: first, from the self-reports of nine senior doctors working in leadership roles in England in the National Health Service; and second from a researcher perspective as we…
Paula Lee Kristmanson
Full Text Available Abstract This paper focuses on an action research project set in the context of one professional learning community‟s (PLC‟s exploration of the Common European Framework of Reference (CEFR and the European Language Portfolio (ELP. Teachers of second and foreign languages in a large urban high school examined the potential of principles and tools related to the CEFR and ELP and shared their experiences during PLC meetings. This study examines data collected as part of the PLC discussions and deliberations and presents two particular pedagogical results emerging from this work: the development of a philosophical stance and an action plan. The paper concludes with a discussion of the process in which teachers engaged as they co-constructed understanding and explored pedagogical implications of their professional dialogue. Résumé Cet article traite d'un projet de recherche action mené dans le contexte d'une communauté d'apprentissage professionnelle (CAP qui a exploré le Cadre européen commun de référence (CECR et le Portfolio européen des langues (PEL et comment la CAP les a mis en oeuvre dans des classes de langue. Les enseignants des langues secondes et étrangères situés à une école secondaire urbaine ont partagé leurs expériences lors des réunions de CAP. Cette étude analyse les données recueillies lors des discussions et des délibérations de la CAP et elle présente deux résultats pédagogiques particuliers émergeant de ce travail— le développement d‟une approche philosophique et un plan d‟action. L'article se termine sur une discussion des processus vécus par les enseignants en co-construisant leurs connaissances pédagogiques par l‟entremise du dialogue professionnel.
Auerbach, Anna Jo; Schussler, Elisabeth E.
Active learning (or learner-centered) pedagogies have been shown to enhance student learning in introductory biology courses. Student collaboration has also been shown to enhance student learning and may be a critical part of effective active learning practices. This study focused on documenting the use of individual active learning and group…
Ksoll, Victor F.; Gouliermis, Dimitrios A.; Klessen, Ralf S.; Grebel, Eva K.; Sabbi, Elena; Anderson, Jay; Lennon, Daniel J.; Cignoni, Michele; de Marchi, Guido; Smith, Linda J.; Tosi, Monica; van der Marel, Roeland P.
The Hubble Tarantula Treasury Project (HTTP) has provided an unprecedented photometric coverage of the entire star-burst region of 30 Doradus down to the half Solar mass limit. We use the deep stellar catalogue of HTTP to identify all the pre-main-sequence (PMS) stars of the region, i.e., stars that have not started their lives on the main-sequence yet. The photometric distinction of these stars from the more evolved populations is not a trivial task due to several factors that alter their colour-magnitude diagram positions. The identification of PMS stars requires, thus, sophisticated statistical methods. We employ Machine Learning Classification techniques on the HTTP survey of more than 800,000 sources to identify the PMS stellar content of the observed field. Our methodology consists of 1) carefully selecting the most probable low-mass PMS stellar population of the star-forming cluster NGC2070, 2) using this sample to train classification algorithms to build a predictive model for PMS stars, and 3) applying this model in order to identify the most probable PMS content across the entire Tarantula Nebula. We employ Decision Tree, Random Forest and Support Vector Machine classifiers to categorise the stars as PMS and Non-PMS. The Random Forest and Support Vector Machine provided the most accurate models, predicting about 20,000 sources with a candidateship probability higher than 50 percent, and almost 10,000 PMS candidates with a probability higher than 95 percent. This is the richest and most accurate photometric catalogue of extragalactic PMS candidates across the extent of a whole star-forming complex.
Background Plastids are an important component of plant cells, being the site of manufacture and storage of chemical compounds used by the cell, and contain pigments such as those used in photosynthesis, starch synthesis/storage, cell color etc. They are essential organelles of the plant cell, also present in algae. Recent advances in genomic technology and sequencing efforts is generating a huge amount of DNA sequence data every day. The predicted proteome of these genomes needs annotation at a faster pace. In view of this, one such annotation need is to develop an automated system that can distinguish between plastid and non-plastid proteins accurately, and further classify plastid-types based on their functionality. We compared the amino acid compositions of plastid proteins with those of non-plastid ones and found significant differences, which were used as a basis to develop various feature-based prediction models using similarity-search and machine learning. Results In this study, we developed separate Support Vector Machine (SVM) trained classifiers for characterizing the plastids in two steps: first distinguishing the plastid vs. non-plastid proteins, and then classifying the identified plastids into their various types based on their function (chloroplast, chromoplast, etioplast, and amyloplast). Five diverse protein features: amino acid composition, dipeptide composition, the pseudo amino acid composition, Nterminal-Center-Cterminal composition and the protein physicochemical properties are used to develop SVM models. Overall, the dipeptide composition-based module shows the best performance with an accuracy of 86.80% and Matthews Correlation Coefficient (MCC) of 0.74 in phase-I and 78.60% with a MCC of 0.44 in phase-II. On independent test data, this model also performs better with an overall accuracy of 76.58% and 74.97% in phase-I and phase-II, respectively. The similarity-based PSI-BLAST module shows very low performance with about 50% prediction
Rienties, Bart; Boroowa, Avinash; Cross, Simon; Kubiak, Chris; Mayles, Kevin; Murphy, Sam
There is an urgent need to develop an evidence-based framework for learning analytics whereby stakeholders can manage, evaluate, and make decisions about which types of interventions work well and under which conditions. In this article, we will work towards developing a foundation of an Analytics4Action Evaluation Framework (A4AEF) that is…
In this account of practice I would like to share my experiences of facilitating a Critical Reflection Action Learning (CRAL) set with a small family run business, struggling to make change and expand their services due to the problems they encountered in separating their business lives from their family lives. The account I present here is based…
Ballantyne, Roy; Packer, Jan
This paper argues the need for the providers of ecotourism and other free-choice environmental learning experiences to promote the adoption of environmentally sustainable actions beyond their own sites, when visitors return to their home environments. Previous research indicates that although visitors often leave such experiences with a heightened…
Newman, Jane L.; Dantzler, John; Coleman, April N.
The purpose of Science in Action (SIA) was to examine the relationship between implementing quality science, technology, engineering, and math (STEM) service-learning (SL) projects and the effect on students' academic engagement in middle school science, civic responsibility, and resilience to at-risk behaviors. The innovative project funded by…
The purpose of this mixed method study was to determine the perceived impact of learning about technology via action research as a professional development activity on faculty and students in higher education. Nine faculty members--also Teaching and Technology Fellows representing various disciplines at St. John's University--were selected based…
Jamal, Salma; Goyal, Sukriti; Shanker, Asheesh; Grover, Abhinav
Alzheimer's disease (AD) is a complex progressive neurodegenerative disorder commonly characterized by short term memory loss. Presently no effective therapeutic treatments exist that can completely cure this disease. The cause of Alzheimer's is still unclear, however one of the other major factors involved in AD pathogenesis are the genetic factors and around 70 % risk of the disease is assumed to be due to the large number of genes involved. Although genetic association studies have revealed a number of potential AD susceptibility genes, there still exists a need for identification of unidentified AD-associated genes and therapeutic targets to have better understanding of the disease-causing mechanisms of Alzheimer's towards development of effective AD therapeutics. In the present study, we have used machine learning approach to identify candidate AD associated genes by integrating topological properties of the genes from the protein-protein interaction networks, sequence features and functional annotations. We also used molecular docking approach and screened already known anti-Alzheimer drugs against the novel predicted probable targets of AD and observed that an investigational drug, AL-108, had high affinity for majority of the possible therapeutic targets. Furthermore, we performed molecular dynamics simulations and MM/GBSA calculations on the docked complexes to validate our preliminary findings. To the best of our knowledge, this is the first comprehensive study of its kind for identification of putative Alzheimer-associated genes using machine learning approaches and we propose that such computational studies can improve our understanding on the core etiology of AD which could lead to the development of effective anti-Alzheimer drugs.