Action Learning in China

ERIC Educational Resources Information Center

Marquardt, Michael J.

2015-01-01

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

Work-based learning using action learning sets.

PubMed

Rosser, Elizabeth

2016-10-27

Elizabeth Rosser, Deputy Dean (Education and Professional Practice) and Professor of Nursing at Bournemouth University reflects on the concept of action learning, and the benefits of being part of an action learning set.

Perceptual learning during action video game playing.

PubMed

Green, C Shawn; Li, Renjie; Bavelier, Daphne

2010-04-01

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.

Its All Action, Its All Learning: Action Learning in SMEs

ERIC Educational Resources Information Center

Clarke, Jean; Thorpe, Richard; Anderson, Lisa; Gold, Jeff

2006-01-01

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…

Statistical learning in social action contexts.

PubMed

Monroy, Claire; Meyer, Marlene; Gerson, Sarah; Hunnius, Sabine

2017-01-01

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

Statistical learning in social action contexts

PubMed Central

Meyer, Marlene; Gerson, Sarah; Hunnius, Sabine

2017-01-01

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

Lifelong learning of human actions with deep neural network self-organization.

PubMed

Parisi, German I; Tani, Jun; Weber, Cornelius; Wermter, Stefan

2017-12-01

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.

Action Learning in Undergraduate Engineering Thesis Supervision

ERIC Educational Resources Information Center

Stappenbelt, Brad

2017-01-01

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…

Enhancing Postgraduate Learning and Development: A Participatory Action Learning and Action Research Approach through Conferences

ERIC Educational Resources Information Center

Wood, Lesley; Louw, Ina; Zuber-Skerritt, Ortrun

2017-01-01

As supervisors who advocate the transformational potential of research both to generate theory and practical and emancipatory outcomes, we practice participatory action learning and action research (PALAR). This paper offers an illustrative case of how supervision practices based on action learning can foster emancipatory and lifelong learning…

Cross-View Action Recognition via Transferable Dictionary Learning.

PubMed

Zheng, Jingjing; Jiang, Zhuolin; Chellappa, Rama

2016-05-01

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.

25 Action Learning Schools.

ERIC Educational Resources Information Center

National Association of Secondary School Principals, Reston, VA.

This booklet on action-learning reflects an interest in preparing youth for the world of real experiences. Arranged in two major parts, the first offers information on the background and development of action-learning. Included in this section are the conclusions of the Panel on Youth of the President's Science Advisory Committee, the National…

Effects of Ventral Striatum Lesions on Stimulus-Based versus Action-Based Reinforcement Learning.

PubMed

Rothenhoefer, Kathryn M; Costa, Vincent D; Bartolo, Ramón; Vicario-Feliciano, Raquel; Murray, Elisabeth A; Averbeck, Bruno B

2017-07-19

Learning the values of actions versus stimuli may depend on separable neural circuits. In the current study, we evaluated the performance of rhesus macaques with ventral striatum (VS) lesions on a two-arm bandit task that had randomly interleaved blocks of stimulus-based and action-based reinforcement learning (RL). Compared with controls, monkeys with VS lesions had deficits in learning to select rewarding images but not rewarding actions. We used a RL model to quantify learning and choice consistency and found that, in stimulus-based RL, the VS lesion monkeys were more influenced by negative feedback and had lower choice consistency than controls. Using a Bayesian model to parse the groups' learning strategies, we also found that VS lesion monkeys defaulted to an action-based choice strategy. Therefore, the VS is involved specifically in learning the value of stimuli, not actions. SIGNIFICANCE STATEMENT Reinforcement learning models of the ventral striatum (VS) often assume that it maintains an estimate of state value. This suggests that it plays a general role in learning whether rewards are assigned based on a chosen action or stimulus. In the present experiment, we examined the effects of VS lesions on monkeys' ability to learn that choosing a particular action or stimulus was more likely to lead to reward. We found that VS lesions caused a specific deficit in the monkeys' ability to discriminate between images with different values, whereas their ability to discriminate between actions with different values remained intact. Our results therefore suggest that the VS plays a specific role in learning to select rewarded stimuli. Copyright © 2017 the authors 0270-6474/17/376902-13$15.00/0.

Learning to Select Actions with Spiking Neurons in the Basal Ganglia

PubMed Central

Stewart, Terrence C.; Bekolay, Trevor; Eliasmith, Chris

2012-01-01

We expand our existing spiking neuron model of decision making in the cortex and basal ganglia to include local learning on the synaptic connections between the cortex and striatum, modulated by a dopaminergic reward signal. We then compare this model to animal data in the bandit task, which is used to test rodent learning in conditions involving forced choice under rewards. Our results indicate a good match in terms of both behavioral learning results and spike patterns in the ventral striatum. The model successfully generalizes to learning the utilities of multiple actions, and can learn to choose different actions in different states. The purpose of our model is to provide both high-level behavioral predictions and low-level spike timing predictions while respecting known neurophysiology and neuroanatomy. PMID:22319465

Action Learning Research? Reflections from the Colloquium at the Third International Conference on Action Learning

ERIC Educational Resources Information Center

Coghlan, David

2013-01-01

The case for the notion of action learning research has been posed and explored in several publications over the past few years. There is no tradition within action learning of understanding it as an approach to research. Within some academic circles, there has been a focus on the "action turn," the development of the notion of actionable…

Action Learning as Invigoration

ERIC Educational Resources Information Center

Chivers, Terence S.

2011-01-01

The present account of action learning describes its adoption for pragmatic reasons by the University of the Third Age (U3A). The reason for the existence of this movement is the education of retired people. The account seeks to explain why the action learning method spread from one local U3A to another and across it to other local U3As. The case…

Impairments in action-outcome learning in schizophrenia.

PubMed

Morris, Richard W; Cyrzon, Chad; Green, Melissa J; Le Pelley, Mike E; Balleine, Bernard W

2018-03-03

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.

Learning and exploration in action-perception loops.

PubMed

Little, Daniel Y; Sommer, Friedrich T

2013-01-01

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.

Blended Learning in Action: A Practical Guide toward Sustainable Change

ERIC Educational Resources Information Center

Tucker, Catlin R.; Wycoff, Tiffany; Green, Jason T.

2017-01-01

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…

Learning through Participatory Action Research for Community Ecotourism Planning.

ERIC Educational Resources Information Center

Guevara, Jose Roberto Q.

1996-01-01

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)

Action Research Approach on Mobile Learning Design for the Underserved

ERIC Educational Resources Information Center

Kim, Paul H.

2009-01-01

This paper discusses an action research study focused on developing a mobile learning model of literacy development for underserved migrant indigenous children in Latin America. The research study incorporated a cyclical action model with four distinctive stages (Strategize, Apply, Evaluate, and Reflect) designed to guide constituencies involved…

Notes toward a Philosophy of Action Learning Research

ERIC Educational Resources Information Center

Coghlan, David; Coughlan, Paul

2010-01-01

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,…

Modeling the Value of Strategic Actions in the Superior Colliculus

PubMed Central

Thevarajah, Dhushan; Webb, Ryan; Ferrall, Christopher; Dorris, Michael C.

2009-01-01

In learning models of strategic game play, an agent constructs a valuation (action value) over possible future choices as a function of past actions and rewards. Choices are then stochastic functions of these action values. Our goal is to uncover a neural signal that correlates with the action value posited by behavioral learning models. We measured activity from neurons in the superior colliculus (SC), a midbrain region involved in planning saccadic eye movements, while monkeys performed two saccade tasks. In the strategic task, monkeys competed against a computer in a saccade version of the mixed-strategy game ”matching-pennies”. In the instructed task, saccades were elicited through explicit instruction rather than free choices. In both tasks neuronal activity and behavior were shaped by past actions and rewards with more recent events exerting a larger influence. Further, SC activity predicted upcoming choices during the strategic task and upcoming reaction times during the instructed task. Finally, we found that neuronal activity in both tasks correlated with an established learning model, the Experience Weighted Attraction model of action valuation (Camerer and Ho, 1999). Collectively, our results provide evidence that action values hypothesized by learning models are represented in the motor planning regions of the brain in a manner that could be used to select strategic actions. PMID:20161807

How Can Action Learning Contribute to Social Capital?

ERIC Educational Resources Information Center

Pedler, Mike; Attwood, Margaret

2011-01-01

This paper explores the contribution that action learning can make to the formation of social capital via experiences of action learning projects in NHS Pathology Services in the UK. The paper describes the development of action learning practice in recent years, reviews the notion of social capital and considers how action learning might…

Critical Action Learning: Extending Its Reach

ERIC Educational Resources Information Center

Ram, Monder

2012-01-01

The trend to imbue action learning with an explicit conception of criticality appears to be gathering momentum. The idea of critical action learning (CAL) foregrounds the connection between power, emotion and organizing. How this triumvirate of forces relate to each other fundamentally shapes the scope for learning. Theoretical and empirical…

Sparse Modeling of Human Actions from Motion Imagery

DTIC Science & Technology

2011-09-02

is here developed. Spatio-temporal features that char- acterize local changes in the image are rst extracted. This is followed by the learning of a...video comes from the optimal sparse linear com- bination of the learned basis vectors (action primitives) representing the actions. A low...computational cost deep-layer model learning the inter- class correlations of the data is added for increasing discriminative power. In spite of its simplicity

Learning robot actions based on self-organising language memory.

PubMed

Wermter, Stefan; Elshaw, Mark

2003-01-01

In the MirrorBot project we examine perceptual processes using models of cortical assemblies and mirror neurons to explore the emergence of semantic representations of actions, percepts and concepts in a neural robot. The hypothesis under investigation is whether a neural model will produce a life-like perception system for actions. In this context we focus in this paper on how instructions for actions can be modeled in a self-organising memory. Current approaches for robot control often do not use language and ignore neural learning. However, our approach uses language instruction and draws from the concepts of regional distributed modularity, self-organisation and neural assemblies. We describe a self-organising model that clusters actions into different locations depending on the body part they are associated with. In particular, we use actual sensor readings from the MIRA robot to represent semantic features of the action verbs. Furthermore, we outline a hierarchical computational model for a self-organising robot action control system using language for instruction.

Spatial Learning and Action Planning in a Prefrontal Cortical Network Model

PubMed Central

Martinet, Louis-Emmanuel; Sheynikhovich, Denis; Benchenane, Karim; Arleo, Angelo

2011-01-01

The interplay between hippocampus and prefrontal cortex (PFC) is fundamental to spatial cognition. Complementing hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive “insight” capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial planning, including prospective coding and distance-to-goal correlates. PMID:21625569

Learning to understand others' actions.

PubMed

Press, Clare; Heyes, Cecilia; Kilner, James M

2011-06-23

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.

Translating visual information into action predictions: Statistical learning in action and nonaction contexts.

PubMed

Monroy, Claire D; Gerson, Sarah A; Hunnius, Sabine

2018-05-01

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.

The Challenge of Evaluating Action Learning

ERIC Educational Resources Information Center

Edmonstone, John

2015-01-01

The paper examines the benefits claimed for action learning at individual, organisational and inter-organisational levels. It goes on to identify both generic difficulties in evaluating development programmes and action learning specifically. The distinction between formative and summative evaluation is considered and a summative evaluation…

Analysis of a physics teacher's pedagogical `micro-actions' that support 17-year-olds' learning of free body diagrams via a modelling approach

NASA Astrophysics Data System (ADS)

Tay, Su Lynn; Yeo, Jennifer

2018-01-01

Great teaching is characterised by the specific actions a teacher takes in the classroom to bring about learning. In the context of model-based teaching (MBT), teachers' difficulty in working with students' models that are not scientifically consistent is troubling. To address this problem, the aim of this study is to identify the pedagogical micro-actions to support the development of scientific models and modelling skills during the evaluation and modification stages of MBT. Taking the perspective of pedagogical content knowing (PCKg), it identifies these micro-actions as an in-situ, dynamic transformation of knowledges of content, pedagogy, student and environment context. Through a case study approach, a lesson conducted by an experienced high-school physics teacher was examined. Audio and video recordings of the lesson contributed to the data sources. Taking a grounded approach in the analysis, eight pedagogical micro-actions enacted by the teacher were identified, namely 'clarification', 'evaluation', 'explanation', 'modification', 'exploration', 'referencing conventions', 'focusing' and 'meta-representing'. These micro-actions support students' learning related to the conceptual, cognitive, discursive and epistemological aspects of modelling. From the micro-actions, we identify the aspects of knowledges of PCKg that teachers need in order to competently select and enact these micro-actions. The in-situ and dynamic transformation of these knowledges implies that professional development should also be situated in the context in which these micro-actions are meaningful.

Learning to understand others' actions

PubMed Central

Press, Clare; Heyes, Cecilia; Kilner, James M.

2011-01-01

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. PMID:21084333

A continuous-time neural model for sequential action.

PubMed

Kachergis, George; Wyatte, Dean; O'Reilly, Randall C; de Kleijn, Roy; Hommel, Bernhard

2014-11-05

Action selection, planning and execution are continuous processes that evolve over time, responding to perceptual feedback as well as evolving top-down constraints. Existing models of routine sequential action (e.g. coffee- or pancake-making) generally fall into one of two classes: hierarchical models that include hand-built task representations, or heterarchical models that must learn to represent hierarchy via temporal context, but thus far lack goal-orientedness. We present a biologically motivated model of the latter class that, because it is situated in the Leabra neural architecture, affords an opportunity to include both unsupervised and goal-directed learning mechanisms. Moreover, we embed this neurocomputational model in the theoretical framework of the theory of event coding (TEC), which posits that actions and perceptions share a common representation with bidirectional associations between the two. Thus, in this view, not only does perception select actions (along with task context), but actions are also used to generate perceptions (i.e. intended effects). We propose a neural model that implements TEC to carry out sequential action control in hierarchically structured tasks such as coffee-making. Unlike traditional feedforward discrete-time neural network models, which use static percepts to generate static outputs, our biological model accepts continuous-time inputs and likewise generates non-stationary outputs, making short-timescale dynamic predictions. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Leadership development through action learning sets: an evaluation study.

PubMed

Walia, Surinder; Marks-Maran, Di

2014-11-01

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.

The Representation of Motor (Inter)action, States of Action, and Learning: Three Perspectives on Motor Learning by Way of Imagery and Execution

PubMed Central

Frank, Cornelia; Schack, Thomas

2017-01-01

Learning in intelligent systems is a result of direct and indirect interaction with the environment. While humans can learn by way of different states of (inter)action such as the execution or the imagery of an action, their unique potential to induce brain- and mind-related changes in the motor action system is still being debated. The systematic repetition of different states of action (e.g., physical and/or mental practice) and their contribution to the learning of complex motor actions has traditionally been approached by way of performance improvements. More recently, approaches highlighting the role of action representation in the learning of complex motor actions have evolved and may provide additional insight into the learning process. In the present perspective paper, we build on brain-related findings and sketch recent research on learning by way of imagery and execution from a hierarchical, perceptual-cognitive approach to motor control and learning. These findings provide insights into the learning of intelligent systems from a perceptual-cognitive, representation-based perspective and as such add to our current understanding of action representation in memory and its changes with practice. Future research should build bridges between approaches in order to more thoroughly understand functional changes throughout the learning process and to facilitate motor learning, which may have particular importance for cognitive systems research in robotics, rehabilitation, and sports. PMID:28588510

Mirroring "meaningful" actions: sensorimotor learning modulates imitation of goal-directed actions.

PubMed

Catmur, Caroline; Heyes, Cecilia

2017-06-19

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.

Sensorimotor Learning Biases Choice Behavior: A Learning Neural Field Model for Decision Making

PubMed Central

Schöner, Gregor; Gail, Alexander

2012-01-01

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

Virtual Action Learning: Practices and Challenges

ERIC Educational Resources Information Center

Dickenson, Mollie; Burgoyne, John; Pedler, Mike

2010-01-01

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…

CLEANing the Reward: Counterfactual Actions to Remove Exploratory Action Noise in Multiagent Learning

NASA Technical Reports Server (NTRS)

HolmesParker, Chris; Taylor, Mathew E.; Tumer, Kagan; Agogino, Adrian

2014-01-01

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

Issues in Action Learning: A Critical Realist Interpretation

ERIC Educational Resources Information Center

Burgoyne, John

2009-01-01

The purpose of this paper is to argue that the perspective of "critical realism" has considerable potential for moving forward the theory and practice of action learning. The paper addresses three questions: (1) Does action learning emphasise the individual or the collective? (2) Can action learning be thought of as critical, but should it also be…

Defining Success in Action Learning: An International Comparison

ERIC Educational Resources Information Center

Bong, Hyeon-Cheol; Cho, Yonjoo

2017-01-01

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…

Understanding the Causal Path between Action, Learning, and Solutions: Maximizing the Power of Action Learning to Achieve Great Results

ERIC Educational Resources Information Center

Leonard, H. Skipton

2015-01-01

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…

Action and Organizational Learning in an Elevator Company

ERIC Educational Resources Information Center

De Loo, Ivo

2006-01-01

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,…

Practicing What We Teach: Using Action Research to Learn about Teaching Action Research

ERIC Educational Resources Information Center

Brown, Barb; Dressler, Roswita; Eaton, Sarah Elaine; Jacobsen, Michele

2015-01-01

In this article, action research is explored as a process for instructor reflection, professional learning and collaboration. The context for the professional learning was the teaching of graduate level education courses in which action research, in conjunction with a cohort-based, collaboratory approach to learning, was used to facilitate…

Solving Wicked Problems through Action Learning

ERIC Educational Resources Information Center

Crul, Liselore

2014-01-01

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…

Modeling Healthy Behavior: Actions and Attitudes in Schools.

ERIC Educational Resources Information Center

Berryman, Judy C.; Breighner, Kathryn W.

This book notes that much of what children and adolescents know about life they learn from watching adult role models: teachers, parents, coaches, and clergy members. It was written to help adults examine their health-related beliefs and actions and evaluate how they model these beliefs and actions, consciously and unconsciously, to children. The…

Switching Reinforcement Learning for Continuous Action Space

NASA Astrophysics Data System (ADS)

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.

Safe or Unsafe? The Paradox of Action Learning

ERIC Educational Resources Information Center

Robertson, Jane; Bell, Diane

2017-01-01

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…

Linking Action Learning and Inter-Organisational Learning: The Learning Journey Approach

ERIC Educational Resources Information Center

Schumacher, Thomas

2015-01-01

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…

Mayan Children's Creation of Learning Ecologies by Initiative and Cooperative Action.

PubMed

de León, Lourdes

2015-01-01

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.

To Act and Learn: A Bakhtinian Exploration of Action Learning

ERIC Educational Resources Information Center

Gold, Jeff; Anderson, Lisa; Clarke, Jean; Thorpe, Richard

2009-01-01

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…

Action Learning for Professionals: A New Approach to Practice

ERIC Educational Resources Information Center

Abbott, Christine; Mayes, Cathy

2014-01-01

Following on from the article "Building Capacity in Social Care: An Evaluation of a National Programme of Action Learning Facilitator Development" (Abbott, C., L. Burtney, and C. Wall. 2013. "Action Learning: Research & Practice" 10 (2): 168--177), this article describes how action learning is being introduced in Cornwall…

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task.

PubMed

Sargent, Barbara; Reimann, Hendrik; Kubo, Masayoshi; Fetters, Linda

2015-06-01

Task-specific actions emerge from spontaneous movement during infancy. It has been proposed that task-specific actions emerge through a discovery-learning process. Here a method is described in which 3-4 month old infants learn a task by discovery and their leg movements are captured to quantify the learning process. This discovery-learning task uses an infant activated mobile that rotates and plays music based on specified leg action of infants. Supine infants activate the mobile by moving their feet vertically across a virtual threshold. This paradigm is unique in that as infants independently discover that their leg actions activate the mobile, the infants' leg movements are tracked using a motion capture system allowing for the quantification of the learning process. Specifically, learning is quantified in terms of the duration of mobile activation, the position variance of the end effectors (feet) that activate the mobile, changes in hip-knee coordination patterns, and changes in hip and knee muscle torque. This information describes infant exploration and exploitation at the interplay of person and environmental constraints that support task-specific action. Subsequent research using this method can investigate how specific impairments of different populations of infants at risk for movement disorders influence the discovery-learning process for task-specific action.

Structure learning in action

PubMed Central

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

2010-01-01

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

Action Learning, the Tool for Problem-Solving in Universities; Uganda Martyrs Nkozi, Makerere and Nkumba Universities

ERIC Educational Resources Information Center

Bwegyeme, Jacinta; Munene, John C.

2015-01-01

The article presents an account of how action learning principles were implemented to alleviate complex problems in universities. It focuses on the registrars and administrators under the academic Registrar's department. The Marquardt model of action learning was used in combination with the constructivist theories of learning, namely community of…

Action Learning, Team Learning and Co-Operation in the Czech Republic

ERIC Educational Resources Information Center

Kubatova, Slava

2012-01-01

This account of practice presents two cases of the application of Action Learning (AL) communication methodology as described by Marquardt [2004. "Optimising the power of action learning". Mountain View, CA: Davies-Black Publishing]. The teams were Czech and international top management teams. The AL methodology was used to improve…

Perspective Taking Promotes Action Understanding and Learning

ERIC Educational Resources Information Center

Lozano, Sandra C.; Martin Hard, Bridgette; Tversky, Barbara

2006-01-01

People often learn actions by watching others. The authors propose and test the hypothesis that perspective taking promotes encoding a hierarchical representation of an actor's goals and subgoals-a key process for observational learning. Observers segmented videos of an object assembly task into coarse and fine action units. They described what…

Psychological Climates in Action Learning Sets: A Manager's Perspective

ERIC Educational Resources Information Center

Yeadon-Lee, Annie

2015-01-01

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…

From Movements to Actions: Two Mechanisms for Learning Action Sequences

ERIC Educational Resources Information Center

Endress, Ansgar D.; Wood, Justin N.

2011-01-01

When other individuals move, we interpret their movements as discrete, hierarchically-organized, goal-directed actions. However, the mechanisms that integrate visible movement features into actions are poorly understood. Here, we consider two sequence learning mechanisms--transitional probability-based (TP) and position-based encoding…

Action Learning Enabled Strategy Making

ERIC Educational Resources Information Center

Oliver, John

2008-01-01

Action learning encourages individual reflection, insightful questioning and assumption breaking that result in changes in attitude and behaviour. This learning process provides the potential to explore and solve complex organizational problems such as the question of how to develop a future business strategy. Existing literature on the process of…

Action Learning in ActionAid Nepal: A Case Study

ERIC Educational Resources Information Center

Lustig, Patricia; Rai, Deep Ranjani

2009-01-01

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.

Reflections on a Failed Action Learning Intervention

ERIC Educational Resources Information Center

Oliver, John

2008-01-01

This paper reflects on the failure of a recent action learning intervention with a UK television company. The aim of the project was to gain insight into the reasons why the viewing figures of their factual programming channels were in decline and to develop a new strategy enabled by the action learning methodology. Unfortunately, this…

Student Accounts of Action Learning on a DBA Programme: Learning Inaction

ERIC Educational Resources Information Center

Mendonça, Roger; Parker, Anthony; Udo, Uwem; Groves, Catherine

2015-01-01

This account of practice sets out the action learning experience of three doctoral students on the same Doctoral Programme in Business Administration at a UK university. It also include the sense-making of a fourth member of the set. It explores the tension between their area of work and their engagement in the action learning process and, in so…

Action Learning Drives the Emerald Academy

ERIC Educational Resources Information Center

Nalborczyk, Sarah; Sandelands, Luke

2012-01-01

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…

Action Learning as Relational Practice

ERIC Educational Resources Information Center

Boydell, Tom; Blantern, Chris

2007-01-01

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…

Action Learning and Executive Education: Achieving Credible Personal, Practitioner and Organisational Learning

ERIC Educational Resources Information Center

Stephens, Simon; Margey, Michael

2015-01-01

Action learning involves balancing the often conflicting forces between working knowledge and academic knowledge. This paper explores the experience of executive learners; academics and external contributors involved in action learning at the postgraduate level. The executive learners are members of cohorts on two masters programmes based in…

Learning to Internalize Action Dialogue

ERIC Educational Resources Information Center

Cotter, Teresa Ellen

2011-01-01

The purpose of this case study was to explore how participants of a communications workshop, "Action Dialogue," perceived their ability to engage in dialogue was improved and enhanced. The study was based on the following assumptions: (1) dialogue skills can be learned and people are able to learn these skills; (2) context and emotion influence…

Civil Society, Adult Learning and Action in India.

ERIC Educational Resources Information Center

Tandon, Rajesh

2000-01-01

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)

Action Learning: Towards a Framework in Inter-Organisational Settings

ERIC Educational Resources Information Center

Coughlan, Paul; Coghlan, David

2004-01-01

While much of the literature on action learning focuses on managers developing their capacity to learn and transform their own organizations, this article explores how action learning has been used in inter-organisational settings. Two settings are presented: the first an EU-funded management development programme called the National Action…

Influence of action-effect associations acquired by ideomotor learning on imitation.

PubMed

Bunlon, Frédérique; Marshall, Peter J; Quandt, Lorna C; Bouquet, Cedric A

2015-01-01

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.

Influence of Action-Effect Associations Acquired by Ideomotor Learning on Imitation

PubMed Central

Bunlon, Frédérique; Marshall, Peter J.; Quandt, Lorna C.; Bouquet, Cedric A.

2015-01-01

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

The Evidence for the Effectiveness of Action Learning

ERIC Educational Resources Information Center

Leonard, H. Skipton; Marquardt, Michael J.

2010-01-01

For the past 50 years, organizations and individuals around the world have reported success in their use of action learning programs to solve problems, develop leaders, build teams and transform their corporate cultures. However, very little rigorous research has been conducted to determine the effectiveness of action learning. The authors…

Action Learning: Images and Pathways. Professional Practices in Adult Education and Lifelong Learning Series.

ERIC Educational Resources Information Center

Dilworth, Robert L.; Willis, Verna J.

This book provides information and strategies on how adult educators can integrate action learning concepts in their teaching practice. The book defines action learning as going beyond the traditional idea of "learn by doing" and applies it to various organizational cultures and educational contexts. Chapter 1 introduces the origins of action…

Procuring a Sustainable Future: An Action Learning Approach to the Development and Modelling of Ethical and Sustainable Procurement Practices

ERIC Educational Resources Information Center

Boak, George; Watt, Peter; Gold, Jeff; Devins, David; Garvey, Robert

2016-01-01

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,…

Action Learning and Constructivist Grounded Theory: Powerfully Overlapping Fields of Practice

ERIC Educational Resources Information Center

Rand, Jane

2013-01-01

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…

Action Learning--An Experiential Tool for Solving Organizational Issues

ERIC Educational Resources Information Center

Kinsey, Sharon B.

2011-01-01

Action Learning can be effectively used in both large and small businesses and organizations by employees, stakeholders, or volunteers through this "learning by doing" approach to evaluate an issue or issues of importance to the organization. First developed in the 1940s, Action Learning has increasingly been used as a method to explore questions…

Statistical learning of action: the role of conditional probability.

PubMed

Meyer, Meredith; Baldwin, Dare

2011-12-01

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.

Renewing Professional Organizations and Action Learning

ERIC Educational Resources Information Center

Mullen, Carol A.

2011-01-01

This account concerns the renewal of established professional organizations though action learning. In order to revitalize one national organization, an executive group of leaders committed to co-leading and co-learning through a friendly, computer-supported governance structure. Manifestations of our work together were an accelerated…

Action learning sets in a nursing and midwifery practice learning context: a realistic evaluation.

PubMed

Machin, Alison I; Pearson, Pauline

2014-08-01

Action learning sets (ALS) are used widely for organisational and workforce development, including in nursing (Anderson and Thorpe, 2004; Pounder, 2009; Young et al., 2010). In the United Kingdom, a multi-faceted educational Pilot programme for new nurses and midwives was implemented to accelerate their clinical practice and leadership development (NHS Education Scotland, 2010). Action Learning Sets were provided for peer support and personal development. The Realistic Evaluation study reported in this paper explored issues of context, mechanism and outcome (Pawson and Tilley, 1997) influencing the action learning experiences of: programme participants (recently qualified nurses and midwives, from different practice settings); and programme supporters. A range of data were collected via: online questionnaires from 66 participants and 29 supporters; three focus groups, each comprising between eight and 10 programme participants; and one focus group with three action learning facilitators. The qualitative data pertaining to the ALS are presented in this paper. Thematic data analysis of context, mechanism and outcome configurations, generated five themes: creating and sustaining a collective learning environment; challenging constructively; collective support; the role of feedback; and effectiveness of ALS. Study outcomes suggest nursing and midwifery action learning should (a) be facilitated positively to improve participants' experience; (b) be renamed to avoid learning methodology confusion; and (c) be outcome focused to evidence impact on practice. Copyright © 2014 Elsevier Ltd. All rights reserved.

Relations between EFL Teachers' Formal Knowledge of Grammar and Their In-Action Mental Models of Children's Minds and Learning

ERIC Educational Resources Information Center

Haim, O.; Strauss, S.; Ravid, D.

2004-01-01

We studied the relations between English as a foreign language teachers' grammar knowledge and their in-action mental models (MMs) of children's minds and learning. The grammar knowledge we examined was English wh-constructions. A total of 74 teachers completed an assessment task and were classified to have deep, intermediate or shallow knowledge.…

A neural network model of causative actions.

PubMed

Lee-Hand, Jeremy; Knott, Alistair

2015-01-01

A common idea in models of action representation is that actions are represented in terms of their perceptual effects (see e.g., Prinz, 1997; Hommel et al., 2001; Sahin et al., 2007; Umiltà et al., 2008; Hommel, 2013). In this paper we extend existing models of effect-based action representations to account for a novel distinction. Some actions bring about effects that are independent events in their own right: for instance, if John smashes a cup, he brings about the event of the cup smashing. Other actions do not bring about such effects. For instance, if John grabs a cup, this action does not cause the cup to "do" anything: a grab action has well-defined perceptual effects, but these are not registered by the perceptual system that detects independent events involving external objects in the world. In our model, effect-based actions are implemented in several distinct neural circuits, which are organized into a hierarchy based on the complexity of their associated perceptual effects. The circuit at the top of this hierarchy is responsible for actions that bring about independently perceivable events. This circuit receives input from the perceptual module that recognizes arbitrary events taking place in the world, and learns movements that reliably cause such events. We assess our model against existing experimental observations about effect-based motor representations, and make some novel experimental predictions. We also consider the possibility that the "causative actions" circuit in our model can be identified with a motor pathway reported in other work, specializing in "functional" actions on manipulable tools (Bub et al., 2008; Binkofski and Buxbaum, 2013).

On the Nature of Problems in Action Learning

ERIC Educational Resources Information Center

Edmonstone, John

2014-01-01

The article aims to explore the nature of problems in action learning. Beginning with Revans' distinction between problems and puzzles, it draws parallels with the notion of wicked and tame problems. It offers four means of considering problems in action learning--in terms of the locus of a set's work; from the viewpoint of an…

Learning, Action and Solutions in Action Learning: Investigation of Facilitation Practice Using the Concept of Living Theories

ERIC Educational Resources Information Center

Sanyal, Chandana

2018-01-01

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…

Cognitive components underpinning the development of model-based learning.

PubMed

Potter, Tracey C S; Bryce, Nessa V; Hartley, Catherine A

2017-06-01

Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9-25, we examined whether the abilities to infer sequential regularities in the environment ("statistical learning"), maintain information in an active state ("working memory") and integrate distant concepts to solve problems ("fluid reasoning") predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Using Action Research and Action Learning for Entrepreneurial Network Capability Development

ERIC Educational Resources Information Center

McGrath, Helen; O'Toole, Thomas

2016-01-01

This paper applies an action research (AR) design and action learning (AL) approach to network capability development in an entrepreneurial context. Recent research suggests that networks are a viable strategy for the entrepreneurial firm to overcome the liabilities associated with newness and smallness. However, a gap emerges as few, if any,…

Reconciling Market Requirements and Operations Resources: An Opportunity for Action Learning

ERIC Educational Resources Information Center

Coughlan, Paul; Coghlan, David

2009-01-01

This article brings together the fields of action learning and operations strategy. It presents a case of action learning focused on strategic operations improvement in the extended manufacturing enterprise. As the third article in the set of explorations in this journal within the fields of action learning, operations strategy and collaborative…

Hybrid generative-discriminative human action recognition by combining spatiotemporal words with supervised topic models

NASA Astrophysics Data System (ADS)

Sun, Hao; Wang, Cheng; Wang, Boliang

2011-02-01

We present a hybrid generative-discriminative learning method for human action recognition from video sequences. Our model combines a bag-of-words component with supervised latent topic models. A video sequence is represented as a collection of spatiotemporal words by extracting space-time interest points and describing these points using both shape and motion cues. The supervised latent Dirichlet allocation (sLDA) topic model, which employs discriminative learning using labeled data under a generative framework, is introduced to discover the latent topic structure that is most relevant to action categorization. The proposed algorithm retains most of the desirable properties of generative learning while increasing the classification performance though a discriminative setting. It has also been extended to exploit both labeled data and unlabeled data to learn human actions under a unified framework. We test our algorithm on three challenging data sets: the KTH human motion data set, the Weizmann human action data set, and a ballet data set. Our results are either comparable to or significantly better than previously published results on these data sets and reflect the promise of hybrid generative-discriminative learning approaches.

Place-Based Learning: Action Learning in MA Program for Educational Practitioners

ERIC Educational Resources Information Center

Glassner, Amnon; Eran-Zoran, Yael

2016-01-01

The study presents a new pedagogical idea and practice for educational practitioners. The practice was developed as a workshop of MA program in order to change and expand the meaning of education for the wellbeing of the community. The "place-based learning" workshop combined action learning (AL) with project-based learning (PBL). The…

Action Learning: Developing Leaders and Supporting Change in a Healthcare Context

ERIC Educational Resources Information Center

Doyle, Louise

2014-01-01

This account of practice outlines how action learning was used as the key component of a leadership development initiative for managers in an acute hospital setting. It explains how the initiative was conceived, why action learning was chosen and how action learning principles were incorporated. Insights into the outcomes and considerations for…

Recognizing human actions by learning and matching shape-motion prototype trees.

PubMed

Jiang, Zhuolin; Lin, Zhe; Davis, Larry S

2012-03-01

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.

Entrepreneurial Learning through Action: A Case Study of the Six-Squared Program

ERIC Educational Resources Information Center

Pittaway, Luke; Missing, Caroline; Hudson, Nigel; Maragh, Dean

2009-01-01

This paper explores the role of "action" in entrepreneurial learning and illustrates how programs designed to support action learning can enhance management development in entrepreneurial businesses. The paper begins by exploring action learning and the way "action" is conceived in different types of program. In the second part, the paper details…

How actions shape perception: learning action-outcome relations and predicting sensory outcomes promote audio-visual temporal binding

PubMed Central

Desantis, Andrea; Haggard, Patrick

2016-01-01

To maintain a temporally-unified representation of audio and visual features of objects in our environment, the brain recalibrates audio-visual simultaneity. This process allows adjustment for both differences in time of transmission and time for processing of audio and visual signals. In four experiments, we show that the cognitive processes for controlling instrumental actions also have strong influence on audio-visual recalibration. Participants learned that right and left hand button-presses each produced a specific audio-visual stimulus. Following one action the audio preceded the visual stimulus, while for the other action audio lagged vision. In a subsequent test phase, left and right button-press generated either the same audio-visual stimulus as learned initially, or the pair associated with the other action. We observed recalibration of simultaneity only for previously-learned audio-visual outcomes. Thus, learning an action-outcome relation promotes temporal grouping of the audio and visual events within the outcome pair, contributing to the creation of a temporally unified multisensory object. This suggests that learning action-outcome relations and the prediction of perceptual outcomes can provide an integrative temporal structure for our experiences of external events. PMID:27982063

How actions shape perception: learning action-outcome relations and predicting sensory outcomes promote audio-visual temporal binding.

PubMed

Desantis, Andrea; Haggard, Patrick

2016-12-16

To maintain a temporally-unified representation of audio and visual features of objects in our environment, the brain recalibrates audio-visual simultaneity. This process allows adjustment for both differences in time of transmission and time for processing of audio and visual signals. In four experiments, we show that the cognitive processes for controlling instrumental actions also have strong influence on audio-visual recalibration. Participants learned that right and left hand button-presses each produced a specific audio-visual stimulus. Following one action the audio preceded the visual stimulus, while for the other action audio lagged vision. In a subsequent test phase, left and right button-press generated either the same audio-visual stimulus as learned initially, or the pair associated with the other action. We observed recalibration of simultaneity only for previously-learned audio-visual outcomes. Thus, learning an action-outcome relation promotes temporal grouping of the audio and visual events within the outcome pair, contributing to the creation of a temporally unified multisensory object. This suggests that learning action-outcome relations and the prediction of perceptual outcomes can provide an integrative temporal structure for our experiences of external events.

Cognitive Components Underpinning the Development of Model-Based Learning

PubMed Central

Potter, Tracey C.S.; Bryce, Nessa V.; Hartley, Catherine A.

2016-01-01

Reinforcement learning theory distinguishes “model-free” learning, which fosters reflexive repetition of previously rewarded actions, from “model-based” learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9–25, we examined whether the abilities to infer sequential regularities in the environment (“statistical learning”), maintain information in an active state (“working memory”) and integrate distant concepts to solve problems (“fluid reasoning”) predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. PMID:27825732

Collaborative action research: implementation of cooperative learning.

PubMed

Smith-Stoner, Marilyn; Molle, Mary E

2010-06-01

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.

Business Action Learning Tasmania (BALT)--An Account of Practice

ERIC Educational Resources Information Center

Cother, Genevieve; Cother, Robert F.

2017-01-01

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…

Attitudes Regarding Action Learning: Undergraduate vs. Graduate Business Students

ERIC Educational Resources Information Center

Rosenstein, Alvin; Ashley, Allan; Gupta, Rakesh; Ulin, Kristin

2008-01-01

Previous research in our Action Learning Program demonstrated that although undergraduates preferred the Action Learning mode to the traditional lecture and discussion mode of instruction, they missed the familiar structure of the more traditional pedagogy. Consequently increased structure was implemented in both an undergraduate and graduate…

Action Learning: How Learning Transfers from Entrepreneurs to Small Firms

ERIC Educational Resources Information Center

Jones, Karen; Sambrook, Sally A.; Pittaway, Luke; Henley, Andrew; Norbury, Heather

2014-01-01

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…

A Framework for the Ethical Practice of Action Learning

ERIC Educational Resources Information Center

Johnson, Craig

2010-01-01

By tradition the action learning community has encouraged an eclectic view of practice. This involves a number of different permutations around a kernel of nebulous ideas. However, the disadvantages of such an open philosophy have never been considered. In particular consumer protection against inauthentic action learning experiences has been…

Action Learning in Virtual Higher Education: Applying Leadership Theory

ERIC Educational Resources Information Center

Curtin, Joseph

2016-01-01

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,…

Learning reliable manipulation strategies without initial physical models

NASA Technical Reports Server (NTRS)

Christiansen, Alan D.; Mason, Matthew T.; Mitchell, Tom M.

1990-01-01

A description is given of a robot, possessing limited sensory and effectory capabilities but no initial model of the effects of its actions on the world, that acquires such a model through exploration, practice, and observation. By acquiring an increasingly correct model of its actions, it generates increasingly successful plans to achieve its goals. In an apparently nondeterministic world, achieving reliability requires the identification of reliable actions and a preference for using such actions. Furthermore, by selecting its training actions carefully, the robot can significantly improve its learning rate.

Action Learning. A Guide for Professional, Management and Educational Development. Second Edition.

ERIC Educational Resources Information Center

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…

Can model-free reinforcement learning explain deontological moral judgments?

PubMed

Ayars, Alisabeth

2016-05-01

Dual-systems frameworks propose that moral judgments are derived from both an immediate emotional response, and controlled/rational cognition. Recently Cushman (2013) proposed a new dual-system theory based on model-free and model-based reinforcement learning. Model-free learning attaches values to actions based on their history of reward and punishment, and explains some deontological, non-utilitarian judgments. Model-based learning involves the construction of a causal model of the world and allows for far-sighted planning; this form of learning fits well with utilitarian considerations that seek to maximize certain kinds of outcomes. I present three concerns regarding the use of model-free reinforcement learning to explain deontological moral judgment. First, many actions that humans find aversive from model-free learning are not judged to be morally wrong. Moral judgment must require something in addition to model-free learning. Second, there is a dearth of evidence for central predictions of the reinforcement account-e.g., that people with different reinforcement histories will, all else equal, make different moral judgments. Finally, to account for the effect of intention within the framework requires certain assumptions which lack support. These challenges are reasonable foci for future empirical/theoretical work on the model-free/model-based framework. Copyright © 2016 Elsevier B.V. All rights reserved.

What Am I to Action Learning and What Is Action Learning to Me?

ERIC Educational Resources Information Center

Doherty, Daniel

2016-01-01

This account of practice charts one organisation development practitioner's experience of the influence of action learning (AL) at various points in his career, from the early 1970s to the present day. It explores the impact of AL upon his practice over the years, chronicling various episodes which had strongest impact. It contrasts AL as it was…

Representation Learning of Logic Words by an RNN: From Word Sequences to Robot Actions.

PubMed

Yamada, Tatsuro; Murata, Shingo; Arie, Hiroaki; Ogata, Tetsuya

2017-01-01

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 unstable space of the network's dynamical system.

Inspecting Cases against Revans' "Gold Standard" of Action Learning

ERIC Educational Resources Information Center

Willis, Verna J.

2004-01-01

A purposive sampling and analysis of ten case histories of action learning in the US suggests that applications tend to be partial, hierarchical, and leader controlled, thus running counter in several significant ways to the gold standard of Revans' action learning theory and egalitarian rules of engagement. Using critical markers to inspect the…

A neural model of hierarchical reinforcement learning.

PubMed

Rasmussen, Daniel; Voelker, Aaron; Eliasmith, Chris

2017-01-01

We develop a novel, biologically detailed neural model of reinforcement learning (RL) processes in the brain. This model incorporates a broad range of biological features that pose challenges to neural RL, such as temporally extended action sequences, continuous environments involving unknown time delays, and noisy/imprecise computations. Most significantly, we expand the model into the realm of hierarchical reinforcement learning (HRL), which divides the RL process into a hierarchy of actions at different levels of abstraction. Here we implement all the major components of HRL in a neural model that captures a variety of known anatomical and physiological properties of the brain. We demonstrate the performance of the model in a range of different environments, in order to emphasize the aim of understanding the brain's general reinforcement learning ability. These results show that the model compares well to previous modelling work and demonstrates improved performance as a result of its hierarchical ability. We also show that the model's behaviour is consistent with available data on human hierarchical RL, and generate several novel predictions.

Does Lean Production Sacrifice Learning in a Manufacturing Environment? An Action Learning Case Study.

ERIC Educational Resources Information Center

Scott, Fiona M.; Butler, Jim; Edwards, John

2001-01-01

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…

Learning Computer Science: Perceptions, Actions and Roles

ERIC Educational Resources Information Center

Berglund, Anders; Eckerdal, Anna; Pears, Arnold; East, Philip; Kinnunen, Paivi; Malmi, Lauri; McCartney, Robert; Mostrom, Jan-Erik; Murphy, Laurie; Ratcliffe, Mark; Schulte, Carsten; Simon, Beth; Stamouli, Ioanna; Thomas, Lynda

2009-01-01

This phenomenographic study opens the classroom door to investigate teachers' experiences of students learning difficult computing topics. Three distinct themes are identified and analysed. "Why" do students succeed or fail to learn these concepts? "What" actions do teachers perceive will ameliorate the difficulties facing…

The Impact of Action Learning Experience on Reflective Practice

ERIC Educational Resources Information Center

Harris, Nicole S.

2012-01-01

This case study examines the changes that occur with respect to reflective practices as a result of participating in an action learning group through the identification of aspects/activities of action learning that contribute to such changes and the impact these aspects/activities had on the program participants at a department of the federal…

Franchisees in Crisis: Using Action Learning to Self-Organise

ERIC Educational Resources Information Center

O'Donoghue, Carol

2011-01-01

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…

Action Learning--A Process Which Supports Organisational Change Initiatives

ERIC Educational Resources Information Center

Joyce, Pauline

2012-01-01

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…

Action Learning. Symposium 21. [Concurrent Symposium Session at AHRD Annual Conference, 2000.

ERIC Educational Resources Information Center

2000

This document contains three papers from a symposium on action learning that was conducted as part of a conference on human resource development (HRD). "Searching for Meaning in Complex Action Learning Data: What Environments, Acts, and Words Reveal" (Verna J. Willis) analyzes complex action learning documents produced as course…

Learning about Learning: Action Learning in Times of Organisational Change

ERIC Educational Resources Information Center

Hill, Robyn

2009-01-01

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…

A neural model of hierarchical reinforcement learning

PubMed Central

Rasmussen, Daniel; Eliasmith, Chris

2017-01-01

We develop a novel, biologically detailed neural model of reinforcement learning (RL) processes in the brain. This model incorporates a broad range of biological features that pose challenges to neural RL, such as temporally extended action sequences, continuous environments involving unknown time delays, and noisy/imprecise computations. Most significantly, we expand the model into the realm of hierarchical reinforcement learning (HRL), which divides the RL process into a hierarchy of actions at different levels of abstraction. Here we implement all the major components of HRL in a neural model that captures a variety of known anatomical and physiological properties of the brain. We demonstrate the performance of the model in a range of different environments, in order to emphasize the aim of understanding the brain’s general reinforcement learning ability. These results show that the model compares well to previous modelling work and demonstrates improved performance as a result of its hierarchical ability. We also show that the model’s behaviour is consistent with available data on human hierarchical RL, and generate several novel predictions. PMID:28683111

Action Learning: Developing Critical Competencies for Knowledge Era Workers

ERIC Educational Resources Information Center

Robinson, Greg

2005-01-01

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,…

Action Learning in an SME: Appetite Comes with Eating

ERIC Educational Resources Information Center

Hauser, Bernhard

2009-01-01

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…

Predictive Movements and Human Reinforcement Learning of Sequential Action

ERIC Educational Resources Information Center

de Kleijn, Roy; Kachergis, George; Hommel, Bernhard

2018-01-01

Sequential action makes up the bulk of human daily activity, and yet much remains unknown about how people learn such actions. In one motor learning paradigm, the serial reaction time (SRT) task, people are taught a consistent sequence of button presses by cueing them with the next target response. However, the SRT task only records keypress…

Work-based learning: a leadership development example from an action research study of shared governance implementation.

PubMed

Williamson, Tracey

2005-11-01

An empowering action research study was undertaken to evaluate and strengthen the implementation of shared governance. One aim was to identify factors that acted as aids or barriers to effective decision-making by clinical leaders. As a work-based learning approach, action research was expected to lead to integration of learning into practice by researcher and participants alike. Shared governance replaces traditional hierarchies and requires and develops clinical leaders. Strategies are needed to maximize learning from introduction of such initiatives at the individual, group and organizational level. Participant-observations and interviews were undertaken with shared governance council members from one model in north-west England. Leadership skills and knowledge and shared governance practices were significantly enhanced. Preparation for council roles was considered inadequate. Increased structured time for reflection and action planning was indicated. Implementation of shared governance has succeeded in developing leadership capacity. Evaluation findings have led to improvements in the overall shared governance model. Action research has been found to have great utility at optimizing work-based learning. Nurse Managers need to develop their coaching and facilitating skills and recognize there is no "quick fix" for developing clinical leaders. Implications include the need to support learners in identifying and implementing changes arising from work-based learning activities, the significant resource implications and the need to optimize the organizational climate if work-based learning approaches to leadership and management development are to succeed.

History and Culture of Alara--The Action Learning and Action Research Association

ERIC Educational Resources Information Center

Zuber-Skerritt, Ortrun; Passfield, Ron

2016-01-01

As co-founders of the Action Learning and Action Research Association (ALARA), we tell the story of this international network organisation through our personal experience. Our history traces the evolution of ALARA from origins at the first World Congress in 1990 in Brisbane, Australia, through development over two and a half decades, to its…

Action learning: an effective way to improve cancer-related pain management.

PubMed

Kasasbeh, Mohammed Ali Mohammed; McCabe, Catherine; Payne, Sheila

2017-11-01

To evaluate the efficacy of action learning for improving cancer related pain management in the acute healthcare settings. Despite the prevalent use of action learning in private, public, clinical and non-clinical settings, no studies were found in the literature that either examined cancer pain management or used action learning as an approach to improve patient care in acute healthcare settings. An intervention pre - posttest design was adopted using an action learning programme (ALPs) as the intervention. Healthcare professionals' knowledge, attitudes and practice were assessed and evaluated before and after the implementation of the six-month ALPs. A pre and post audit and survey were conducted for data collection. The data were collected from the entire population of 170 healthcare professionals in one healthcare organisation. The management of cancer related pain improved significantly following the intervention. Significant improvement were also seen in healthcare professionals' knowledge, attitudes with improved cancer related pain management as a consequence of this. Despite many organisational challenges to practice development and collaborative working in healthcare settings there is evidence that action learning can achieve positive outcomes for improving CRP and supporting collaborative working. Action learning needs to be considered as a strategy for achieving high quality standards. © 2016 John Wiley & Sons Ltd.

Service Learning: An Action Oriented Program Evaluation

ERIC Educational Resources Information Center

Kelley, George

2013-01-01

Service learning is an academic discipline that provides students with "hands-on" opportunities for developing skills in real-world, community-based projects that serve and benefit community members. This dissertation reflects an action-oriented process for improving the quality of the Service Learning Program at City University of…

Joint Facial Action Unit Detection and Feature Fusion: A Multi-conditional Learning Approach.

PubMed

Eleftheriadis, Stefanos; Rudovic, Ognjen; Pantic, Maja

2016-10-05

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.

From action to abstraction: Using the hands to learn math

PubMed Central

Novack, Miriam A.; Congdon, Eliza L.; Hemani-Lopez, Naureen; Goldin-Meadow, Susan

2014-01-01

Previous research has shown that children benefit from gesturing during math instruction. Here we ask whether gesturing promotes learning because it is itself a physical action, or because it uses physical action to represent abstract ideas. To address this question, we taught third-grade children a strategy for solving mathematical equivalence problems that was instantiated in one of three ways: (1) in the physical action children performed on objects, (2) in a concrete gesture miming that action, or (3) in an abstract gesture. All three types of hand movements helped children learn how to solve the problems on which they were trained. However, only gesture led to success on problems that required generalizing the knowledge gained. The results provide the first evidence that gesture promotes transfer of knowledge better than action, and suggest that the beneficial effects gesture has on learning may reside in the features that differentiate it from action. PMID:24503873

A Biologically Inspired Computational Model of Basal Ganglia in Action Selection.

PubMed

Baston, Chiara; Ursino, Mauro

2015-01-01

The basal ganglia (BG) are a subcortical structure implicated in action selection. The aim of this work is to present a new cognitive neuroscience model of the BG, which aspires to represent a parsimonious balance between simplicity and completeness. The model includes the 3 main pathways operating in the BG circuitry, that is, the direct (Go), indirect (NoGo), and hyperdirect pathways. The main original aspects, compared with previous models, are the use of a two-term Hebb rule to train synapses in the striatum, based exclusively on neuronal activity changes caused by dopamine peaks or dips, and the role of the cholinergic interneurons (affected by dopamine themselves) during learning. Some examples are displayed, concerning a few paradigmatic cases: action selection in basal conditions, action selection in the presence of a strong conflict (where the role of the hyperdirect pathway emerges), synapse changes induced by phasic dopamine, and learning new actions based on a previous history of rewards and punishments. Finally, some simulations show model working in conditions of altered dopamine levels, to illustrate pathological cases (dopamine depletion in parkinsonian subjects or dopamine hypermedication). Due to its parsimonious approach, the model may represent a straightforward tool to analyze BG functionality in behavioral experiments.

A Biologically Inspired Computational Model of Basal Ganglia in Action Selection

PubMed Central

Baston, Chiara

2015-01-01

The basal ganglia (BG) are a subcortical structure implicated in action selection. The aim of this work is to present a new cognitive neuroscience model of the BG, which aspires to represent a parsimonious balance between simplicity and completeness. The model includes the 3 main pathways operating in the BG circuitry, that is, the direct (Go), indirect (NoGo), and hyperdirect pathways. The main original aspects, compared with previous models, are the use of a two-term Hebb rule to train synapses in the striatum, based exclusively on neuronal activity changes caused by dopamine peaks or dips, and the role of the cholinergic interneurons (affected by dopamine themselves) during learning. Some examples are displayed, concerning a few paradigmatic cases: action selection in basal conditions, action selection in the presence of a strong conflict (where the role of the hyperdirect pathway emerges), synapse changes induced by phasic dopamine, and learning new actions based on a previous history of rewards and punishments. Finally, some simulations show model working in conditions of altered dopamine levels, to illustrate pathological cases (dopamine depletion in parkinsonian subjects or dopamine hypermedication). Due to its parsimonious approach, the model may represent a straightforward tool to analyze BG functionality in behavioral experiments. PMID:26640481

A Collaborative Action Research Approach to Professional Learning

ERIC Educational Resources Information Center

Bleicher, Robert E.

2014-01-01

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)…

Learning to use working memory: a reinforcement learning gating model of rule acquisition in rats

PubMed Central

Lloyd, Kevin; Becker, Nadine; Jones, Matthew W.; Bogacz, Rafal

2012-01-01

Learning to form appropriate, task-relevant working memory representations is a complex process central to cognition. Gating models frame working memory as a collection of past observations and use reinforcement learning (RL) to solve the problem of when to update these observations. Investigation of how gating models relate to brain and behavior remains, however, at an early stage. The current study sought to explore the ability of simple RL gating models to replicate rule learning behavior in rats. Rats were trained in a maze-based spatial learning task that required animals to make trial-by-trial choices contingent upon their previous experience. Using an abstract version of this task, we tested the ability of two gating algorithms, one based on the Actor-Critic and the other on the State-Action-Reward-State-Action (SARSA) algorithm, to generate behavior consistent with the rats'. Both models produced rule-acquisition behavior consistent with the experimental data, though only the SARSA gating model mirrored faster learning following rule reversal. We also found that both gating models learned multiple strategies in solving the initial task, a property which highlights the multi-agent nature of such models and which is of importance in considering the neural basis of individual differences in behavior. PMID:23115551

Agroecology Education: Action-Oriented Learning and Research

ERIC Educational Resources Information Center

Lieblein, Geir; Breland, Tor Arvid; Francis, Charles; Ostergaard, Edvin

2012-01-01

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…

Learning Organization Models and Their Application to the U.S. Army

DTIC Science & Technology

2016-06-01

Watkins and Marsick’s action imperatives. While different, these models agree on several components including reduced bureaucracy and hierarchy, a shared...David Garvin’s building blocks of a learning organization, Michael Marquardt’s systems-linked learning organization, and Karen Watkins ’ and Victoria...Organization (Marquardt, 1996) ....................................5 Learning Organization Action Imperatives (Marsick and Watkins , 1999

Action Learning in Postgraduate Executive Management Education: An Account of Practice

ERIC Educational Resources Information Center

Ruane, Meadbh

2016-01-01

The merits of action learning as a change tool and enabler of deep learning are well recognised. However, there is a gap in the literature of participants' stories regarding their experiences on accredited postgraduate executive programmes underpinned by an action learning philosophy. The following account of practice addresses this gap and…

Predictive representations can link model-based reinforcement learning to model-free mechanisms.

PubMed

Russek, Evan M; Momennejad, Ida; Botvinick, Matthew M; Gershman, Samuel J; Daw, Nathaniel D

2017-09-01

Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation.

Predictive representations can link model-based reinforcement learning to model-free mechanisms

PubMed Central

Botvinick, Matthew M.

2017-01-01

Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation. PMID:28945743

Designing and Implementing Collaborative Improvement in the Extended Manufacturing Enterprise: Action Learning and Action Research (ALAR) in CO-IMPROVE

ERIC Educational Resources Information Center

Coghlan, David; Coughlan, Paul

2006-01-01

Purpose: The purpose of this article is to provide a design and implementation framework for ALAR (action learning action research) programme which aims to address collaborative improvement in the extended manufacturing enterprise. Design/methodology/approach: This article demonstrates the design of a programme in which action learning and action…

Assessing the Impact of Learning Environments on Students' Approaches to Learning: Comparing Conventional and Action Learning Designs

ERIC Educational Resources Information Center

Wilson, Keithia; Fowler, Jane

2005-01-01

This study investigated whether students' approaches to learning were influenced by the design of university courses. Pre- and post-evaluations of the approaches to learning of the same group of students concurrently enrolled in a conventional course (lectures and tutorials) and an action learning-based course (project work, learning groups) were…

The Alchemy of Action Learning

ERIC Educational Resources Information Center

West, Penny; Choueke, Richard

2003-01-01

This paper examines the authors' experiences as action learning set facilitators within a public sector organisation undergoing change. Our objectives were to assist in the identification of internal and external drivers for change and to work with the set to explore how people's roles and responsibilities might be enhanced and developed in a…

A unified probabilistic framework for spontaneous facial action modeling and understanding.

PubMed

Tong, Yan; Chen, Jixu; Ji, Qiang

2010-02-01

Facial expression is a natural and powerful means of human communication. Recognizing spontaneous facial actions, however, is very challenging due to subtle facial deformation, frequent head movements, and ambiguous and uncertain facial motion measurements. Because of these challenges, current research in facial expression recognition is limited to posed expressions and often in frontal view. A spontaneous facial expression is characterized by rigid head movements and nonrigid facial muscular movements. More importantly, it is the coherent and consistent spatiotemporal interactions among rigid and nonrigid facial motions that produce a meaningful facial expression. Recognizing this fact, we introduce a unified probabilistic facial action model based on the Dynamic Bayesian network (DBN) to simultaneously and coherently represent rigid and nonrigid facial motions, their spatiotemporal dependencies, and their image measurements. Advanced machine learning methods are introduced to learn the model based on both training data and subjective prior knowledge. Given the model and the measurements of facial motions, facial action recognition is accomplished through probabilistic inference by systematically integrating visual measurements with the facial action model. Experiments show that compared to the state-of-the-art techniques, the proposed system yields significant improvements in recognizing both rigid and nonrigid facial motions, especially for spontaneous facial expressions.

Representation Learning of Logic Words by an RNN: From Word Sequences to Robot Actions

PubMed Central

Yamada, Tatsuro; Murata, Shingo; Arie, Hiroaki; Ogata, Tetsuya

2017-01-01

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 unstable space of

Culture and Commitment: The Key to the Creation of an Action Learning Organization

ERIC Educational Resources Information Center

Hind, Matthew; Koenigsberger, John

2007-01-01

This article examines the introduction and practice of action learning into a highly volatile, commercial environment. During nine years of action learning projects, the impact on individuals, the action learning sets into which they were formed, the organization and its structure and the organizational culture were evaluated. The article…

Model-Based and Model-Free Pavlovian Reward Learning: Revaluation, Revision and Revelation

PubMed Central

Dayan, Peter; Berridge, Kent C.

2014-01-01

Evidence supports at least two methods for learning about reward and punishment and making predictions for guiding actions. One method, called model-free, progressively acquires cached estimates of the long-run values of circumstances and actions from retrospective experience. The other method, called model-based, uses representations of the environment, expectations and prospective calculations to make cognitive predictions of future value. Extensive attention has been paid to both methods in computational analyses of instrumental learning. By contrast, although a full computational analysis has been lacking, Pavlovian learning and prediction has typically been presumed to be solely model-free. Here, we revise that presumption and review compelling evidence from Pavlovian revaluation experiments showing that Pavlovian predictions can involve their own form of model-based evaluation. In model-based Pavlovian evaluation, prevailing states of the body and brain influence value computations, and thereby produce powerful incentive motivations that can sometimes be quite new. We consider the consequences of this revised Pavlovian view for the computational landscape of prediction, response and choice. We also revisit differences between Pavlovian and instrumental learning in the control of incentive motivation. PMID:24647659

Model-based and model-free Pavlovian reward learning: revaluation, revision, and revelation.

PubMed

Dayan, Peter; Berridge, Kent C

2014-06-01

Evidence supports at least two methods for learning about reward and punishment and making predictions for guiding actions. One method, called model-free, progressively acquires cached estimates of the long-run values of circumstances and actions from retrospective experience. The other method, called model-based, uses representations of the environment, expectations, and prospective calculations to make cognitive predictions of future value. Extensive attention has been paid to both methods in computational analyses of instrumental learning. By contrast, although a full computational analysis has been lacking, Pavlovian learning and prediction has typically been presumed to be solely model-free. Here, we revise that presumption and review compelling evidence from Pavlovian revaluation experiments showing that Pavlovian predictions can involve their own form of model-based evaluation. In model-based Pavlovian evaluation, prevailing states of the body and brain influence value computations, and thereby produce powerful incentive motivations that can sometimes be quite new. We consider the consequences of this revised Pavlovian view for the computational landscape of prediction, response, and choice. We also revisit differences between Pavlovian and instrumental learning in the control of incentive motivation.

Trial-and-error copying of demonstrated actions reveals how fledglings learn to ‘imitate’ their mothers

PubMed Central

Lotem, Arnon

2017-01-01

Understanding how humans and other animals learn to perform an act from seeing it done has been a major challenge in the study of social learning. To determine whether this ability is based on ‘true imitation’, many studies have applied the two-action experimental paradigm, examining whether subjects learn to perform the specific action demonstrated to them. Here, we show that the insights gained from animals' success in two-action experiments may be limited, and that a better understanding is achieved by monitoring subjects' entire behavioural repertoire. Hand-reared house sparrows that followed a model of a mother demonstrator were successful in learning to find seeds hidden under a leaf, using the action demonstrated by the mother (either pushing the leaf or pecking it). However, they also produced behaviours that had not been demonstrated but were nevertheless related to the demonstrated act. This finding suggests that while the learners were clearly influenced by the demonstrator, they did not accurately imitate her. Rather, they used their own behavioural repertoire, gradually fitting it to the demonstrated task solution through trial and error. This process is consistent with recent views on how animals learn to imitate, and may contribute to a unified process-level analysis of social learning mechanisms. PMID:28228516

Learning, attentional control and action video games

PubMed Central

Green, C.S.; Bavelier, D.

2012-01-01

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

Efficient model learning methods for actor-critic control.

PubMed

Grondman, Ivo; Vaandrager, Maarten; Buşoniu, Lucian; Babuska, Robert; Schuitema, Erik

2012-06-01

We propose two new actor-critic algorithms for reinforcement learning. Both algorithms use local linear regression (LLR) to learn approximations of the functions involved. A crucial feature of the algorithms is that they also learn a process model, and this, in combination with LLR, provides an efficient policy update for faster learning. The first algorithm uses a novel model-based update rule for the actor parameters. The second algorithm does not use an explicit actor but learns a reference model which represents a desired behavior, from which desired control actions can be calculated using the inverse of the learned process model. The two novel methods and a standard actor-critic algorithm are applied to the pendulum swing-up problem, in which the novel methods achieve faster learning than the standard algorithm.

Prefrontal involvement in imitation learning of hand actions: effects of practice and expertise.

PubMed

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

2007-10-01

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.

Cross-Situational Learning with Bayesian Generative Models for Multimodal Category and Word Learning in Robots

PubMed Central

Taniguchi, Akira; Taniguchi, Tadahiro; Cangelosi, Angelo

2017-01-01

In this paper, we propose a Bayesian generative model that can form multiple categories based on each sensory-channel and can associate words with any of the four sensory-channels (action, position, object, and color). This paper focuses on cross-situational learning using the co-occurrence between words and information of sensory-channels in complex situations rather than conventional situations of cross-situational learning. We conducted a learning scenario using a simulator and a real humanoid iCub robot. In the scenario, a human tutor provided a sentence that describes an object of visual attention and an accompanying action to the robot. The scenario was set as follows: the number of words per sensory-channel was three or four, and the number of trials for learning was 20 and 40 for the simulator and 25 and 40 for the real robot. The experimental results showed that the proposed method was able to estimate the multiple categorizations and to learn the relationships between multiple sensory-channels and words accurately. In addition, we conducted an action generation task and an action description task based on word meanings learned in the cross-situational learning scenario. The experimental results showed that the robot could successfully use the word meanings learned by using the proposed method. PMID:29311888

The Soft-Skills Learning Triangle: A Learning Model for Supporting Online Management & Leadership Development

ERIC Educational Resources Information Center

Adams, Jean

2010-01-01

The purpose of this paper is to present the Soft-skills Learning Triangle (SLT)--a model created to help coaches, mentors, and educators understand how web-technologies can be used to support management learning and soft-skills development. SLT emerged as part of a larger action-learning research project--the NewMindsets Management Education…

Leadership Development through Virtual Action Learning: An Evaluation

ERIC Educational Resources Information Center

Aspinwall, Kath; Pedler, Mike; Radcliff, Phil

2018-01-01

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…

Spontaneous Action and Transformative Learning: Empirical Investigations and Pragmatist Reflections

ERIC Educational Resources Information Center

Nohl, Arnd-Michael

2009-01-01

Whereas present theories of transformative learning tend to focus on the rational and reflective actor, in this article it is suggested that spontaneous action may play a decisive role in transformative learning too. In the spontaneity of action, novelty finds its way into life, gains momentum, is respected by others and reflected by the actor.…

Obstinate Actions-Oriented Behaviour towards Applying Theoractive Learning: An Ontology of Educational Learning and Leadership Theories in Practice

ERIC Educational Resources Information Center

Rajbhandari, Mani Man Singh

2018-01-01

Obstinate actions-oriented behaviour is the study of learning and practicing behaviour theoractively, which is acquired from the content based, process based learning and spawning critical reflexivity to the learnt theoretical phenomena into practical actions. Obstinate actions-oriented behaviour is a multi-faceted behaviour that is generally…

Altered Connectivity and Action Model Formation in Autism Is Autism

PubMed Central

Mostofsky, Stewart H.; Ewen, Joshua B.

2014-01-01

Internal action models refer to sensory-motor programs that form the brain basis for a wide range of skilled behavior and for understanding others’ actions. Development of these action models, particularly those reliant on visual cues from the external world, depends on connectivity between distant brain regions. Studies of children with autism reveal anomalous patterns of motor learning and impaired execution of skilled motor gestures. These findings robustly correlate with measures of social and communicative function, suggesting that anomalous action model formation may contribute to impaired development of social and communicative (as well as motor) capacity in autism. Examination of the pattern of behavioral findings, as well as convergent data from neuroimaging techniques, further suggests that autism-associated action model formation may be related to abnormalities in neural connectivity, particularly decreased function of long-range connections. This line of study can lead to important advances in understanding the neural basis of autism and, more critically, can be used to guide effective therapies targeted at improving social, communicative, and motor function. PMID:21467306

Action Learning for Strategic Innovation in Mature Organizations: Key Cognitive, Design and Contextual Considerations

ERIC Educational Resources Information Center

Kuhn, Jeffrey S.; Marsick, Victoria J.

2005-01-01

This article lays out a model of action learning for catalyzing strategic innovation in mature organizations that are faced with a new competitive playing field. Central to this model is the development of a set of sophisticated cognitive capabilities--sensemaking, strategic thinking, critical thinking, divergent thinking, conceptual capacity and…

Comparison as a Universal Learning Action

ERIC Educational Resources Information Center

Merkulova, T. V.

2016-01-01

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…

Action Learning: Potential for Inner City Youth

ERIC Educational Resources Information Center

Epps, Edgar G.

1974-01-01

Working class and minority participation in action-learning poses potential problems likely to be overlooked by program planners. This presentation reveals the trouble spots and offers constructive suggestions. (Editor)

Action-outcome learning and prediction shape the window of simultaneity of audiovisual outcomes.

PubMed

Desantis, Andrea; Haggard, Patrick

2016-08-01

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.

Using Collaborative Action Learning Projects to Increase the Impact of Management Development

ERIC Educational Resources Information Center

Lyso, Ingunn Hybertsen; Mjoen, Kristian; Levin, Morten

2011-01-01

This article aims to contribute to the field of human resource development by exploring the conditions that influence the organizational impact of action learning projects. Many organizations use such projects as an integral part of their management development programs. Past research on action learning projects has shown how balancing action and…

Permaculture in higher education: Teaching sustainability through action learning

NASA Astrophysics Data System (ADS)

Battisti, Bryce Thomas

This is a case study of the use of Action Learning (AL) theory to teach and confer degrees in Permaculture and other forms of sustainability at the newly formed Gaia University International (GUI). In Chapter Two I argue that GUI, as an institution of higher learning, is organized to provide support for learning. The goal of the university structure is to provide students, called Associates, with a vehicle for accumulation of credit towards a bachelor's degree. This organizational structure is necessary, but insufficient for AL because Associates need more than an organization to provide and coordinate their degree programs. In other words, just because the network of university structures are organized in ways that make AL possible and convenient, it does not necessarily follow that Action Learning will occur for any individual Associate. The support structures within GUI's degrees are discussed in Chapter Three. To a greater or lesser degree GUI provides support for personal learning among Associates as advisors and advisees with the goal of helping Associates complete and document the outcomes of world-change projects. The support structures are necessary, but not sufficient for AL because the personal learning process occurring for each Associate requires transformative reflection. Additionally, because Associates' attrition rate is very high, many Associates do not remain enrolled in GUI long enough to benefit from the support structures. At the simplest organizational level I discuss the reflection process conducted in the patterned interactions of assigned learning groups called Guilds (Chapter Four). These groups of Associates work to provide each other with the best possible environment for personal learning through reflection. As its Associates experience transformative reflection, GUI is able to help elevate the quality of world-change efforts in the Permaculture community. Provided the organizational and support structures are in place, this reflection

Learning, attentional control, and action video games.

PubMed

Green, C S; Bavelier, D

2012-03-20

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 © 2012 Elsevier Ltd. All rights reserved.

Learning of spatial relationships between observed and imitated actions allows invariant inverse computation in the frontal mirror neuron system.

PubMed

Oh, Hyuk; Gentili, Rodolphe J; Reggia, James A; Contreras-Vidal, José L

2011-01-01

It has been suggested that the human mirror neuron system can facilitate learning by imitation through coupling of observation and action execution. During imitation of observed actions, the functional relationship between and within the inferior frontal cortex, the posterior parietal cortex, and the superior temporal sulcus can be modeled within the internal model framework. The proposed biologically plausible mirror neuron system model extends currently available models by explicitly modeling the intraparietal sulcus and the superior parietal lobule in implementing the function of a frame of reference transformation during imitation. Moreover, the model posits the ventral premotor cortex as performing an inverse computation. The simulations reveal that: i) the transformation system can learn and represent the changes in extrinsic to intrinsic coordinates when an imitator observes a demonstrator; ii) the inverse model of the imitator's frontal mirror neuron system can be trained to provide the motor plans for the imitated actions.

Action Learning: a new method to increase tractor rollover protective structure (ROPS) adoption.

PubMed

Biddle, Elyce Anne; Keane, Paul R

2012-01-01

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.

Action Learning: A New Method to Increase Tractor Rollover Protective Structure (ROPS) Adoption

PubMed Central

Biddle, Elyce Anne; Keane, Paul R.

2016-01-01

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

Mindfulness into Action: Transformational Learning through Collaborative Inquiry

ERIC Educational Resources Information Center

Vergara, Mariana Ines

2016-01-01

This action research exploratory study sought to learn how to better develop my practice by using grounded theory. It explored the apparent cognitive transformational experience of nine participants over a period of four weeks after the implementation of an intervention called Mindfulness into Action. The informal intervention was used with the…

The Role of Facilitators in Project Action Learning Implementation

ERIC Educational Resources Information Center

Cao, Rui; Chuah, Kong Bieng; Chao, Yiu Chung; Kwong, Kar Fai; Law, Mo Yin

2012-01-01

Purpose: This paper addresses the importance of a more proactive role of organizational learning (OL) facilitators, learning motivation reinforcer, through a two-part longitudinal study in a case company. The first part of this study aims to investigate and analyze some unexpected challenges in the project action learning-driven (PAL) OL…

Analysis of a Physics Teacher's Pedagogical "Micro-Actions" That Support 17-Year-Olds' Learning of Free Body Diagrams via a Modelling Approach

ERIC Educational Resources Information Center

Tay, Su Lynn; Yeo, Jennifer

2018-01-01

Great teaching is characterised by the specific actions a teacher takes in the classroom to bring about learning. In the context of model-based teaching (MBT), teachers' difficulty in working with students' models that are not scientifically consistent is troubling. To address this problem, the aim of this study is to identify the pedagogical…

With you or against you: social orientation dependent learning signals guide actions made for others.

PubMed

Christopoulos, George I; King-Casas, Brooks

2015-01-01

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.

With you or against you: Social orientation dependent learning signals guide actions made for others

PubMed Central

Christopoulos, George I.; King-Casas, Brooks

2014-01-01

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 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 towards 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. PMID:25224998

Action learning: a tool for the development of strategic skills for Nurse Consultants?

PubMed

Young, Sarah; Nixon, Eileen; Hinge, Denise; McFadyen, Jan; Wright, Vanessa; Lambert, Pauline; Pilkington, Carolyn; Newsome, Christine

2010-01-01

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.

Learning Networks--Enabling Change through Community Action Research

ERIC Educational Resources Information Center

Bleach, Josephine

2016-01-01

Learning networks are a critical element of ethos of the community action research approach taken by the Early Learning Initiative at the National College of Ireland, a community-based educational initiative in the Dublin Docklands. Key criteria for networking, whether at local, national or international level, are the individual's and…

Participating in a Collaborative Action Learning Set (CAL): Beginning the Journey

ERIC Educational Resources Information Center

McCormack, Brendan; Henderson, Elizabeth; Boomer, Christine; Collin, Ita; Robinson, David

2008-01-01

Action learning is being increasingly utilised as a strategy to underpin practitioner focused development and research projects in healthcare generally and nursing in particular. Whilst facilitators of and participants in action learning have a variety of resource materials to guide their practice and participation, there continue to be few…

Assessing the Value of Action Learning for Social Enterprises and Charities

ERIC Educational Resources Information Center

Smith, Sue; Smith, Laurie

2017-01-01

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, Trayner, and de Laat…

A cooperative inquiry into action learning and praxis development in a community nursing module.

PubMed

Jenkins, Emrys R; Mabbett, Gaynor M; Surridge, Andrea G; Warring, Joanna; Gwynn, Elizabeth D

2009-09-01

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.

Transitioning to a More Sustainable Society: Unpacking the Role of the Learning-Action Nexus

ERIC Educational Resources Information Center

Moyer, Joanne M.; Sinclair, A. John; Quinn, Lisa

2016-01-01

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.…

Case-Based Modeling for Learning: Socially Constructed Skill Development

ERIC Educational Resources Information Center

Lyons, Paul; Bandura, Randall P.

2018-01-01

Purpose: Grounded on components of experiential learning theory (ELT) and self-regulation of learning (SRL) theory, augmented by elements of action theory and script development, the purpose of this paper is to demonstrate the case-based modeling (CBM) instructional approach that stimulates learning in groups or teams. CBM is related to individual…

Video Game Learning Dynamics: Actionable Measures of Multidimensional Learning Trajectories

ERIC Educational Resources Information Center

Reese, Debbie Denise; Tabachnick, Barbara G.; Kosko, Robert E.

2015-01-01

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…

The Implementation of Models-Based Practice in Physical Education through Action Research

ERIC Educational Resources Information Center

Casey, Ashley; Dyson, Ben

2009-01-01

The purpose of this study was to explore the use of action research as a framework to investigate cooperative learning and tactical games as instructional models in physical education (PE). The teacher/researcher taught a tennis unit using a combination of Cooperative Learning and Teaching Games for Understanding to three classes of boys aged…

Developing Results-Based Leadership Attributes and Team Cohesiveness through Action Learning

ERIC Educational Resources Information Center

Troupe, David

2010-01-01

Those who develop leaders in manufacturing settings have little data that describe the usefulness of action learning as a method of developing leaders' abilities to improve results-based leadership attributes or perceptions about their team's cohesiveness. The two purposes of this study were to evaluate an action learning program with regards to…

Learning from Toyota: How Action Learning Can Foster Competitive Advantage in New Product Development (NPD)

ERIC Educational Resources Information Center

Fuchs, Barbara

2007-01-01

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…

Innovation Development--An Action Learning Programme for Medical Scientists and Engineers

ERIC Educational Resources Information Center

Beniston, Lee; Ellwood, Paul; Gold, Jeff; Roberts, James; Thorpe, Richard

2014-01-01

There is increasing evidence that action learning is valuable in a higher education setting. This paper goes on to report a personal development programme, based on principles of critical action learning, where the aim is to equip early-career scientists and engineers working in a university setting with the knowledge, skills and confidence to…

Context transfer in reinforcement learning using action-value functions.

PubMed

Mousavi, Amin; Nadjar Araabi, Babak; Nili Ahmadabadi, Majid

2014-01-01

This paper discusses the notion of context transfer in reinforcement learning tasks. Context transfer, as defined in this paper, implies knowledge transfer between source and target tasks that share the same environment dynamics and reward function but have different states or action spaces. In other words, the agents learn the same task while using different sensors and actuators. This requires the existence of an underlying common Markov decision process (MDP) to which all the agents' MDPs can be mapped. This is formulated in terms of the notion of MDP homomorphism. The learning framework is Q-learning. To transfer the knowledge between these tasks, the feature space is used as a translator and is expressed as a partial mapping between the state-action spaces of different tasks. The Q-values learned during the learning process of the source tasks are mapped to the sets of Q-values for the target task. These transferred Q-values are merged together and used to initialize the learning process of the target task. An interval-based approach is used to represent and merge the knowledge of the source tasks. Empirical results show that the transferred initialization can be beneficial to the learning process of the target task.

Context Transfer in Reinforcement Learning Using Action-Value Functions

PubMed Central

Mousavi, Amin; Nadjar Araabi, Babak; Nili Ahmadabadi, Majid

2014-01-01

This paper discusses the notion of context transfer in reinforcement learning tasks. Context transfer, as defined in this paper, implies knowledge transfer between source and target tasks that share the same environment dynamics and reward function but have different states or action spaces. In other words, the agents learn the same task while using different sensors and actuators. This requires the existence of an underlying common Markov decision process (MDP) to which all the agents' MDPs can be mapped. This is formulated in terms of the notion of MDP homomorphism. The learning framework is Q-learning. To transfer the knowledge between these tasks, the feature space is used as a translator and is expressed as a partial mapping between the state-action spaces of different tasks. The Q-values learned during the learning process of the source tasks are mapped to the sets of Q-values for the target task. These transferred Q-values are merged together and used to initialize the learning process of the target task. An interval-based approach is used to represent and merge the knowledge of the source tasks. Empirical results show that the transferred initialization can be beneficial to the learning process of the target task. PMID:25610457

Multi-task learning with group information for human action recognition

NASA Astrophysics Data System (ADS)

Qian, Li; Wu, Song; Pu, Nan; Xu, Shulin; Xiao, Guoqiang

2018-04-01

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.

Professional Learning Communities: A Middle School Model

ERIC Educational Resources Information Center

Gentile, David N.

2010-01-01

This research project explored the transition from a traditional model to a Professional Learning Community model in a NJ Middle School. The administration overcame obstacles during the transition such as scheduling conflicts, teacher apathy, and resistance. This action research study gathered data to determine how to best structure the…

A Computer Model of Simple Forms of Learning.

ERIC Educational Resources Information Center

Jones, Thomas L.

A basic unsolved problem in science is that of understanding learning, the process by which people and machines use their experience in a situation to guide future action in similar situations. The ideas of Piaget, Pavlov, Hull, and other learning theorists, as well as previous heuristic programing models of human intelligence, stimulated this…

Novel associative-memory-based self-learning neurocontrol model

NASA Astrophysics Data System (ADS)

Chen, Ke

1992-09-01

Intelligent control is an important field of AI application, which is closely related to machine learning, and the neurocontrol is a kind of intelligent control that controls actions of a physical system or a plant. Linear associative memory model is a good analytic tool for artificial neural networks. In this paper, we present a novel self-learning neurocontrol on the basis of the linear associative memory model to support intelligent control. Using our self-learning neurocontrol model, the learning process is viewed as an extension of one of J. Piaget's developmental stages. After a particular linear associative model developed by us is presented, a brief introduction to J. Piaget's cognitive theory is described as the basis of our self-learning style control. It follows that the neurocontrol model is presented, which usually includes two learning stages, viz. primary learning and high-level learning. As a demonstration of our neurocontrol model, an example is also presented with simulation techniques, called that `bird' catches an aim. The tentative experimental results show that the learning and controlling performance of this approach is surprisingly good. In conclusion, future research is pointed out to improve our self-learning neurocontrol model and explore other areas of application.

Action Recognition Using Nonnegative Action Component Representation and Sparse Basis Selection.

PubMed

Wang, Haoran; Yuan, Chunfeng; Hu, Weiming; Ling, Haibin; Yang, Wankou; Sun, Changyin

2014-02-01

In this paper, we propose using high-level action units to represent human actions in videos and, based on such units, a novel sparse model is developed for human action recognition. There are three interconnected components in our approach. First, we propose a new context-aware spatial-temporal descriptor, named locally weighted word context, to improve the discriminability of the traditionally used local spatial-temporal descriptors. Second, from the statistics of the context-aware descriptors, we learn action units using the graph regularized nonnegative matrix factorization, which leads to a part-based representation and encodes the geometrical information. These units effectively bridge the semantic gap in action recognition. Third, we propose a sparse model based on a joint l2,1-norm to preserve the representative items and suppress noise in the action units. Intuitively, when learning the dictionary for action representation, the sparse model captures the fact that actions from the same class share similar units. The proposed approach is evaluated on several publicly available data sets. The experimental results and analysis clearly demonstrate the effectiveness of the proposed approach.

An Exploration of Significant Leadership Development Factors in Action Learning: A Comparison of Three Action Learning Programs

ERIC Educational Resources Information Center

Cowan, Chris Allen

2013-01-01

As the need for new leaders has increased, so has the need for new and more effective forms of leadership development (Hamel, 2007; Lojeski, 2010; Gratton, 2011). Action learning has been popularized as one of these new forms of leadership development (Peters & Smith, 1998; Byrnes, 2005; ASTD, 2008; Trehan & Pedler, 2011). However,…

Developing Citizen Leaders through Action Learning

ERIC Educational Resources Information Center

Foley, Dolores

2006-01-01

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…

Action Learning in Postgraduate Research Training

ERIC Educational Resources Information Center

Marchand, Trevor

2017-01-01

This account of practice explores the benefits and challenges of using Action Learning (AL) with junior researchers. Findings are grounded in an AL set of six doctoral students, organised and convened by the author. The case study reveals the range of emotional and structural hurdles that Ph.D. candidates typically face in completing their…

Toxin-Induced Experimental Models of Learning and Memory Impairment

PubMed Central

More, Sandeep Vasant; Kumar, Hemant; Cho, Duk-Yeon; Yun, Yo-Sep; Choi, Dong-Kug

2016-01-01

Animal models for learning and memory have significantly contributed to novel strategies for drug development and hence are an imperative part in the assessment of therapeutics. Learning and memory involve different stages including acquisition, consolidation, and retrieval and each stage can be characterized using specific toxin. Recent studies have postulated the molecular basis of these processes and have also demonstrated many signaling molecules that are involved in several stages of memory. Most insights into learning and memory impairment and to develop a novel compound stems from the investigations performed in experimental models, especially those produced by neurotoxins models. Several toxins have been utilized based on their mechanism of action for learning and memory impairment such as scopolamine, streptozotocin, quinolinic acid, and domoic acid. Further, some toxins like 6-hydroxy dopamine (6-OHDA), 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and amyloid-β are known to cause specific learning and memory impairment which imitate the disease pathology of Parkinson’s disease dementia and Alzheimer’s disease dementia. Apart from these toxins, several other toxins come under a miscellaneous category like an environmental pollutant, snake venoms, botulinum, and lipopolysaccharide. This review will focus on the various classes of neurotoxin models for learning and memory impairment with their specific mechanism of action that could assist the process of drug discovery and development for dementia and cognitive disorders. PMID:27598124

Toxin-Induced Experimental Models of Learning and Memory Impairment.

PubMed

More, Sandeep Vasant; Kumar, Hemant; Cho, Duk-Yeon; Yun, Yo-Sep; Choi, Dong-Kug

2016-09-01

Animal models for learning and memory have significantly contributed to novel strategies for drug development and hence are an imperative part in the assessment of therapeutics. Learning and memory involve different stages including acquisition, consolidation, and retrieval and each stage can be characterized using specific toxin. Recent studies have postulated the molecular basis of these processes and have also demonstrated many signaling molecules that are involved in several stages of memory. Most insights into learning and memory impairment and to develop a novel compound stems from the investigations performed in experimental models, especially those produced by neurotoxins models. Several toxins have been utilized based on their mechanism of action for learning and memory impairment such as scopolamine, streptozotocin, quinolinic acid, and domoic acid. Further, some toxins like 6-hydroxy dopamine (6-OHDA), 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and amyloid-β are known to cause specific learning and memory impairment which imitate the disease pathology of Parkinson's disease dementia and Alzheimer's disease dementia. Apart from these toxins, several other toxins come under a miscellaneous category like an environmental pollutant, snake venoms, botulinum, and lipopolysaccharide. This review will focus on the various classes of neurotoxin models for learning and memory impairment with their specific mechanism of action that could assist the process of drug discovery and development for dementia and cognitive disorders.

How to use coaching and action learning to support mentors in the workplace.

PubMed

Nash, Sue; Scammell, Janet

Using the example of mentoring preregistration student nurses, this article explores facilitation of learning in the workplace and examines the use of coaching and action learning to support mentors and the wider clinical team. A case study, where a mentor has difficulties with an underperforming student, is considered. Action learning and coaching are then explored, with the aim of maximising personal and team learning. These strategies can be easily transferred to other work based learning situations.

Artist-Teachers' In-Action Mental Models While Teaching Visual Arts

ERIC Educational Resources Information Center

Russo-Zimet, Gila

2017-01-01

Studies have examined the assumption that teachers have previous perceptions, beliefs and knowledge about learning (Cochran-Smith & Villegas, 2015). This study presented the In-Action Mental Model of twenty leading artist-teachers while teaching Visual Arts in three Israeli art institutions of higher Education. Data was collected in two…

Participatory Action Research and Environmental Learning: Implications for Resilient Forests and Communities

ERIC Educational Resources Information Center

Ballard, Heidi L.; Belsky, Jill M.

2010-01-01

How can a participatory approach to research promote environmental learning and enhance social-ecological systems resilience? Participatory action research (PAR) is an approach to research that its' supporters claim can foster new knowledge, learning, and action to support positive social and environmental change through reorienting the standard…

Action-Driven Visual Object Tracking With Deep Reinforcement Learning.

PubMed

Yun, Sangdoo; Choi, Jongwon; Yoo, Youngjoon; Yun, Kimin; Choi, Jin Young

2018-06-01

In this paper, we propose an efficient visual tracker, which directly captures a bounding box containing the target object in a video by means of sequential actions learned using deep neural networks. The proposed deep neural network to control tracking actions is pretrained using various training video sequences and fine-tuned during actual tracking for online adaptation to a change of target and background. The pretraining is done by utilizing deep reinforcement learning (RL) as well as supervised learning. The use of RL enables even partially labeled data to be successfully utilized for semisupervised learning. Through the evaluation of the object tracking benchmark data set, the proposed tracker is validated to achieve a competitive performance at three times the speed of existing deep network-based trackers. The fast version of the proposed method, which operates in real time on graphics processing unit, outperforms the state-of-the-art real-time trackers with an accuracy improvement of more than 8%.

Distinct prediction errors in mesostriatal circuits of the human brain mediate learning about the values of both states and actions: evidence from high-resolution fMRI.

PubMed

Colas, Jaron T; Pauli, Wolfgang M; Larsen, Tobias; Tyszka, J Michael; O'Doherty, John P

2017-10-01

Prediction-error signals consistent with formal models of "reinforcement learning" (RL) have repeatedly been found within dopaminergic nuclei of the midbrain and dopaminoceptive areas of the striatum. However, the precise form of the RL algorithms implemented in the human brain is not yet well determined. Here, we created a novel paradigm optimized to dissociate the subtypes of reward-prediction errors that function as the key computational signatures of two distinct classes of RL models-namely, "actor/critic" models and action-value-learning models (e.g., the Q-learning model). The state-value-prediction error (SVPE), which is independent of actions, is a hallmark of the actor/critic architecture, whereas the action-value-prediction error (AVPE) is the distinguishing feature of action-value-learning algorithms. To test for the presence of these prediction-error signals in the brain, we scanned human participants with a high-resolution functional magnetic-resonance imaging (fMRI) protocol optimized to enable measurement of neural activity in the dopaminergic midbrain as well as the striatal areas to which it projects. In keeping with the actor/critic model, the SVPE signal was detected in the substantia nigra. The SVPE was also clearly present in both the ventral striatum and the dorsal striatum. However, alongside these purely state-value-based computations we also found evidence for AVPE signals throughout the striatum. These high-resolution fMRI findings suggest that model-free aspects of reward learning in humans can be explained algorithmically with RL in terms of an actor/critic mechanism operating in parallel with a system for more direct action-value learning.

A Descriptive Review of Mainline E-Learning Projects in the European Union: E-Learning Action Plan and E-Learning Program

ERIC Educational Resources Information Center

Uzunboylu, Huseyin

2006-01-01

This study's purpose was to survey the literature on European Union (EU) e-learning strategies specifically related to two mainline e-learning projects: the learning Action Plan and the E-Learning Program. Results of the evaluation and interpretation of the literature show that the European Commission has positively impacted European Union…

Toward a dual-learning systems model of speech category learning

PubMed Central

Chandrasekaran, Bharath; Koslov, Seth R.; Maddox, W. T.

2014-01-01

More than two decades of work in vision posits the existence of dual-learning systems of category learning. The reflective system uses working memory to develop and test rules for classifying in an explicit fashion, while the reflexive system operates by implicitly associating perception with actions that lead to reinforcement. Dual-learning systems models hypothesize that in learning natural categories, learners initially use the reflective system and, with practice, transfer control to the reflexive system. The role of reflective and reflexive systems in auditory category learning and more specifically in speech category learning has not been systematically examined. In this article, we describe a neurobiologically constrained dual-learning systems theoretical framework that is currently being developed in speech category learning and review recent applications of this framework. Using behavioral and computational modeling approaches, we provide evidence that speech category learning is predominantly mediated by the reflexive learning system. In one application, we explore the effects of normal aging on non-speech and speech category learning. Prominently, we find a large age-related deficit in speech learning. The computational modeling suggests that older adults are less likely to transition from simple, reflective, unidimensional rules to more complex, reflexive, multi-dimensional rules. In a second application, we summarize a recent study examining auditory category learning in individuals with elevated depressive symptoms. We find a deficit in reflective-optimal and an enhancement in reflexive-optimal auditory category learning. Interestingly, individuals with elevated depressive symptoms also show an advantage in learning speech categories. We end with a brief summary and description of a number of future directions. PMID:25132827

Action Control, Motivated Strategies, and Integrative Motivation as Predictors of Language Learning Affect and the Intention to Continue Learning French

ERIC Educational Resources Information Center

MacIntyre, Peter D.; Blackie, Rebecca A.

2012-01-01

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…

A reward optimization method based on action subrewards in hierarchical reinforcement learning.

PubMed

Fu, Yuchen; Liu, Quan; Ling, Xionghong; Cui, Zhiming

2014-01-01

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.

Facilitating Lecturer Development and Student Learning through Action Research

ERIC Educational Resources Information Center

van der Westhuizen, C. N.

2008-01-01

The aim of the action research project is to improve my own practice as research methodology lecturer to facilitate effective student learning to enable students to become reflective practitioners with responsibility for their own professional development through action research in their own classrooms, and to motivate the students and increase…

Patterns in Elementary School Students' Strategic Actions in Varying Learning Situations

ERIC Educational Resources Information Center

Malmberg, Jonna; Järvenoja, Hanna; Järvelä, Sanna

2013-01-01

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…

Action Learning: The Possibility of Differing Hierarchies in Learning Sets

ERIC Educational Resources Information Center

Yeadon-Lee, Annie

2013-01-01

This paper presents the proposition that a variety of differing hierarchies exist in an action learning set at any one time, and each hierarchy has the potential to affect an individual's behaviour within the set. An interpretivist philosophy underpins the research framework adopted in this paper. Data were captured by means of 11 in-depth…

How Action-Learning Coaches Foster a Climate Conducive to Learning

ERIC Educational Resources Information Center

Gibson, Sara Henderson

2011-01-01

Today's businesses rely on the effective functioning of self-directed work teams to learn how to solve complex problems and take action. A key factor in a team's ability to perform in this manner is a group climate characterized by psychological safety. Psychological safety must often compete with a climate of evaluative pressure frequently found…

The Origins of Verb Learning: Preverbal and Postverbal Infants' Learning of Word-Action Relations

ERIC Educational Resources Information Center

Gogate, Lakshmi; Maganti, Madhavilatha

2017-01-01

Purpose: This experiment examined English- or Spanish-learning preverbal (8-9 months, n = 32) and postverbal (12-14 months, n = 40) infants' learning of word-action pairings prior to and after the transition to verb comprehension and its relation to naturally learned vocabulary. Method: Infants of both verbal levels were first habituated to 2…

Model learning for robot control: a survey.

PubMed

Nguyen-Tuong, Duy; Peters, Jan

2011-11-01

Models are among the most essential tools in robotics, such as kinematics and dynamics models of the robot's own body and controllable external objects. It is widely believed that intelligent mammals also rely on internal models in order to generate their actions. However, while classical robotics relies on manually generated models that are based on human insights into physics, future autonomous, cognitive robots need to be able to automatically generate models that are based on information which is extracted from the data streams accessible to the robot. In this paper, we survey the progress in model learning with a strong focus on robot control on a kinematic as well as dynamical level. Here, a model describes essential information about the behavior of the environment and the influence of an agent on this environment. In the context of model-based learning control, we view the model from three different perspectives. First, we need to study the different possible model learning architectures for robotics. Second, we discuss what kind of problems these architecture and the domain of robotics imply for the applicable learning methods. From this discussion, we deduce future directions of real-time learning algorithms. Third, we show where these scenarios have been used successfully in several case studies.

Gaze data reveal distinct choice processes underlying model-based and model-free reinforcement learning

PubMed Central

Konovalov, Arkady; Krajbich, Ian

2016-01-01

Organisms appear to learn and make decisions using different strategies known as model-free and model-based learning; the former is mere reinforcement of previously rewarded actions and the latter is a forward-looking strategy that involves evaluation of action-state transition probabilities. Prior work has used neural data to argue that both model-based and model-free learners implement a value comparison process at trial onset, but model-based learners assign more weight to forward-looking computations. Here using eye-tracking, we report evidence for a different interpretation of prior results: model-based subjects make their choices prior to trial onset. In contrast, model-free subjects tend to ignore model-based aspects of the task and instead seem to treat the decision problem as a simple comparison process between two differentially valued items, consistent with previous work on sequential-sampling models of decision making. These findings illustrate a problem with assuming that experimental subjects make their decisions at the same prescribed time. PMID:27511383

Practising What We Teach: Vocational Teachers Learn to Research through Applying Action Learning Techniques

ERIC Educational Resources Information Center

Lasky, Barbara; Tempone, Irene

2004-01-01

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…

The Contradictions of Impact: Action Learning and Power in Organizations

ERIC Educational Resources Information Center

Vince, Russ

2012-01-01

In this polemical essay, Professor Russ Vince argues that it is important to understand the contradictions that can be generated by action learning. This method is a powerful and effective approach to managers' learning that can underpin transformations of management practice. However, any method for learning, no matter how convinced we are of its…

A Framework for Hierarchical Perception-Action Learning Utilizing Fuzzy Reasoning.

PubMed

Windridge, David; Felsberg, Michael; Shaukat, Affan

2013-02-01

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.

Learning the ShamWow: Creating Infomercials to Teach the AIDA Model

ERIC Educational Resources Information Center

Lee, Seung Hwan; Hoffman, K. Douglas

2015-01-01

The AIDA Model (Attention-Interest-Desire-Action) is one of the classical promotional theories in marketing. Through active-learning techniques and peer critiques, we use infomercials as an innovative educational tool to instruct the four components of the AIDA model. Student evaluations regarding this active-learning assignment reveal that the…

Collaborative Action Research on Technology Integration for Science Learning

NASA Astrophysics Data System (ADS)

Wang, Chien-Hsing; Ke, Yi-Ting; Wu, Jin-Tong; Hsu, Wen-Hua

2012-02-01

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.

Improved probabilistic inference as a general learning mechanism with action video games.

PubMed

Green, C Shawn; Pouget, Alexandre; Bavelier, Daphne

2010-09-14

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 ([10], 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 [16] 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.

Low-Rank Tensor Subspace Learning for RGB-D Action Recognition.

PubMed

Jia, Chengcheng; Fu, Yun

2016-07-09

Since RGB-D action data inherently equip with extra depth information compared with RGB data, recently many works employ RGB-D data in a third-order tensor representation containing spatio-temporal structure to find a subspace for action recognition. However, there are two main challenges of these methods. First, the dimension of subspace is usually fixed manually. Second, preserving local information by finding intraclass and inter-class neighbors from a manifold is highly timeconsuming. In this paper, we learn a tensor subspace, whose dimension is learned automatically by low-rank learning, for RGB-D action recognition. Particularly, the tensor samples are factorized to obtain three Projection Matrices (PMs) by Tucker Decomposition, where all the PMs are performed by nuclear norm in a close-form to obtain the tensor ranks which are used as tensor subspace dimension. Additionally, we extract the discriminant and local information from a manifold using a graph constraint. This graph preserves the local knowledge inherently, which is faster than the previous way by calculating both the intra-class and inter-class neighbors of each sample. We evaluate the proposed method on four widely used RGB-D action datasets including MSRDailyActivity3D, MSRActionPairs, MSRActionPairs skeleton and UTKinect-Action3D datasets, and the experimental results show higher accuracy and efficiency of the proposed method.

Improving Adolescent Learning: An Action Agenda. A TASC Report

ERIC Educational Resources Information Center

Duffrin, Elizabeth

2014-01-01

At a recent national forum at the Ford Foundation in New York, 140 education and youth development professionals discussed how to better support adolescent learning. Drawing on the discussion and the latest research in neuroscience, psychology and cognitive learning science, TASC presents an action agenda that can be tailored to circumstances in…

Challenges of Adopting Constructive Alignment in Action Learning Education

ERIC Educational Resources Information Center

Remneland Wikhamn, Björn

2017-01-01

This paper will critically examine how the two influential pedagogical approaches of action-based learning and constructive alignment relate to each other, and how they may differ in focus and basic assumptions. From the outset, they are based on similar underpinnings, with the student and the learning outcomes in the center. Drawing from…

Organizational Support for Action Learning in South Korean Organizations

ERIC Educational Resources Information Center

Cho, Yonjoo; Egan, Toby

2013-01-01

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…

Making Facilitation Work: The Challenges on an International DBA Action Learning Set

ERIC Educational Resources Information Center

OFarrell, Jack

2018-01-01

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…

Critical by Design: Enacting Critical Action Learning in a Small Business Context

ERIC Educational Resources Information Center

Ram, Monder; Trehan, Kiran

2009-01-01

A small but growing strand of literature is beginning to make the case for "critical action learning" (CAL). Much of this interest operates on theoretical terrain, speculating on the extent to which it might differ from more conventional notions of action learning. This paper draws on insights from (CAL) to demonstrate the importance of being…

Doing Poverty: Learning Outcomes among Students Participating in the Community Action Poverty Simulation Program

ERIC Educational Resources Information Center

Steck, Laura West; Engler, Jennifer N.; Ligon, Mary; Druen, Perri B.; Cosgrove, Erin

2011-01-01

This article discusses an application of the Lewinian/Kolb experiential learning model in the context of undergraduate participation in the Missouri Community Action Poverty Simulation (CAPS) program. CAPS is designed to simulate common, everyday experiences among people living in poverty as participants take on the roles of family members working…

Collaborative Knowledge and Intellectual Property: An Action Learning Conundrum

ERIC Educational Resources Information Center

Elliott, Tish; Pedler, Mike

2018-01-01

If everyone is contributing, if action learning involves collective learning, then new knowledge is created through a collaborative process. This is not expert knowledge and no 'one truth' is produced, this is a collective knowledge arising from a common purpose and a shared quest. Such knowledge continues to evolve without the intention to fix or…

Defining Learning Space in a Serious Game in Terms of Operative and Resultant Actions

NASA Technical Reports Server (NTRS)

Martin, Michael W.; Shen, Yuzhong

2012-01-01

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.

Dual learning processes underlying human decision-making in reversal learning tasks: functional significance and evidence from the model fit to human behavior

PubMed Central

Bai, Yu; Katahira, Kentaro; Ohira, Hideki

2014-01-01

Humans are capable of correcting their actions based on actions performed in the past, and this ability enables them to adapt to a changing environment. The computational field of reinforcement learning (RL) has provided a powerful explanation for understanding such processes. Recently, the dual learning system, modeled as a hybrid model that incorporates value update based on reward-prediction error and learning rate modulation based on the surprise signal, has gained attention as a model for explaining various neural signals. However, the functional significance of the hybrid model has not been established. In the present study, we used computer simulation in a reversal learning task to address functional significance in a probabilistic reversal learning task. The hybrid model was found to perform better than the standard RL model in a large parameter setting. These results suggest that the hybrid model is more robust against the mistuning of parameters compared with the standard RL model when decision-makers continue to learn stimulus-reward contingencies, which can create abrupt changes. The parameter fitting results also indicated that the hybrid model fit better than the standard RL model for more than 50% of the participants, which suggests that the hybrid model has more explanatory power for the behavioral data than the standard RL model. PMID:25161635

Collaborative Action Research on Technology Integration for Science Learning

ERIC Educational Resources Information Center

Wang, Chien-hsing; Ke, Yi-Ting; Wu, Jin-Tong; Hsu, Wen-Hua

2012-01-01

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,…

Professional Learning in Canada: Learning Forward Releases a Landmark Study and Call to Action

ERIC Educational Resources Information Center

Learning Professional, 2017

2017-01-01

Learning Forward recently released findings from a new study that fills a long-standing gap in existing Pan-Canadian research, identifying key components of effective professional learning based on findings from educators' experiences in Canada. Accompanying the study is a call to action by Michael Fullan and Andy Hargreaves making the case for a…

Systems Thinking, Lean Production and Action Learning

ERIC Educational Resources Information Center

Seddon, John; Caulkin, Simon

2007-01-01

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…

Dorsal striatum is necessary for stimulus-value but not action-value learning in humans

PubMed Central

Vo, Khoi; Rutledge, Robb B.; Chatterjee, Anjan

2014-01-01

Several lines of evidence implicate the striatum in learning from experience on the basis of positive and negative feedback. However, the necessity of the striatum for such learning has been difficult to demonstrate in humans, because brain damage is rarely restricted to this structure. Here we test a rare individual with widespread bilateral damage restricted to the dorsal striatum. His performance was impaired and not significantly different from chance on several classic learning tasks, consistent with current theories regarding the role of the striatum. However, he also exhibited remarkably intact performance on a different subset of learning paradigms. The tasks he could perform can all be solved by learning the value of actions, while those he could not perform can only be solved by learning the value of stimuli. Although dorsal striatum is often thought to play a specific role in action-value learning, we find surprisingly that dorsal striatum is necessary for stimulus-value but not action-value learning in humans. PMID:25273995

Action learning in virtual higher education: applying leadership theory.

PubMed

Curtin, Joseph

2016-05-03

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.

Mentoring, coaching and action learning: interventions in a national clinical leadership development programme.

PubMed

McNamara, Martin S; Fealy, Gerard M; Casey, Mary; O'Connor, Tom; Patton, Declan; Doyle, Louise; Quinlan, Christina

2014-09-01

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.

Learning Actions, Objects and Types of Interaction: A Methodological Analysis of Expansive Learning among Pre-Service Teachers

ERIC Educational Resources Information Center

Rantavuori, Juhana; Engeström, Yrjö; Lipponen, Lasse

2016-01-01

The paper analyzes a collaborative learning process among Finnish pre-service teachers planning their own learning in a self-regulated way. The study builds on cultural-historical activity theory and the theory of expansive learning, integrating for the first time an analysis of learning actions and an analysis of types of interaction. We examine…

Dynamic mesolimbic dopamine signaling during action sequence learning and expectation violation

PubMed Central

Collins, Anne L.; Greenfield, Venuz Y.; Bye, Jeffrey K.; Linker, Kay E.; Wang, Alice S.; Wassum, Kate M.

2016-01-01

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

Exploring Constructivist Social Learning Practices in Aiding Russian-Speaking Teachers to Learn Estonian: An Action Research Approach

ERIC Educational Resources Information Center

Kiilo, Tatjana; Kutsar, Dagmar

2012-01-01

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…

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

PubMed Central

Keysers, Christian; Gazzola, Valeria

2014-01-01

Spike-timing-dependent plasticity is considered the neurophysiological basis of Hebbian learning and has been shown to be sensitive to both contingency and contiguity between pre- and postsynaptic activity. Here, we will examine how applying this Hebbian learning rule to a system of interconnected 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. PMID:24778372

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

PubMed

Keysers, Christian; Gazzola, Valeria

2014-01-01

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

Delivering Australian Vocational Qualifications through Action Learning

ERIC Educational Resources Information Center

Cother, Robert; Cother, Genevieve

2017-01-01

In 2009, Skills Tasmania approached the authors to deliver their Lean Action Learning programme in Tasmania. This programme had run successfully in South Australia for some five years. For Tasmania, a requirement was that participants in the programme be eligible for a nationally recognised VET qualification on completion of the programme. This…

Unlearning, Critical Action Learning and Wicked Problems

ERIC Educational Resources Information Center

Pedler, Mike; Hsu, Shih-wei

2014-01-01

This paper explores the idea of unlearning in Critical Action Learning (CAL) as applied to the wicked problems of organisations and societies. It draws on data and ideas developed during a research project conducted for "Skills for Care" by Pedler, Abbott, Brook and Burgoyne ("Skills for Care" 2014) and from experiences on…

Discovering motion primitives for unsupervised grouping and one-shot learning of human actions, gestures, and expressions.

PubMed

Yang, Yang; Saleemi, Imran; Shah, Mubarak

2013-07-01

This paper proposes a novel representation of articulated human actions and gestures and facial expressions. The main goals of the proposed approach are: 1) to enable recognition using very few examples, i.e., one or k-shot learning, and 2) meaningful organization of unlabeled datasets by unsupervised clustering. Our proposed representation is obtained by automatically discovering high-level subactions or motion primitives, by hierarchical clustering of observed optical flow in four-dimensional, spatial, and motion flow space. The completely unsupervised proposed method, in contrast to state-of-the-art representations like bag of video words, provides a meaningful representation conducive to visual interpretation and textual labeling. Each primitive action depicts an atomic subaction, like directional motion of limb or torso, and is represented by a mixture of four-dimensional Gaussian distributions. For one--shot and k-shot learning, the sequence of primitive labels discovered in a test video are labeled using KL divergence, and can then be represented as a string and matched against similar strings of training videos. The same sequence can also be collapsed into a histogram of primitives or be used to learn a Hidden Markov model to represent classes. We have performed extensive experiments on recognition by one and k-shot learning as well as unsupervised action clustering on six human actions and gesture datasets, a composite dataset, and a database of facial expressions. These experiments confirm the validity and discriminative nature of the proposed representation.

The Impact of Action Learning: What Difference Are We Making in the World?

ERIC Educational Resources Information Center

Turner, Arthur; Heneberry, Pamela

2013-01-01

Involvement in a number of action-learning programmes and associated development opportunities has led the Professional Development Centre Limited to question the relevance of a strict adherence to the "rules" of action learning as described by Reg Revans. A deliberate focus of one such programme to a financial services organisation…

LEAD at Lunch: Inquiry, Learning, and Action

ERIC Educational Resources Information Center

Roberts, Cynthia

2012-01-01

This account of practice discusses the author's experience in facilitating a small group of managers in health care over lunchtime utilizing an action learning approach. This was part of a larger leadership development initiative which took place in the organization and the intention was to create a more intimate, informal and safe setting whereby…

Task-Based Language Learning and Teaching: An Action-Research Study

ERIC Educational Resources Information Center

Calvert, Megan; Sheen, Younghee

2015-01-01

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…

HiTEC: a connectionist model of the interaction between perception and action planning.

PubMed

Haazebroek, Pascal; Raffone, Antonino; Hommel, Bernhard

2017-11-01

Increasing evidence suggests that perception and action planning do not represent separable stages of a unidirectional processing sequence, but rather emerging properties of highly interactive processes. To capture these characteristics of the human cognitive system, we have developed a connectionist model of the interaction between perception and action planning: HiTEC, based on the Theory of Event Coding (Hommel et al. in Behav Brain Sci 24:849-937, 2001). The model is characterized by representations at multiple levels and by shared representations and processes. It complements available models of stimulus-response translation by providing a rationale for (1) how situation-specific meanings of motor actions emerge, (2) how and why some aspects of stimulus-response translation occur automatically and (3) how task demands modulate sensorimotor processing. The model is demonstrated to provide a unitary account and simulation of a number of key findings with multiple experimental paradigms on the interaction between perception and action such as the Simon effect, its inversion (Hommel in Psychol Res 55:270-279, 1993), and action-effect learning.

Beyond rational imitation: learning arbitrary means actions from communicative demonstrations.

PubMed

Király, Ildikó; Csibra, Gergely; Gergely, György

2013-10-01

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.

Beyond rational imitation: Learning arbitrary means actions from communicative demonstrations

PubMed Central

Király, Ildikó; Csibra, Gergely; Gergely, György

2015-01-01

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 re-enact a specific behavior or not. Puzzlingly, however, 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 present empirical evidence supporting this proposal. In Experiment 1, we found that 14-month-old infants re-enacted 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 their re-enactment of the demonstrated novel actions reflects epistemic 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 vs. communicative actions – are integrated as a system for learning socially constituted instrumental knowledge in humans. PMID:23499323

An Action Research Project by Teacher Candidates and Their Instructor into Using Math Inquiry: Learning about Relations between Theory and Practice

ERIC Educational Resources Information Center

Betts, Paul; McLarty, Michelle; Dickson, Krysta

2017-01-01

This paper reports on what two teacher candidates and their instructor learned from an action research project into the use of inquiry to teach mathematics. We use a model of the relation between theory and practice in teacher education to interpret what we learned about inquiry. This model describes three modes for teacher candidates to learn…

Distinct prediction errors in mesostriatal circuits of the human brain mediate learning about the values of both states and actions: evidence from high-resolution fMRI

PubMed Central

Pauli, Wolfgang M.; Larsen, Tobias; Tyszka, J. Michael; O’Doherty, John P.

2017-01-01

Prediction-error signals consistent with formal models of “reinforcement learning” (RL) have repeatedly been found within dopaminergic nuclei of the midbrain and dopaminoceptive areas of the striatum. However, the precise form of the RL algorithms implemented in the human brain is not yet well determined. Here, we created a novel paradigm optimized to dissociate the subtypes of reward-prediction errors that function as the key computational signatures of two distinct classes of RL models—namely, “actor/critic” models and action-value-learning models (e.g., the Q-learning model). The state-value-prediction error (SVPE), which is independent of actions, is a hallmark of the actor/critic architecture, whereas the action-value-prediction error (AVPE) is the distinguishing feature of action-value-learning algorithms. To test for the presence of these prediction-error signals in the brain, we scanned human participants with a high-resolution functional magnetic-resonance imaging (fMRI) protocol optimized to enable measurement of neural activity in the dopaminergic midbrain as well as the striatal areas to which it projects. In keeping with the actor/critic model, the SVPE signal was detected in the substantia nigra. The SVPE was also clearly present in both the ventral striatum and the dorsal striatum. However, alongside these purely state-value-based computations we also found evidence for AVPE signals throughout the striatum. These high-resolution fMRI findings suggest that model-free aspects of reward learning in humans can be explained algorithmically with RL in terms of an actor/critic mechanism operating in parallel with a system for more direct action-value learning. PMID:29049406

Demonstrating and Evaluating an Action Learning Approach to Building Project Management Competence

NASA Technical Reports Server (NTRS)

Kotnour, Tim; Starr, Stan; Steinrock, T. (Technical Monitor)

2001-01-01

This paper contributes a description of an action-learning approach to building project management competence. This approach was designed, implemented, and evaluated for use with the Dynacs Engineering Development Contract at the Kennedy Space Center. The aim of the approach was to improve three levels of competence within the organization: individual project management skills, project team performance. and organizational capabilities such as the project management process and tools. The overall steps to the approach, evaluation results, and lessons learned are presented. Managers can use this paper to design a specific action-learning approach for their organization.

Implementing a New Model for Teachers' Professional Learning in Papua New Guinea

ERIC Educational Resources Information Center

Honan, Eileen; Evans, Terry; Muspratt, Sandy; Paraide, Patricia; Reta, Medi; Baroutsis, Aspa

2012-01-01

This article reports on a study that investigates the possibilities of developing a professional learning model based on action research that could lead to sustained improvements in teaching and learning in schools in remote areas of Papua New Guinea. The issues related to the implementation of this model are discussed using a critical lens that…

Towards tailored teaching: using participatory action research to enhance the learning experience of Longitudinal Integrated Clerkship students in a South African rural district hospital.

PubMed

von Pressentin, Klaus B; Waggie, Firdouza; Conradie, Hoffie

2016-03-08

The introduction of Stellenbosch University's Longitudinal Integrated Clerkship (LIC) model as part of the undergraduate medical curriculum offers a unique and exciting training model to develop generalist doctors for the changing South African health landscape. At one of these LIC sites, the need for an improvement of the local learning experience became evident. This paper explores how to identify and implement a tailored teaching and learning intervention to improve workplace-based learning for LIC students. A participatory action research approach was used in a co-operative inquiry group (ten participants), consisting of the students, clinician educators and researchers, who met over a period of 5 months. Through a cyclical process of action and reflection this group identified a teaching intervention. The results demonstrate the gaps and challenges identified when implementing a LIC model of medical education. A structured learning programme for the final 6 weeks of the students' placement at the district hospital was designed by the co-operative inquiry group as an agreed intervention. The post-intervention group reflection highlighted a need to create a structured programme in the spirit of local collaboration and learning across disciplines. The results also enhance our understanding of both students and clinician educators' perceptions of this new model of workplace-based training. This paper provides practical strategies to enhance teaching and learning in a new educational context. These strategies illuminate three paradigm shifts: (1) from the traditional medical education approach towards a transformative learning approach advocated for the 21(st) century health professional; (2) from the teaching hospital context to the district hospital context; and (3) from block-based teaching towards a longitudinal integrated learning model. A programme based on balancing structured and tailored learning activities is recommended in order to address the local

Robots show us how to teach them: feedback from robots shapes tutoring behavior during action learning.

PubMed

Vollmer, Anna-Lisa; Mühlig, Manuel; Steil, Jochen J; Pitsch, Karola; Fritsch, Jannik; Rohlfing, Katharina J; Wrede, Britta

2014-01-01

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.

Robots Show Us How to Teach Them: Feedback from Robots Shapes Tutoring Behavior during Action Learning

PubMed Central

Vollmer, Anna-Lisa; Mühlig, Manuel; Steil, Jochen J.; Pitsch, Karola; Fritsch, Jannik; Rohlfing, Katharina J.; Wrede, Britta

2014-01-01

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. PMID:24646510

Experiential learning in nursing consultation education via clinical simulation with actors: action research.

PubMed

de Oliveira, Saionara Nunes; do Prado, Marta Lenise; Kempfer, Silvana Silveira; Martini, Jussara Gue; Caravaca-Morera, Jaime Alonso; Bernardi, Mariely Carmelina

2015-02-01

This was an action research study conducted during an undergraduate nursing course. The objective was to propose and implement experiential learning for nursing consultation education using clinical simulation with actors. The 4 steps of action research were followed: planning, action, observation and reflection. Three nursing undergraduate students participated in the study. Data were collected in May and July 2013 via participant comments and interviews and were analyzed in accordance with the operative proposal for qualitative data analysis. Planning included constructing and validating the clinical guides, selecting and training the actors, organizing and preparing the scenario and the issuing invitations to the participants. The action was carried out according to Kolb's (1984) 4 stages of learning cycles: Concrete Experience, Reflective Observation, Abstract Conceptualization and Active Experimentation. Clinical simulation involves different subjects' participation in all stages, and action research is a method that enables the clinical stimulation to be implemented. It must be guided by clear learning objectives and by a critical pedagogy that encourages critical thinking in students. Using actors and a real scenario facilitated psychological fidelity, and debriefing was the key moment of the reflective process that facilitated the integral training of students through experiential learning. Copyright © 2014 Elsevier Ltd. All rights reserved.

Organizational Learning Post Catastrophic Events: A Descriptive Case Study Exploring NASA's Learning over Time Following Two Catastrophic Shuttle Accidents Using the Schwandt's Organizational Learning System Model

ERIC Educational Resources Information Center

Castro, Edgar Oscar

2013-01-01

A 30-year contribution of the Space Shuttle Program is the evolution of NASA's social actions through organizational learning. This study investigated how NASA learned over time following two catastrophic accidents. Schwandt's (1997) organizational Learning System Model (OLSM) characterized the learning in this High Reliability…

Leaders Learning from Leaders as an Emergent Action Learning Strategy Type of Paper: Account of Practice

ERIC Educational Resources Information Center

Mullen, Carol A.; Rodríguez, Mariela A.; Allen, Tawannah G.

2015-01-01

This account of practice describes what three executive leaders in a professional association have learned about action learning and their own practices of organizational renewal. Data are approached narratively and stories are told from the perspectives of diverse educators' experiences, agency, and expertise. Mature organizations can be…

Learning by Doing: A Handbook for Professional Learning Communities at Work™ (Second Edition)-- Action Guide

ERIC Educational Resources Information Center

Solution Tree, 2010

2010-01-01

This action guide is intended to assist in the reading of and reflection upon "Learning by Doing: A Handbook for Professional Learning Communities at Work, Second Edition" by Richard DuFour, Rebecca DuFour, Richard Eaker, and Thomas Many. The guide can be used by an individual, a small group, or an entire faculty to identify key points,…

Basic actions to reduce dropout rates in distance learning.

PubMed

Gregori, Pablo; Martínez, Vicente; Moyano-Fernández, Julio José

2018-02-01

Today's society, which is strongly based on knowledge and interaction with information, has a key component in technological innovation, a fundamental tool for the development of the current teaching methodologies. Nowadays, there are a lot of online resources, such as MOOCs (Massive Open Online Courses) and distance learning courses. One aspect that is common to all of these is a high dropout rate: about 90% in MOOCs and 50% in the courses of the Spanish National Distance Education University, among other examples. In this paper, we analyze a number of actions undertaken in the Master's Degree in Computational Mathematics at Universitat Jaume I in Castellón, Spain. These actions seem to help decrease the dropout rate in distance learning; the available data confirm their effectiveness. Copyright © 2017 Elsevier Ltd. All rights reserved.

Learning to reach by reinforcement learning using a receptive field based function approximation approach with continuous actions.

PubMed

Tamosiunaite, Minija; Asfour, Tamim; Wörgötter, Florentin

2009-03-01

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.

Problem-Based Learning Associated by Action-Process-Object-Schema (APOS) Theory to Enhance Students' High Order Mathematical Thinking Ability

ERIC Educational Resources Information Center

Mudrikah, Achmad

2016-01-01

The research has shown a model of learning activities that can be used to stimulate reflective abstraction in students. Reflective abstraction as a method of constructing knowledge in the Action-Process-Object-Schema theory, and is expected to occur when students are in learning activities, will be able to encourage students to make the process of…

E-Model for Online Learning Communities.

PubMed

Rogo, Ellen J; Portillo, Karen M

2015-10-01

The purpose of this study was to explore the students' perspectives on the phenomenon of online learning communities while enrolled in a graduate dental hygiene program. A qualitative case study method was designed to investigate the learners' experiences with communities in an online environment. A cross-sectional purposive sampling method was used. Interviews were the data collection method. As the original data were being analyzed, the researchers noted a pattern evolved indicating the phenomenon developed in stages. The data were re-analyzed and validated by 2 member checks. The participants' experiences revealed an e-model consisting of 3 stages of formal learning community development as core courses in the curriculum were completed and 1 stage related to transmuting the community to an informal entity as students experienced the independent coursework in the program. The development of the formal learning communities followed 3 stages: Building a Foundation for the Learning Community, Building a Supportive Network within the Learning Community and Investing in the Community to Enhance Learning. The last stage, Transforming the Learning Community, signaled a transition to an informal network of learners. The e-model was represented by 3 key elements: metamorphosis of relationships, metamorphosis through the affective domain and metamorphosis through the cognitive domain, with the most influential element being the affective development. The e-model describes a 4 stage process through which learners experience a metamorphosis in their affective, relationship and cognitive development. Synergistic learning was possible based on the interaction between synergistic relationships and affective actions. Copyright © 2015 The American Dental Hygienists’ Association.

Learning Sequences of Actions in Collectives of Autonomous Agents

NASA Technical Reports Server (NTRS)

Turner, Kagan; Agogino, Adrian K.; Wolpert, David H.; Clancy, Daniel (Technical Monitor)

2001-01-01

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'.

Do action learning sets facilitate collaborative, deliberative learning?: A focus group evaluation of Graduate Entry Pre-registration Nursing (GEN) students' experience.

PubMed

Maddison, Charlotte; Strang, Gus

2018-01-01

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.

Leadership Development in SMEs: An Action Learning Approach

ERIC Educational Resources Information Center

Leitch, Claire M.; McMullan, Christel; Harrison, Richard T.

2009-01-01

In this paper we evaluate an action learning-based, leadership development programme designed for founders and leaders of growth-oriented, entrepreneurial small to medium-sized enterprises. Based on in-depth, qualitative interviews with participants on one cohort, undertaken two years after completion of the seven-month programme, we demonstrate…

Managing and learning with multiple models: Objectives and optimization algorithms

USGS Publications Warehouse

Probert, William J. M.; Hauser, C.E.; McDonald-Madden, E.; Runge, M.C.; Baxter, P.W.J.; Possingham, H.P.

2011-01-01

The quality of environmental decisions should be gauged according to managers' objectives. Management objectives generally seek to maximize quantifiable measures of system benefit, for instance population growth rate. Reaching these goals often requires a certain degree of learning about the system. Learning can occur by using management action in combination with a monitoring system. Furthermore, actions can be chosen strategically to obtain specific kinds of information. Formal decision making tools can choose actions to favor such learning in two ways: implicitly via the optimization algorithm that is used when there is a management objective (for instance, when using adaptive management), or explicitly by quantifying knowledge and using it as the fundamental project objective, an approach new to conservation.This paper outlines three conservation project objectives - a pure management objective, a pure learning objective, and an objective that is a weighted mixture of these two. We use eight optimization algorithms to choose actions that meet project objectives and illustrate them in a simulated conservation project. The algorithms provide a taxonomy of decision making tools in conservation management when there is uncertainty surrounding competing models of system function. The algorithms build upon each other such that their differences are highlighted and practitioners may see where their decision making tools can be improved. ?? 2010 Elsevier Ltd.

Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach.

PubMed

Liu, Li; Shao, Ling; Li, Xuelong; Lu, Ke

2016-01-01

Extracting discriminative and robust features from video sequences is the first and most critical step in human action recognition. In this paper, instead of using handcrafted features, we automatically learn spatio-temporal motion features for action recognition. This is achieved via an evolutionary method, i.e., genetic programming (GP), which evolves the motion feature descriptor on a population of primitive 3D operators (e.g., 3D-Gabor and wavelet). In this way, the scale and shift invariant features can be effectively extracted from both color and optical flow sequences. We intend to learn data adaptive descriptors for different datasets with multiple layers, which makes fully use of the knowledge to mimic the physical structure of the human visual cortex for action recognition and simultaneously reduce the GP searching space to effectively accelerate the convergence of optimal solutions. In our evolutionary architecture, the average cross-validation classification error, which is calculated by an support-vector-machine classifier on the training set, is adopted as the evaluation criterion for the GP fitness function. After the entire evolution procedure finishes, the best-so-far solution selected by GP is regarded as the (near-)optimal action descriptor obtained. The GP-evolving feature extraction method is evaluated on four popular action datasets, namely KTH, HMDB51, UCF YouTube, and Hollywood2. Experimental results show that our method significantly outperforms other types of features, either hand-designed or machine-learned.

The Innovation Paradox: A Selective Review of the Literature on Action Learning and Innovation

ERIC Educational Resources Information Center

Pedler, Mike; Brook, Cheryl

2017-01-01

This paper explores selective literatures in the two fields of action learning and innovation, and seeks insights into the processes of, and connections between, innovation, engagement and implementation. We searched the action learning articles for references to innovation, beginning with the work of Revans, who highlights the innovation paradox,…

Turning to Case Studies as a Mechanism for Learning in Action Learning

ERIC Educational Resources Information Center

O'Leary, Denise; Coughlan, Paul; Rigg, Clare; Coghlan, David

2017-01-01

Case studies are a useful means of capturing and sharing experiential knowledge by allowing researchers to explore the social, organisational and political contexts of a specific case. Although accounts of action learning are often reported using a case study approach, it is not common to see individual case studies being used as a learning…

Inquiring into the Dilemmas of Implementing Action Learning. Innovative Session 6. [Concurrent Innovative Session at AHRD Annual Conference, 2000.

ERIC Educational Resources Information Center

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…

Count Me in: The Role of Action Learning in Making Learning and Skills Provision More Inclusive

ERIC Educational Resources Information Center

O'Toole, Gill

2007-01-01

This article explores the role of action learning in a national programme of research and development. The aim of the programme was to improve provision for disabled learners in the learning and skills sector by supporting providers in implementing the requirements of the Disability Discrimination Act (2002). Practitioners worked on a wide range…

Facilitating the learning process in design-based learning practices: an investigation of teachers' actions in supervising students

NASA Astrophysics Data System (ADS)

Gómez Puente, S. M.; van Eijck, M.; Jochems, W.

2013-11-01

Background: In research on design-based learning (DBL), inadequate attention is paid to the role the teacher plays in supervising students in gathering and applying knowledge to design artifacts, systems, and innovative solutions in higher education. Purpose: In this study, we examine whether teacher actions we previously identified in the DBL literature as important in facilitating learning processes and student supervision are present in current DBL engineering practices. Sample: The sample (N=16) consisted of teachers and supervisors in two engineering study programs at a university of technology: mechanical and electrical engineering. We selected randomly teachers from freshman and second-year bachelor DBL projects responsible for student supervision and assessment. Design and method: Interviews with teachers, and interviews and observations of supervisors were used to examine how supervision and facilitation actions are applied according to the DBL framework. Results: Major findings indicate that formulating questions is the most common practice seen in facilitating learning in open-ended engineering design environments. Furthermore, other DBL actions we expected to see based upon the literature were seldom observed in the coaching practices within these two programs. Conclusions: Professionalization of teachers in supervising students need to include methods to scaffold learning by supporting students in reflecting and in providing formative feedback.

The Reflective Teacher Leader: An Action Research Model

ERIC Educational Resources Information Center

Furtado, Leena; Anderson, Dawnette

2012-01-01

This study presents four teacher reflections from action research projects ranging from kindergarten to adult school improvements. A teacher leadership matrix guided participants to connect teaching and learning theory to best practices by exploring uncharted territory within an iterative cycle of research and action. Teachers developed the…

The Role of the NHS in the Development of Revans' Action Learning: Correspondence and Contradiction in Action Learning Development and Practice

ERIC Educational Resources Information Center

Brook, Cheryl

2010-01-01

In adapting Bowles' and Gintis's correspondence principle of education, this paper suggests that there are ways in which the theory and practice of action learning developed "in correspondence" with the NHS. In doing so, the paper draws, in part, upon an historical assessment of Revans' Hospital Internal Communications Project of the…

"Knowing Is Not Enough; We Must Apply": Reflections on a Failed Action Learning Application

ERIC Educational Resources Information Center

Reese, Simon

2015-01-01

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…

Methods and Techniques: An Action Learning Approach to Financial Management Training for Union Officers.

ERIC Educational Resources Information Center

Maunders, Keith

1988-01-01

The author reports on his experience in organizing and running a two-week workshop for finance officers of African trade unions. A notable aspect of this was an attempt to use action learning methodology. He illustrates the advantages and the barriers to applying the action learning philosophy in a relatively short-period, off-site training…

Bourdieu's Habitus and Field: Implications on the Practice and Theory of Critical Action Learning

ERIC Educational Resources Information Center

Warwick, Rob; McCray, Janet; Board, Douglas

2017-01-01

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…

Action selection performance of a reconfigurable basal ganglia inspired model with Hebbian–Bayesian Go-NoGo connectivity

PubMed Central

Berthet, Pierre; Hellgren-Kotaleski, Jeanette; Lansner, Anders

2012-01-01

Several studies have shown a strong involvement of the basal ganglia (BG) in action selection and dopamine dependent learning. The dopaminergic signal to striatum, the input stage of the BG, has been commonly described as coding a reward prediction error (RPE), i.e., the difference between the predicted and actual reward. The RPE has been hypothesized to be critical in the modulation of the synaptic plasticity in cortico-striatal synapses in the direct and indirect pathway. We developed an abstract computational model of the BG, with a dual pathway structure functionally corresponding to the direct and indirect pathways, and compared its behavior to biological data as well as other reinforcement learning models. The computations in our model are inspired by Bayesian inference, and the synaptic plasticity changes depend on a three factor Hebbian–Bayesian learning rule based on co-activation of pre- and post-synaptic units and on the value of the RPE. The model builds on a modified Actor-Critic architecture and implements the direct (Go) and the indirect (NoGo) pathway, as well as the reward prediction (RP) system, acting in a complementary fashion. We investigated the performance of the model system when different configurations of the Go, NoGo, and RP system were utilized, e.g., using only the Go, NoGo, or RP system, or combinations of those. Learning performance was investigated in several types of learning paradigms, such as learning-relearning, successive learning, stochastic learning, reversal learning and a two-choice task. The RPE and the activity of the model during learning were similar to monkey electrophysiological and behavioral data. Our results, however, show that there is not a unique best way to configure this BG model to handle well all the learning paradigms tested. We thus suggest that an agent might dynamically configure its action selection mode, possibly depending on task characteristics and also on how much time is available. PMID:23060764

Evaluating the Impact of Action Plans on Trainee Compliance with Learning Objectives

ERIC Educational Resources Information Center

Aumann, Michael J.

2013-01-01

This mixed methods research study evaluated the use of technology-based action plans as a way to help improve compliance with the learning objectives of an online training event. It explored how the action planning strategy impacted subjects in a treatment group and compared them to subjects in a control group who did not get the action plan. The…

Discovering and Articulating What Is Not yet Known: Using Action Learning and Grounded Theory as a Knowledge Management Strategy

ERIC Educational Resources Information Center

Pauleen, David J.; Corbitt, Brian; Yoong, Pak

2007-01-01

Purpose: To provide a conceptual model for the discovery and articulation of emergent organizational knowledge, particularly knowledge that develops when people work with new technologies. Design/methodology/approach: The model is based on two widely accepted research methods--action learning and grounded theory--and is illustrated using a case…

A Playbook for Data: Real-Life Scenario Demonstrates Learning Forward's Data Standard in Action

ERIC Educational Resources Information Center

Hirsh, Stephanie; Hord, Shirley

2012-01-01

This article is an excerpt from "A Playbook for Professional Learning: Putting the Standards Into Action" (Learning Forward, 2012). Written by Learning Forward Executive Director Stephanie Hirsh and Scholar Laureate Shirley Hord, "A Playbook for Professional Learning" provides those who work in professional learning with readily accessible…

Processing of action- but not stimulus-related prediction errors differs between active and observational feedback learning.

PubMed

Kobza, Stefan; Bellebaum, Christian

2015-01-01

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.

The Nurses Memorandum of 1938: A First Step in the Development of Action Learning?

ERIC Educational Resources Information Center

Bourner, Tom; Brook, Cheryl; Pedler, Mike

2018-01-01

This article concerns the origins of the idea of action learning, especially the claim by Revans that his Memorandum on "The Entry of Girls into the Nursing Profession" in Essex hospitals written in 1938 was the first step in the development of action learning. Whilst Revans repeatedly made this claim, there is no evidence in the actual…

Action Research in a Business Classroom--Another Lens to Examine Learning

ERIC Educational Resources Information Center

Smith, Janice Witt; Clark, Gloria

2010-01-01

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…

Learning from Action Research about Science Teacher Preparation

ERIC Educational Resources Information Center

Mitchener, Carole P.; Jackson, Wendy M.

2012-01-01

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…

Reconstructing constructivism: Causal models, Bayesian learning mechanisms and the theory theory

PubMed Central

Gopnik, Alison; Wellman, Henry M.

2012-01-01

We propose a new version of the “theory theory” grounded in the computational framework of probabilistic causal models and Bayesian learning. Probabilistic models allow a constructivist but rigorous and detailed approach to cognitive development. They also explain the learning of both more specific causal hypotheses and more abstract framework theories. We outline the new theoretical ideas, explain the computational framework in an intuitive and non-technical way, and review an extensive but relatively recent body of empirical results that supports these ideas. These include new studies of the mechanisms of learning. Children infer causal structure from statistical information, through their own actions on the world and through observations of the actions of others. Studies demonstrate these learning mechanisms in children from 16 months to 4 years old and include research on causal statistical learning, informal experimentation through play, and imitation and informal pedagogy. They also include studies of the variability and progressive character of intuitive theory change, particularly theory of mind. These studies investigate both the physical and psychological and social domains. We conclude with suggestions for further collaborative projects between developmental and computational cognitive scientists. PMID:22582739

Reconstructing constructivism: causal models, Bayesian learning mechanisms, and the theory theory.

PubMed

Gopnik, Alison; Wellman, Henry M

2012-11-01

We propose a new version of the "theory theory" grounded in the computational framework of probabilistic causal models and Bayesian learning. Probabilistic models allow a constructivist but rigorous and detailed approach to cognitive development. They also explain the learning of both more specific causal hypotheses and more abstract framework theories. We outline the new theoretical ideas, explain the computational framework in an intuitive and nontechnical way, and review an extensive but relatively recent body of empirical results that supports these ideas. These include new studies of the mechanisms of learning. Children infer causal structure from statistical information, through their own actions on the world and through observations of the actions of others. Studies demonstrate these learning mechanisms in children from 16 months to 4 years old and include research on causal statistical learning, informal experimentation through play, and imitation and informal pedagogy. They also include studies of the variability and progressive character of intuitive theory change, particularly theory of mind. These studies investigate both the physical and the psychological and social domains. We conclude with suggestions for further collaborative projects between developmental and computational cognitive scientists.

Model-based learning protects against forming habits.

PubMed

Gillan, Claire M; Otto, A Ross; Phelps, Elizabeth A; Daw, Nathaniel D

2015-09-01

Studies in humans and rodents have suggested that behavior can at times be "goal-directed"-that is, planned, and purposeful-and at times "habitual"-that is, inflexible and automatically evoked by stimuli. This distinction is central to conceptions of pathological compulsion, as in drug abuse and obsessive-compulsive disorder. Evidence for the distinction has primarily come from outcome devaluation studies, in which the sensitivity of a previously learned behavior to motivational change is used to assay the dominance of habits versus goal-directed actions. However, little is known about how habits and goal-directed control arise. Specifically, in the present study we sought to reveal the trial-by-trial dynamics of instrumental learning that would promote, and protect against, developing habits. In two complementary experiments with independent samples, participants completed a sequential decision task that dissociated two computational-learning mechanisms, model-based and model-free. We then tested for habits by devaluing one of the rewards that had reinforced behavior. In each case, we found that individual differences in model-based learning predicted the participants' subsequent sensitivity to outcome devaluation, suggesting that an associative mechanism underlies a bias toward habit formation in healthy individuals.

Developing Deep Group Reflection within a Critical Reflection Action Learning Set

ERIC Educational Resources Information Center

Shepherd, Gary

2016-01-01

This account of practice describes how a manufacturing company in the North of England transformed their approach to problem-solving and action through the use of a Critical Reflection Action Learning (CRAL) methodology. The company, who had been in business for over 25 years, experienced problems due to a diminishing customer base and substantial…

School-University Action Research: Impacts on Teaching Practices and Pupil Learning

ERIC Educational Resources Information Center

Attorps, Iiris; Kellner, Eva

2017-01-01

The aim of this article is to describe a design and implementation of a school-university action research project about teaching and learning biology and mathematics in primary school. Nine teachers in grades 1 to 6, in collaboration with two researchers, were using content representation (CoRe) in learning study (LS)-inspired cycle as pedagogical…

Learning Human Actions by Combining Global Dynamics and Local Appearance.

PubMed

Luo, Guan; Yang, Shuang; Tian, Guodong; Yuan, Chunfeng; Hu, Weiming; Maybank, Stephen J

2014-12-01

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.

Beyond the Information Given: Infants' Transfer of Actions Learned through Imitation

ERIC Educational Resources Information Center

Yang, Dahe; Sidman, Jason; Bushnell, Emily W.

2010-01-01

Five experiments were conducted to investigate infants' ability to transfer actions learned via imitation to new objects and to examine what components of the original context are critical to such transfer. Infants of 15 months observed an experimenter perform an action with one or two toys and then were offered a novel toy that was not…

Toddlers' imitative learning in interactive and observational contexts: the role of age and familiarity of the model.

PubMed

Shimpi, Priya M; Akhtar, Nameera; Moore, Chris

2013-10-01

Three experiments examined the effects of age and familiarity of a model on toddlers' imitative learning in observational contexts (Experiments 1, 2, and 3) and interactive contexts (Experiments 2 and 3). Experiment 1 (N=112 18-month-old toddlers) varied the age (child vs. adult) and long-term familiarity (kin vs. stranger) of the person who modeled the novel actions. Experiment 2 (N=48 18-month-olds and 48 24-month-olds) and Experiment 3 (N=48 24-month-olds) varied short-term familiarity with the model (some or none) and learning context (interactive or observational). The most striking findings were that toddlers were able to learn a new action from observing completely unfamiliar strangers who did not address them and were far less likely to imitate an unfamiliar model who directly interacted with them. These studies highlight the robustness of toddlers' observational learning and reveal limitations of learning from unfamiliar models in interactive contexts. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Learning to learn causal models.

PubMed

Kemp, Charles; Goodman, Noah D; Tenenbaum, Joshua B

2010-09-01

Learning to understand a single causal system can be an achievement, but humans must learn about multiple causal systems over the course of a lifetime. We present a hierarchical Bayesian framework that helps to explain how learning about several causal systems can accelerate learning about systems that are subsequently encountered. Given experience with a set of objects, our framework learns a causal model for each object and a causal schema that captures commonalities among these causal models. The schema organizes the objects into categories and specifies the causal powers and characteristic features of these categories and the characteristic causal interactions between categories. A schema of this kind allows causal models for subsequent objects to be rapidly learned, and we explore this accelerated learning in four experiments. Our results confirm that humans learn rapidly about the causal powers of novel objects, and we show that our framework accounts better for our data than alternative models of causal learning. Copyright © 2010 Cognitive Science Society, Inc.

The Effects of the Coordination Support on Shared Mental Models and Coordinated Action

ERIC Educational Resources Information Center

Kim, Hyunsong; Kim, Dongsik

2008-01-01

The purpose of this study was to examine the effects of coordination support (tool support and tutor support) on the development of shared mental models (SMMs) and coordinated action in a computer-supported collaborative learning environment. Eighteen students were randomly assigned to one of three conditions, including the tool condition, the…

Leading Change in Tissue Viability Best Practice: An Action Learning Programme for Link Nurse Practitioners

ERIC Educational Resources Information Center

Kellie, Jean; Henderson, Eileen; Milsom, Brian; Crawley, Hayley

2010-01-01

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…

Doing Different Things or Doing Things Different: Exploring the Role of Action Learning in Innovation

ERIC Educational Resources Information Center

Abbott, Christine; Weiss, Michael

2016-01-01

The notion of action learning driven innovation is explored with reference to three action-learning projects carried out in the last year and a proposed multi stakeholder project starting in 2016. The authors also provide an account of "innovation", including its rationale and characteristics, and argues for its particular suitability in…

Shared Mechanisms in the Estimation of Self-Generated Actions and the Prediction of Other's Actions by Humans.

PubMed

Ikegami, Tsuyoshi; Ganesh, Gowrishankar

2017-01-01

The question of how humans predict outcomes of observed motor actions by others is a fundamental problem in cognitive and social neuroscience. Previous theoretical studies have suggested that the brain uses parts of the forward model (used to estimate sensory outcomes of self-generated actions) to predict outcomes of observed actions. However, this hypothesis has remained controversial due to the lack of direct experimental evidence. To address this issue, we analyzed the behavior of darts experts in an understanding learning paradigm and utilized computational modeling to examine how outcome prediction of observed actions affected the participants' ability to estimate their own actions. We recruited darts experts because sports experts are known to have an accurate outcome estimation of their own actions as well as prediction of actions observed in others. We first show that learning to predict the outcomes of observed dart throws deteriorates an expert's abilities to both produce his own darts actions and estimate the outcome of his own throws (or self-estimation). Next, we introduce a state-space model to explain the trial-by-trial changes in the darts performance and self-estimation through our experiment. The model-based analysis reveals that the change in an expert's self-estimation is explained only by considering a change in the individual's forward model, showing that an improvement in an expert's ability to predict outcomes of observed actions affects the individual's forward model. These results suggest that parts of the same forward model are utilized in humans to both estimate outcomes of self-generated actions and predict outcomes of observed actions.

Neurocognitive mechanisms underlying social learning in infancy: infants' neural processing of the effects of others' actions.

PubMed

Paulus, Markus; Hunnius, Sabine; Bekkering, Harold

2013-10-01

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.

Exploring the Challenges in Scaling up the Delivery of Action Learning Facilitator Training within a Global Organisation

ERIC Educational Resources Information Center

Antell, Sonja; Heywood, John

2015-01-01

Action learning is often used as an element of leadership development programmes. The intention is to support classroom learning with an experiential thread which runs throughout the life of the programme. Action Learning Associates (ALA) has been working with an international organisation for three years to deliver the global "First Line…

Using the Cognitive Apprenticeship Model with a Chat Tool to Enhance Online Collaborative Learning

ERIC Educational Resources Information Center

Rodríguez-Bonces, Mónica; Ortiz, Kris

2016-01-01

In Colombia, many institutions are in the firm quest of virtual learning environments to improve instruction, and making the most of online tools is clearly linked to offering quality learning. Thus, the purpose of this action research was to identify how the Cognitive Apprenticeship Model enhances online collaborative learning by using a chat…

Dissecting children's observational learning of complex actions through selective video displays.

PubMed

Flynn, Emma; Whiten, Andrew

2013-10-01

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.

The Relationship of Learning Traits, Motivation and Performance-Learning Response Dynamics

ERIC Educational Resources Information Center

Hwang, Wu-Yuin; Chang, Chen-Bin; Chen, Gan-Jung

2004-01-01

This paper proposes a model of learning dynamics and learning energy, one that analyzes learning systems scientifically. This model makes response to the learner action by means of some equations relating to learning dynamics, learning energy, learning speed, learning force, and learning acceleration, which is analogous to the notion of Newtonian…

The Ongoing Development of an Effective Model of Action Learning for Use by the Busy GP Veterinary Surgeon

ERIC Educational Resources Information Center

Shuttleworth, Sue

2005-01-01

I passionately believe that reflective practice is an essential competency for the busy GP veterinary surgeon to develop throughout their career. Action learning sets would appear to offer a way of promoting this while at the same time helping the GP veterinary surgeon find a way forward with professional issues. In this article I reflect on my…

Action Learning and Organisation Development: Overlapping Fields of Practice

ERIC Educational Resources Information Center

Edmonstone, John

2011-01-01

This paper explores the relationship between action learning and Organisation Development (OD). It proposes that they are overlapping fields of practice, with interesting similarities and differences. Both fields of practice are experienced as challenging to conventional ways of viewing organisations and people but are also subject to increasing…

Supplemental action learning workshops: Understanding the effects of independent and cooperative workshops on students' knowledge

NASA Astrophysics Data System (ADS)

Morris, Kathryn Michelle

Community colleges enroll more than half of the undergraduate population in the United States, thereby retaining students of varying demographics with extracurricular demands differing from traditional four-year university students. Often in a collegiate lecture course, students are limited in their abilities to absorb and process information presented by their instructors due to content-specific cognitive gaps between the instructor and the student (Preszler, 2009). Research has shown that implementation of instructor-facilitated action learning workshops as supplemental instruction may help bridge these cognitive gaps allowing better student conceptualization and dissemination of knowledge (Drake, 2011; Fullilove & Treisman, 1990; Preszler, 2009; Udovic, Morris, Dickman, Postlethwait, & Wetherwax, 2002). The purpose of this study was to determine the effects of cooperative action learning workshops and independent action learning workshops on students' knowledge of specified topics within a General Biology I with lab course. The results of this investigation indicate that implementation of an instructor-facilitated action learning workshop did not affect students' knowledge gain; furthermore, attendance of a particular workshop style (independent or cooperative) did not affect students' knowledge gain.

Ares I-X Thermal Model Correlation and Lessons Learned

NASA Technical Reports Server (NTRS)

Amundsen, Ruth M.

2010-01-01

The Ares I-X vehicle launched and flew successfully on October 28, 2009. This paper will describe the correlation of the vehicle thermal model to both ground testing and flight data. A main purpose of the vehicle model and ground testing was to ensure that the avionics within the vehicle were held within their thermal limits prior to launch and during flight. The correlation of the avionics box temperatures will be shown. Also, the lessons learned in the thermal discipline during the modeling, test, correlation to test, and flight of the Ares I-X flight test vehicle will be described. Lessons learned will cover thermal modeling, as well as management of the thermal discipline, thermal team, and thermal-related actions in design, testing, and flight.

Cognitive-Motivational Determinants of Residents' Civic Engagement and Health (Inequities) in the Context of Noise Action Planning: A Conceptual Model.

PubMed

Riedel, Natalie; van Kamp, Irene; Köckler, Heike; Scheiner, Joachim; Loerbroks, Adrian; Claßen, Thomas; Bolte, Gabriele

2017-05-30

The Environmental Noise Directive expects residents to be actively involved in localising and selecting noise abatement interventions during the noise action planning process. Its intervention impact is meant to be homogeneous across population groups. Against the background of social heterogeneity and environmental disparities, however, the impact of noise action planning on exposure to traffic-related noise and its health effects is unlikely to follow homogenous distributions. Until now, there has been no study evaluating the impact of noise action measures on the social distribution of traffic-related noise exposure and health outcomes. We develop a conceptual (logic) model on cognitive-motivational determinants of residents' civic engagement and health (inequities) by integrating arguments from the Model on household's Vulnerability to the local Environment, the learned helplessness model in environmental psychology, the Cognitive Activation Theory of Stress, and the reserve capacity model. Specifically, we derive four hypothetical patterns of cognitive-motivational determinants yielding different levels of sustained physiological activation and expectancies of civic engagement. These patterns may help us understand why health inequities arise in the context of noise action planning and learn how to transform noise action planning into an instrument conducive to health equity. While building on existing frameworks, our conceptual model will be tested empirically in the next stage of our research process.

Variability in Dopamine Genes Dissociates Model-Based and Model-Free Reinforcement Learning

PubMed Central

Bath, Kevin G.; Daw, Nathaniel D.; Frank, Michael J.

2016-01-01

Considerable evidence suggests that multiple learning systems can drive behavior. Choice can proceed reflexively from previous actions and their associated outcomes, as captured by “model-free” learning algorithms, or flexibly from prospective consideration of outcomes that might occur, as captured by “model-based” learning algorithms. However, differential contributions of dopamine to these systems are poorly understood. Dopamine is widely thought to support model-free learning by modulating plasticity in striatum. Model-based learning may also be affected by these striatal effects, or by other dopaminergic effects elsewhere, notably on prefrontal working memory function. Indeed, prominent demonstrations linking striatal dopamine to putatively model-free learning did not rule out model-based effects, whereas other studies have reported dopaminergic modulation of verifiably model-based learning, but without distinguishing a prefrontal versus striatal locus. To clarify the relationships between dopamine, neural systems, and learning strategies, we combine a genetic association approach in humans with two well-studied reinforcement learning tasks: one isolating model-based from model-free behavior and the other sensitive to key aspects of striatal plasticity. Prefrontal function was indexed by a polymorphism in the COMT gene, differences of which reflect dopamine levels in the prefrontal cortex. This polymorphism has been associated with differences in prefrontal activity and working memory. Striatal function was indexed by a gene coding for DARPP-32, which is densely expressed in the striatum where it is necessary for synaptic plasticity. We found evidence for our hypothesis that variations in prefrontal dopamine relate to model-based learning, whereas variations in striatal dopamine function relate to model-free learning. SIGNIFICANCE STATEMENT Decisions can stem reflexively from their previously associated outcomes or flexibly from deliberative

Variability in Dopamine Genes Dissociates Model-Based and Model-Free Reinforcement Learning.

PubMed

Doll, Bradley B; Bath, Kevin G; Daw, Nathaniel D; Frank, Michael J

2016-01-27

Considerable evidence suggests that multiple learning systems can drive behavior. Choice can proceed reflexively from previous actions and their associated outcomes, as captured by "model-free" learning algorithms, or flexibly from prospective consideration of outcomes that might occur, as captured by "model-based" learning algorithms. However, differential contributions of dopamine to these systems are poorly understood. Dopamine is widely thought to support model-free learning by modulating plasticity in striatum. Model-based learning may also be affected by these striatal effects, or by other dopaminergic effects elsewhere, notably on prefrontal working memory function. Indeed, prominent demonstrations linking striatal dopamine to putatively model-free learning did not rule out model-based effects, whereas other studies have reported dopaminergic modulation of verifiably model-based learning, but without distinguishing a prefrontal versus striatal locus. To clarify the relationships between dopamine, neural systems, and learning strategies, we combine a genetic association approach in humans with two well-studied reinforcement learning tasks: one isolating model-based from model-free behavior and the other sensitive to key aspects of striatal plasticity. Prefrontal function was indexed by a polymorphism in the COMT gene, differences of which reflect dopamine levels in the prefrontal cortex. This polymorphism has been associated with differences in prefrontal activity and working memory. Striatal function was indexed by a gene coding for DARPP-32, which is densely expressed in the striatum where it is necessary for synaptic plasticity. We found evidence for our hypothesis that variations in prefrontal dopamine relate to model-based learning, whereas variations in striatal dopamine function relate to model-free learning. Decisions can stem reflexively from their previously associated outcomes or flexibly from deliberative consideration of potential choice outcomes

Associative vocabulary learning: development and testing of two paradigms for the (re-) acquisition of action- and object-related words.

PubMed

Freundlieb, Nils; Ridder, Volker; Dobel, Christian; Enriquez-Geppert, Stefanie; Baumgaertner, Annette; Zwitserlood, Pienie; Gerloff, Christian; Hummel, Friedhelm C; Liuzzi, Gianpiero

2012-01-01

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

Launch of Revans Academy for Action Learning and Research: Manchester Business School November 26, 2008

ERIC Educational Resources Information Center

Clark, Elaine

2009-01-01

This article reports on the launching of the Revans Academy for Action Learning and Research at Manchester Business School on 26 November 2008. The goal of the Academy is to foster the development of action learning as a unifying framework within Manchester Business School. Its goal is to provide a hub for dialogue, collaboration, exploitation and…

Actionable Data Projects: Social Science and Service-Learning in General Education Courses

ERIC Educational Resources Information Center

Maloyed, Christie L.

2016-01-01

The use of service-learning pedagogies in general education courses is often limited to increasing volunteerism or civic literacy with problem-based or research-based projects reserved for upper level courses. This article examines the implementation of an "actionable data" service-learning project in an introductory, general studies…

Implementing Action Research and Professional Learning Communities in a Professional Development School Setting to Support Teacher Candidate Learning

ERIC Educational Resources Information Center

Shanks, Joyce

2016-01-01

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…

After-Action Reports: Capturing Lessons Learned and Identifying Areas for Improvement. Lessons Learned from School Crises and Emergencies. Volume 2, Issue 1, 2007

ERIC Educational Resources Information Center

US Department of Education, 2007

2007-01-01

"Lessons Learned" is a series of publications that are a brief recounting of actual school emergencies and crises. This issue of "Lessons Learned" addresses after-action reports, which are an integral part of the emergency preparedness planning continuum and support effective crisis response. After-action reports have a threefold purpose. They…

An Extreme Case of Action Learning at BAT Niemeyer

ERIC Educational Resources Information Center

Eckstein, Emiel; Veenhoven, Gert; De Loo, Ivo

2009-01-01

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…

Towards Actionable Learning Analytics Using Dispositions

ERIC Educational Resources Information Center

Tempelaar, Dirk T.; Rienties, Bart; Nguyen, Quan

2017-01-01

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…

Corticostriatal circuit mechanisms of value-based action selection: Implementation of reinforcement learning algorithms and beyond.

PubMed

Morita, Kenji; Jitsev, Jenia; Morrison, Abigail

2016-09-15

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.

Toward Self-Referential Autonomous Learning of Object and Situation Models.

PubMed

Damerow, Florian; Knoblauch, Andreas; Körner, Ursula; Eggert, Julian; Körner, Edgar

2016-01-01

Most current approaches to scene understanding lack the capability to adapt object and situation models to behavioral needs not anticipated by the human system designer. Here, we give a detailed description of a system architecture for self-referential autonomous learning which enables the refinement of object and situation models during operation in order to optimize behavior. This includes structural learning of hierarchical models for situations and behaviors that is triggered by a mismatch between expected and actual action outcome. Besides proposing architectural concepts, we also describe a first implementation of our system within a simulated traffic scenario to demonstrate the feasibility of our approach.

Layers of Learning: Promoting Performance Improvement and Action Learning in Higher Education. Innovative Session 5. [AHRD Conference, 2001].

ERIC Educational Resources Information Center

Foucar-Szocki, Diane; Mitchell, Randy; Larson, Rick; Harris, Laurie; Sherman, Nancy

This document presents a case study for an innovative session exploring the nature of learning and the relationship between action learning within academic programs in adult education/human resource development (HRD) and the higher education institutions that house them. The first two sections discuss the dilemmas confronting higher education and…

A computational model of Dopamine and Acetylcholine aberrant learning in Basal Ganglia.

PubMed

Baston, Chiara; Ursino, Mauro

2015-01-01

Basal Ganglia (BG) are implied in many motor and cognitive tasks, such as action selection, and have a central role in many pathologies, primarily Parkinson Disease. In the present work, we use a recently developed biologically inspired BG model to analyze how the dopamine (DA) level can affect the temporal response during action selection, and the capacity to learn new actions following rewards and punishments. The model incorporates the 3 main pathways (direct, indirect and hyperdirect) working in BG functioning. The behavior of 2 alternative networks (the first with normal DA levels, the second with reduced DA) is analyzed both in untrained conditions, and during training performed in different epochs. The results show that reduced DA causes delayed temporal responses in the untrained network, and difficult of learning during training, characterized by the necessity of much more epochs. The results provide interesting hints to understand the behavior of healthy and dopamine depleted subjects, such as parkinsonian patients.

What can action learning offer a beleaguered system? A narrative representing the relationship.

PubMed

Traeger, James

2017-05-02

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.

An Action Learning Project on Diversity: Pitfalls and Possibilities.

ERIC Educational Resources Information Center

Hite, Linda M.

1997-01-01

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…

Sowing the Seeds of Change: Action Learning in Merseytravel

ERIC Educational Resources Information Center

Thornton, Andy

2010-01-01

Merseytravel is a large and diverse public sector organisation facing significant changes, but faced with a cultural inertia which is a legacy inherited from historical management styles. Action learning is now being used with great success as part of their change programme, to promote empowerment of the staff, challenge historical ways of working…

The Compatibility of Action Learning with Inner Game Coaching

ERIC Educational Resources Information Center

Aitkenhead, Andy

2009-01-01

Using "inner game" coaching techniques in the remediation of a challenged programme at a Global Investment Bank the environment was transformed into a delivery focused culture. The techniques included group sessions that would be familiar to anyone aware of action learning and were an integral part of the strategy to ensure sustainable…

Using Science to Take a Stand: Action-Oriented Learning in an Afterschool Science Club

NASA Astrophysics Data System (ADS)

Hagenah, Sara

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.

Imitative Learning of Actions on Objects by Children, Chimpanzees, and Enculturated Chimpanzees.

ERIC Educational Resources Information Center

Tomasello, Michael; And Others

1993-01-01

Compared the abilities of 3 mother-reared and 3 human-raised (enculturated) chimpanzees and 16 human toddlers to imitatively learn novel actions on objects. Found that mother-reared chimpanzees were poorer imitators than both enculturated chimpanzees and human children, who did not differ from one another in imitative learning. On time delay…

The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

PubMed

Orr, Mark G; Thrush, Roxanne; Plaut, David C

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

The Theory of Reasoned Action as Parallel Constraint Satisfaction: Towards a Dynamic Computational Model of Health Behavior

PubMed Central

Orr, Mark G.; Thrush, Roxanne; Plaut, David C.

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual’s pre-existing belief structure and the beliefs of others in the individual’s social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics. PMID:23671603

Action Learning for Organizational and Systemic Development: Towards a "Both-and" Understanding of "I" and "We"

ERIC Educational Resources Information Center

Rigg, Clare

2008-01-01

In public services delivery, action learning is increasingly employed in the hope of improving capacity to address complex, multi-casual and "wicked" social issues to improve the lives of citizens. Yet the understanding of how and why action learning might have potential for enhancing organizational or systemic capability rarely goes…

Virtual Action Learning: A Pilot in Building Leadership Capacity

ERIC Educational Resources Information Center

Radcliff, Phil

2017-01-01

This account of practice encompasses a pilot virtual action learning programme with a small group of learners. This was an 18-month extension to the one-week Leadership Open Programme that the participants had previously completed at the Business School. It includes insights from an evaluation study completed in early 2016. It considers in…

Learning Difficulties and Ethnicity: Updating a Framework for Action

ERIC Educational Resources Information Center

Poxton, Richard

2012-01-01

This update of the Framework for Action highlights the continuing relevance of its message as well as those raised by Valuing People Now. People with learning difficulties and their families from Black and minority ethnic (BME) communities have been highlighted as a priority group by Valuing People since 2001 and remain a priority for better…

Action Prediction Allows Hypothesis Testing via Internal Forward Models at 6 Months of Age

PubMed Central

Gredebäck, Gustaf; Lindskog, Marcus; Juvrud, Joshua C.; Green, Dorota; Marciszko, Carin

2018-01-01

We propose that action prediction provides a cornerstone in a learning process known as internal forward models. According to this suggestion infants’ predictions (looking to the mouth of someone moving a spoon upward) will moments later be validated or proven false (spoon was in fact directed toward a bowl), information that is directly perceived as the distance between the predicted and actual goal. Using an individual difference approach we demonstrate that action prediction correlates with the tendency to react with surprise when social interactions are not acted out as expected (action evaluation). This association is demonstrated across tasks and in a large sample (n = 118) at 6 months of age. These results provide the first indication that infants might rely on internal forward models to structure their social world. Additional analysis, consistent with prior work and assumptions from embodied cognition, demonstrates that the latency of infants’ action predictions correlate with the infant’s own manual proficiency. PMID:29593600

Integrating cortico-limbic-basal ganglia architectures for learning model-based and model-free navigation strategies

PubMed Central

Khamassi, Mehdi; Humphries, Mark D.

2012-01-01

Behavior in spatial navigation is often organized into map-based (place-driven) vs. map-free (cue-driven) strategies; behavior in operant conditioning research is often organized into goal-directed vs. habitual strategies. Here we attempt to unify the two. We review one powerful theory for distinct forms of learning during instrumental conditioning, namely model-based (maintaining a representation of the world) and model-free (reacting to immediate stimuli) learning algorithms. We extend these lines of argument to propose an alternative taxonomy for spatial navigation, showing how various previously identified strategies can be distinguished as “model-based” or “model-free” depending on the usage of information and not on the type of information (e.g., cue vs. place). We argue that identifying “model-free” learning with dorsolateral striatum and “model-based” learning with dorsomedial striatum could reconcile numerous conflicting results in the spatial navigation literature. From this perspective, we further propose that the ventral striatum plays key roles in the model-building process. We propose that the core of the ventral striatum is positioned to learn the probability of action selection for every transition between states of the world. We further review suggestions that the ventral striatal core and shell are positioned to act as “critics” contributing to the computation of a reward prediction error for model-free and model-based systems, respectively. PMID:23205006

Shared Mechanisms in the Estimation of Self-Generated Actions and the Prediction of Other’s Actions by Humans

PubMed Central

Ganesh, Gowrishankar

2017-01-01

Abstract The question of how humans predict outcomes of observed motor actions by others is a fundamental problem in cognitive and social neuroscience. Previous theoretical studies have suggested that the brain uses parts of the forward model (used to estimate sensory outcomes of self-generated actions) to predict outcomes of observed actions. However, this hypothesis has remained controversial due to the lack of direct experimental evidence. To address this issue, we analyzed the behavior of darts experts in an understanding learning paradigm and utilized computational modeling to examine how outcome prediction of observed actions affected the participants’ ability to estimate their own actions. We recruited darts experts because sports experts are known to have an accurate outcome estimation of their own actions as well as prediction of actions observed in others. We first show that learning to predict the outcomes of observed dart throws deteriorates an expert’s abilities to both produce his own darts actions and estimate the outcome of his own throws (or self-estimation). Next, we introduce a state-space model to explain the trial-by-trial changes in the darts performance and self-estimation through our experiment. The model-based analysis reveals that the change in an expert’s self-estimation is explained only by considering a change in the individual’s forward model, showing that an improvement in an expert’s ability to predict outcomes of observed actions affects the individual’s forward model. These results suggest that parts of the same forward model are utilized in humans to both estimate outcomes of self-generated actions and predict outcomes of observed actions. PMID:29340300

Living While Being Alive: Education and Learning in the Treatment Action Campaign

ERIC Educational Resources Information Center

Endresen, Kristin; Von Kotze, Astrid

2005-01-01

This paper is based on research into the Treatment Action Campaign (TAC) in South Africa. The research investigated whether, through being active members of this social movement, HIV-positive activists learn things they could not otherwise learn about their status and the epidemic, and how they put such knowledge to use. We show how activists…

Role of research in occupational therapy clinical practice: applying action learning and action research in pursuit of evidence-based practice.

PubMed

du Toit, Sanet H J; Wilkinson, Annette C; Adam, Kerry

2010-10-01

 In South Africa, as in many other countries, the development of research capacity in students and their early professional career is regarded as of major importance. Within the context of clinical education for occupational therapy students at the University of the Free State, a lecturer and her students embarked on a collaborative journey while fulfilling the requirements of their undergraduate curriculum. The outcome is a model promoting evidence-based practice (EBP) during service development on a dementia care ward. The practical use of action learning, action research (ALAR) approach in the clinical context, was used to encourage student engagement in successive small-scale research projects while simulating EBP. The projects ranged from the development of therapeutic multi-sensory environments to compiling activity profiles for identified residents. At the same time, students had the opportunity to experience the value of a scientific approach to practice development, which stimulated their awareness of the importance of research. Reflection by the researcher contributed towards more effective ways for compiling project assignments and a formalised approach for assessing projects. Students described personal and professional gains because of participation in projects against the life-changing experience of rendering a service to elderly persons suffering from dementia. The formalised approach guiding thoughts and actions finally assisted in developing a practical process model that could support EBP. The ALAR model contributed towards a scholarship of practice where the students, clinical educator and residents of a dementia unit all experienced the value of research. © 2010 The Authors. Australian Occupational Therapy Journal © 2010 Australian Association of Occupational Therapists.

Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling

PubMed Central

Cuperlovic-Culf, Miroslava

2018-01-01

Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of machine learning methods has been applied in bioinformatics and metabolism analyses including self-organizing maps, support vector machines, the kernel machine, Bayesian networks or fuzzy logic. To a lesser extent, machine learning has also been utilized to take advantage of the increasing availability of genomics and metabolomics data for the optimization of metabolic network models and their analysis. In this context, machine learning has aided the development of metabolic networks, the calculation of parameters for stoichiometric and kinetic models, as well as the analysis of major features in the model for the optimal application of bioreactors. Examples of this very interesting, albeit highly complex, application of machine learning for metabolism modeling will be the primary focus of this review presenting several different types of applications for model optimization, parameter determination or system analysis using models, as well as the utilization of several different types of machine learning technologies. PMID:29324649

Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling.

PubMed

Cuperlovic-Culf, Miroslava

2018-01-11

Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of machine learning methods has been applied in bioinformatics and metabolism analyses including self-organizing maps, support vector machines, the kernel machine, Bayesian networks or fuzzy logic. To a lesser extent, machine learning has also been utilized to take advantage of the increasing availability of genomics and metabolomics data for the optimization of metabolic network models and their analysis. In this context, machine learning has aided the development of metabolic networks, the calculation of parameters for stoichiometric and kinetic models, as well as the analysis of major features in the model for the optimal application of bioreactors. Examples of this very interesting, albeit highly complex, application of machine learning for metabolism modeling will be the primary focus of this review presenting several different types of applications for model optimization, parameter determination or system analysis using models, as well as the utilization of several different types of machine learning technologies.

From creatures of habit to goal-directed learners: Tracking the developmental emergence of model-based reinforcement learning

PubMed Central

Decker, Johannes H.; Otto, A. Ross; Daw, Nathaniel D.; Hartley, Catherine A.

2016-01-01

Theoretical models distinguish two decision-making strategies that have been formalized in reinforcement-learning theory. A model-based strategy leverages a cognitive model of potential actions and their consequences to make goal-directed choices, whereas a model-free strategy evaluates actions based solely on their reward history. Research in adults has begun to elucidate the psychological mechanisms and neural substrates underlying these learning processes and factors that influence their relative recruitment. However, the developmental trajectory of these evaluative strategies has not been well characterized. In this study, children, adolescents, and adults, performed a sequential reinforcement-learning task that enables estimation of model-based and model-free contributions to choice. Whereas a model-free strategy was evident in choice behavior across all age groups, evidence of a model-based strategy only emerged during adolescence and continued to increase into adulthood. These results suggest that recruitment of model-based valuation systems represents a critical cognitive component underlying the gradual maturation of goal-directed behavior. PMID:27084852

From Creatures of Habit to Goal-Directed Learners: Tracking the Developmental Emergence of Model-Based Reinforcement Learning.

PubMed

Decker, Johannes H; Otto, A Ross; Daw, Nathaniel D; Hartley, Catherine A

2016-06-01

Theoretical models distinguish two decision-making strategies that have been formalized in reinforcement-learning theory. A model-based strategy leverages a cognitive model of potential actions and their consequences to make goal-directed choices, whereas a model-free strategy evaluates actions based solely on their reward history. Research in adults has begun to elucidate the psychological mechanisms and neural substrates underlying these learning processes and factors that influence their relative recruitment. However, the developmental trajectory of these evaluative strategies has not been well characterized. In this study, children, adolescents, and adults performed a sequential reinforcement-learning task that enabled estimation of model-based and model-free contributions to choice. Whereas a model-free strategy was apparent in choice behavior across all age groups, a model-based strategy was absent in children, became evident in adolescents, and strengthened in adults. These results suggest that recruitment of model-based valuation systems represents a critical cognitive component underlying the gradual maturation of goal-directed behavior. © The Author(s) 2016.

Cognitive-Motivational Determinants of Residents’ Civic Engagement and Health (Inequities) in the Context of Noise Action Planning: A Conceptual Model

PubMed Central

Riedel, Natalie; van Kamp, Irene; Köckler, Heike; Scheiner, Joachim; Loerbroks, Adrian; Claßen, Thomas; Bolte, Gabriele

2017-01-01

The Environmental Noise Directive expects residents to be actively involved in localising and selecting noise abatement interventions during the noise action planning process. Its intervention impact is meant to be homogeneous across population groups. Against the background of social heterogeneity and environmental disparities, however, the impact of noise action planning on exposure to traffic-related noise and its health effects is unlikely to follow homogenous distributions. Until now, there has been no study evaluating the impact of noise action measures on the social distribution of traffic-related noise exposure and health outcomes. We develop a conceptual (logic) model on cognitive-motivational determinants of residents’ civic engagement and health (inequities) by integrating arguments from the Model on household’s Vulnerability to the local Environment, the learned helplessness model in environmental psychology, the Cognitive Activation Theory of Stress, and the reserve capacity model. Specifically, we derive four hypothetical patterns of cognitive-motivational determinants yielding different levels of sustained physiological activation and expectancies of civic engagement. These patterns may help us understand why health inequities arise in the context of noise action planning and learn how to transform noise action planning into an instrument conducive to health equity. While building on existing frameworks, our conceptual model will be tested empirically in the next stage of our research process. PMID:28556813

An Action Learning Method for Increased Innovation Capability in Organisations

ERIC Educational Resources Information Center

Olsson, Annika; Wadell, Carl; Odenrick, Per; Norell Bergendahl, Margareta

2010-01-01

Product innovation in highly complex and technological areas, such as medical technology, puts high requirements on the innovation capability of an organisation. Previous research and publications have highlighted organisational issues and learning matters as important and necessary for the development of innovation capability. Action learning…

"Cast Your Net Widely": Three Steps to Expanding and Refining Your Problem before Action Learning Application

ERIC Educational Resources Information Center

Reese, Simon R.

2015-01-01

This paper reflects upon a three-step process to expand the problem definition in the early stages of an action learning project. The process created a community-powered problem-solving approach within the action learning context. The simple three steps expanded upon in the paper create independence, dependence, and inter-dependence to aid the…

The Coordination Dynamics of Observational Learning: Relative Motion Direction and Relative Phase as Informational Content Linking Action-Perception to Action-Production.

PubMed

Buchanan, John J

2016-01-01

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.

Beyond You and Me: Stories for Collective Action and Learning? Perspectives from an Action Research Project

ERIC Educational Resources Information Center

Gearty, Margaret

2015-01-01

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…

Implementing Blended Self-Managed Action Learning for Digital Entrepreneurs in Higher Education

ERIC Educational Resources Information Center

Shurville, Simon; Rospigliosi, Asher

2009-01-01

We report upon implementing blended self-managed action learning (SMAL) within graduate and postgraduate courses in digital entrepreneurship. In four out of five cases, we found that SMAL was highly motivating to our learners and integrated well with a blended and flexible approach to learning. We report a case where a SMAL set broke down due to…

First Time Facilitator's Experience: Designing and Facilitating an Action Learning Programme in China

ERIC Educational Resources Information Center

Wang, Jinshuai; Bloodworth, Mike

2016-01-01

This paper describes an action learning programme with China Unicom Broadband Limited (CUBO) to support its vision of transforming to become a world-leading broadband communications and information service provider. 64 Department directors and supervisors were invited to take part in the "China Unicom Broadband Online Phoenix Action Learning…

An Action Research Study from Implementing the Flipped Classroom Model in Primary School History Teaching and Learning

ERIC Educational Resources Information Center

Aidinopoulou, Vasiliki; Sampson, Demetrios G.

2017-01-01

The benefits of the flipped classroom (FC) model in students' learning are claimed in many recent studies. These benefits are typically accounted to the pedagogically efficient use of classroom time for engaging students in active learning. Although there are several relevant studies for the deployment of the FC model in Science, Technology,…

Using Action Learning Sets to Support Students Managing Transition into the Clinical Learning Environment in a UK Medical School

ERIC Educational Resources Information Center

McKee, Anne; Markless, Sharon

2017-01-01

This paper reports on a Curriculum Innovation Project to empower third-year Undergraduate Medical students to recognise learning opportunities in their clinical placements and to proactively use them to develop their understanding and practice. The project created action learning sets (ALS) in response to the challenges students face when trying…

Imitation and observational learning of hand actions: prefrontal involvement and connectivity.

PubMed

Higuchi, S; Holle, H; Roberts, N; Eickhoff, S B; Vogt, S

2012-01-16

The first aim of this event-related fMRI study was to identify the neural circuits involved in imitation learning. We used a rapid imitation task where participants directly imitated pictures of guitar chords. The results provide clear evidence for the involvement of dorsolateral prefrontal cortex, as well as the fronto-parietal mirror circuit (FPMC) during action imitation when the requirements for working memory are low. Connectivity analyses further indicated a robust connectivity between left prefrontal cortex and the components of the FPMC bilaterally. We conclude that a mechanism of automatic perception-action matching alone is insufficient to account for imitation learning. Rather, the motor representation of an observed, complex action, as provided by the FPMC, only serves as the 'raw material' for higher-order supervisory and monitoring operations associated with the prefrontal cortex. The second aim of this study was to assess whether these neural circuits are also recruited during observational practice (OP, without motor execution), or only during physical practice (PP). Whereas prefrontal cortex was not consistently activated in action observation across all participants, prefrontal activation intensities did predict the behavioural practice effects, thus indicating a crucial role of prefrontal cortex also in OP. In addition, whilst OP and PP produced similar activation intensities in the FPMC when assessed during action observation, during imitative execution, the practice-related activation decreases were significantly more pronounced for PP than for OP. This dissociation indicates a lack of execution-related resources in observationally practised actions. More specifically, we found neural efficiency effects in the right motor cingulate-basal ganglia circuit and the FPMC that were only observed after PP but not after OP. Finally, we confirmed that practice generally induced activation decreases in the FPMC during both action observation and

"Model age-based" and "copy when uncertain" biases in children's social learning of a novel task.

PubMed

Wood, Lara A; Harrison, Rachel A; Lucas, Amanda J; McGuigan, Nicola; Burdett, Emily R R; Whiten, Andrew

2016-10-01

Theoretical models of social learning predict that individuals can benefit from using strategies that specify when and whom to copy. Here the interaction of two social learning strategies, model age-based biased copying and copy when uncertain, was investigated. Uncertainty was created via a systematic manipulation of demonstration efficacy (completeness) and efficiency (causal relevance of some actions). The participants, 4- to 6-year-old children (N=140), viewed both an adult model and a child model, each of whom used a different tool on a novel task. They did so in a complete condition, a near-complete condition, a partial demonstration condition, or a no-demonstration condition. Half of the demonstrations in each condition incorporated causally irrelevant actions by the models. Social transmission was assessed by first responses but also through children's continued fidelity, the hallmark of social traditions. Results revealed a bias to copy the child model both on first response and in continued interactions. Demonstration efficacy and efficiency did not affect choice of model at first response but did influence solution exploration across trials, with demonstrations containing causally irrelevant actions decreasing exploration of alternative methods. These results imply that uncertain environments can result in canalized social learning from specific classes of model. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

The Implementation of Collaborative Learning Model "Find Someone Who and Flashcard Game" to Enhance Social Studies Learning Motivation for the Fifth Grade Students

ERIC Educational Resources Information Center

Nurhaniyah, Binti; Soetjipto, Budi Eko; Hanurawan, Fattah

2015-01-01

The aims of this classroom action research are to describe: (1) the implementation of cooperative learning model "find someone who and flashcard game" to boost students' motivation to learn social studies for the fifth grade students; (2) the response of the fifth grade students at SDN Klanderan, Kediri, East Java on the implementation…

Engaging Students in a Simulated Collaborative Action Research Project: An Evaluation of a Participatory Approach to Learning

ERIC Educational Resources Information Center

Congdon, Graham John; Congdon, Shirley

2011-01-01

This article reports an action research project designed to develop and implement a new participatory learning and teaching approach to enable postgraduate healthcare students to develop skills and knowledge in preparation for undertaking an action research study within their practice setting. The learning and teaching approach was based upon the…

Project InterActions: A Multigenerational Robotic Learning Environment

NASA Astrophysics Data System (ADS)

Bers, Marina U.

2007-12-01

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.

A Bayesian Developmental Approach to Robotic Goal-Based Imitation Learning.

PubMed

Chung, Michael Jae-Yoon; Friesen, Abram L; Fox, Dieter; Meltzoff, Andrew N; Rao, Rajesh P N

2015-01-01

A fundamental challenge in robotics today is building robots that can learn new skills by observing humans and imitating human actions. We propose a new Bayesian approach to robotic learning by imitation inspired by the developmental hypothesis that children use self-experience to bootstrap the process of intention recognition and goal-based imitation. Our approach allows an autonomous agent to: (i) learn probabilistic models of actions through self-discovery and experience, (ii) utilize these learned models for inferring the goals of human actions, and (iii) perform goal-based imitation for robotic learning and human-robot collaboration. Such an approach allows a robot to leverage its increasing repertoire of learned behaviors to interpret increasingly complex human actions and use the inferred goals for imitation, even when the robot has very different actuators from humans. We demonstrate our approach using two different scenarios: (i) a simulated robot that learns human-like gaze following behavior, and (ii) a robot that learns to imitate human actions in a tabletop organization task. In both cases, the agent learns a probabilistic model of its own actions, and uses this model for goal inference and goal-based imitation. We also show that the robotic agent can use its probabilistic model to seek human assistance when it recognizes that its inferred actions are too uncertain, risky, or impossible to perform, thereby opening the door to human-robot collaboration.

A Protean Practice? Perspectives on the Practice of Action Learning

ERIC Educational Resources Information Center

Brook, Cheryl; Pedler, Mike; Burgoyne, John G

2013-01-01

Purpose: The purpose of the paper is to assess the extent to which these practitioners ' perspectives and practices match Willis's conception of a Revans "gold standard" of action learning. Design/methodology/approach: This study adopts a qualitative design and methodology based on interviews and the collection of cases or accounts of…

The Methods of Teaching Course Based on Constructivist Learning Approach: An Action Research

ERIC Educational Resources Information Center

Altun, Sertel; Yücel-Toy, Banu

2015-01-01

This purpose of this study is to investigate how the course designed based on constructivist principles has been implemented, what actions have been taken to solve problems and what thoughts have arisen in the minds of teacher candidates with regard to the constructivist learning approach. In this study, an action research was employed which…

Action video game play facilitates the development of better perceptual templates.

PubMed

Bejjanki, Vikranth R; Zhang, Ruyuan; Li, Renjie; Pouget, Alexandre; Green, C Shawn; Lu, Zhong-Lin; Bavelier, Daphne

2014-11-25

The field of perceptual learning has identified changes in perceptual templates as a powerful mechanism mediating the learning of statistical regularities in our environment. By measuring threshold-vs.-contrast curves using an orientation identification task under varying levels of external noise, the perceptual template model (PTM) allows one to disentangle various sources of signal-to-noise changes that can alter performance. We use the PTM approach to elucidate the mechanism that underlies the wide range of improvements noted after action video game play. We show that action video game players make use of improved perceptual templates compared with nonvideo game players, and we confirm a causal role for action video game play in inducing such improvements through a 50-h training study. Then, by adapting a recent neural model to this task, we demonstrate how such improved perceptual templates can arise from reweighting the connectivity between visual areas. Finally, we establish that action gamers do not enter the perceptual task with improved perceptual templates. Instead, although performance in action gamers is initially indistinguishable from that of nongamers, action gamers more rapidly learn the proper template as they experience the task. Taken together, our results establish for the first time to our knowledge the development of enhanced perceptual templates following action game play. Because such an improvement can facilitate the inference of the proper generative model for the task at hand, unlike perceptual learning that is quite specific, it thus elucidates a general learning mechanism that can account for the various behavioral benefits noted after action game play.

Action video game play facilitates the development of better perceptual templates

PubMed Central

Bejjanki, Vikranth R.; Zhang, Ruyuan; Li, Renjie; Pouget, Alexandre; Green, C. Shawn; Lu, Zhong-Lin; Bavelier, Daphne

2014-01-01

The field of perceptual learning has identified changes in perceptual templates as a powerful mechanism mediating the learning of statistical regularities in our environment. By measuring threshold-vs.-contrast curves using an orientation identification task under varying levels of external noise, the perceptual template model (PTM) allows one to disentangle various sources of signal-to-noise changes that can alter performance. We use the PTM approach to elucidate the mechanism that underlies the wide range of improvements noted after action video game play. We show that action video game players make use of improved perceptual templates compared with nonvideo game players, and we confirm a causal role for action video game play in inducing such improvements through a 50-h training study. Then, by adapting a recent neural model to this task, we demonstrate how such improved perceptual templates can arise from reweighting the connectivity between visual areas. Finally, we establish that action gamers do not enter the perceptual task with improved perceptual templates. Instead, although performance in action gamers is initially indistinguishable from that of nongamers, action gamers more rapidly learn the proper template as they experience the task. Taken together, our results establish for the first time to our knowledge the development of enhanced perceptual templates following action game play. Because such an improvement can facilitate the inference of the proper generative model for the task at hand, unlike perceptual learning that is quite specific, it thus elucidates a general learning mechanism that can account for the various behavioral benefits noted after action game play. PMID:25385590

Action observation versus motor imagery in learning a complex motor task: a short review of literature and a kinematics study.

PubMed

Gatti, R; Tettamanti, A; Gough, P M; Riboldi, E; Marinoni, L; Buccino, G

2013-04-12

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.

Evaluating Action Learning: A Critical Realist Complex Network Theory Approach

ERIC Educational Resources Information Center

Burgoyne, John G.

2010-01-01

This largely theoretical paper will argue the case for the usefulness of applying network and complex adaptive systems theory to an understanding of action learning and the challenge it is evaluating. This approach, it will be argued, is particularly helpful in the context of improving capability in dealing with wicked problems spread around…

Joint Patch and Multi-label Learning for Facial Action Unit Detection

PubMed Central

Zhao, Kaili; Chu, Wen-Sheng; De la Torre, Fernando; Cohn, Jeffrey F.; Zhang, Honggang

2016-01-01

The face is one of the most powerful channel of nonverbal communication. The most commonly used taxonomy to describe facial behaviour is the Facial Action Coding System (FACS). FACS segments the visible effects of facial muscle activation into 30+ action units (AUs). AUs, which may occur alone and in thousands of combinations, can describe nearly all-possible facial expressions. Most existing methods for automatic AU detection treat the problem using one-vs-all classifiers and fail to exploit dependencies among AU and facial features. We introduce joint-patch and multi-label learning (JPML) to address these issues. JPML leverages group sparsity by selecting a sparse subset of facial patches while learning a multi-label classifier. In four of five comparisons on three diverse datasets, CK+, GFT, and BP4D, JPML produced the highest average F1 scores in comparison with state-of-the art. PMID:27382243

Action-learning collaboratives as a platform for community-based participatory research to advance obesity prevention.

PubMed

Bazos, Dorothy A; Schifferdecker, Karen E; Fedrizzi, Rudolph; Hoebeke, Jaime; Ruggles, Laural; Goldsberry, Yvonne

2013-01-01

Although process elements that define community-based participatory research (CBPR) are well articulated and provide guidance for bringing together researchers and communities, additional models to implement CBPR are needed. One potential model for implementing and monitoring CBPR is Action Learning Collaboratives (ALCs); short term, team-based learning processes that are grounded in quality improvement. Since 2010, the Prevention Research Center at Dartmouth (PRCD) has used ALCs with three communities as a platform to design, implement and evaluate CBPR. The first ALC provided an opportunity for academia and community leadership to strengthen their relationships and knowledge of respective assets through design and evaluation of community-based QI projects. Building on this work, we jointly designed and are implementing a second ALC, a cross-community research project focused on obesity prevention in vulnerable populations. An enhanced community capacity now exists to support CBPR activities with a high degree of sophistication and decreased reliance on external facilitation.

Professional Learning Communities: Concepts in Action in a Principal Preparation Program, an Elementary School Team, a Leadership Team, and a Business Partnership

ERIC Educational Resources Information Center

Servais, Kristine; Derrington, Mary Lynne; Sanders, Kellie

2009-01-01

The Professional Learning Community (PLC) model has moved to the forefront in the field of education as one of the most effective frameworks to improve student achievement and overall school success. The research conducted for this paper provides evidence for systemic and action based improvement using the PLC model in four diverse venues:…

A Bayesian Developmental Approach to Robotic Goal-Based Imitation Learning

PubMed Central

Chung, Michael Jae-Yoon; Friesen, Abram L.; Fox, Dieter; Meltzoff, Andrew N.; Rao, Rajesh P. N.

2015-01-01

A fundamental challenge in robotics today is building robots that can learn new skills by observing humans and imitating human actions. We propose a new Bayesian approach to robotic learning by imitation inspired by the developmental hypothesis that children use self-experience to bootstrap the process of intention recognition and goal-based imitation. Our approach allows an autonomous agent to: (i) learn probabilistic models of actions through self-discovery and experience, (ii) utilize these learned models for inferring the goals of human actions, and (iii) perform goal-based imitation for robotic learning and human-robot collaboration. Such an approach allows a robot to leverage its increasing repertoire of learned behaviors to interpret increasingly complex human actions and use the inferred goals for imitation, even when the robot has very different actuators from humans. We demonstrate our approach using two different scenarios: (i) a simulated robot that learns human-like gaze following behavior, and (ii) a robot that learns to imitate human actions in a tabletop organization task. In both cases, the agent learns a probabilistic model of its own actions, and uses this model for goal inference and goal-based imitation. We also show that the robotic agent can use its probabilistic model to seek human assistance when it recognizes that its inferred actions are too uncertain, risky, or impossible to perform, thereby opening the door to human-robot collaboration. PMID:26536366

Nambu sigma model and effective membrane actions

NASA Astrophysics Data System (ADS)

Jurčo, Branislav; Schupp, Peter

2012-07-01

We propose an effective action for a p‧-brane with open p-branes ending on it. The action has dual descriptions similar to the commutative and non-commutative ones of the DBI action for D-branes and open strings. The Poisson structure governing the non-commutativity of the D-brane is replaced by a Nambu structure and the open-closed string relations are generalized to the case of p-branes utilizing a novel Nambu sigma model description of p-branes. In the case of an M5-brane our action interpolates between M5-actions already proposed in the literature and matrix-model like actions involving Nambu structures.

Professional Learning with Action Research in Innovative Middle Schools

ERIC Educational Resources Information Center

Netcoh, Steven; Olofson, Mark W.; Downes, John M.; Bishop, Penny A.

2017-01-01