These four papers were presented at a symposium on action learning moderated by Lex Dilworth at the 1996 conference of the Academy of Human Resource Development. "Developing an Infrastructure for Individual and Organizational Change: Transfer of Learning from an Action Reflection Learning (ARL) Program" (ARL Inquiry) reports findings…
Botvinick, Matthew; Weinstein, Ari
Recent work has reawakened interest in goal-directed or ‘model-based’ choice, where decisions are based on prospective evaluation of potential action outcomes. Concurrently, there has been growing attention to the role of hierarchy in decision-making and action control. We focus here on the intersection between these two areas of interest, considering the topic of hierarchical model-based control. To characterize this form of action control, we draw on the computational framework of hierarchical reinforcement learning, using this to interpret recent empirical findings. The resulting picture reveals how hierarchical model-based mechanisms might play a special and pivotal role in human decision-making, dramatically extending the scope and complexity of human behaviour. PMID:25267822
Botvinick, Matthew; Weinstein, Ari
Recent work has reawakened interest in goal-directed or 'model-based' choice, where decisions are based on prospective evaluation of potential action outcomes. Concurrently, there has been growing attention to the role of hierarchy in decision-making and action control. We focus here on the intersection between these two areas of interest, considering the topic of hierarchical model-based control. To characterize this form of action control, we draw on the computational framework of hierarchical reinforcement learning, using this to interpret recent empirical findings. The resulting picture reveals how hierarchical model-based mechanisms might play a special and pivotal role in human decision-making, dramatically extending the scope and complexity of human behaviour.
Chenhall, Everon C.; Chermack, Thomas J.
Purpose: The purpose of this paper is to propose an integrated model of action learning based on an examination of four reviewed action learning models, definitions, and espoused outcomes. Design/methodology/approach: A clear articulation of the strengths and limitations of each model was essential to developing an integrated model, which could be…
Mumford, Alan, Ed.
This book contains 34 papers examining the theory, process, and outcomes of action learning at work. The following papers are included: "An Introduction to the Text" (Alan Mumford); "The Learning Equation" (Reg Revans); "Action Learning as a Vehicle for Learning" (Alan Mumford); "Placing Action Learning and…
Corley, Aileen; Thorne, Ann
Action learning is based on the premise that action and learning are inextricably entwined and it is this potential, to enable action, which has contributed to the growth of action learning within education and management development programmes. However has this growth in action learning lead to an evolution or a dilution of Revan's classical…
Marquardt, Michael J.
Action learning was introduced into China less than 20 years ago, but has rapidly become a valuable tool for organizations seeking to solve problems, develop their leaders, and become learning organizations. This article provides an historical overview of action learning in China, its cultural underpinnings, and five case studies. It concludes…
This document contains four papers from a symposium on adult learning issues and human resource development (HRD). "Creating a Systemic Framework for the Transfer of Learning from an Action Learning Experience" (Suzanne D. Butterfield, Kitty Gold, Verna J. Willis) discusses a study of the organizational elements that affect learning and…
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…
Marquardt, Michael J.
Today's leaders perform the following roles: systems thinker, change agent, innovator, servant, polychronic coordinator, teacher-mentor, and visionary. The elements of action learning (real problems, teams, reflective inquiry, commitment to action, focus on learning) contribute to the development of these critical skills. (Author/SK)
Frings, A.; And Others
This handbook is intended to help trainers and development workers plan and conduct training programs based on the Action Training Model (ATM). The ATM combines training with action and learning with production by building upon participants' knowledge and learning needs and involving participants in a process of active learning and cooperative…
Fee, Michale S.
In its simplest formulation, reinforcement learning is based on the idea that if an action taken in a particular context is followed by a favorable outcome, then, in the same context, the tendency to produce that action should be strengthened, or reinforced. While reinforcement learning forms the basis of many current theories of basal ganglia (BG) function, these models do not incorporate distinct computational roles for signals that convey context, and those that convey what action an animal takes. Recent experiments in the songbird suggest that vocal-related BG circuitry receives two functionally distinct excitatory inputs. One input is from a cortical region that carries context information about the current “time” in the motor sequence. The other is an efference copy of motor commands from a separate cortical brain region that generates vocal variability during learning. Based on these findings, I propose here a general model of vertebrate BG function that combines context information with a distinct motor efference copy signal. The signals are integrated by a learning rule in which efference copy inputs gate the potentiation of context inputs (but not efference copy inputs) onto medium spiny neurons in response to a rewarded action. The hypothesis is described in terms of a circuit that implements the learning of visually guided saccades. The model makes testable predictions about the anatomical and functional properties of hypothesized context and efference copy inputs to the striatum from both thalamic and cortical sources. PMID:22754501
Braun, Daniel A.; Mehring, Carsten; Wolpert, Daniel M.
‘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
Windridge, David; Kittler, Josef
As well as having the ability to formulate models of the world capable of experimental falsification, it is evident that human cognitive capability embraces some degree of representational plasticity, having the scope (at least in infancy) to modify the primitives in terms of which the world is delineated. We hence employ the term 'cognitive bootstrapping' to refer to the autonomous updating of an embodied agent's perceptual framework in response to the perceived requirements of the environment in such a way as to retain the ability to refine the environment model in a consistent fashion across perceptual changes.We will thus argue that the concept of cognitive bootstrapping is epistemically ill-founded unless there exists an a priori percept/motor interrelation capable of maintaining an empirical distinction between the various possibilities of perceptual categorization and the inherent uncertainties of environment modeling.As an instantiation of this idea, we shall specify a very general, logically-inductive model of perception-action learning capable of compact re-parameterization of the percept space. In consequence of the a priori percept/action coupling, the novel perceptual state transitions so generated always exist in bijective correlation with a set of novel action states, giving rise to the required empirical validation criterion for perceptual inferences. Environmental description is correspondingly accomplished in terms of progressively higher-level affordance conjectures which are likewise validated by exploratory action.Application of this mechanism within simulated perception-action environments indicates that, as well as significantly reducing the size and specificity of the a priori perceptual parameter-space, the method can significantly reduce the number of iterations required for accurate convergence of the world-model. It does so by virtue of the active learning characteristics implicit in the notion of cognitive bootstrapping.
Baldassarre, Gianluca; Mannella, Francesco; Fiore, Vincenzo G; Redgrave, Peter; Gurney, Kevin; Mirolli, Marco
Reinforcement (trial-and-error) learning in animals is driven by a multitude of processes. Most animals have evolved several sophisticated systems of 'extrinsic motivations' (EMs) that guide them to acquire behaviours allowing them to maintain their bodies, defend against threat, and reproduce. Animals have also evolved various systems of 'intrinsic motivations' (IMs) that allow them to acquire actions in the absence of extrinsic rewards. These actions are used later to pursue such rewards when they become available. Intrinsic motivations have been studied in Psychology for many decades and their biological substrates are now being elucidated by neuroscientists. In the last two decades, investigators in computational modelling, robotics and machine learning have proposed various mechanisms that capture certain aspects of IMs. However, we still lack models of IMs that attempt to integrate all key aspects of intrinsically motivated learning and behaviour while taking into account the relevant neurobiological constraints. This paper proposes a bio-constrained system-level model that contributes a major step towards this integration. The model focusses on three processes related to IMs and on the neural mechanisms underlying them: (a) the acquisition of action-outcome associations (internal models of the agent-environment interaction) driven by phasic dopamine signals caused by sudden, unexpected changes in the environment; (b) the transient focussing of visual gaze and actions on salient portions of the environment; (c) the subsequent recall of actions to pursue extrinsic rewards based on goal-directed reactivation of the representations of their outcomes. The tests of the model, including a series of selective lesions, show how the focussing processes lead to a faster learning of action-outcome associations, and how these associations can be recruited for accomplishing goal-directed behaviours. The model, together with the background knowledge reviewed in the paper
Martinet, Louis-Emmanuel; Sheynikhovich, Denis; Benchenane, Karim; Arleo, Angelo
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.
Marlow, Annette; Spratt, Christine; Reilly, Amanda
The paper describes the processes and outcomes of a major curriculum innovation which was conducted by a collaborative multi-disciplinary team (nurse academics, educational developers and software developers). The paper argues that collaborative professional development in pedagogical innovation in nursing can be successfully supported by action learning as a framework for practice. In presenting this argument the paper draws on the experience of the School of Nursing and Midwifery (SNM) at the University of Tasmania in integrating high-fidelity simulation-based learning into an existing undergraduate case-based learning curriculum in the three year Bachelor of Nursing (BN).
Clarke, Jean; Thorpe, Richard; Anderson, Lisa; Gold, Jeff
Purpose: The purpose of this paper is to argue that action learning (AL) may provide a means of successfully developing small to medium-sized enterprises (SMEs). Design/methodology/approach: The literature around SME learning suggests a number of processes are important for SME learning which similarity, it is argued, are encompassed in AL. AL may…
Felix, Eversley; Keevill, Joan
This account tells the story of the development of an action learning culture in the BBC between 2002 and 2007. From its early beginnings as a sporadic, unsystematic intervention with a small number of leaders scattered throughout the organisation, action learning has now become embedded in our approach to the way we develop our leaders. In this…
Norris, Cynthia J.; Barnett, Bruce G.; Basom, Margaret R.; Yerkes, Diane M.
In this book, a working model for leadership development is presented, resulting from groundbreaking work with learning communities in educational leadership preparation programs. Chapter 1 develops the concept of a learning community as both a structure for the delivery of course content (the product) and a laboratory for promoting collaborative…
Dezfouli, Amir; Balleine, Bernard W.
It is now widely accepted that instrumental actions can be either goal-directed or habitual; whereas the former are rapidly acquire and regulated by their outcome, the latter are reflexive, elicited by antecedent stimuli rather than their consequences. Model-based reinforcement learning (RL) provides an elegant description of goal-directed action. Through exposure to states, actions and rewards, the agent rapidly constructs a model of the world and can choose an appropriate action based on quite abstract changes in environmental and evaluative demands. This model is powerful but has a problem explaining the development of habitual actions. To account for habits, theorists have argued that another action controller is required, called model-free RL, that does not form a model of the world but rather caches action values within states allowing a state to select an action based on its reward history rather than its consequences. Nevertheless, there are persistent problems with important predictions from the model; most notably the failure of model-free RL correctly to predict the insensitivity of habitual actions to changes in the action-reward contingency. Here, we suggest that introducing model-free RL in instrumental conditioning is unnecessary and demonstrate that reconceptualizing habits as action sequences allows model-based RL to be applied to both goal-directed and habitual actions in a manner consistent with what real animals do. This approach has significant implications for the way habits are currently investigated and generates new experimental predictions. PMID:22487034
Dezfouli, Amir; Balleine, Bernard W
It is now widely accepted that instrumental actions can be either goal-directed or habitual; whereas the former are rapidly acquired and regulated by their outcome, the latter are reflexive, elicited by antecedent stimuli rather than their consequences. Model-based reinforcement learning (RL) provides an elegant description of goal-directed action. Through exposure to states, actions and rewards, the agent rapidly constructs a model of the world and can choose an appropriate action based on quite abstract changes in environmental and evaluative demands. This model is powerful but has a problem explaining the development of habitual actions. To account for habits, theorists have argued that another action controller is required, called model-free RL, that does not form a model of the world but rather caches action values within states allowing a state to select an action based on its reward history rather than its consequences. Nevertheless, there are persistent problems with important predictions from the model; most notably the failure of model-free RL correctly to predict the insensitivity of habitual actions to changes in the action-reward contingency. Here, we suggest that introducing model-free RL in instrumental conditioning is unnecessary, and demonstrate that reconceptualizing habits as action sequences allows model-based RL to be applied to both goal-directed and habitual actions in a manner consistent with what real animals do. This approach has significant implications for the way habits are currently investigated and generates new experimental predictions.
Cotter, Teresa Ellen
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…
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…
A small group of training professionals within the John Lewis Partnership set up an action learning group about 2 years ago. The main aim was to explore the technique for our own learning and development. The timing and lifespan of the group reflected the generally strategic and long-term nature of our projects. One of these was to introduce…
This article describes how action learning can be accompanied by a project to encourage shared learning about organisation culture, the external environment, political context and team dynamics, while allowing space for personal issues. It drives forward reflective practice and encourages sets to deliver a tangible pay-back to the organisation.…
Boak, George; Watt, Peter; Gold, Jeff; Devins, David; Garvey, Robert
This paper contributes to an understanding of the processes by which organisational actors learn how to affect positive and sustainable social change in their local region through action learning, action research and appreciative inquiry. The paper is based on a critically reflective account of key findings from an ongoing action research project,…
Chersi, Fabian; Mirolli, Marco; Pezzulo, Giovanni; Baldassarre, Gianluca
Dual-system theories postulate that actions are supported either by a goal-directed or by a habit-driven response system. Neuroimaging and anatomo-functional studies have provided evidence that the prefrontal cortex plays a fundamental role in the first type of action control, while internal brain areas such as the basal ganglia are more active during habitual and overtrained responses. Additionally, it has been shown that areas of the cortex and the basal ganglia are connected through multiple parallel "channels", which are thought to function as an action selection mechanism resolving competitions between alternative options available in a given context. In this paper we propose a multi-layer network of spiking neurons that implements in detail the thalamo-cortical circuits that are believed to be involved in action learning and execution. A key feature of this model is that neurons are organized in small pools in the motor cortex and form independent loops with specific pools of the basal ganglia where inhibitory circuits implement a multistep selection mechanism. The described model has been validated utilizing it to control the actions of a virtual monkey that has to learn to turn on briefly flashing lights by pressing corresponding buttons on a board. When the animal is able to fluently execute the task the button-light associations are remapped so that it has to suppress its habitual behavior in order to execute goal-directed actions. The model nicely shows how sensory-motor associations for action sequences are formed at the cortico-basal ganglia level and how goal-directed decisions may override automatic motor responses.
This paper seeks to improve our understanding of the emotional and political dynamics that are generated (and too often avoided) in action learning. The idea at the centre of the paper is a distinction between "learning-in-action" and "learning inaction". The phrase "learning-in-action" represents the value of action…
Whalen, Andrew; Cownden, Daniel; Laland, Kevin
Previous empirical work on animal social learning has found that many species lack the ability to learn entire action sequences solely through reliance on social information. Conversely, acquiring action sequences through asocial learning can be difficult due to the large number of potential sequences arising from even a small number of base actions. In spite of this, several studies report that some primates use action sequences in the wild. We investigate how social information can be integrated with asocial learning to facilitate the learning of action sequences. We formalize this problem by examining how learners using temporal difference learning, a widely applicable model of reinforcement learning, can combine social cues with their own experiences to acquire action sequences. The learning problem is modeled as a Markov decision process. The learning of nettle processing by mountain gorillas serves as a focal example. Through simulations, we find that the social facilitation of component actions can combine with individual learning to facilitate the acquisition of action sequences. Our analysis illustrates that how even simple forms of social learning, combined with asocial learning, generate substantially faster learning of action sequences compared to asocial processes alone, and that the benefits of social information increase with the length of the action sequence and the number of base actions.
Cos, Ignasi; Khamassi, Mehdi; Girard, Benoît
Recent experiments showed that the bio-mechanical ease and end-point stability associated to reaching movements are predicted prior to movement onset, and that these factors exert a significant influence on the choice of movement. As an extension of these results, here we investigate whether the knowledge about biomechanical costs and their influence on decision-making are the result of an adaptation process taking place during each experimental session or whether this knowledge was learned at an earlier stage of development. Specifically, we analysed both the pattern of decision-making and its fluctuations during each session, of several human subjects making free choices between two reaching movements that varied in path distance (target relative distance), biomechanical cost, aiming accuracy and stopping requirement. Our main result shows that the effect of biomechanics is well established at the start of the session, and that, consequently, the learning of biomechanical costs in decision-making occurred at an earlier stage of development. As a means to characterise the dynamics of this learning process, we also developed a model-based reinforcement learning model, which generates a possible account of how biomechanics may be incorporated into the motor plan to select between reaching movements. Results obtained in simulation showed that, after some pre-training corresponding to a motor babbling phase, the model can reproduce the subjects' overall movement preferences. Although preliminary, this supports that the knowledge about biomechanical costs may have been learned in this manner, and supports the hypothesis that the fluctuations observed in the subjects' behaviour may adapt in a similar fashion.
West, Penny; Choueke, Richard
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…
This document contains three papers on action learning. "Action Learning: Case Studies of Most Valued Learning and Application" (Suzanne D. Butterfield) reports on a qualitative study in which longitudinal data was collected from document analysis and first-line consulting managers who had participated in action learning. The study…
Norman, Clare; Powell, Anne
This article aims to answer the questions: (1) How can action learning aid in strategic change?; (2) What are the benefits of using action learning as part of a broader learning intervention?; (3) What are the issues to consider when introducing action learning into a corporate environment?; and (4) How can you engage people in reflection as a…
Guevara, Jose Roberto Q.
Ecologically sound tourism planning and policy require an empowering community participation. The participatory action research model helps a community gain understanding of its social reality, learn how to learn, initiate dialog, and discover new possibilities for addressing its situation. (SK)
Dewar, Belinda; Sharp, Cathy
This article discusses the use of action learning as a structured and deliberate learning process to support practitioners to implement change in an action research project. It discusses both action learning and action research before describing the context of the study. The article then goes on to discuss how the process of action learning…
Waterman, Margaret; Weber, Janet; Pracht, Carl; Conway, Kathleen; Kunz, David; Evans, Beverly; Hoffman, Steven; Smentkowski, Brian; Starrett, David
The Scholarship of Teaching and Learning (SoTL) Fellows Program at Southeast Missouri State University supports an annual cohort of 10 faculty Fellows to evaluate, through individual research projects, the effect of teaching on student learning of two or more of the university's General Education objectives. Designed around practical action…
Green, C Shawn; Li, Renjie; Bavelier, Daphne
Action video games have been shown to enhance behavioral performance on a wide variety of perceptual tasks, from those that require effective allocation of attentional resources across the visual scene, to those that demand the successful identification of fleetingly presented stimuli. Importantly, these effects have not only been shown in expert action video game players, but a causative link has been established between action video game play and enhanced processing through training studies. Although an account based solely on attention fails to capture the variety of enhancements observed after action game playing, a number of models of perceptual learning are consistent with the observed results, with behavioral modeling favoring the hypothesis that avid video game players are better able to form templates for, or extract the relevant statistics of, the task at hand. This may suggest that the neural site of learning is in areas where information is integrated and actions are selected; yet changes in low-level sensory areas cannot be ruled out.
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…
This ASA Teaching Workshop explored the potential of Action Learning to use teachers' tacit knowledge to collaboratively confront pedagogical issues. The Action Learning model grows out of industrial management and is based on the notion that peers are a valuable resource for learning about how to solve the problems encountered in the workplace.…
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…
Aidinopoulou, Vasiliki; Sampson, Demetrios G.
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,…
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…
Endress, Ansgar D.; Wood, Justin N.
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…
Lustig, Patricia; Rai, Deep Ranjani
This article describes an example of how action learning was used as a framework for an organisational intervention to fundamentally change the organisational culture over a period of time. It also identifies our learning over that period of time and what worked well (and not so well) in an International Non-Governmental Organisation in Nepal.
Webster, Richard S.
This paper defines and explains action learning and suggests some ideas and resources for putting action learning into practice. The paper is organized in eight sections of about one page each. The sections cover the following topics: (1) what action learning is; (2) how action learning works; (3) action learning and training--key differences; (4)…
The University for Applied Management is a semi-virtual institution widely using blended learning as an integrated approach of face-to-face instruction and e-learning. Virtual action learning is offered in all bachelor and master programmes. The module is transfer orientated and aims at encouraging reflection and supporting students to develop a…
Nalborczyk, Sarah; Sandelands, Luke
This account examines the action learning process adopted by Emerald Group Publishing Ltd., embedded in the organization through the in-company Emerald Academy. In case study format, the paper emphasizes that in order to align learning with organizational objectives joined up thinking and practice is needed beyond the learning and development…
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…
Gold, Jeff; Anderson, Lisa; Clarke, Jean; Thorpe, Richard
This paper considers the work of the Russian social philosopher and cultural theorist, Mikhail Mikhailovich Bakhtin as a source of understanding for those involved in action learning. Drawing upon data gathered over two years during the evaluation of 20 action learning sets in the north of England, we will seek to work with the ideas of Bakhtin to…
Pedler, Mike; Hauser, Bernhard; Caulat, Ghislaine
This paper brings together the reflections of the authors on their shared and individual experiences of virtual action learning. Whilst many conclusions are shared, there are also some points of difference in practices.
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…
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
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…
Mullen, Carol A.
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…
Pedler, Mike; Attwood, Margaret
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…
Coghlan, David; Coughlan, Paul
The philosophical foundations of action learning research have not received a great deal of attention. In the context of action learning postgraduate and professional programmes in universities, articulation of a philosophy of action learning research seems timely and appropriate. This article explores a philosophy of action learning research,…
McClune, Billy; Jarman, Ruth
Science programmes which prepare students to read critically and respond thoughtfully to science-based reports in the media could play an important role in promoting informed participation in the public debate about issues relating to science, technology and society. Evidence based guidance about the practice and pattern of use of science-based media in the classroom is limited. This study sought to identify learning intentions that teachers believe ought to underpin the development of programmes of study designed to achieve this end-result. Teachers' views of knowledge, skills and attitudes required to engage critically with science-based news served as a basis for this study. Teachers developed a pedagogical model by selecting appropriate statements of learning intentions, grouping these into coherent and manageable themes and coding them according to perceived level of difficulty. The model is largely compatible with current curricular provision in the UK, highlights opportunities for interdisciplinary collaboration and illustrates the developmental nature of the topic.
O'Neil, Judy A.; Lamm, Sharon L.
A team of learning coaches facilitated an action learning group in a public utility. The coaches' diversity raised interpersonal issues but added a wealth of perspectives and experience. Important components were team formation, a balance of program and individual needs, and group diversity. (SK)
Jones, Karen; Sambrook, Sally A.; Pittaway, Luke; Henley, Andrew; Norbury, Heather
This paper presents research with small- and medium-sized enterprise (SME) owners who have participated in a leadership development programme. The primary focus of this paper is on learning transfer and factors affecting it, arguing that entrepreneurs must engage in "action" in order to "learn" and that under certain conditions…
Naylor, Patti-Jean; Macdonald, Heather M; Zebedee, Janelle A; Reed, Katherine E; McKay, Heather A
The 'active school' model offers promise for promoting school-based physical activity (PA); however, few intervention trials have evaluated its effectiveness. Thus, our purpose was to: (1) describe Action Schools! BC (AS! BC) and its implementation (fidelity and feasibility) and (2) evaluate the impact of AS! BC on school provision of PA. Ten elementary schools were randomly assigned to one of the three conditions: Usual Practice (UP, three schools), Liaison (LS, four schools) or Champion (CS, three schools). Teachers in LS and CS schools received AS! BC training and resources but differed on the level of facilitation provided. UP schools continued with regular PA. Delivery of PA during the 11-month intervention was assessed with weekly Activity Logs and intervention fidelity and feasibility were assessed using Action Plans, workshop evaluations, teacher surveys and focus groups with administrators, teachers, parents and students. Physical activity delivered was significantly greater in LS (+67.4 min/week; 95% CI: 18.7-116.1) and CS (+55.2 min/week; 95% CI: 26.4-83.9) schools than UP schools. Analysis of Action Plans and Activity Logs showed fidelity to the model and moderate levels of compliance (75%). Teachers were highly satisfied with training and support. Benefits of AS! BC included positive changes in the children and school climate, including provision of resources, improved communication and program flexibility. These results support the use of the 'active school' model to positively alter the school environment. The AS! BC model was effective, providing more opportunities for "more children to be more active more often" and as such has the potential to provide health benefits to elementary school children.
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…
Seddon, John; Caulkin, Simon
Systems thinking underpins "lean" management and is best understood through action-learning as the ideas are counter-intuitive. The Toyota Production System is just that--a system; the failure to appreciate that starting-place and the advocacy of "tools" leads many to fail to grasp what is, without doubt, a significant…
Pedler, Mike; Hsu, Shih-wei
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…
Aronstein, Laurence W.; Olsen, Edward G.
By engaging students in community service projects, action learning uses resources of the real world to give students opportunities to participate in performing tasks and making decisions that confront societal problems. Such projects should be decided on after a study of the needs of the community. After a project is selected, all relevant…
Kozubska, Joanna; MacKenzie, Bob
Here, we argue that action learning (AL) has been evolving into different variations, whose respective advocates appear to concentrate on one of the several components inherent in Revans' formulation of AL as L = P + Q. They do this--sometimes inappropriately--to the virtual or relative exclusion of other aspects, and this has consequences for the…
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…
Smith-Stoner, Marilyn; Molle, Mary E
Nurse educators must continually improve their teaching skills through innovation. However, research about the process used by faculty members to transform their teaching methods is limited. This collaborative study uses classroom action research to describe, analyze, and address problems encountered in implementing cooperative learning in two undergraduate nursing courses. After four rounds of action and reflection, the following themes emerged: students did not understand the need for structured cooperative learning; classroom structure and seating arrangement influenced the effectiveness of activities; highly structured activities engaged the students; and short, targeted activities that involved novel content were most effective. These findings indicate that designing specific activities to prepare students for class is critical to cooperative learning.
Boutin, Arnaud; Blandin, Yannick; Massen, Cristina; Heuer, Herbert; Badets, Arnaud
Many everyday skills are unconsciously learned through repetitions of the same behaviour by binding independent motor acts into unified sets of actions. However, our ability to be consciously aware of producing newly and highly trained motor skills raises the question of the role played by conscious awareness of action upon skill acquisition. In this study we strengthened conscious awareness of self-produced sequential finger movements by way of asking participants to judge their performance in terms of maximal fluency after each trial. Control conditions in which participants did not make any judgment or performance-unrelated judgments were also included. Findings indicate that conscious awareness of action, enhanced via subjective appraisal of motor efficiency, potentiates sensorimotor learning and skilful motor production in optimising the processing and sequencing of action units, as compared to the control groups. The current work lends support to the claim that the learning and skilful expression of sensorimotor behaviours might be grounded upon our ability to be consciously aware of our own motor capability and efficiency.
Green, C.S.; Bavelier, D.
While humans have an incredible capacity to acquire new skills and alter their behavior as a result of experience, enhancements in performance are typically narrowly restricted to the parameters of the training environment, with little evidence of generalization to different, even seemingly highly related, tasks. Such specificity is a major obstacle for the development of many real-world training or rehabilitation paradigms, which necessarily seek to promote more general learning. In contrast to these typical findings, research over the past decade has shown that training on ‘action video games’ produces learning that transfers well beyond the training task. This has led to substantial interest among those interested in rehabilitation, for instance, after stroke or to treat amblyopia, or training for various precision-demanding jobs, for instance, endoscopic surgery or piloting unmanned aerial drones. Although the predominant focus of the field has been on outlining the breadth of possible action-game-related enhancements, recent work has concentrated on uncovering the mechanisms that underlie these changes, an important first step towards the goal of designing and using video games for more definite purposes. Game playing may not convey an immediate advantage on new tasks (increased performance from the very first trial), but rather the true effect of action video game playing may be to enhance the ability to learn new tasks. Such a mechanism may serve as a signature of training regimens that are likely to produce transfer of learning. PMID:22440805
Reese, Debbie Denise; Tabachnick, Barbara G.; Kosko, Robert E.
Valid, accessible, reusable methods for instructional video game design and embedded assessment can provide actionable information enhancing individual and collective achievement. Cyberlearning through game-based, metaphor-enhanced learning objects (CyGaMEs) design and embedded assessment quantify player behavior to study knowledge discovery and…
Sobel, David M.; Sommerville, Jessica A.
Shown commensurate actions and information by an adult, preschoolers' causal learning was influenced by the pedagogical context in which these actions occurred. Four-year-olds who were provided with a reason for an experimenter's action relevant to learning causal structure showed more accurate causal learning than children exposed to the same…
Park, Sunyoung; Kang, Ingu; Valencic, Taryn R.; Cho, Yonjoo
The purpose of this study was to examine the contexts in which action learning has been used and provide implications for the design of action learning programmes. We performed a content analysis of 127 articles (case studies and case reports included) published in "Action Learning: Research and Practice" between 2004 and 2012. In this…
Bong, Hyeon-Cheol; Cho, Yonjoo
Purpose: The purpose of this paper was to explore how the two groups of action learning experts (Korean and non-Korean experts) define success of action learning to see whether there are any cultural differences. To this end, the authors conducted a total of 44 interviews with action learning experts around the world. Research questions guiding…
Abbott, Christine; Mayes, Cathy
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…
Cho, Yonjoo; Bong, Hyeon-Cheol
Despite considerable commitment to the application of action learning as leadership and organization development by a large number of Korean organizations, few identified empirical studies of action learning practices have been reported. The purpose of this study was to conduct case studies of South Korean action learning practices to examine…
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…
Lee-Hand, Jeremy; Knott, Alistair
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). PMID:26175685
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…
De Loo, Ivo
Purpose: To highlight the relevance of management control in action learning programs that aim to foster organizational learning. Design/methodology/approach: Literature review plus case study. The latter consists of archival analysis and multiple interviews. Findings: When action learning programs are built around singular learning experiences,…
Little, Daniel Y; Sommer, Friedrich T
Discovering the structure underlying observed data is a recurring problem in machine learning with important applications in neuroscience. It is also a primary function of the brain. When data can be actively collected in the context of a closed action-perception loop, behavior becomes a critical determinant of learning efficiency. Psychologists studying exploration and curiosity in humans and animals have long argued that learning itself is a primary motivator of behavior. However, the theoretical basis of learning-driven behavior is not well understood. Previous computational studies of behavior have largely focused on the control problem of maximizing acquisition of rewards and have treated learning the structure of data as a secondary objective. Here, we study exploration in the absence of external reward feedback. Instead, we take the quality of an agent's learned internal model to be the primary objective. In a simple probabilistic framework, we derive a Bayesian estimate for the amount of information about the environment an agent can expect to receive by taking an action, a measure we term the predicted information gain (PIG). We develop exploration strategies that approximately maximize PIG. One strategy based on value-iteration consistently learns faster than previously developed reward-free exploration strategies across a diverse range of environments. Psychologists believe the evolutionary advantage of learning-driven exploration lies in the generalized utility of an accurate internal model. Consistent with this hypothesis, we demonstrate that agents which learn more efficiently during exploration are later better able to accomplish a range of goal-directed tasks. We will conclude by discussing how our work elucidates the explorative behaviors of animals and humans, its relationship to other computational models of behavior, and its potential application to experimental design, such as in closed-loop neurophysiology studies.
Little, Daniel Y.; Sommer, Friedrich T.
Discovering the structure underlying observed data is a recurring problem in machine learning with important applications in neuroscience. It is also a primary function of the brain. When data can be actively collected in the context of a closed action-perception loop, behavior becomes a critical determinant of learning efficiency. Psychologists studying exploration and curiosity in humans and animals have long argued that learning itself is a primary motivator of behavior. However, the theoretical basis of learning-driven behavior is not well understood. Previous computational studies of behavior have largely focused on the control problem of maximizing acquisition of rewards and have treated learning the structure of data as a secondary objective. Here, we study exploration in the absence of external reward feedback. Instead, we take the quality of an agent's learned internal model to be the primary objective. In a simple probabilistic framework, we derive a Bayesian estimate for the amount of information about the environment an agent can expect to receive by taking an action, a measure we term the predicted information gain (PIG). We develop exploration strategies that approximately maximize PIG. One strategy based on value-iteration consistently learns faster than previously developed reward-free exploration strategies across a diverse range of environments. Psychologists believe the evolutionary advantage of learning-driven exploration lies in the generalized utility of an accurate internal model. Consistent with this hypothesis, we demonstrate that agents which learn more efficiently during exploration are later better able to accomplish a range of goal-directed tasks. We will conclude by discussing how our work elucidates the explorative behaviors of animals and humans, its relationship to other computational models of behavior, and its potential application to experimental design, such as in closed-loop neurophysiology studies. PMID:23579347
Wermter, Stefan; Elshaw, Mark
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.
Kostaris, Christoforos; Sergis, Stylianos; Sampson, Demetrios G.; Giannakos, Michail N.; Pelliccione, Lina
The emerging Flipped Classroom approach has been widely used to enhance teaching practices in many subject domains and educational levels, reporting promising results for enhancing student learning experiences. However, despite this encouraging body of research, the subject domain of Information and Communication Technologies (ICT) teaching at…
Kola-Olusanya, Anthony O.
This thesis explores the ways in which young-adults' environmental learning and experiences influence their decision to live sustainably. In particular, this thesis focuses on young adults' environmental and sustainability learning. It elaborates on young peoples' views about environmental and sustainability issues, such as climate change, the sources for their learning about these issues, and how young adults' learning encounters, in turn, affect their actions toward environmental protection and decision-making. Through a series of in-depth individual interviews with 18 young adults from three universities in southeastern Ontario, this qualitative study provides in-depth insight into young adults' understanding, learning experiences, and actions in relation to environmental and sustainability issues. Employing a Contextual Model of Learning framework the narratives of the young adults in this study are analyzed and discussed within three overlapping environmental learning contexts: personal, sociocultural, and physical settings. This framework allows for an examination of the complex interactions and relationships that shape how and where environmental learning occurs. The findings in this study suggest that the three overlapping learning contexts, that is the personal, sociocultural, and physical play an important role in shaping young adults' learning about environmental and sustainability issues. The data reveal that despite the unavailability or near-absence of environmental studies and education within the formal school curriculum (particularly at the elementary and high school levels), the young adults rely on other locations for learning, such as the internet, environmental non-governmental organisations (ENGOs), television, and family. In light of this, the research participants suggest the re-introduction of environmental programs and content in the school curriculum. Finally, the results of this study demonstrate the centrality of knowledge and
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…
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…
Brown, Barb; Dressler, Roswita; Eaton, Sarah Elaine; Jacobsen, Michele
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…
Leonard, H. Skipton
Clients and practitioners alike are often confused about the ultimate purpose of action learning (AL). Because of the title of the method, many believe the primary goal of AL is to generate learning. This article clarifies the relationship between action, learning, and solutions. It also provides historical evidence to support the conclusion that…
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…
Thevarajah, Dhushan; Webb, Ryan; Ferrall, Christopher; Dorris, Michael C.
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
Leo, Tara; Cowan, D'Ette
A Professional Learning Community (PLC) is a school where administrators and teachers continuously seek and share learning to increase their effectiveness for students and act on what they learn. PLCs are characterized by five dimensions: shared and supportive leadership, shared values and vision, collective learning and application of learning,…
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…
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…
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.…
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,…
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…
Harris, Nicole S.
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…
Leonard, H. Skipton; Marquardt, Michael J.
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…
Kurt Lewin's epigrammatic paradox is particularly true for action learning. Marquardt and Waddill (2004), and previously Yorks O'Neil and Marsick (1999) have approached the issue of the relationship between theory and action learning by looking at a variety of theories which they have placed in "schools". This provides an interesting analysis, but…
Walia, Surinder; Marks-Maran, Di
This article examines the use of action learning sets in a leadership module delivered by a university in south east England. An evaluation research study was undertaking using survey method to evaluate student engagement with action learning sets, and their value, impact and sustainability. Data were collected through a questionnaire with a mix of Likert-style and open-ended questions and qualitative and quantitative data analysis was undertaken. Findings show that engagement in the action learning sets was very high. Action learning sets also had a positive impact on the development of leadership knowledge and skills and are highly valued by participants. It is likely that they would be sustainable as the majority would recommend action learning to colleagues and would consider taking another module that used action learning sets. When compared to existing literature on action learning, this study offers new insights as there is little empirical literature on student engagement with action learning sets and even less on value and sustainability.
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…
Bleicher, Robert E.
The field of professional development is moving towards the notion of professional learning, highlighting the active learning role that teachers play in changing their knowledge bases, beliefs and practice. This article builds on this idea and argues for creating professional learning that is guided by a collaborative action research (CAR)…
Cao, Rui; Chuah, Kong Bieng; Chao, Yiu Chung; Kwong, Kar Fai; Law, Mo Yin
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…
Bwegyeme, Jacinta; Munene, John C.
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…
HolmesParker, Chris; Taylor, Mathew E.; Tumer, Kagan; Agogino, Adrian
Learning in multiagent systems can be slow because agents must learn both how to behave in a complex environment and how to account for the actions of other agents. The inability of an agent to distinguish between the true environmental dynamics and those caused by the stochastic exploratory actions of other agents creates noise in each agent's reward signal. This learning noise can have unforeseen and often undesirable effects on the resultant system performance. We define such noise as exploratory action noise, demonstrate the critical impact it can have on the learning process in multiagent settings, and introduce a reward structure to effectively remove such noise from each agent's reward signal. In particular, we introduce Coordinated Learning without Exploratory Action Noise (CLEAN) rewards and empirically demonstrate their benefits
Sobel, David M; Letourneau, Susan M
It is widely believed that exploration is a mechanism for young children's learning. The present investigation examines preschoolers' beliefs about how learning occurs. We asked 3- to 5-year-olds to articulate how characters in a set of stories learned about a new toy. Younger preschoolers were more likely to overemphasize the role of characters' actions in learning than older children were (Experiment 1, N = 53). Overall performance improved when the stories explicitly stated that characters were originally ignorant and clarified the characters' actions, but general developmental trends remained (Experiment 2, N = 48). These data suggest that explicit metacognitive understanding of the relation between actions and learning is developing during the preschool years, which might have implications for how children learn from exploration.
Lyman, Lawrence; Foyle, Harvey C.
Cooperative learning is a teaching strategy involving students in small group learning activities that promote positive interaction. Research studies have consistently found that cooperative learning promotes increased academic achievement and involves relative use of implementation and reasonable costs. Improved behavior, increased positive…
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…
Herwig, Arvid; Waszak, Florian
According to ideomotor theory, action-effect associations are crucial for voluntary action control. Recently, a number of studies started to investigate the conditions that mediate the acquisition and application of action-effect associations by comparing actions carried out in response to exogenous stimuli (stimulus-based) with actions selected endogenously (intention-based). There is evidence that the acquisition and/or application of action-effect associations is boosted when acting in an intention-based action mode. For instance, bidirectional action-effect associations were diagnosed in a forced choice test phase if participants previously experienced action-effect couplings in an intention-based but not in a stimulus-based action mode. The present study aims at investigating effects of the action mode on action-effect associations in more detail. In a series of experiments, we compared the strength and durability of short-term action-effect associations (binding) immediately following intention- as well as stimulus-based actions. Moreover, long-term action-effect associations (learning) were assessed in a subsequent test phase. Our results show short-term action-effect associations of equal strength and durability for both action modes. However, replicating previous results, long-term associations were observed only following intention-based actions. These findings indicate that the effect of the action mode on long-term associations cannot merely be a result of accumulated short-term action-effect bindings. Instead, only those episodic bindings are selectively perpetuated and retrieved that integrate action-relevant aspects of the processing event, i.e., in case of intention-based actions, the link between action and ensuing effect.
Durden, Jared; Brewe, Eric; Kramer, Laird
We present "Implicit Action", a discourse management tool, through a qualitative video analysis of a Florida International University Modeling Instruction Introductory Physics I class. Implicit Action in Modeling Instruction is where instructors deliberately create intellectual space in which students ideally see value and need for the construction of new classroom norms and tools that are productive in developing a learning community. This space is created by the implications expressed through the instructors' deliberate actions. Discourse Management is a technique to moderate student discourse in Modeling Instruction classes at the university level that was initially described by Desbien . Implicit Action is one of 9 Modeling Discourse Management tools that we have identified. By means of qualitative analysis we illustrate the effectiveness of Implicit Action in implementing the Modeling Theory of Instruction.
Jones-Evans, Dylan; Williams, William; Deacon, Jonathan
Describes development and marketing of a Welsh business school's diploma in entrepreneurial practice, an action learning-based program. Discusses problems encountered in dealing with the concept of business ambiguity, program flexibility, and measurement of outcomes. (SK)
Schensul, Jean J.; Berg, Marlene
This article describes a model of participatory action research and service-learning conducted with urban, high school African American, West Indian/Caribbean, and Puerto Rican/Latino youth and adult facilitators, in a nonclassroom setting, in a mid-sized northeastern city. Youth Participatory Action Research (YPAR) integrates critical theory,…
Adaptive learning system on the salient features, expounded personalized learning is adaptive learning system adaptive to learners key to learning. From the perspective of design theory, put forward an adaptive learning system to learn design thinking individual model, and using data mining techniques, the initial establishment of personalized adaptive systems model of learning.
Vergara, Mariana Ines
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…
Lieblein, Geir; Breland, Tor Arvid; Francis, Charles; Ostergaard, Edvin
Purpose: This article examines and evaluates the potential contributions from action learning and action research with stakeholders to higher education in agriculture and food systems. Design/Methodology/Approach: The research is based on our experiences over the past two decades of running PhD courses and an MSc degree programme in Agroecology in…
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…
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…
Cho, Yonjoo; Egan, Toby
The purpose of this study was (1) to examine the impact of organizational support on employee learning and performance and (2) to elaborate on the context of organizational support for action learning in South Korean organizations. For this inquiry, two central questions were posed: What are employee reactions to organizational support for action…
Wang, Chien-hsing; Ke, Yi-Ting; Wu, Jin-Tong; Hsu, Wen-Hua
This paper briefly reports the outcomes of an action research inquiry on the use of blogs, MS PowerPoint [PPT], and the Internet as learning tools with a science class of sixth graders for project-based learning. Multiple sources of data were essential to triangulate the key findings articulated in this paper. Corresponding to previous studies,…
McGrath, Helen; O'Toole, Thomas
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,…
Zuber-Skerritt, Ortrun; Passfield, Ron
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…
Kachergis, George; Wyatte, Dean; O'Reilly, Randall C.; de Kleijn, Roy; Hommel, Bernhard
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. PMID:25267830
de León, Lourdes
This chapter examines Mayan children's initiatives in creating their own learning environments in collaboration with others as they engage in culturally relevant endeavors of family and community life. To this end, I carry out a fine-grained ethnographic and linguistic analysis of the interactional emergence of learning ecologies. Erickson defines learning ecology as a socioecological system where participants mutually influence one another through verbal and nonverbal actions, as well as through other forms of semiotic communication (2010, 254). In analyzing learning ecologies, I adopt a "theory of action" approach, taking into account multimodal communication (e.g., talk, gesture, gaze, body positioning), participants' sociospatial organization, embodied action, objects, tools, and other culturally relevant materials brought together to build action (Goodwin, 2000, 2013; Hutchins, 1995). I use microethnographic analysis (Erickson, 1992) to bring to the surface central aspects of children's agentive roles in learning through "cooperative actions" (Goodwin, 2013) and "hands-on" experience (Ingold, 2007) the skills of competent members of their community. I examine three distinct Learning Ecologies created by children's initiatives among the Mayan children that I observed: (i) children requesting guidance to collaborate in a task, (ii) older children working on their own initiative with subsequent monitoring and correction from competent members, and (iii) children with near competence in a task with occasional monitoring and no guidance. I argue that these findings enrich and add power to models of family- and community-based learning such as Learning by Observing and Pitching In (Rogoff, 2014).
Scott, Fiona M.; Butler, Jim; Edwards, John
An action learning program was implemented by a manufacturer using lean production practices. Action learning practices were accommodated during times of stability, but abandoned in times of crisis. The meaning of work in this organizational culture excluded all practices, such as reflection, that were not visible and targeted at immediate…
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…
Mendonça, Roger; Parker, Anthony; Udo, Uwem; Groves, Catherine
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…
Dunphy, Liz; Proctor, Gillian; Bartlett, Ruth; Haslam, Mark; Wood, Chris
This paper describes the delivery of action learning sets to students on the peer educator course provided by the Dementia Studies Department at University of Bradford. Our understanding of action learning sets is laid out together with our rationale for their use on this course. Feedback is presented that described a conflicted, even confused…
Stephens, Simon; Margey, Michael
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…
Ellmer, Eva; Rynne, Steven
The exponential growth in action and adventure sport (e.g. snowboarding, bicycle motorcross (BMX), surfing, parkour) participation over the past two decades has been showcased in world championship events and the inclusion in Olympic programs. Yet, by virtue of their alternative, escapist and/or adventure-based origins, these sports do not fully…
Complex, systemic issues continue to challenge public services without respect for organisational and professional boundaries. In practice, collaborative working with others who have differing professional cultural norms and systems confront members with the need to learn about each other's values, priorities and practices. This paper explores the…
Based on the assumption that the more teachers know about brain science, the better prepared they will be to make instructional decisions, this book presents information on current research regarding learning and memory, and applies the research to situations that educators face daily. Chapter 1 examines the structure of the brain and its…
This article makes a number of interconnected arguments. First, spatially and temporally distributed project teams constitute a new form of interprofessional work and, as a corollary, a new site for interprofessional learning. Second, researchers in cultural-historical activity theory have generated some concepts and methods, for example,…
Hoffmann, Joachim; Lenhard, Alexandra; Sebald, Albrecht; Pfister, Roland
According to ideomotor theory, actions become linked to the sensory feedback they contingently produce, so that anticipating the feedback automatically evokes the action it typically results from. Numerous recent studies have provided evidence in favour of such action-effect learning but left an important issue unresolved. It remains unspecified to what extent action-effect learning is based on associating effect-representations to representations of the performed movements or to representations of the targets at which the behaviour aimed at. Two experiments were designed to clarify this issue. In an acquisition phase, participants learned the contingency between key presses and effect tones. In a following test phase, key-effect and movement-effect relations were orthogonally assessed by changing the hand-key mapping for one half of the participants. Experiment 1 showed precedence for target-effect over movement-effect learning in a forced-choice RT task. In Experiment 2, target-effect learning was also shown to influence the outcome of response selection in a free-choice task. Altogether, the data indicate that both movement-effect and target-effect associations contribute to the formation of action-effect linkages-provided that movements and targets are likewise contingently related to the effects.
Boggs, David L.
The purposes of this article are first, to consider the role of senior citizens as advocates, both in matters of specific concern to their fellow age cohorts and in issues of general interest to the community; and, second, to examine the relationship of self-education and learning to advocacy in civic affairs. Literature on sociological and political theory as well as adult civic education provides a conceptual base from which to explain the involvement of persons in their later years in advocacy efforts and in learning activities designed to enhance civic involvement. Citizens have banded together to advocate their vision of a desired future throughout history. Citizen participation in political and civic affairs is generally age-integrated and intergenerational, thus affording opportunities to dispel negative age stereotypes. Participation in civic affairs invokes ageless values, creates meaning in life, and allows elderly participants to transcend themselves and their limitations.
Bogacz, Rafal; McClure, Samuel M; Li, Jian; Cohen, Jonathan D; Montague, P Read
Recent experimental and theoretical work on reinforcement learning has shed light on the neural bases of learning from rewards and punishments. One fundamental problem in reinforcement learning is the credit assignment problem, or how to properly assign credit to actions that lead to reward or punishment following a delay. Temporal difference learning solves this problem, but its efficiency can be significantly improved by the addition of eligibility traces (ET). In essence, ETs function as decaying memories of previous choices that are used to scale synaptic weight changes. It has been shown in theoretical studies that ETs spanning a number of actions may improve the performance of reinforcement learning. However, it remains an open question whether including ETs that persist over sequences of actions allows reinforcement learning models to better fit empirical data regarding the behaviors of humans and other animals. Here, we report an experiment in which human subjects performed a sequential economic decision game in which the long-term optimal strategy differed from the strategy that leads to the greatest short-term return. We demonstrate that human subjects' performance in the task is significantly affected by the time between choices in a surprising and seemingly counterintuitive way. However, this behavior is naturally explained by a temporal difference learning model which includes ETs persisting across actions. Furthermore, we review recent findings that suggest that short-term synaptic plasticity in dopamine neurons may provide a realistic biophysical mechanism for producing ETs that persist on a timescale consistent with behavioral observations.
Glassner, Amnon; Eran-Zoran, Yael
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…
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…
Jiang, Zhuolin; Lin, Zhe; Davis, Larry S
A shape-motion prototype-based approach is introduced for action recognition. The approach represents an action as a sequence of prototypes for efficient and flexible action matching in long video sequences. During training, an action prototype tree is learned in a joint shape and motion space via hierarchical K-means clustering and each training sequence is represented as a labeled prototype sequence; then a look-up table of prototype-to-prototype distances is generated. During testing, based on a joint probability model of the actor location and action prototype, the actor is tracked while a frame-to-prototype correspondence is established by maximizing the joint probability, which is efficiently performed by searching the learned prototype tree; then actions are recognized using dynamic prototype sequence matching. Distance measures used for sequence matching are rapidly obtained by look-up table indexing, which is an order of magnitude faster than brute-force computation of frame-to-frame distances. Our approach enables robust action matching in challenging situations (such as moving cameras, dynamic backgrounds) and allows automatic alignment of action sequences. Experimental results demonstrate that our approach achieves recognition rates of 92.86 percent on a large gesture data set (with dynamic backgrounds), 100 percent on the Weizmann action data set, 95.77 percent on the KTH action data set, 88 percent on the UCF sports data set, and 87.27 percent on the CMU action data set.
Gerson, Sarah A; Woodward, Amanda L
Prior research suggests that infants' action production affects their action understanding, but little is known about the aspects of motor experience that render these effects. In Study 1, the relative contributions of self-produced (n = 30) and observational (n = 30) action experience on 3-month-old infants' action understanding was assessed using a visual habituation paradigm. In Study 2, generalization of training to a new context was examined (n = 30). Results revealed a unique effect of active over observational experience. Furthermore, findings suggest that benefits of trained actions do not generalize broadly, at least following brief training.
Meyer, Meredith; Baldwin, Dare
Identification of distinct units within a continuous flow of human action is fundamental to action processing. Such segmentation may rest in part on statistical learning. In a series of four experiments, we examined what types of statistics people can use to segment a continuous stream involving many brief, goal-directed action elements. The results of Experiment 1 showed no evidence for sensitivity to conditional probability, whereas Experiment 2 displayed learning based on joint probability. In Experiment 3, we demonstrated that additional exposure to the input failed to engender sensitivity to conditional probability. However, the results of Experiment 4 showed that a subset of adults-namely, those more successful at identifying actions that had been seen more frequently than comparison sequences-were also successful at learning conditional-probability statistics. These experiments help to clarify the mechanisms subserving processing of intentional action, and they highlight important differences from, as well as similarities to, prior studies of statistical learning in other domains, including language.
Mousavi, Amin; Nadjar Araabi, Babak; Nili Ahmadabadi, Majid
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.
Mousavi, Amin; Nadjar Araabi, Babak; Nili Ahmadabadi, Majid
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
Király, Ildikó; Csibra, Gergely; Gergely, György
The principle of rationality has been invoked to explain that infants expect agents to perform the most efficient means action to attain a goal. It has also been demonstrated that infants take into account the efficiency of observed actions to achieve a goal outcome when deciding whether to reenact a specific behavior or not. It is puzzling, however, that they also tend to imitate an apparently suboptimal unfamiliar action even when they can bring about the same outcome more efficiently by applying a more rational action alternative available to them. We propose that this apparently paradoxical behavior is explained by infants' interpretation of action demonstrations as communicative manifestations of novel and culturally relevant means actions to be acquired, and we present empirical evidence supporting this proposal. In Experiment 1, we found that 14-month-olds reenacted novel arbitrary means actions only following a communicative demonstration. Experiment 2 showed that infants' inclination to reproduce communicatively manifested novel actions is restricted to behaviors they can construe as goal-directed instrumental acts. The study also provides evidence that infants' reenactment of the demonstrated novel actions reflects epistemic motives rather than purely social motives. We argue that ostensive communication enables infants to represent the teleological structure of novel actions even when the causal relations between means and end are cognitively opaque and apparently violate the efficiency expectation derived from the principle of rationality. This new account of imitative learning of novel means shows how the teleological stance and natural pedagogy--two separate cognitive adaptations to interpret instrumental versus communicative actions--are integrated as a system for learning socially constituted instrumental knowledge in humans.
Haazebroek, Pascal; van Dantzig, Saskia; Hommel, Bernhard
Robots are increasingly expected to perform tasks in complex environments. To this end, engineers provide them with processing architectures that are based on models of human information processing. In contrast to traditional models, where information processing is typically set up in stages (i.e., from perception to cognition to action), it is increasingly acknowledged by psychologists and robot engineers that perception and action are parts of an interactive and integrated process. In this paper, we present HiTEC, a novel computational (cognitive) model that allows for direct interaction between perception and action as well as for cognitive control, demonstrated by task-related attentional influences. Simulation results show that key behavioral studies can be readily replicated. Three processing aspects of HiTEC are stressed for their importance for cognitive robotics: (1) ideomotor learning of action control, (2) the influence of task context and attention on perception, action planning, and learning, and (3) the interaction between perception and action planning. Implications for the design of cognitive robotics are discussed.
MacIntyre, Peter D.; Blackie, Rebecca A.
The present study examines the relative ability of variables from three motivational frameworks to predict four non-linguistic outcomes of language learning. The study examines Action Control Theory with its measures of (1) hesitation, (2) volatility and (3) rumination. The study also examined Pintrich's expectancy-value model that uses measures…
Heneberry, Pamela; Turner, Arthur
This paper is written to outline our ideas on rituals and reflective places and how this thinking has emerged through our writing, facilitation and reflections around critical action learning and critical leadership. We attempt to show the conceptual framework that underpins our vision of Critical Leadership and how out of this work we have begun…
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…
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…
Brook, Cheryl; Pedler, Mike; Burgoyne, John G
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…
Olsson, Annika; Wadell, Carl; Odenrick, Per; Norell Bergendahl, Margareta
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…
Burgoyne, John G.
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…
Eckstein, Emiel; Veenhoven, Gert; De Loo, Ivo
Becoming a "winning organization" when one currently is an "ugly ducking" can be a difficult and strenuous task. BAT Niemeyer in the Netherlands succeeded in making such a transformation over the course of four years. Action learning was used, among other methods, to steer part of this transformation, in which employee…
Pittaway, Luke; Missing, Caroline; Hudson, Nigel; Maragh, Dean
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…
Gentile, David N.
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…
Bavelier, Daphne; Green, C Shawn; Pouget, Alexandre; Schrater, Paul
The ability of the human brain to learn is exceptional. Yet, learning is typically quite specific to the exact task used during training, a limiting factor for practical applications such as rehabilitation, workforce training, or education. The possibility of identifying training regimens that have a broad enough impact to transfer to a variety of tasks is thus highly appealing. This work reviews how complex training environments such as action video game play may actually foster brain plasticity and learning. This enhanced learning capacity, termed learning to learn, is considered in light of its computational requirements and putative neural mechanisms.
Sargent, Barbara; Reimann, Hendrik; Kubo, Masayoshi; Fetters, Linda
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.
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…
Christopoulos, George I.; King-Casas, Brooks
In social environments, it is crucial that decision-makers take account of the impact of their actions not only for oneself, but also on other social agents. Previous work has identified neural signals in the striatum encoding value-based prediction errors for outcomes to oneself; also, recent work suggests 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
Christopoulos, George I; King-Casas, Brooks
In social environments, it is crucial that decision-makers take account of the impact of their actions not only for oneself, but also on other social agents. Previous work has identified neural signals in the striatum encoding value-based prediction errors for outcomes to oneself; also, recent work suggests that neural activity in prefrontal cortex may similarly encode value-based prediction errors related to outcomes to others. However, prior work also indicates that social valuations are not isomorphic, with social value orientations of decision-makers ranging on a cooperative to competitive continuum; this variation has not been examined within social learning environments. Here, we combine a computational model of learning with functional neuroimaging to examine how individual differences in orientation impact neural mechanisms underlying 'other-value' learning. Across four experimental conditions, reinforcement learning signals for other-value were identified in medial prefrontal cortex, and were distinct from self-value learning signals identified in striatum. Critically, the magnitude and direction of the other-value learning signal depended strongly on an individual's cooperative or competitive orientation toward others. These data indicate that social decisions are guided by a social orientation-dependent learning system that is computationally similar but anatomically distinct from self-value learning. The sensitivity of the medial prefrontal learning signal to social preferences suggests a mechanism linking such preferences to biases in social actions and highlights the importance of incorporating heterogeneous social predispositions in neurocomputational models of social behavior.
Blaschke, Daniel N.; Steinacker, Harold
We show how gravitational actions, in particular the Einstein-Hilbert action, can be obtained from additional terms in Yang-Mills matrix models. This is consistent with recent results on induced gravitational actions in these matrix models, realizing spacetime as four-dimensional brane solutions. It opens up the possibility for a controlled non-perturbative description of gravity through simple matrix models, with interesting perspectives for the problem of vacuum energy. The relation with UV/IR mixing and non-commutative gauge theory is discussed.
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
Wang, Chien-Hsing; Ke, Yi-Ting; Wu, Jin-Tong; Hsu, Wen-Hua
This paper briefly reports the outcomes of an action research inquiry on the use of blogs, MS PowerPoint [PPT], and the Internet as learning tools with a science class of sixth graders for project-based learning. Multiple sources of data were essential to triangulate the key findings articulated in this paper. Corresponding to previous studies, the incorporation of technology and project-based learning could motivate students in self-directed exploration. The students were excited about the autonomy over what to learn and the use of PPT to express what they learned. Differing from previous studies, the findings pointed to the lack information literacy among students. The students lacked information evaluation skills, note-taking and information synthesis. All these findings imply the importance of teaching students about information literacy and visual literacy when introducing information technology into the classroom. The authors suggest that further research should focus on how to break the culture of "copy-and-paste" by teaching the skills of note-taking and synthesis through inquiry projects for science learning. Also, further research on teacher professional development should focus on using collaboration action research as a framework for re-designing graduate courses for science teachers in order to enhance classroom technology integration.
Reichenbach, Michael R.
How Extension fosters social change and innovation can be improved through the use of theory-based educational models. Educational models can serve as foundations for the conceptual designs of educational interventions. I describe, using examples from my own work, one such model: the awareness, solidarity, and action model. This three-part model…
Cowan, Chris Allen
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,…
Anglim, Jeromy; Wynton, Sarah K A
The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking task, which logged participant actions, enabling measurement of strategy use and subtask performance. Model comparison was performed using deviance information criterion (DIC), posterior predictive checks, plots of model fits, and model recovery simulations. Results showed that although learning tended to be monotonically decreasing and decelerating, and approaching an asymptote for all subtasks, there was substantial inconsistency in learning curves both at the group- and individual-levels. This inconsistency was most apparent when constraining both the rate and the ratio of learning to asymptote to be equal across subtasks, thereby giving learning curves only 1 parameter for scaling. The inclusion of 6 strategy covariates provided improved prediction of subtask performance capturing different subtask learning processes and subtask trade-offs. In addition, strategy use partially explained the inconsistency in subtask learning. Overall, the model provided a more nuanced representation of how complex tasks can be decomposed in terms of simpler learning mechanisms.
Fradet, Terrence; Retzepi, Kalliroi; Fry, Ben; Sabeti, Pardis
Background Assessment of the response to the 2014–15 Ebola outbreak indicates the need for innovations in data collection, sharing, and use to improve case detection and treatment. Here we introduce a Machine Learning pipeline for Ebola Virus Disease (EVD) prognosis prediction, which packages the best models into a mobile app to be available in clinical care settings. The pipeline was trained on a public EVD clinical dataset, from 106 patients in Sierra Leone. Methods/Principal Findings We used a new tool for exploratory analysis, Mirador, to identify the most informative clinical factors that correlate with EVD outcome. The small sample size and high prevalence of missing records were significant challenges. We applied multiple imputation and bootstrap sampling to address missing data and quantify overfitting. We trained several predictors over all combinations of covariates, which resulted in an ensemble of predictors, with and without viral load information, with an area under the receiver operator characteristic curve of 0.8 or more, after correcting for optimistic bias. We ranked the predictors by their F1-score, and those above a set threshold were compiled into a mobile app, Ebola CARE (Computational Assignment of Risk Estimates). Conclusions/Significance This method demonstrates how to address small sample sizes and missing data, while creating predictive models that can be readily deployed to assist treatment in future outbreaks of EVD and other infectious diseases. By generating an ensemble of predictors instead of relying on a single model, we are able to handle situations where patient data is partially available. The prognosis app can be updated as new data become available, and we made all the computational protocols fully documented and open-sourced to encourage timely data sharing, independent validation, and development of better prediction models in outbreak response. PMID:26991501
Steck, Laura West; Engler, Jennifer N.; Ligon, Mary; Druen, Perri B.; Cosgrove, Erin
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…
Solution Tree, 2010
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,…
Mullen, Carol A.; Rodríguez, Mariela A.; Allen, Tawannah G.
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…
Harrington, Paula; Gillam, Katy; Andrews, Jane; Day, Christopher
The article reports work over one year by three teachers from the Milton Keynes Primary Schools Learning Network. Their collaborative classroom-focused action research investigated the limits and possibilities of pupils' and teachers' learning through self-evaluation. In phase one the teacher researchers used questionnaires, interviews and…
Jenkins, Emrys R; Mabbett, Gaynor M; Surridge, Andrea G; Warring, Joanna; Gwynn, Elizabeth D
As nurse lecturers we investigated practice development and action learning approaches aimed at enabling postregistration bachelor's- and master's-level nursing students (Community Health Studies, Nursing in the Home) to advance practice in the context of policy and professional developments. A patchwork text was used to assess summatively what students achieved (practice change/development) and how this was informed critically, via an extended epistemology. First-person inquiry supplemented by cooperative inquiry postcourse completion (including reflective discussions with 16 students and 16 practice mentors) were used to assist coresearcher constructions of meaning. A relational, tripartite approach to learning and assessment (students', teachers', and practice mentors' collective contributions) depends on continuing reflective attention. Action learning enhances interrelation of experience with dialectic thinking. The patchwork text functions to promote creative writing, evaluative thinking, and praxis development. Role modeling by all, being genuine and not just "talking" genuine, is challenging yet crucial if people are to function as mutual resources for learning.
Johnson, Jason K.; Oyen, Diane Adele; Chertkov, Michael; Netrapalli, Praneeth
Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However, exact inference is intractable in general graphical models, which suggests the problem of seeking the best approximation to a collection of random variables within some tractable family of graphical models. In this paper, we focus on the class of planar Ising models, for which exact inference is tractable using techniques of statistical physics. Based on these techniques and recent methods for planarity testing and planar embedding, we propose a greedy algorithm for learning the best planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. Finally, we demonstrate our method in simulations and for two applications: modeling senate voting records and identifying geo-chemical depth trends from Mars rover data.
Johnson, Jason K.; Oyen, Diane Adele; Chertkov, Michael; ...
Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However, exact inference is intractable in general graphical models, which suggests the problem of seeking the best approximation to a collection of random variables within some tractable family of graphical models. In this paper, we focus on the class of planar Ising models, for which exact inference is tractable using techniques of statistical physics. Based on these techniques and recent methods for planarity testing and planar embedding, we propose a greedy algorithm for learning the bestmore » planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. Finally, we demonstrate our method in simulations and for two applications: modeling senate voting records and identifying geo-chemical depth trends from Mars rover data.« less
Johnson, Jason K; Chertkov, Michael; Netrapalli, Praneeth
Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However, exact inference is intractable in general graphical models, which suggests the problem of seeking the best approximation to a collection of random variables within some tractable family of graphical models. In this paper, we focus our attention on the class of planar Ising models, for which inference is tractable using techniques of statistical physics [Kac and Ward; Kasteleyn]. Based on these techniques and recent methods for planarity testing and planar embedding [Chrobak and Payne], we propose a simple greedy algorithm for learning the best planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. We present the results of numerical experiments evaluating the performance of our algorithm.
ABSTRACT 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.
Yakushijin, Reiko; Jacobs, Robert A
We report the results of an experiment in which human subjects were trained to perform a perceptual matching task. Subjects were asked to manipulate comparison objects until they matched target objects using the fewest manipulations possible. An unusual feature of the experimental task is that efficient performance requires an understanding of the hidden or latent causal structure governing the relationships between actions and perceptual outcomes. We use two benchmarks to evaluate the quality of subjects' learning. One benchmark is based on optimal performance as calculated by a dynamic programming procedure. The other is based on an adaptive computational agent that uses a reinforcement-learning method known as Q-learning to learn to perform the task. Our analyses suggest that subjects were successful learners. In particular, they learned to perform the perceptual matching task in a near-optimal manner (i.e., using a small number of manipulations) at the end of training. Subjects were able to achieve near-optimal performance because they learned, at least partially, the causal structure underlying the task. In addition, subjects' performances were broadly consistent with those of model-based reinforcement-learning agents that built and used internal models of how their actions influenced the external environment. We hypothesize that people will achieve near-optimal performances on tasks requiring sequences of action-especially sensorimotor tasks with underlying latent causal structures-when they can detect the effects of their actions on the environment, and when they can represent and reason about these effects using an internal mental model.
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…
Moyer, Joanne M.; Sinclair, A. John; Quinn, Lisa
In recent years, action on sustainability has been highly influential around the globe and many now recognize the importance of individual and social learning for inspiring action and achieving sustainability outcomes. Transformative learning theory has been criticized, however, for insufficient development of the link between learning and action.…
This 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…
Coughlan, Paul; Coghlan, David
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…
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…
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…
Keramidas Charidakos, I.; Lingam, M.; Morrison, P. J.; White, R. L.; Wurm, A.
The general, non-dissipative, two-fluid model in plasma physics is Hamiltonian, but this property is sometimes lost or obscured in the process of deriving simplified (or reduced) two-fluid or one-fluid models from the two-fluid equations of motion. To ensure that the reduced models are Hamiltonian, we start with the general two-fluid action functional, and make all the approximations, changes of variables, and expansions directly within the action context. The resulting equations are then mapped to the Eulerian fluid variables using a novel nonlocal Lagrange-Euler map. Using this method, we recover Lüst's general two-fluid model, extended magnetohydrodynamic (MHD), Hall MHD, and electron MHD from a unified framework. The variational formulation allows us to use Noether's theorem to derive conserved quantities for each symmetry of the action.
Ito, Makoto; Doya, Kenji
Computational models of reinforcement learning have recently been applied to analysis of brain imaging and neural recording data to identity neural correlates of specific processes of decision making, such as valuation of action candidates and parameters of value learning. However, for such model-based analysis paradigms, selecting an appropriate model is crucial. In this study we analyze the process of choice learning in rats using stochastic rewards. We show that "Q-learning," which is a standard reinforcement learning algorithm, does not adequately reflect the features of choice behaviors. Thus, we propose a generalized reinforcement learning (GRL) algorithm that incorporates the negative reward effect of reward loss and forgetting of values of actions not chosen. Using the Bayesian estimation method for time-varying parameters, we demonstrated that the GRL algorithm can predict an animal's choice behaviors as efficiently as the best Markov model. The results suggest the usefulness of the GRL for the model-based analysis of neural processes involved in decision making.
Turner, Kagan; Agogino, Adrian K.; Wolpert, David H.; Clancy, Daniel (Technical Monitor)
In this paper we focus on the problem of designing a collective of autonomous agents that individually learn sequences of actions such that the resultant sequence of joint actions achieves a predetermined global objective. We are particularly interested in instances of this problem where centralized control is either impossible or impractical. For single agent systems in similar domains, machine learning methods (e.g., reinforcement learners) have been successfully used. However, applying such solutions directly to multi-agent systems often proves problematic, as agents may work at cross-purposes, or have difficulty in evaluating their contribution to achievement of the global objective, or both. Accordingly, the crucial design step in multiagent systems centers on determining the private objectives of each agent so that as the agents strive for those objectives, the system reaches a good global solution. In this work we consider a version of this problem involving multiple autonomous agents in a grid world. We use concepts from collective intelligence to design goals for the agents that are 'aligned' with the global goal, and are 'learnable' in that agents can readily see how their behavior affects their utility. We show that reinforcement learning agents using those goals outperform both 'natural' extensions of single agent algorithms and global reinforcement, learning solutions based on 'team games'.
Ariel, Ellen; Owens, Leigh
The module described and evaluated here was created in response to perceived learning difficulties in diagnostic test design and interpretation for students in third-year Clinical Microbiology. Previously, the activities in lectures and laboratory classes in the module fell into the lower cognitive operations of "knowledge" and "understanding." The new approach was to exchange part of the traditional activities with elements of interactive learning, where students had the opportunity to engage in deep learning using a variety of learning styles. The effectiveness of the new curriculum was assessed by means of on-course student assessment throughout the module, a final exam, an anonymous questionnaire on student evaluation of the different activities and a focus group of volunteers. Although the new curriculum enabled a major part of the student cohort to achieve higher pass grades (p < 0.001), it did not meet the requirements of the weaker students, and the proportion of the students failing the module remained at 34%. The action research applied here provided a number of valuable suggestions from students on how to improve future curricula from their perspective. Most importantly, an interactive online program that facilitated flexibility in the learning space for the different reagents and their interaction in diagnostic tests was proposed. The methods applied to improve and assess a curriculum refresh by involving students as partners in the process, as well as the outcomes, are discussed. Journal of Microbiology & Biology Education.
Ariel, Ellen; Owens, Leigh
The module described and evaluated here was created in response to perceived learning difficulties in diagnostic test design and interpretation for students in third-year Clinical Microbiology. Previously, the activities in lectures and laboratory classes in the module fell into the lower cognitive operations of “knowledge” and “understanding.” The new approach was to exchange part of the traditional activities with elements of interactive learning, where students had the opportunity to engage in deep learning using a variety of learning styles. The effectiveness of the new curriculum was assessed by means of on-course student assessment throughout the module, a final exam, an anonymous questionnaire on student evaluation of the different activities and a focus group of volunteers. Although the new curriculum enabled a major part of the student cohort to achieve higher pass grades (p < 0.001), it did not meet the requirements of the weaker students, and the proportion of the students failing the module remained at 34%. The action research applied here provided a number of valuable suggestions from students on how to improve future curricula from their perspective. Most importantly, an interactive online program that facilitated flexibility in the learning space for the different reagents and their interaction in diagnostic tests was proposed. The methods applied to improve and assess a curriculum refresh by involving students as partners in the process, as well as the outcomes, are discussed. Journal of Microbiology & Biology Education PMID:26753024
Alberta Advanced Education, 2006
The Aboriginal Learning Subcommittee looked specifically at developing recommendations that address First Nations, Metis and Inuit learning needs and supports. The Subcommittee proposes policy actions and recommends that all stakeholders work together to implement these actions. The first recommendation for action is to build on partnerships to…
Moore, Angela R.; Buchanan, Natasha D.; Fairley, Temeika L.; Smith, Judith Lee
Long-term objectives associated with cancer survivors have been suggested by Healthy People 2020, including increasing the proportion of survivors living beyond 5 years after diagnosis and improving survivors’ mental and physical health-related quality of life. Prior to reaching these objectives, several intermediate steps must be taken to improve the physical, social, emotional, and financial well-being of cancer survivors. Public health has a role in developing strategic, actionable, and measurable approaches to facilitate change at multiple levels to improve the lives of survivors and their families. The social ecological model has been used by the public health community as the foundation of multilevel intervention design and implementation, encouraging researchers and practitioners to explore methods that promote internal and external changes at the individual, interpersonal, organizational, community, and policy levels. The survivorship community, including public health professionals, providers, policymakers, survivors, advocates, and caregivers, must work collaboratively to identify, develop, and implement interventions that benefit cancer survivors. The National Action Plan for Cancer Survivorship highlights public health domains and associated strategies that can be the impetus for collaboration between and among the levels in the social ecological model and are integral to improving survivor outcomes. This paper describes the Public Health Action Model for Cancer Survivorship, an integrative framework that combines the National Action Plan for Cancer Survivorship with the social ecological model to demonstrate how interaction among the various levels may promote better outcomes for survivors. PMID:26590641
Beek, P J; Dessing, J C; Peper, C E; Bullock, D
In recent years, several phenomenological dynamical models have been formulated that describe how perceptual variables are incorporated in the control of motor variables. We call these short-route models as they do not address how perception-action patterns might be constrained by the dynamical properties of the sensory, neural and musculoskeletal subsystems of the human action system. As an alternative, we advocate a long-route modelling approach in which the dynamics of these subsystems are explicitly addressed and integrated to reproduce interceptive actions. The approach is exemplified through a discussion of a recently developed model for interceptive actions consisting of a neural network architecture for the online generation of motor outflow commands, based on time-to-contact information and information about the relative positions and velocities of hand and ball. This network is shown to be consistent with both behavioural and neurophysiological data. Finally, some problems are discussed with regard to the question of how the motor outflow commands (i.e. the intended movement) might be modulated in view of the musculoskeletal dynamics. PMID:14561342
Keramidas Charidakos, Ioannis; Lingam, Manasvi; Morrison, Philip; White, Ryan; Wurm, Alexander
The general, non-dissipative, two-fluid model in plasma physics is Hamiltonian, but this property is sometimes lost in the process of deriving simplified two-fluid or one-fluid models from the two-fluid equations of motion. One way to ensure that the reduced models are Hamiltonian is to derive them from an action. We start with the general two-fluid action functional for an electron and an ion fluid interacting with an electromagnetic field, expressed in Lagrangian variables. We perform a change of variables and make various approximations (eg. quasineutrality and ordering of the fields) and small parameter expansions directly in the action. The resulting equations of motion are then mapped to the Eulerian fluid variables using a novel nonlocal Lagrange-Euler map. The correct Eulerian equations are obtained after we impose locality. Using this method and the proper approximations and expansions, we recover Lust's general two-fluid model, extended MHD, Hall MHD, and Electron MHD from a unified framework. The variational formulation allows us to use Noether's theorem to derive conserved quantities for each symmetry of the action. U.S. Dept. of Energy Contract # DE-FG05-80ET-53088, Western New England University Research Fund.
Bers, Marina U.
This paper presents Project InterActions, a series of 5-week workshops in which very young learners (4- to 7-year-old children) and their parents come together to build and program a personally meaningful robotic project in the context of a multigenerational robotics-based community of practice. The goal of these family workshops is to teach both parents and children about the mechanical and programming aspects involved in robotics, as well as to initiate them in a learning trajectory with and about technology. Results from this project address different ways in which parents and children learn together and provide insights into how to develop educational interventions that would educate parents, as well as children, in new domains of knowledge and skills such as robotics and new technologies.
Nguyen-Tuong, Duy; Peters, Jan
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.
Potter, Tracey C S; Bryce, Nessa V; Hartley, Catherine A
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.
Copperman, Elana; Beeri, Catriel; Ben-Zvi, Nava
This paper introduces various visual models for the analysis and description of learning processes. The models analyse learning on two levels: the dynamic level (as a process over time) and the functional level. Two types of model for dynamic modelling are proposed: the session trace, which documents a specific learner in a particular learning…
Hirsh, Stephanie; Hord, Shirley
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…
Christiansen, Alan D.; Mason, Matthew T.; Mitchell, Tom M.
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.
Tsoi, Mun Fie; Goh, Ngoh Khang; Chia, Lian Sai
This paper provides insights on a hybrid learning model for multimedia learning design conceptualized from the Piagetian science learning cycle model and the Kolb's experiential learning model. This model represents learning as a cognitive process in a cycle of four phases, namely, Translating, Sculpting, Operationalizing, and Integrating and is…
Cooper, Jeffrey C.; Dunne, Simon; Furey, Teresa; O’Doherty, John P.
The dorsal striatum plays a key role in the learning and expression of instrumental reward associations that are acquired through direct experience. However, not all learning about instrumental actions require direct experience. Instead, humans and other animals are also capable of acquiring instrumental actions by observing the experiences of others. In this study, we investigated the extent to which human dorsal striatum is involved in observational as well as experiential instrumental reward learning. Human participants were scanned with fMRI while they observed a confederate over a live video performing an instrumental conditioning task to obtain liquid juice rewards. Participants also performed a similar instrumental task for their own rewards. Using a computational model-based analysis, we found reward prediction errors in the dorsal striatum not only during the experiential learning condition but also during observational learning. These results suggest a key role for the dorsal striatum in learning instrumental associations, even when those associations are acquired purely by observing others. PMID:21812568
Gibson, Sara Henderson
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…
Lyso, Ingunn Hybertsen; Mjoen, Kristian; Levin, Morten
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…
Rantavuori, Juhana; Engeström, Yrjö; Lipponen, Lasse
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…
Chatti, Mohamed Amine; Jarke, Matthias; Specht, Marcus
Recognizing the failures of traditional Technology Enhanced Learning (TEL) initiatives to achieve performance improvement, we need to rethink how we design new TEL models that can respond to the learning requirements of the 21st century and mirror the characteristics of knowledge and learning which are fundamentally personal, social, distributed,…
Kendal, Jeremy R.
The application of modelling to social learning in monkey populations has been a neglected topic. Recently, however, a number of statistical, simulation and analytical approaches have been developed to help examine social learning processes, putative traditions, the use of social learning strategies and the diffusion dynamics of socially…
Casey, Ashley; Dyson, Ben
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…
Tipps, Steve; And Others
This paper describes three models of brain function, each of which contributes to an integrated understanding of human learning. The first model, the up-and-down model, emphasizes the interconnection between brain structures and functions, and argues that since physiological, emotional, and cognitive responses are inseparable, the learning context…
Aldridge, Jill M.; Fraser, Barry J.; Bell, Lisa; Dorman, Jeffrey
This article reports the development, validation and use of an instrument designed to provide teachers with feedback information, based on students' perceptions, about their classroom environments. The instrument was developed to provide teachers with feedback that they could use to reflect on their teaching practices and, in turn, guide the implementation of strategies to improve their learning environments. To determine the validity and reliability of the new instrument, data from 2043 grade 11 and 12 students from 147 classes in 9 schools were analysed. The Rasch model was used to convert data collected using a frequency response scale into interval data that are suitable for parametric analyses. During an action research process, reflective journals, written feedback, discussions at a forum and interviews with eight teachers helped to illuminate the processes used by teachers during action research. This article reports the views of these teachers in general and examines more closely how one of the teachers used student responses to the learning environment questionnaire as a tool for reflection and as a guide in transforming her classroom environment. This case study helped us to gauge the extent to which action research based on students' perceptions of the learning environment was useful in guiding teachers' improvements of their classroom learning environments.
Red'ko, Vladimir G; Mosalov, Oleg P; Prokhorov, Danil V
We study a model of evolving populations of self-learning agents and analyze the interaction between learning and evolution. We consider an agent-broker that predicts stock price changes and uses its predictions for selecting actions. Each agent is equipped with a neural network adaptive critic design for behavioral adaptation. We discuss three cases in which either evolution or learning, or both, are active in our model. We show that the Baldwin effect can be observed in our model, viz. originally acquired adaptive policy of best agent-brokers becomes inherited over the course of the evolution. We also compare the behavioral tactics of our agents to the searching behavior of simple animals.
Biddle, Elyce Anne; Keane, Paul R
Action Learning is a problem-solving process that is used in various industries to address difficult problems. This project applied Action Learning to a leading problem in agricultural safety. Tractor overturns are the leading cause of fatal injury to farmworkers. This cause of injury is preventable using rollover protective structures (ROPS), protective equipment that functions as a roll bar structure to protect the operator in the event of an overturn. For agricultural tractors manufactured after 1976 and employee operated, Occupational Safety and Health Administration (OSHA) regulation requires employers to equip them with ROPS and seat belts. By the mid-1980s, US tractor manufacturers began adding ROPS on all farm tractors over 20 horsepower sold in the United States (http://www.nasdonline.org/document/113/d001656/rollover-protection-for-farm-tractor-operators.html). However, many older tractors remain in use without ROPS, putting tractor operators at continued risk for traumatic injury and fatality. For many older tractor models ROPS are available for retrofit, but for a variety of reasons, tractor owners have not chosen to retrofit those ROPS. The National Institute for Occupational Safety and Health (NIOSH) attempted various means to ameliorate this occupational safety risk, including the manufacture of a low-cost ROPS for self-assembly. Other approaches address barriers to adoption. An Action Learning approach to increasing adoption of ROPS was followed in Virginia and New York, with mixed results. Virginia took action to increase the manufacturing and adoption of ROPS, but New York saw problems that would be insurmountable. Increased focus on team composition might be needed to establish effective Action Learning teams to address this problem.
Aleven, Vincent; Roll, Ido; McLaren, Bruce M.; Koedinger, Kenneth R.
Assessment of students' self-regulated learning (SRL) requires a method for evaluating whether observed actions are appropriate acts of self-regulation in theEv specific learning context in which they occur. We review research that has resulted in an automated method for context-sensitive assessment of a specific SRL strategy, help seeking while…
Vollmer, Anna-Lisa; Mühlig, Manuel; Steil, Jochen J.; Pitsch, Karola; Fritsch, Jannik; Rohlfing, Katharina J.; Wrede, Britta
Robot learning by imitation requires the detection of a tutor's action demonstration and its relevant parts. Current approaches implicitly assume a unidirectional transfer of knowledge from tutor to learner. The presented work challenges this predominant assumption based on an extensive user study with an autonomously interacting robot. We show that by providing feedback, a robot learner influences the human tutor's movement demonstrations in the process of action learning. We argue that the robot's feedback strongly shapes how tutors signal what is relevant to an action and thus advocate a paradigm shift in robot action learning research toward truly interactive systems learning in and benefiting from interaction. PMID:24646510
Vollmer, Anna-Lisa; Mühlig, Manuel; Steil, Jochen J; Pitsch, Karola; Fritsch, Jannik; Rohlfing, Katharina J; Wrede, Britta
Robot learning by imitation requires the detection of a tutor's action demonstration and its relevant parts. Current approaches implicitly assume a unidirectional transfer of knowledge from tutor to learner. The presented work challenges this predominant assumption based on an extensive user study with an autonomously interacting robot. We show that by providing feedback, a robot learner influences the human tutor's movement demonstrations in the process of action learning. We argue that the robot's feedback strongly shapes how tutors signal what is relevant to an action and thus advocate a paradigm shift in robot action learning research toward truly interactive systems learning in and benefiting from interaction.
Desantis, Andrea; Haggard, Patrick
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
Pauleen, David J.; Corbitt, Brian; Yoong, Pak
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…
Watson, Connie; Wu, Aimee Tiu
This chapter describes how the concept of learning cities evolved from the "learning society" and the lifelong education and learning movements, and advances multiple forms of communities of learning.
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…
Bunlon, Frédérique; Marshall, Peter J; Quandt, Lorna C; Bouquet, Cedric A
According to the ideomotor theory, actions are represented in terms of their perceptual effects, offering a solution for the correspondence problem of imitation (how to translate the observed action into a corresponding motor output). This effect-based coding of action is assumed to be acquired through action-effect learning. Accordingly, performing an action leads to the integration of the perceptual codes of the action effects with the motor commands that brought them about. While ideomotor theory is invoked to account for imitation, the influence of action-effect learning on imitative behavior remains unexplored. In two experiments, imitative performance was measured in a reaction time task following a phase of action-effect acquisition. During action-effect acquisition, participants freely executed a finger movement (index or little finger lifting), and then observed a similar (compatible learning) or a different (incompatible learning) movement. In Experiment 1, finger movements of left and right hands were presented as action-effects during acquisition. In Experiment 2, only right-hand finger movements were presented during action-effect acquisition and in the imitation task the observed hands were oriented orthogonally to participants' hands in order to avoid spatial congruency effects. Experiments 1 and 2 showed that imitative performance was improved after compatible learning, compared to incompatible learning. In Experiment 2, although action-effect learning involved perception of finger movements of right hand only, imitative capabilities of right- and left-hand finger movements were equally affected. These results indicate that an observed movement stimulus processed as the effect of an action can later prime execution of that action, confirming the ideomotor approach to imitation. We further discuss these findings in relation to previous studies of action-effect learning and in the framework of current ideomotor approaches to imitation.
Klaes, Christian; Schneegans, Sebastian; Schöner, Gregor; Gail, Alexander
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
Bishop, Christopher M
Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.
Bishop, Christopher M.
Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications. PMID:23277612
Grondman, Ivo; Vaandrager, Maarten; Buşoniu, Lucian; Babuska, Robert; Schuitema, Erik
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.
Kiilo, Tatjana; Kutsar, Dagmar
Based on appreciative inquiry and threshold concepts from an intercultural learning perspective, the article makes insights into the constructivist social learning practice of Estonian language learning amongst Russian-speaking teachers in Estonia. The application of educational action research methodology, more specifically that of Bridget…
Draskovic, I.; Holdrinet, R.; Bulte, J.; Bolhuis, S.; Van Leeuwe, J.
This article presents findings from an empirical study on the relations between the variables comprising learning mechanisms in small collaborative groups. Variables comprising the central learning mechanisms component were "task related interactions," "knowledge elaborations," and "subjective estimation of knowledge acquisition." Student related…
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…
Green, C Shawn; Pouget, Alexandre; Bavelier, Daphne
Action video game play benefits performance in an array of sensory, perceptual, and attentional tasks that go well beyond the specifics of game play [1-9]. That a training regimen may induce improvements in so many different skills is notable because the majority of studies on training-induced learning report improvements on the trained task but limited transfer to other, even closely related, tasks (, but see also [11-13]). Here we ask whether improved probabilistic inference may explain such broad transfer. By using a visual perceptual decision making task [14, 15], the present study shows for the first time that action video game experience does indeed improve probabilistic inference. A neural model of this task  establishes how changing a single parameter, namely the strength of the connections between the neural layer providing the momentary evidence and the layer integrating the evidence over time, captures improvements in action-gamers behavior. These results were established in a visual, but also in a novel auditory, task, indicating generalization across modalities. Thus, improved probabilistic inference provides a general mechanism for why action video game playing enhances performance in a wide variety of tasks. In addition, this mechanism may serve as a signature of training regimens that are likely to produce transfer of learning.
Beniston, Lee; Ellwood, Paul; Gold, Jeff; Roberts, James; Thorpe, Richard
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…
McCormack, Brendan; Henderson, Elizabeth; Boomer, Christine; Collin, Ita; Robinson, David
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…
Abbott, Christine; Weiss, Michael
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…
Cooper, Jeffrey C.; Dunne, Simon; Furey, Teresa; O'Doherty, John P.
The dorsal striatum plays a key role in the learning and expression of instrumental reward associations that are acquired through direct experience. However, not all learning about instrumental actions require direct experience. Instead, humans and other animals are also capable of acquiring instrumental actions by observing the experiences of…
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…
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…
Krishna, Vijay; Marquardt, Michael J.
Organizational commitment has been explored extensively over the past 40 years because of its benefits to individuals and the organization. Action learning, in turn, has been used by companies worldwide to develop leaders, teams and organizations. No study, however, has been undertaken to determine how action learning might develop organizational…
Ballard, Heidi L.; Belsky, Jill M.
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…
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…
Kellie, Jean; Henderson, Eileen; Milsom, Brian; Crawley, Hayley
This account of practice reports on an action learning initiative designed and implemented in partnership between a regional NHS Acute Trust and a UK Business School. The central initiative was the implementation of an action learning programme entitled "Leading change in tissue viability best practice: a development programme for Link Nurse…
Turner, Arthur; Heneberry, Pamela
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…
Reese, Simon R.
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…
Action learning (AL) has been called the "engine of the learning organisation". It has been demonstrated that it can help individuals adapt to, and be more effective in, the fast-changing world. This article reports on a one-day conference held at Henley Business School. The conference was jointly organised by Henley Business School and…
Wickett, R. E. Y.
Five models of independent learning are suitable for use in adult education programs. The common factor is a facilitator who works in some way with the student in the learning process. They display different characteristics, including the extent of independence in relation to content and/or process. Nondirective tutorial instruction and learning…
Duchastel, P.; And Others
Discusses intelligent computer assisted instruction (ICAI) and presents various models of learning which have been proposed. Topics discussed include artificial intelligence; intelligent tutorial systems; tutorial strategies; learner control; system design; learning theory; and knowledge representation of proper and improper (i.e., incorrect)…
Daviess County School District, Owensboro, KY.
This handbook describes the model learning resources center in operation at Daviess County (Kentucky) State Vocational-Technical School and details its objectives, materials, and methods of operation. The manual is organized in six sections. The first section describes the learning resources center, and details its philosophy, purpose, objectives,…
Morita, Kenji; Jitsev, Jenia; Morrison, Abigail
Value-based action selection has been suggested to be realized in the corticostriatal local circuits through competition among neural populations. In this article, we review theoretical and experimental studies that have constructed and verified this notion, and provide new perspectives on how the local-circuit selection mechanisms implement reinforcement learning (RL) algorithms and computations beyond them. The striatal neurons are mostly inhibitory, and lateral inhibition among them has been classically proposed to realize "Winner-Take-All (WTA)" selection of the maximum-valued action (i.e., 'max' operation). Although this view has been challenged by the revealed weakness, sparseness, and asymmetry of lateral inhibition, which suggest more complex dynamics, WTA-like competition could still occur on short time scales. Unlike the striatal circuit, the cortical circuit contains recurrent excitation, which may enable retention or temporal integration of information and probabilistic "soft-max" selection. The striatal "max" circuit and the cortical "soft-max" circuit might co-implement an RL algorithm called Q-learning; the cortical circuit might also similarly serve for other algorithms such as SARSA. In these implementations, the cortical circuit presumably sustains activity representing the executed action, which negatively impacts dopamine neurons so that they can calculate reward-prediction-error. Regarding the suggested more complex dynamics of striatal, as well as cortical, circuits on long time scales, which could be viewed as a sequence of short WTA fragments, computational roles remain open: such a sequence might represent (1) sequential state-action-state transitions, constituting replay or simulation of the internal model, (2) a single state/action by the whole trajectory, or (3) probabilistic sampling of state/action.
Policymakers and education scholars recommend incorporating mathematical modeling into mathematics education. Limited implementation of modeling instruction in schools, however, has constrained research on how students learn to model, leaving unresolved debates about whether modeling should be reified and explicitly taught as a competence, whether…
Fermin, Alan S. R.; Yoshida, Takehiko; Yoshimoto, Junichiro; Ito, Makoto; Tanaka, Saori C.; Doya, Kenji
Humans can select actions by learning, planning, or retrieving motor memories. Reinforcement Learning (RL) associates these processes with three major classes of strategies for action selection: exploratory RL learns state-action values by exploration, model-based RL uses internal models to simulate future states reached by hypothetical actions, and motor-memory RL selects past successful state-action mapping. In order to investigate the neural substrates that implement these strategies, we conducted a functional magnetic resonance imaging (fMRI) experiment while humans performed a sequential action selection task under conditions that promoted the use of a specific RL strategy. The ventromedial prefrontal cortex and ventral striatum increased activity in the exploratory condition; the dorsolateral prefrontal cortex, dorsomedial striatum, and lateral cerebellum in the model-based condition; and the supplementary motor area, putamen, and anterior cerebellum in the motor-memory condition. These findings suggest that a distinct prefrontal-basal ganglia and cerebellar network implements the model-based RL action selection strategy. PMID:27539554
Furtado, Leena; Anderson, Dawnette
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…
Cribbin, John, Ed.; Kennedy, Peter, Ed.
This document consists of 32 papers presenting Hong Kong practitioners' perspectives on lifelong learning. The following papers are included: "Lifelong Learning" (Albert Tuijnman); "Growth and Development of Lifelong Learning in Hong Kong " (John Cribbin); "Competition and Collaboration" (John Cribbin); "A…
Dale, Rick; Roche, Jennifer; Snyder, Kristy; McCall, Ryan
Much evidence exists supporting a richer interaction between cognition and action than commonly assumed. Such findings demonstrate that short-timescale processes, such as motor execution, may relate in systematic ways to longer-timescale cognitive processes, such as learning. We further substantiate one direction of this interaction: the flow of cognition into action systems. Two experiments explored match-to-sample paired-associate learning, in which participants learned randomized pairs of unfamiliar symbols. During the experiments, their hand movements were continuously tracked using the Nintendo Wiimote. Across learning, participant arm movements are initiated and completed more quickly, exhibit lower fluctuation, and exert more perturbation on the Wiimote during the button press. A second experiment demonstrated that action dynamics index novel learning scenarios, and not simply acclimatization to the Wiimote interface. Results support a graded and systematic covariation between cognition and action, and recommend ways in which this theoretical perspective may contribute to applied learning contexts.
Aumann, Michael J.
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…
Haith, Mark P.; Whittingham, Katrina A.
What is an action learning set (ALS)? An ALS is a regular, action focused peer discussion group, generally facilitated, to address work place issues. Methods of undertaking ALS: methods are flexible within a range of approaches according to the group's developing needs. Benefits of ALS: builds trust, professional development, enables action,…
Postsecondary teaching and learning must be reoriented to equip learners with the knowledge, skills, and values they will need for creating a more sustainable world. This action research study examined the effects of implementing the "Burns model of sustainability pedagogy" in university courses taught by the researcher. This model is comprised of…
Lee, Joo Yun; Park, Hyeoun-Ae
The aim of this study is to test the applicability of the International Standards Organization (ISO) Reference terminology model (RTM) for nursing action to describe Detailed Clinical Models (DCMs) for nursing action. All verb and target terms were mapped to 'Action' and 'Target' category of RTM for nursing actions. Among 72 attributes qualifying the verb terms, 50 attributes were mapped to Means, Route, Timing, or Site categories of the nursing action model. Among 142 attributes qualifying the target terms, 20 attributes were mapped to Means, Timing, or Site categories of the nursing action model and 6 attributes were mapped to Degree or Judgment categories of the nursing diagnosis model. The findings suggest the need for an integrated RTM for nursing.
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.
Buntine, Wray L.; Lum, Henry, Jr. (Technical Monitor)
Probabilistic graphical models are being used widely in artificial intelligence, for instance, in diagnosis and expert systems, as a unified qualitative and quantitative framework for representing and reasoning with probabilities and independencies. Their development and use spans several fields including artificial intelligence, decision theory and statistics, and provides an important bridge between these communities. This paper shows by way of example that these models can be extended to machine learning, neural networks and knowledge discovery by representing the notion of a sample on the graphical model. Not only does this allow a flexible variety of learning problems to be represented, it also provides the means for representing the goal of learning and opens the way for the automatic development of learning algorithms from specifications.
Saeb, Sohrab; Weber, Cornelius; Triesch, Jochen
The brain is able to perform actions based on an adequate internal representation of the world, where task-irrelevant features are ignored and incomplete sensory data are estimated. Traditionally, it is assumed that such abstract state representations are obtained purely from the statistics of sensory input for example by unsupervised learning methods. However, more recent findings suggest an influence of the dopaminergic system, which can be modeled by a reinforcement learning approach. Standard reinforcement learning algorithms act on a single layer network connecting the state space to the action space. Here, we involve in a feature detection stage and a memory layer, which together, construct the state space for a learning agent. The memory layer consists of the state activation at the previous time step as well as the previously chosen action. We present a temporal difference based learning rule for training the weights from these additional inputs to the state layer. As a result, the performance of the network is maintained both, in the presence of task-irrelevant features, and at randomly occurring time steps during which the input is invisible. Interestingly, a goal-directed forward model emerges from the memory weights, which only covers the state-action pairs that are relevant to the task. The model presents a link between reinforcement learning, feature detection and forward models and may help to explain how reward systems recruit cortical circuits for goal-directed feature detection and prediction.
Gouko, Manabu; Tomi, Naoki; Nagano, Tomoaki; Ito, Koji
In this paper, we propose a self-organized learning model that can generate behaviors for successfully performing various tasks. The model memorizes various relationships between changes in a state pattern and a motor command through learning. After the learning, the model can perform various tasks by generating the various behaviors automatically. We confirmed the performance of the model by applying it to a mobile robot simulation. The results indicate that suitable behaviors for all the tasks generated spontaneously. Additionally, we propose a sequential learning method which modifies the memorized various relationships while the model executes the task. And we confirmed the effectiveness of the sequential learning by the simulation.
In T. Roth -Berghofer, N. Tintarev, & D.B. Leake (Eds.) Explanation-Aware Computing: Papers from the IJCAI Workshop. Barcelona, Spain. Molineaux, M...pp. 65- 70). Edinburgh, Scotland : IEEE Press. Sutton, R.S., & Barto, A.G. (1998). Reinforcement learning: An introduction. Cambridge, MA: MIT Press
Kirsch, Louise P.; Cross, Emily S.
The way in which we perceive others in action is biased by one's prior experience with an observed action. For example, we can have auditory, visual, or motor experience with actions we observe others perform. How action experience via 1, 2, or all 3 of these modalities shapes action perception remains unclear. Here, we combine pre- and post-training functional magnetic resonance imaging measures with a dance training manipulation to address how building experience (from auditory to audiovisual to audiovisual plus motor) with a complex action shapes subsequent action perception. Results indicate that layering experience across these 3 modalities activates a number of sensorimotor cortical regions associated with the action observation network (AON) in such a way that the more modalities through which one experiences an action, the greater the response is within these AON regions during action perception. Moreover, a correlation between left premotor activity and participants' scores for reproducing an action suggests that the better an observer can perform an observed action, the stronger the neural response is. The findings suggest that the number of modalities through which an observer experiences an action impacts AON activity additively, and that premotor cortical activity might serve as an index of embodiment during action observation. PMID:26209850
Kirsch, Louise P; Cross, Emily S
The way in which we perceive others in action is biased by one's prior experience with an observed action. For example, we can have auditory, visual, or motor experience with actions we observe others perform. How action experience via 1, 2, or all 3 of these modalities shapes action perception remains unclear. Here, we combine pre- and post-training functional magnetic resonance imaging measures with a dance training manipulation to address how building experience (from auditory to audiovisual to audiovisual plus motor) with a complex action shapes subsequent action perception. Results indicate that layering experience across these 3 modalities activates a number of sensorimotor cortical regions associated with the action observation network (AON) in such a way that the more modalities through which one experiences an action, the greater the response is within these AON regions during action perception. Moreover, a correlation between left premotor activity and participants' scores for reproducing an action suggests that the better an observer can perform an observed action, the stronger the neural response is. The findings suggest that the number of modalities through which an observer experiences an action impacts AON activity additively, and that premotor cortical activity might serve as an index of embodiment during action observation.
Haddad, B.I.; Parish, G.B.; Hauge, L.
An environmental investigation uncovered petroleum contamination at a gasoline station in southern Wisconsin. The site was located in part of the ancestral Rock River valley in Rock County, Wisconsin where the valley is filled with sands and gravels. Groundwater pump tests were conducted for determination of aquifer properties needed to plan a remediation system; the results were indicative of a very high hydraulic conductivity. The site hydrogeology was modeled using the U.S. Geological Survey`s groundwater model, Modflow. The calibrated model was used to determine the number, pumping rate, and configuration of recovery wells to remediate the site. The most effective configuration was three wells pumping at 303 liters per minute (1/m) (80 gallons per minute (gpm)), producing a total pumping rate of 908 l/m (240 gpm). Treating 908 l/min (240 gpm) or 1,308,240 liters per day (345,600 gallons per day) constituted a significant volume to be treated and discharged. It was estimated that pumping for the two year remediation would cost $375,000 while the air sparging would cost $200,000. The recommended remedial system consisted of eight air sparging wells and four vapor recovery laterals. The Wisconsin Department of Natural Resources (WDNR) approved the remedial action plan in March, 1993. After 11 months of effective operation the concentrations of removed VOCs had decreased by 94 percent and groundwater sampling indicated no detectable concentrations of gasoline contaminants. Groundwater modeling was an effective technique to determine the economic feasibility of a groundwater remedial alternative.
While the subject of learning has attracted immense interest from both behavioral and neural scientists, only relatively few investigators have observed single-neuron activity while animals are acquiring an operantly conditioned response, or when that response is extinguished. But even in these cases, observation periods usually encompass only a single stage of learning, i.e. acquisition or extinction, but not both (exceptions include protocols employing reversal learning; see Bingman et al.1 for an example). However, acquisition and extinction entail different learning mechanisms and are therefore expected to be accompanied by different types and/or loci of neural plasticity. Accordingly, we developed a behavioral paradigm which institutes three stages of learning in a single behavioral session and which is well suited for the simultaneous recording of single neurons' action potentials. Animals are trained on a single-interval forced choice task which requires mapping each of two possible choice responses to the presentation of different novel visual stimuli (acquisition). After having reached a predefined performance criterion, one of the two choice responses is no longer reinforced (extinction). Following a certain decrement in performance level, correct responses are reinforced again (reacquisition). By using a new set of stimuli in every session, animals can undergo the acquisition-extinction-reacquisition process repeatedly. Because all three stages of learning occur in a single behavioral session, the paradigm is ideal for the simultaneous observation of the spiking output of multiple single neurons. We use pigeons as model systems, but the task can easily be adapted to any other species capable of conditioned discrimination learning. PMID:24961391
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.
Ae, Tadashi; Kioi, Kazumasa
We discuss a new model for concept based on topological learning, where the learning process on the neural network is represented by mathematical topology. The topological learning of neural networks is summarized by a quotient of input space and the hierarchical step induces a tree where each node corresponds to a quotient. In general, the concept acquisition is a difficult problem, but the emotion for a subject is represented by providing the questions to a person. Therefore, a kind of concept is captured by such data and the answer sheet can be mapped into a topology consisting of trees. In this paper, we will discuss a way of mapping the emotional concept to a topological learning model.
Sun, Hao; Wang, Cheng; Wang, Boliang
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.
Broda, Herbert W.
Since Herb Broda published Schoolyard-Enhanced Learning, his groundbreaking first book on outdoor learning, many schools across North America have embraced the benefits of "greening" their learning programs. Herb has visited dozens of these schools and nature centers, and he showcases the very best examples of schoolyard-enhanced…
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…
Pitti, Alexandre; Braud, Raphaël; Mahé, Sylvain; Quoy, Mathias; Gaussier, Philippe
During development, infants learn to differentiate their motor behaviors relative to various contexts by exploring and identifying the correct structures of causes and effects that they can perform; these structures of actions are called task sets or internal models. The ability to detect the structure of new actions, to learn them and to select on the fly the proper one given the current task set is one great leap in infants cognition. This behavior is an important component of the child's ability of learning-to-learn, a mechanism akin to the one of intrinsic motivation that is argued to drive cognitive development. Accordingly, we propose to model a dual system based on (1) the learning of new task sets and on (2) their evaluation relative to their uncertainty and prediction error. The architecture is designed as a two-level-based neural system for context-dependent behavior (the first system) and task exploration and exploitation (the second system). In our model, the task sets are learned separately by reinforcement learning in the first network after their evaluation and selection in the second one. We perform two different experimental setups to show the sensorimotor mapping and switching between tasks, a first one in a neural simulation for modeling cognitive tasks and a second one with an arm-robot for motor task learning and switching. We show that the interplay of several intrinsic mechanisms drive the rapid formation of the neural populations with respect to novel task sets.
Learning style is one of the individual differences that play an important but controversial role in the learning process. This paper aims at providing a critical analysis regarding learning styles and their use in technology enhanced learning. The identified criticism issues are addressed by reappraising the so called Unified Learning Style Model (ULSM). A detailed description of the ULSM components is provided, together with their rationale. The practical applicability of the model in adaptive web-based educational systems and its advantages versus traditional learning style models are also outlined.
Kim, Hyunsong; Kim, Dongsik
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…
Mevorach, Miriam; Strauss, Sidney
In previous studies on teachers' cognition, we discovered that teachers' teaching can be described via a general in-action mental model (IAMM) concerning the structure of the mind and the roles of teaching in fostering children's learning. The purpose of our study was to examine teacher educators' IAMM regarding student teachers' minds and…
Joksimovic, Srecko; Hatala, Marek; Gaševic, Dragan
Teaching and learning in networked settings has attracted significant attention recently. The central topic of networked learning research is human-human and human-information interactions occurring within a networked learning environment. The nature of these interactions is highly complex and usually requires a multi-dimensional approach to…
Martin, Michael W.; Shen, Yuzhong
This paper explores the distinction between operative and resultant actions in games, and proposes that the learning space created by a serious game is a function of these actions. Further, it suggests a possible relationship between these actions and the forms of cognitive load imposed upon the game player. Association of specific types of cognitive load with respective forms of actions in game mechanics also presents some heuristics for integrating learning content into serious games. Research indicates that different balances of these types of actions are more suitable for novice or experienced learners. By examining these relationships, we can develop a few basic principles of game design which have an increased potential to promote positive learning outcomes.
Liu, Quan; Ling, Xionghong; Cui, Zhiming
Reinforcement learning (RL) is one kind of interactive learning methods. Its main characteristics are “trial and error” and “related reward.” A hierarchical reinforcement learning method based on action subrewards is proposed to solve the problem of “curse of dimensionality,” which means that the states space will grow exponentially in the number of features and low convergence speed. The method can reduce state spaces greatly and choose actions with favorable purpose and efficiency so as to optimize reward function and enhance convergence speed. Apply it to the online learning in Tetris game, and the experiment result shows that the convergence speed of this algorithm can be enhanced evidently based on the new method which combines hierarchical reinforcement learning algorithm and action subrewards. The “curse of dimensionality” problem is also solved to a certain extent with hierarchical method. All the performance with different parameters is compared and analyzed as well. PMID:24600318
Schuetze, Hans G.
To answer the question "Financing what?" this article distinguishes several models of lifelong learning as well as a variety of lifelong learning activities. Several financing methods are briefly reviewed, however the principal focus is on Individual Learning Accounts (ILAs) which were seen by some analysts as a promising model for…
Gill, Simone V.; Adolph, Karen E.; Vereijken, Beatrix
A critical aspect of perception-action coupling is the ability to modify ongoing actions in accordance with variations in the environment. Infants' ability to modify their gait patterns to walk down shallow and steep slopes was examined at three nested time scales. Across sessions, a microgenetic training design showed rapid improvements after the…
Tobin, Jennifer Ann
This action research study used narrative analysis to explore the role of the body in the writing process of creative writers. Specifically, the purpose of this action research study was threefold: it was first to examine how professional creative writers describe their writing process with particular attention to their perceptions of the role and…
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…
Lloyd, Kevin; Becker, Nadine; Jones, Matthew W.; Bogacz, Rafal
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
Freeman, Michael K.; Whitson, Donna L.
Reviews models of learning style, cognitive style, and thinking style and makes recommendations: (1) style preferences are not unchangeable; (2) style refers to learner actions not ability; (3) learning should be considered broader than cognitive achievement; and (4) teachers should adopt a bilateral approach to influencing student actions. (SK)
The purpose of this article is to present a specific approach to the practice of action research "in complex organisations". Clearly, there are many approaches to the challenge of doing action research in organisations; approaches that are, and also must be, quite context dependent and specific. But my purpose is neither to give an…
Karallis, Takis; Sandelands, Eric
This article provides a case study of how Kentz Engineers & Constructors, with more than 10,000 employees in 26 countries, are leveraging learning to "Build better futures" for its stakeholders: clients, shareholders, employees and communities. Kentz provide opportunities for learning at all levels, ensuring that "no one is left behind". This case…
Doos, Marianne; Wilhelmson, Lena
Purpose: The paper seeks to argue for a theoretical contribution that deals with the detection of collective learning. The aim is to examine and clarify the genesis processes of collective learning. The empirical basis is a telecoms context with task-driven networking across both internal and external organisational borders.…
Eidson, Karla W.; Nickson, Lautrice; Hughes, Teresa
Preservice teacher education candidates identified personal and professional benefits of participating in a service-learning project helping a food pantry, culminating in a 48-hour fast. At the end of the project, student reflections revealed that the service-learning component influenced participants' preconceptions about hunger.
This dissertation applies reinforcement learning to the adaptive control of active sensory-motor systems. Active sensory-motor systems, in addition...distinct states in the external world. This phenomenon, called perceptual aliasing, is shown to destabilize existing reinforcement learning algorithms
Scheuer, Oliver; Muhlenbrock, Martin; Melis, Erica
Recently, there is a growing interest in the automatic analysis of learner activity in web-based learning environments. The approach and system SIAM (System for Interaction Analysis by Machine learning) presented in this article aims at helping to establish a basis for the automatic analysis of interaction data by developing a data logging and…
National Foundation for the Improvement of Education, Washington, DC.
Focusing on the use of advanced technologies in classrooms to reshape the educational environment in which students learn, this report on Phase II of the Learning Tomorrow program contains brief descriptions of the most promising educational practices submitted by teachers in response to two nation-wide calls for Innovation in Practice. The report…
Scheer, Andrea; Noweski, Christine; Meinel, Christoph
In an ever changing society of the 21st century, there is a demand to equip students with meta competences going beyond cognitive knowledge. Education, therefore, needs a transition from transferring knowledge to developing individual potentials with the help of constructivist learning. Advantages of constructivist learning, and criteria for its…
Ostergaard, Edvin; Lieblein, Geir; Breland, Tor Arvid; Francis, Charles
Preparing students for a complex and dynamic future is a challenge for educators. This article explores three crucial issues related to agroecological education and learning: (1) the phenomenological foundation for learning agroecology in higher education; (2) the process of students' interactions with a wide range of various learners within and…
van de Vijver, Irene; Ridderinkhof, K. Richard; Cohen, Michael X.
Frontal oscillatory dynamics in the theta (4-8 Hz) and beta (20-30 Hz) frequency bands have been implicated in cognitive control processes. Here we investigated the changes in coordinated activity within and between frontal brain areas during feedback-based response learning. In a time estimation task, participants learned to press a button after…
Teixeira-Poit, Stephanie M.; Cameron, Abigail E.; Schulman, Michael D.
How can instructors use experiential learning strategies to enhance student understanding of research ethics and responsible research conduct? In this article, the authors review literature on using experiential learning to teach research ethics and responsible research conduct. They present a three-step exercise for teaching research ethics and…
Yu, Shengquan; Yang, Xianmin; Cheng, Gang; Wang, Minjuan
This paper presents a new model for organizing learning resources: Learning Cell. This model is open, evolving, cohesive, social, and context-aware. By introducing a time dimension into the organization of learning resources, Learning Cell supports the dynamic evolution of learning resources while they are being used. In addition, by introducing a…
Wang, Jinshuai; Bloodworth, Mike
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…
Childers, Jane B.; Tomasello, Michael
Examined 2-year-olds' comprehension and production of novel nouns, verbs, or actions at 3 intervals after training conducted in massed or distributed exposures. Found that for comprehension, children learned all item types in all training conditions at all retention intervals. Production was better for nonverbal actions than for either word type…
Kawulich, Barbara B.
This manuscript shares lessons learned from conducting an action evaluation of the use of multimedia case studies in Management Information Systems (MIS) courses. Three undergraduate MIS classes took part in the study. The purpose for using case studies in these classes was to teach students about the role of MIS in business. An action evaluation…
Mills, Jane; Gibbon, David; Ingram, Julie; Reed, Matt; Short, Christopher; Dwyer, Janet
The paper explored key factors that might lead to successful agri-environmental social learning and collective action in order to deliver landscape-scale resource management within agri-environment schemes. Using the theory of collective action as an analytical framework the paper examined findings from in-depth interviews with 20 members of two…
Nevid, Jeffrey S.; McClelland, Nate
We used a set of action verbs based on Bloom's taxonomy to assess learning outcomes in two college-level introductory psychology courses. The action verbs represented an acronym, IDEA, comprising skills relating to identifying, defining or describing, evaluating or explaining, and applying psychological knowledge. Exam performance demonstrated…
Altun, Sertel; Yücel-Toy, Banu
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…
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…
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…
Cooper, Terry L.; Sundeen, Richard
The urban studies learning model described in this article was found to increase students' self-esteem, imbue a more flexible and open perspective, contribute to the capacity for self-direction, produce increases on the feeling reactivity, spontaneity, and acceptance of aggression scales, and expand interpersonal competence. (Author/WI)
Caropreso, Edward J.; Haggerty, Mark
Describes an alternative approach to introductory economics based on a cooperative learning model, "Learning Together." Discussion of issues in economics education and cooperative learning in higher education leads to explanation of how to adapt the Learning Together Model to lesson planning in economics. A flow chart illustrates the process for a…
Bolly, Madina; Jonas, Nicolas
Action Research on Measuring Literacy Programme Participants' Learning Outcomes (RAMAA) aims to develop, implement and collaborate on the creation of a methodological approach to measure acquired learning and study the various factors that influence its development. This report examines how RAMAA I has been implemented over the past four years in…
Rector, Patricia; Lyons, Rachel; Yost, Theresa
Using an interdisciplinary approach to water resource education, 4-H Youth Development and Environmental Extension agents enlisted 4-H teens to connect local watershed education with social action. Teens participated in a dynamic service learning project that included learning about nonpoint source pollution; constructing, decorating, and teaching…
Maloyed, Christie L.
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…
This article explores learning opportunities offered by students' written reflections as they learn through writing an action research proposal. From tapping into students' reported struggles, I analysed data using three stages of qualitative data analysis: data reduction, data display, and conclusion drawing (Miles and Huberman 1994). It emerged…
US Department of Education, 2012
Today, the U.S. Department of Education joins the National Task Force on Civic Learning and Democratic Engagement, the American Commonwealth Partnership, and the Campaign for the Civic Mission of Schools in a new national call to action to infuse and enhance civic learning and democratic engagement for all students throughout the American…
Smith, Janice Witt; Clark, Gloria
This research study looks at the implementation of an action research project within a blended learning human resource management class in employee and labor relations. The internal and external environment created conditions that converged in the Perfect Storm and resulted in an almost disastrous learning experience for faculty and students. What…
This paper examines the learning gained from facilitating four action-learning sets whose members were drawn from management teams of local authority, health, education and police, working in partnership. Facilitation posed a series of difficult choices which impacted on personal and organizational dynamics within and between the partnership…
Calvert, Megan; Sheen, Younghee
The creation, implementation, and evaluation of language learning tasks remain a challenge for many teachers, especially those with limited experience with using tasks in their teaching. This action-research study reports on one teacher's experience of developing, implementing, critically reflecting on, and modifying a language learning task…
Edmonstone, John; Robson, Jean
This account of practice describes the introduction of an accredited postgraduate management qualification which used action learning as a major contribution to a blended learning approach in a fragile cross-border setting on the edge of Europe. Conventional management education has frequently been challenged on the grounds of relevance, efficacy…
Ravensbergen, Frances; Vanderplaat, Madine
This paper explores the use of "learning circles" as one form of knowledge production in social action research. It reports on a project that used learning circles as a setting within which to increase the engagement of people living with low income in developing strategies for the reduction and elimination of poverty in Canada. It…
Gabrielsson, Jonas; Tell, Joakim; Politis, Diamanto
Recent calls to close the rigour-relevance gap in business school education have suggested incorporating principles and ideas from action learning in small business management education. In this paper we discuss how business simulation exercises can be used as a platform to trigger students' learning by providing them with a platform where they…
Endresen, Kristin; Von Kotze, Astrid
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…
Attorps, Iiris; Kellner, Eva
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…
Boswell, Laura; Nugent, Peg
Teacher action research using both qualitative and quantitative methods of data collection were used to examine impacts of using visual learning strategies on five preschool children (ages 3-5) with autism in a self-contained classroom. During the six weeks of the study, pictures representing nine learning areas and specific developmental…
Previous research has provided evidence that mental imagery and embodied action can facilitate lexical learning in a novel language. However, it is unclear "how" these factors interact--as well as "why" they play a role--in lexical learning. Through a set of four experiments, this research demonstrated that neither mental…
Shurville, Simon; Rospigliosi, Asher
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…
Hennessy, Michael; Bleakley, Amy; Fishbein, Martin
Quantitative researchers distinguish between causal and effect indicators. What are the analytic problems when both types of measures are present in a quantitative reasoned action analysis? To answer this question, we use data from a longitudinal study to estimate the association between two constructs central to reasoned action theory: behavioral beliefs and attitudes toward the behavior. The belief items are causal indicators that define a latent variable index while the attitude items are effect indicators that reflect the operation of a latent variable scale. We identify the issues when effect and causal indicators are present in a single analysis and conclude that both types of indicators can be incorporated in the analysis of data based on the reasoned action approach.
Hennessy, Michael; Bleakley, Amy; Fishbein, Martin
Quantitative researchers distinguish between causal and effect indicators. What are the analytic problems when both types of measures are present in a quantitative reasoned action analysis? To answer this question, we use data from a longitudinal study to estimate the association between two constructs central to reasoned action theory: behavioral beliefs and attitudes toward the behavior. The belief items are causal indicators that define a latent variable index while the attitude items are effect indicators that reflect the operation of a latent variable scale. We identify the issues when effect and causal indicators are present in a single analysis and conclude that both types of indicators can be incorporated in the analysis of data based on the reasoned action approach. PMID:23243315
Chandrasekaran, Bharath; Koslov, Seth R.; Maddox, W. T.
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
Learmonth, Alyson; Pedler, Mike
Health policy traditionally has tended to focus on health care policy. The World Health Organisation Investment for Health approach aims to influence policy development by locating health as both the outcome of, and an asset for, sustainable economic and social development. The policy context in England offers a range of drivers and opportunities to operationalise the Investment for Health approach through action to improve health and reduce inequalities, nationally and as importantly at a regional and local level. This paper traces developments in the North East of England April 2002-November 2002, from the perspective of an advocate for developing a systemic and systematic approach using an Investment for Health approach. The tool used to track change is based in action learning [M. Pedler, Action Learning for Managers, Lemos and Crane, London, 1996]. The Action Learning Problem Brief identifies why the goal is important, who to, how progress might be identified, difficulties and benefits. Generally, this acts as a starting point for problem solving within an Action Learning Set. This piece of work uses the framework for reflection and tracking, with input from a mentor, at four to eight weekly intervals, 'Auto Action Learning'. The authors pull out key learning points from the process, using a framework 'Towards a model for systematic learning from doing in the North East of England'.
Doll, Bradley B; Simon, Dylan A; Daw, Nathaniel D
The reward prediction error (RPE) theory of dopamine (DA) function has enjoyed great success in the neuroscience of learning and decision-making. This theory is derived from model-free reinforcement learning (RL), in which choices are made simply on the basis of previously realized rewards. Recently, attention has turned to correlates of more flexible, albeit computationally complex, model-based methods in the brain. These methods are distinguished from model-free learning by their evaluation of candidate actions using expected future outcomes according to a world model. Puzzlingly, signatures from these computations seem to be pervasive in the very same regions previously thought to support model-free learning. Here, we review recent behavioral and neural evidence about these two systems, in attempt to reconcile their enigmatic cohabitation in the brain.
Kotnour, Tim; Starr, Stan; Steinrock, T. (Technical Monitor)
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.
York Univ., Toronto (Ontario).
This document summarizes and presents materials produced during a qualitative international study of the role of transformative learning in achieving sustainable societies and global responsibility that included the following activities: case studies of experiences with transformative learning in seven countries; international survey and workshop;…
Moradabadi, Behnaz; Meybodi, Mohammad Reza
Link prediction is a social network research area that tries to predict future links using network structure. The main approaches in this area are based on predicting future links using network structure at a specific period, without considering the links behavior through different periods. For example, a common traditional approach in link prediction calculates a chosen similarity metric for each non-connected link and outputs the links with higher similarity scores as the prediction result. In this paper, we propose a new link prediction method based on temporal similarity metrics and Continuous Action set Learning Automata (CALA). The proposed method takes advantage of using different similarity metrics as well as different time periods. In the proposed algorithm, we try to model the link prediction problem as a noisy optimization problem and use a team of CALAs to solve the noisy optimization problem. CALA is a reinforcement based optimization tool which tries to learn the optimal behavior from the environment feedbacks. To determine the importance of different periods and similarity metrics on the prediction result, we define a coefficient for each of different periods and similarity metrics and use a CALA for each coefficient. Each CALA tries to learn the true value of the corresponding coefficient. Final link prediction is obtained from a combination of different similarity metrics in different times based on the obtained coefficients. The link prediction results reported here show satisfactory of the proposed method for some social network data sets.
Luoma, Markku; Nokelainen, Petri; Ruohotie, Pekka
The factors contributing to organizational learning in police units in Finland and elsewhere were examined to find strategies to improve the prerequisites of learning and compare linear and nonlinear methods of modeling organizational learning prerequisites. A questionnaire was used to collect data from the 281 staff members of five police…
Huang, Chi-Tai; Charman, Tony
This study explored different gradations of emulation in the imitation of actions on objects by 17-month-olds. Experiment 1 established levels of behavioral reproduction following prerecorded video demonstrations similar to those levels following live demonstrations. In Experiment 2, two digitally modified videos, where object movements or body movements critical to producing the target action were highlighted in isolation, were developed. Infants produced the target action equally frequently by observing the object movement video and observing the unmodified video. In contrast, their performance was much less successful based on the body movement video. In Experiment 3, the performance obtained following the object movement video was similar to that following a further video that emphasized the object movements produced in unsuccessful attempts to produce the target action. These findings suggest that emulation in the form of object movement reenactment or affordance learning plays a role in the social learning of actions on objects during infancy.
van de Vijver, Irene; Ridderinkhof, K Richard; Cohen, Michael X
Frontal oscillatory dynamics in the theta (4-8 Hz) and beta (20-30 Hz) frequency bands have been implicated in cognitive control processes. Here we investigated the changes in coordinated activity within and between frontal brain areas during feedback-based response learning. In a time estimation task, participants learned to press a button after specific, randomly selected time intervals (300-2000 msec) using the feedback after each button press (correct, too fast, too slow). Consistent with previous findings, theta-band activity over medial frontal scalp sites (presumably reflecting medial frontal cortex activity) was stronger after negative feedback, whereas beta-band activity was stronger after positive feedback. Theta-band power predicted learning only after negative feedback, and beta-band power predicted learning after positive and negative feedback. Furthermore, negative feedback increased theta-band intersite phase synchrony (a millisecond resolution measure of functional connectivity) among right lateral prefrontal, medial frontal, and sensorimotor sites. These results demonstrate the importance of frontal theta- and beta-band oscillations and intersite communication in the realization of reinforcement learning.
This account of practice explores the concept of resistance in action learning. Resistance is conceptualized as an attempt of self-protection that is manifested in action learners' struggles with their sense of self-efficacy and their social Self. These struggles are an inherent part of the action learning process and may elicit defensive…
Rodríguez-Bonces, Mónica; Ortiz, Kris
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…
Antell, Sonja; Heywood, John
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…
Frese, Michael; Keith, Nina
Every organization is confronted with errors. Most errors are corrected easily, but some may lead to negative consequences. Organizations often focus on error prevention as a single strategy for dealing with errors. Our review suggests that error prevention needs to be supplemented by error management--an approach directed at effectively dealing with errors after they have occurred, with the goal of minimizing negative and maximizing positive error consequences (examples of the latter are learning and innovations). After defining errors and related concepts, we review research on error-related processes affected by error management (error detection, damage control). Empirical evidence on positive effects of error management in individuals and organizations is then discussed, along with emotional, motivational, cognitive, and behavioral pathways of these effects. Learning from errors is central, but like other positive consequences, learning occurs under certain circumstances--one being the development of a mind-set of acceptance of human error.
Vo, Khoi; Rutledge, Robb B.; Chatterjee, Anjan
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
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
Castro, Edgar Oscar
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…
This study reports on graduate students' thoughts and beliefs about utilizing action research as a means of professional development two years after their graduation from a Master of Arts program in Education. Because many school districts now encourage teachers to engage in self-study and to collect data that informs their instruction, the author…
Wagner, Christian; Ip, Rachael K. F.
Virtual worlds, computer-based simulated environments in which users interact via avatars, provide an opportunity for the highly realistic enactment of real life activities online. Unlike computer games, which have a pre-defined purpose, pay-off structure, and action patterns, virtual worlds can leave many of these elements for users to determine.…
This report is a follow-up to the first publication of the Child Proofing Our Communities Campaign, titled "Poisoned Schools: Invisible Threats, Visible Actions." The previous report looked at the problems of public schools built on contaminated land years ago, the trend of proposing new schools on contaminated land, and the threat of…
Wright, Dana E.; Mahiri, Jabari
This case study describes the literacy development of a struggling reader over a seven-month period as he engaged in a youth-led participatory action research (PAR) project. The project's goal was for youth participants to develop a proposal for productive change in their local community and present it to community stakeholders. The study focused…
Bers, Marina U.
This paper presents Project InterActions, a series of 5-week workshops in which very young learners (4- to 7-year-old children) and their parents come together to build and program a personally meaningful robotic project in the context of a multigenerational robotics-based community of practice. The goal of these family workshops is to teach both…
International Association for K-12 Online Learning, 2013
This brief summarizes iNACOL's New Learning Models, which personalize learning using competency-based approaches. Supported by blended and online learning modalities, teachers use technology to differentiate instruction and engage students in deeper learning. By adapting instruction to reflect a student's level of mastery, blended and online…
Woodrow, Lindy J.
This study applies theorizing from educational psychology and language learning to hypothesize a model of language learning that takes into account affect, motivation, and language learning strategies. The study employed a questionnaire to assess variables of motivation, self-efficacy, anxiety, and language learning strategies. The sample…
More, Sandeep Vasant; Kumar, Hemant; Cho, Duk-Yeon; Yun, Yo-Sep; Choi, Dong-Kug
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.
More, Sandeep Vasant; Kumar, Hemant; Cho, Duk-Yeon; Yun, Yo-Sep; Choi, Dong-Kug
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
Warden, Clyde A.; Stanworth, James O.; Ren, Jian Biao; Warden, Antony R.
Low cost and significant advances in technology now allow instructors to create their own virtual learning environments. Creating social interactions within a virtual space that emulates the physical classroom remains challenging. While students are familiar with virtual worlds and video meetings, they are inexperienced as virtual learners. Over a…
Mitchell, Jane; Riley, Philip; Loughran, John
School leadership and teacher professional development are two well-defined fields of research within the education literature, yet there is relatively little research that has examined the leadership of teachers' professional development and learning. The study reported in this paper seeks to understand the experience of teachers who have…
Dickson, Geraldine; Green, Kathryn L.
Twelve older Aboriginal women in a Canadian city were trained to be co-researchers as part of a participatory health assessment and health promotion project involving 40 such women. Lessons were learned about project ownership, Native perceptions of research, use of traditions, participants' capacity to engage in research and analysis, conflict…
Isles, A. R.; Humby, T.
Background: It is now widely acknowledged that there may be a genetic contribution to learning disability and neuropsychiatric disorders, stemming from evidence provided by family, twin and adoption studies, and from explicit syndromic conditions. Recently it has been recognized that in some cases the presentation of genetic syndromes (or discrete…
Stewart, Trae, Ed.; Webster, Nicole, Ed.
Interest in and research on civic engagement and service-learning have increased exponentially. In this rapid growth, efforts have been made to institutionalize pedagogies of engagement across both K-12 and higher education. As a result, increased positive attention has been complemented equally by well-founded critiques complicating experiential…
Nave, Bill, Ed.
What does student-centered learning look like in real-life classrooms? In this collection, educator Bill Nave and nine award-winning K-12 teachers tell the story of how and why they changed their teaching and redesigned their classrooms in order to "reach every child." They reflect on their successes and struggles to put students in…
Noguchi, Fumiko; Guevara, Jose Roberto; Yorozu, Rika
This handbook identifies principles and policy mechanisms to advance community-based learning for sustainable development based on the commitments endorsed by the participants of the "Kominkan-CLC International Conference on Education for Sustainable Development," which took place in Okayama City, Japan, in October 2014. To inform…
Camahalan, Faye Marsha G.; Ruley, Andrea G.
This teacher research project focused on utilizing blended learning to teach writing to middle school students. The intervention was designed to fit into individual lessons needed to improve students' writing skills with the main focus on sentence structure. Sixteen (16) 7th grade students were assessed with a writing sample applying the new…
Tan, Kean Ming; London, Palma; Mohan, Karthik; Lee, Su-In; Fazel, Maryam; Witten, Daniela
We consider the problem of learning a high-dimensional graphical model in which there are a few hub nodes that are densely-connected to many other nodes. Many authors have studied the use of an ℓ1 penalty in order to learn a sparse graph in the high-dimensional setting. However, the ℓ1 penalty implicitly assumes that each edge is equally likely and independent of all other edges. We propose a general framework to accommodate more realistic networks with hub nodes, using a convex formulation that involves a row-column overlap norm penalty. We apply this general framework to three widely-used probabilistic graphical models: the Gaussian graphical model, the covariance graph model, and the binary Ising model. An alternating direction method of multipliers algorithm is used to solve the corresponding convex optimization problems. On synthetic data, we demonstrate that our proposed framework outperforms competitors that do not explicitly model hub nodes. We illustrate our proposal on a webpage data set and a gene expression data set.
Keysers, Christian; Gazzola, Valeria
Spike-timing-dependent plasticity is considered the neurophysiological basis of Hebbian learning and has been shown to be sensitive to both contingency and contiguity between pre- and postsynaptic activity. Here, we will examine how applying this Hebbian learning rule to a system of interconnected neurons in the presence of direct or indirect re-afference (e.g. seeing/hearing one's own actions) predicts the emergence of mirror neurons with predictive properties. In this framework, we analyse how mirror neurons become a dynamic system that performs active inferences about the actions of others and allows joint actions despite sensorimotor delays. We explore how this system performs a projection of the self onto others, with egocentric biases to contribute to mind-reading. Finally, we argue that Hebbian learning predicts mirror-like neurons for sensations and emotions and review evidence for the presence of such vicarious activations outside the motor system. PMID:24778372
This article conveys results from a participatory action research (PAR) engagement with activist/educators working in Ghanaian social movements. First, this PAR group has articulated two typologies from which to understand Ghanaian social movements based on their processes of organization, communication and learning rather than merely the issues,…
Gómez Puente, S. M.; van Eijck, M.; Jochems, W.
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…
This paper summarizes and reviews the literature regarding language learning strategies and it's training model, pointing out the significance of language learning strategies to EFL learners and an applicable and effective language learning strategies training model, which is beneficial both to EFL learners and instructors, is badly needed.
We show that student learning can be accurately modeled using a mixture of learning curves, each of which specifies error probability as a function of time. This approach generalizes Knowledge Tracing , which can be viewed as a mixture model in which the learning curves are step functions. We show that this generality yields order-of-magnitude…
Carmel, D.; Markovitch, S.
Agents that operate in a multi-agent system need an efficient strategy to handle their encounters with other agents involved. Searching for an optimal interactive strategy is a hard problem because it depends mostly on the behavior of the others. In this work, interaction among agents is represented as a repeated two-player game, where the agents` objective is to look for a strategy that maximizes their expected sum of rewards in the game. We assume that agents` strategies can be modeled as finite automata. A model-based approach is presented as a possible method for learning an effective interactive strategy. First, we describe how an agent should find an optimal strategy against a given model. Second, we present an unsupervised algorithm that infers a model of the opponent`s automaton from its input/output behavior. A set of experiments that show the potential merit of the algorithm is reported as well.
Baston, Chiara; Ursino, Mauro
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
Adult Learning, 2012
This article presents the Belem Framework for Action. This framework focuses on harnessing the power and potential of adult learning and education for a viable future. This framework begins with a preamble on adult education and towards lifelong learning.
Malin, Jane T.; Ryan, D. P.; Schreckenghost, D. L.
This paper describes two linked technology development projects to support Space Shuttle ground operations personnel, both during mission preparation analysis and related analyses in missions. The Space Propulsion Robust Analysis Tool (SPRAT) will provide intelligent support and automation for mission analysis setup, interpretation, reporting and documentation. SPRAT models the actions taken by flight support personnel during mission preparation and uses this model to generate an action plan. CONFIG will provide intelligent automation for procedure analyses and failure impact analyses, by simulating the interactions between operations and systems with embedded failures. CONFIG models the actions taken by crew during space vehicle malfunctions and simulates how the planned action sequences in procedures affect a device model. Jointly the SPRAT and CONFIG projects provide an opportunity to investigate how the nature of a task affects the representation of actions, and to determine a more general action representation supporting a broad range of tasks. This paper describes the problems in representing actions for mission preparation and their relation to planning and scheduling.
This report describes work funded under the DARPA Planning and Scheduling Initiative that led to the development of SOCAP (System for Operations Crisis Action Planning). In particular, it describes lessons learned in applying SIPE-2, the underlying AI planning technology within SOCAP, to the domain of military operations deliberate and crisis action planning. SOCAP was demonstrated at the U.S. Central Command and at the Pentagon in early 1992. A more detailed report about the lessons learned is currently being prepared. This report was presented during one of the panel discussions on 'The Relevance of Scheduling to AI Planning Systems.'
de Oliveira, Saionara Nunes; do Prado, Marta Lenise; Kempfer, Silvana Silveira; Martini, Jussara Gue; Caravaca-Morera, Jaime Alonso; Bernardi, Mariely Carmelina
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.
Richardson, Jacques, Ed.
The 21 essays in this two-part book provide conceptual and operational understanding of the nature of models as representations of reality and as tools for description, analysis, interpretation, and forecasting. Topic areas addressed in part 1 (concept) include: the nature of models; the earth as a system; the determination of form; some…
Taschereau-Dumouchel, Vincent; Hétu, Sébastien; Michon, Pierre-Emmanuel; Vachon-Presseau, Etienne; Massicotte, Elsa; De Beaumont, Louis; Fecteau, Shirley; Poirier, Judes; Mercier, Catherine; Chagnon, Yvon C.; Jackson, Philip L.
Motor representations in the human mirror neuron system are tuned to respond to specific observed actions. This ability is widely believed to be influenced by genetic factors, but no study has reported a genetic variant affecting this system so far. One possibility is that genetic variants might interact with visuomotor associative learning to configure the system to respond to novel observed actions. In this perspective, we conducted a candidate gene study on the Brain-derived neurotrophic factor (BDNF) Val66Met polymorphism, a genetic variant linked to motor learning in regions of the mirror neuron system, and tested the effect of this polymorphism on motor facilitation and visuomotor associative learning. In a single-pulse TMS study carried on 16 Met (Val/Met and Met/Met) and 16 Val/Val participants selected from a large pool of healthy volunteers, Met participants showed significantly less muscle-specific corticospinal sensitivity during action observation, as well as reduced visuomotor associative learning, compared to Val homozygotes. These results are the first evidence of a genetic variant tuning sensitivity to action observation and bring to light the importance of considering the intricate relation between genetics and associative learning in order to further understand the origin and function of the human mirror neuron system. PMID:27703276
Polizzi di Sorrentino, Eugenia; Sabbatini, Gloria; Truppa, Valentina; Bordonali, Anna; Taffoni, Fabrizio; Formica, Domenico; Baldassarre, Gianluca; Mirolli, Marco; Guglielmelli, Eugenio; Visalberghi, Elisabetta
Animals have a strong propensity to explore the environment. Spontaneous exploration has a great biological significance since it allows animals to discover and learn the relation between specific behaviours and their consequences. The role of the contingency between action and outcome for learning has been mainly investigated in instrumental learning settings and much less in free exploration contexts. We tested 16 capuchin monkeys (Sapajus spp.) with a mechatronic platform that allowed complex modules to be manipulated and to produce different outcomes. Experimental subjects could manipulate the modules and discover the contingencies between their own specific actions and the outcomes produced (i.e., the opening and lighting of a box). By contrast, Control subjects could operate on the modules, but the outcomes experienced were those performed by their paired Experimental subjects ("yoked-control" paradigm). In the exploration phase, in which no food reward was present, Experimental subjects spent more time on the board and manipulated the modules more than Yoked subjects. Experimental subjects outperformed Yoked subjects in the following test phase, where success required recalling the effective action so to open the box, now baited with food. These findings demonstrate that the opportunity to experience action-outcome contingencies in the absence of extrinsic rewards promotes capuchins' exploration and facilitates learning processes. Thus, this intrinsically motivated learning represents a powerful mechanism allowing the acquisition of skills and cognitive competence that the individual can later exploit for adaptive purposes.
Nichols, Dionne DeShall
Professional learning communities (PLCs) have become one of the most talked about ideas in education today. Many K-12 schools are working to become PLCs in the hope that student learning will improve when adults commit themselves to talking collaboratively about teaching and learning and then take action that will improve student learning and…
Servais, Kristine; Derrington, Mary Lynne; Sanders, Kellie
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:…
Welch, Larry A.
Presents an activity to help students understand the precepts of the Hardy-Weinberg principle and simultaneously permit observation of a model of evolution through natural selection in a nonthreatening setting. (PR)
Windridge, David; Felsberg, Michael; Shaukat, Affan
Perception-action (P-A) learning is an approach to cognitive system building that seeks to reduce the complexity associated with conventional environment-representation/action-planning approaches. Instead, actions are directly mapped onto the perceptual transitions that they bring about, eliminating the need for intermediate representation and significantly reducing training requirements. We here set out a very general learning framework for cognitive systems in which online learning of the P-A mapping may be conducted within a symbolic processing context, so that complex contextual reasoning can influence the P-A mapping. In utilizing a variational calculus approach to define a suitable objective function, the P-A mapping can be treated as an online learning problem via gradient descent using partial derivatives. Our central theoretical result is to demonstrate top-down modulation of low-level perceptual confidences via the Jacobian of the higher levels of a subsumptive P-A hierarchy. Thus, the separation of the Jacobian as a multiplying factor between levels within the objective function naturally enables the integration of abstract symbolic manipulation in the form of fuzzy deductive logic into the P-A mapping learning. We experimentally demonstrate that the resulting framework achieves significantly better accuracy than using P-A learning without top-down modulation. We also demonstrate that it permits novel forms of context-dependent multilevel P-A mapping, applying the mechanism in the context of an intelligent driver assistance system.
Russell, C K; Gregory, D M; Wotton, D; Mordoch, E; Counts, M M
GENESIS (General Ethnographic and Nursing Evaluation Studies In the State) is a tested and proven community analysis strategy that integrates ethnographic and epidemiologic data to arrive at a comprehensive, holistic description of the health of a community and its residents. Communities analyzed in most project GENESIS studies have been rural or semirural. ACTION (Assessing Communities Together in the Identification Of Needs) is an extension of the GENESIS community analysis model that was developed to meet the unique needs of community-level research and analysis in an urban, multicultural setting. Significant differences in the context in which the ACTION projects took place necessitated extensions in specific components of the GENESIS model. Application of the GENESIS model by the ACTION team is described. Based on the experiences with ACTION, recommendations are offered for future urban, multicultural community analysis projects.
Cruz, Georgina E.; Sahley, Christie L.; Muller, Kenneth J.
The spatial and temporal patterns of action potential initiations were studied in a behaving leech preparation to determine the basis of increased firing that accompanies sensitization, a form of non-associative learning requiring the S-interneurons. Little is known at the network level about mechanisms of behavioral sensitization. The S-interneurons, one in each ganglion and linked by electrical synapses with both neighbors to form a chain, are interposed between sensory and motor neurons. In sensitized preparations the strength of shortening is related to S-cell firing, which itself is the result of impulses initiating in several S-cells. Because the S-cells, as independent initiation sites, all contribute to activity in the chain, it was hypothesized that during sensitization, increased multi-site activity increased the chain's firing rate. However, it was found that during sensitization, the single site with the largest initiation rate, the S-cell in the stimulated segment, suppressed initiations in adjacent ganglia. Experiments showed this was both because (1) it received the earliest, greatest input and (2) the delayed synaptic input to the adjacent S-cells coincided with the action potential refractory period. A compartmental model of the S-cell and its inputs showed that a simple, intrinsic mechanism of inexcitability after each action potential may account for suppression of impulse initiations. Thus, a non-synaptic competition between neurons alters synaptic integration in the chain. In one mode, inputs to different sites sum independently, whereas in another, synaptic input to a single site precisely specifies the overall pattern of activity. PMID:17644266
Lee, Seung Hwan; Hoffman, K. Douglas
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…
Honan, Eileen; Evans, Terry; Muspratt, Sandy; Paraide, Patricia; Reta, Medi; Baroutsis, Aspa
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…
Probert, William J. M.; Hauser, C.E.; McDonald-Madden, E.; Runge, M.C.; Baxter, P.W.J.; Possingham, H.P.
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.
Thirkettle, Martin; Walton, Thomas; Shah, Ashvin; Gurney, Kevin; Redgrave, Peter; Stafford, Tom
Animals, interacting with the environment, learn and exploit the consequences of their movements. Fundamental to this is the pairing of salient sensory input with recent motor output to form an action-outcome pair linking a performed movement with its outcome. Short-latency dopamine (DA) signalling in the basal ganglia has been proposed to support this crucial task. For visual stimuli, this DA signalling is triggered at short latency by input from the superior colliculus (SC). While some aspects of the visual signal (e.g. luminance), are relayed directly to the SC via the retinotectal projection, other information unavailable to this subcortical pathway must take a more circuitous route to the SC, first submitting to early visual processing in cortex. By comparing action-outcome pairing when the visual stimulus denoting success was immediately available to the SC, via the retinotectal pathway, against that when cortical processing of the signal was required, the impact this additional sensory processing has on action-outcome learning can be established. We found that action acquisition was significantly impaired when the action was reinforced by a stimulus ineligible for the retinotectal pathway. Furthermore, we found that when the stimulus was eligible for the retinotectal pathway but evoked an increased latency, action acquisition was not impaired. These results suggest that the afferent sensory pathway via the SC is certainly primary and possibly instrumental to the DA neurons' role in the discovery of novel actions and that the differences found are not due to simple sensory latency.
Research on avian song learning has traditionally been based on an instructional model, as exemplified by the sensorimotor model of song development. Several large-scale, species-wide field studies of learned birdsongs have revealed that variation is narrowly restricted to certain aspects of song structure. Other aspects are sufficiently stereotyped and so widely shared by species' members that they qualify as species-specific universals. The limitations on natural song variation are difficult to reconcile with a fully open, instructive model of song learning. An alternative model based on memorization by selection postulates a system of innate neural templates that facilitate the recognition and rapid memorization of conspecific song patterns. Behavioral evidence compatible with this model includes learning preferences, rapid conspecific song learning, and widespread ocurrence of species-specific song universals that are recognized innately but fail to develop in songs of social isolates. A third model combines instruction, in the memorization phase, with selection during song production. An overproduced repertoire of plastic songs previously memorized by instruction is winnowed by selection imposed during social interactions at the time of adult song crystallization. Selection during production is well established as a factor in the song development of several species, in the form of action-based learning. The possible role of selective processes in song memorization merits further neurobiological investigation.
Petri - nets to this formalism. In , extending the HD- automata as supporting model, the authors define a logic for dynamic creation and...modular mix of capabilities into basic units (e.g. Platoons , regiments, etc…); 2) modular and nested composition of groups of units; 3) patterns of command
Yu, Shengquan; Yang, Xianmin; Cheng, Gang
The key to implementing ubiquitous learning is the construction and organization of learning resources. While current research on ubiquitous learning has primarily focused on concept models, supportive environments and small-scale empirical research, exploring ways to organize learning resources to make them available anywhere on-demand is also…
Gómez Puente, S. M.; van Eijck, M.; Jochems, W.
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.
Rosenbaum, M.; Vergara, J. D.; Minzoni, A. A.
Quantum Mechanics, as a mini-superspace of Field Theory has been assumed to provide physically relevant information on quantum processes in Field Theory. In the case of Quantum Gravity this would imply using Cosmological models to investigate quantum processes at distances of the order of the Planck scale. However because of the Stone-von Neuman Theorem, it is well known that quantization of Cosmological models by the Wheeler-DeWitt procedure in the context of a Heisenberg-Weyl group with piecewise continuous parameters leads irremediably to a volume singularity. In order to avoid this information catastrophe it has been suggested recently the need to introduce in an effective theory of the quantization some form of reticulation in 3-space. On the other hand, since in the geometry of the General Relativistic formulation of Gravitation space can not be visualized as some underlying static manifold in which the physical system evolves, it would be interesting to investigate whether the effective reticulation which removes the singularity in such simple cosmologies as the Bianchi models has a dynamical origin manifested by a noncommutativity of the generators of the Heisenberg-Weyl algebra, as would be expected from an operational point of view at the Planck length scale.
Rosenbaum, M.; Vergara, J. D.; Minzoni, A. A.
Quantum Mechanics, as a mini-superspace of Field Theory has been assumed to provide physically relevant information on quantum processes in Field Theory. In the case of Quantum Gravity this would imply using Cosmological models to investigate quantum processes at distances of the order of the Planck scale. However because of the Stone-von Neuman Theorem, it is well known that quantization of Cosmological models by the Wheeler-DeWitt procedure in the context of a Heisenberg-Weyl group with piecewise continuous parameters leads irremediably to a volume singularity. In order to avoid this information catastrophe it has been suggested recently the need to introduce in an effective theory of the quantization some form of reticulation in 3-space. On the other hand, since in the geometry of the General Relativistic formulation of Gravitation space can not be visualized as some underlying static manifold in which the physical system evolves, it would be interesting to investigate whether the effective reticulation which removes the singularity in such simple cosmologies as the Bianchi models has a dynamical origin manifested by a noncommutativity of the generators of the Heisenberg-Weyl algebra, as would be expected from an operational point of view at the Planck length scale.
Sheynikhovich, Denis; Arleo, Angelo
In contrast to predictions derived from the associative learning theory, a number of behavioral studies suggested the absence of competition between geometric cues and landmarks in some experimental paradigms. In parallel to these studies, neurobiological experiments suggested the existence of separate independent memory systems which may not always interact according to classic associative principles. In this paper we attempt to combine these two lines of research by proposing a model of spatial learning that is based on the theory of multiple memory systems. In our model, a place-based locale strategy uses activities of modeled hippocampal place cells to drive navigation to a hidden goal, while a stimulus-response taxon strategy, presumably mediated by the dorso-lateral striatum, learns landmark-approaching behavior. A strategy selection network, proposed to reside in the prefrontal cortex, implements a simple reinforcement learning rule to switch behavioral strategies. The model is used to reproduce the results of a behavioral experiment in which an interaction between a landmark and geometric cues was studied. We show that this model, built on the basis of neurobiological data, can explain the lack of competition between the landmark and geometry, potentiation of geometry learning by the landmark, and blocking. Namely, we propose that the geometry potentiation is a consequence of cooperation between memory systems during learning, while blocking is due to competition between the memory systems during action selection.
What contributes to longevity in an action learning (AL) set? What holds it together over a long period? The article relates the chronology and reasons why a self-managed set has flourished when so many sets of voluntary membership peter out. Major attributes of successful longevity are the adherence to strong ground rules and disciplined…
This Account of Practice describes the introduction and development of action learning within a level 5 module of "Communications at Work" delivered as part of a Business & Technology Education Council (BTEC) Professional Certificate in Management (CMS) between 2005/2006 and 2009/2010. This will commence with a personal narrative and…
Kamath, Shyam; Agrawal, Jagdish; Krickx, Guido
This paper discusses the theoretical foundations and implementation challenges and outcomes of a unique "hands-on" global consulting program that is integrated into an international EMBA program for mid-career and senior American and European managers. It details the challenges for the integration of experiential action learning, double-loop…
Wong, Hilleas Chi Hang; Man, Thomas Wing Yan
Based on a comparative survey supplemented with focus group interviews, it was found that an action learning activity in an entrepreneurship programme produced both positive and negative results with regard to the entrepreneurial traits of students and their inclination towards entrepreneurship, depending on the influence of external and…
Stringer, Ernest T.; Christensen, Lois McFadyen; Baldwin, Shelia C.
This book demonstrates how teachers can use action research as an integral component of teaching and learning. The text uses examples and lesson plans to demonstrate how student research processes can be incorporated into classroom lessons that are linked to standards. Key features of this book are: (1) Guides teachers through systematic steps of…
Lizzio, Alf; Wilson, Keithia
This study investigated the extent to which a course, designed using peer and action learning principles to function as an 'on campus practicum', can develop the professional capabilities of students. As part of their formal coursework, third year behavioural science students, functioning as 'student consultants', entered into a…
Banegas, Dario; Pavese, Anahi; Velazquez, Aurelia; Velez, Sandra Maria
In 2011 we, a group of English-as-a-foreign-language teachers at a secondary school in Argentina, decided to investigate our teaching practices through collaborative action research so as to improve our students' learning opportunities and thus revitalise English-language teaching in our context. We implemented and evaluated the integration of…
Scott-Ladd, Brenda; Chan, Christopher C. A.
This article reports on a study investigating strategies that students can use to develop skills in managing team learning. Two groups of second-year management students participated in a semester-long action research project over two semesters. The students were educated on team development, team processes and conflict management and how to…
Harrison, Patricia; Edwards, Carys
This account of practice provides a practical example of the use of action learning within a masters educational programme, an MA in Change Management designed and delivered by a collaborative partnership between the Isle of Anglesey County Council (ACC) and Liverpool Business School (LBS), Liverpool John Moores University. The account has been…
Laiken, Marilyn E.
At the Ontario Institute for Studies in Education of the University of Ontario, a course entitled Developing and Leading High Performing Teams: Theory and Practice is experimenting with a design that surfaces the action/reflection paradox for the purpose of learning how to manage this polarity. Whether the product is defined as services or goods,…
This paper presents findings from action research in a conservatoire (the Guildhall School of Music & Drama) which focused on teaching and learning effective breathing in playing the oboe. A range of approaches and techniques emerged from a literature review. These were implemented in practice with oboe students at the Guildhall School, and…
Marsh, Catherine; Johnson, Carrie
This study examines action learning as a vehicle for the transfer of organizational values in a multi-cultural, virtual-team based leadership development process. A Case Study of Kanbay International's Global Leadership Development Program is used as a lens through which HRD researchers and practitioners may glimpse new possibilities for the…
Muskett, Judith A.; Village, Andrew
Rural clergy often lack colleagues and may struggle with isolation, especially if over-extended in multi-parish benefices. Theory suggests that this sense of isolation could be addressed by launching clergy action learning sets, which have the potential to establish a peer support network through the formation of social capital as a by-product of…
Donovan, Paul Jeffrey
"Undiscussables" are topics associated with threat or embarrassment that are avoided by groups, where that avoidance is also not discussed. Their deleterious effect on executive groups has been a point of discussion for several decades. More recently critical action learning (AL) has brought a welcome focus to power relations within AL…
McAllister, Margaret; Oprescu, Florin; Downer, Teresa; Lyons, Michael; Pelly, Fiona; Barr, Nigel
Transformative learning aims to awaken students to issues of injustice, and to promote their critical analysis of assumptions, beliefs and values that lead to and sustain social inequities, so that they may become agents of social change. This paper introduces the Sensitise Take Action and Reflection (STAR) framework, which encapsulates…
Bear, Teresa J.
This quantitative action science research study utilized a causal-comparative experimental research design in order to determine if the use of student response systems (clickers), as an active learning strategy in a community college course, improved student performance in the course. Students in the experimental group (n = 26) used clickers to…
Service-learning has been shown to be an effective practice that positively affects students' academic achievement, self-esteem, and problem-solving skills (Billig, 2002; Eyler & Giles, 1999; Wilczenski & Coomey, 2007). This mixed-method action research case study was conducted to explore the possible link between service-learning…
Breathnach, Catherine; Stephenson, Frances
The authors explore their experience of a course for long-term unemployed people and reflect as to whether the traits identified by Tom Bourner on readiness for action learning actually relate to their experience. They conclude that based on the obvious development by the members of the group over the course, they observed, in some small way, the…
Brook, Cheryl; Christy, Gill
The question addressed in this paper is whether action learning as a management development technique can be more effective in promoting ethical decision-making than more traditional approaches. Recent examples of moral failures which have emerged in both corporate and public sector organisations in the UK during recent years have prompted a…
Brook, Cheryl; Milner, Christopher
The purpose of this paper is to consider some issues in the uses of what we have termed "creative" action learning in a business education context, and to review some aspects of its practice. A review of the literature, including its use in higher education, is followed by a case illustration of its use in a UK business school with…
Zainuddin, Hanizah; Moore, Rashid A.
This article examines a study on how preservice teachers enhance their understanding of theory and research in second language learning through an action research project that took place in a TESOL (Teachers of English to Speakers of Other Languages) education course. The study focuses on how interaction with English language learners (ELLs)…
This paper reviews how action learning was used as part of a regional leadership development programme involving a number of public sector organisations. It explores how the sets were designed and set up and the significant challenges that this particular approach brought. A number of positive tangible outcomes were produced from the sets and…
Jacobs, David M.; Vaz, Daniela V.; Michaels, Claire F.
In cart-pole balancing, one moves a cart in 1 dimension so as to balance an attached inverted pendulum. We approached perception-action and learning in this task from an ecological perspective. This entailed identifying a space of informational variables that balancers use as they perform the task and demonstrating that they improve by traversing…
Barish, Diane J.
This study questions whether or not participatory action research is an effective and practical method for increasing learning transfer of recovery-based principles. The participants (N = 250) were ethnically and educationally diverse clinicians, in an urban state mental health institute. The Self-Assessment of Recovery-Based Behaviors survey ( n…
Kristmanson, Paula Lee; Lafargue, Chantal; Culligan, Karla
This paper focuses on an action research project set in the context of one professional learning community's (PLC's) exploration of the Common European Framework of Reference (CEFR) and the European Language Portfolio (ELP). Teachers of second and foreign languages in a large urban high school examined the potential of principles and tools related…
MacNaughton, Glenda; Hughes, Patrick; Smith, Kylie
This article describes an action-learning project that helped teachers to rethink their approaches to children who challenge. The project enabled and encouraged teachers to reflect critically on why and how particular children challenged them and then to use their critical reflections to strengthen their capacity to work with those children. The…
Anderson, Lisa; Gold, Jeff
In this paper we consider the construction of narrative identity and particularly how managers of small businesses may construct new narrative identities within the activity of the action learning situation. We build on recent work to suggest that the "world" of managers can be explored through a consideration of Vygotsky's socio-cultural theory…
Elbert, Norb; Cumiskey, Kevin J.
This paper describes an action learning simulation designed for a Professional Golf Management (PGM) program housed in a College of Business of a public university. The PGA Golf Management University Program, a 4.5- to 5-year college curriculum for aspiring PGA Professionals is offered at 19 PGA accredited universities nationwide. The program…
Tuan, Hsiao-Lin; Chin, Chi-Chin; Tsai, Chih-Chung
This study reported how four science teachers used action research to promote their students' motivation in learning physical science. Four teachers with one of their 8th grade physical science classes participated in the study. A combination of qualitative and quantitative research design were used in the study, and data collection included…
Conklin, James; Cohen-Schneider, Rochelle; Linkewich, Beth; Legault, Emma
This paper reports on a study of how action learning facilitates the movement of knowledge between social contexts. The study involved a community organization that provides educational services related to aphasia and members of a complex continuing care (CCC) practice that received training from the agency. People with aphasia (PWA) (a disability…
Dejonckheere, Peter J. N.; Desoete, Annemie; Fonck, Nathalie; Roderiguez, Dave; Six, Leen; Vermeersch, Tine; Vermeulen, Lies
Introduction: In the present study we used a metaphorical representation in order to stimulate the numerical competences of six-year-olds. It was expected that when properties of physical action are used for mathematical thinking or when abstract mathematical thinking is grounded in sensorimotor processes, learning gains should be more pronounced…
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.
Collins, Anne L.; Greenfield, Venuz Y.; Bye, Jeffrey K.; Linker, Kay E.; Wang, Alice S.; Wassum, Kate M.
Prolonged mesolimbic dopamine concentration changes have been detected during spatial navigation, but little is known about the conditions that engender this signaling profile or how it develops with learning. To address this, we monitored dopamine concentration changes in the nucleus accumbens core of rats throughout acquisition and performance of an instrumental action sequence task. Prolonged dopamine concentration changes were detected that ramped up as rats executed each action sequence and declined after earned reward collection. With learning, dopamine concentration began to rise increasingly earlier in the execution of the sequence and ultimately backpropagated away from stereotyped sequence actions, becoming only transiently elevated by the most distal and unexpected reward predictor. Action sequence-related dopamine signaling was reactivated in well-trained rats if they became disengaged in the task and in response to an unexpected change in the value, but not identity of the earned reward. Throughout training and test, dopamine signaling correlated with sequence performance. These results suggest that action sequences can engender a prolonged mode of dopamine signaling in the nucleus accumbens core and that such signaling relates to elements of the motivation underlying sequence execution and is dynamic with learning, overtraining and violations in reward expectation. PMID:26869075
String models of unified interactions are elegant sets of Feynman rules for the scattering of gravitons, gauge bosons, and a host of massive excitations. The purpose of these lectures is to describe the progress towards a nonperturbative formulation of the theory. Such a formulation should make the geometrical meaning of string theory manifest and explain the many ''miracles'' exhibited by the string Feynman rules. There are some new results on gauge invariant observables, on the cosmological constant, and on the symmetries of interacting string field theory. 49 refs.
Waldrip, Bruce; Yu, Jeong Jin; Prain, Vaughan
This article focuses on a Personalised Learning model which has 19 scales that were used to evaluate regional students' perceptions of their readiness to learn, assessment processes, engagement, extent to which their learning is personalised and their associations with academic efficacy, academic achievement and student well-being. The data came…
Anglim, Jeromy; Wynton, Sarah K. A.
The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking…
Hollows, Kerrilee; Fritzon, Katarina
This study aimed to address the limitations of the existing genocide literature with the development of an empirically based classification system. Using Shye's (1985) action systems model, it was hypothesized that four types of perpetrators would exist and would be distinguishable by differences in the sources and target of individual criminal actions. Court transcripts from 80 perpetrators sentenced by the international courts were subject to content analysis and revealed 39 offense action variables, 17 perpetrator characteristic variables, and 6 perpetrator motive variables. A smallest space analysis using the Jaccard coefficient of association was conducted on the offense variables. The results supported the proposed framework, producing four distinct types of genocidal perpetrators. Correlational analyses were then conducted to examine the relationships between each of the perpetrator types and the remaining variables. The results of those correlations provided further support for the proposed framework. The implications of these findings are discussed.
California Community Colleges, Sacramento. High-Tech Center for the Disabled.
This document provides an overview of the California Community Colleges Learning Disabilities Eligibility Model. The model provides a uniform system for identifying adults who are eligible for learning disabilities services within the California Community Colleges. Research for the development of the model included an examination of the clinical…
Osborne, Roger; Schollum, Brendan
In the action-research phase of the Learning in Science Project, four groups of people worked on problems identified in the project's second (in-depth) phase. The Physics action-research group considered problems related to the teaching and learning of ideas associated with force and motion, suggesting that children's ideas of these concepts might…
Binnie, Lynne M.; Allen, Kristen; Beck, Elaine
This paper outlines the efforts of an Educational Psychology Service (EPS) to develop its practice in the area of research. It will argue that the Action Enquiry model of service delivery can empower teaching staff and may allow an effective means of change and improvement to take place in schools. This model steers research towards providing…
This article presents and problematizes a peered and tiered model of creative and educational knowledge transfer piloted in Culture Shack, a community-based arts education program in Melbourne, Australia. Drawing on Eisner and Sefton-Green and Soep, I argue the value of this approach as a potential new pedagogical strategy in both secondary…
Goss, Claire Brown; Bouffard, Suzanne
This report highlights Multnomah County's (Oregon) SUN Service System, an antipoverty and prevention effort that connects educational, social, health, and other services under one umbrella. The SUN model of combining educational, social, and health supports is rooted in a strong history of community involvement and partnerships in Multnomah…
Franz, E. A.
The present paper builds on the idea that attention is largely in service of our actions. A framework and model which captures the allocation of attention for learning of goal-directed actions is proposed and developed. This framework highlights an evolutionary model based on the notion that rudimentary functions of the basal ganglia have become embedded into increasingly higher levels of networks which all contribute to adaptive learning. Supporting the proposed model, background literature is presented alongside key evidence based on experimental studies in the so-called “split-brain” (surgically divided cerebral hemispheres), and selected evidence from related areas of research. Although overlap with other existing findings and models is acknowledged, the proposed framework is an original synthesis of cognitive experimental findings with supporting evidence of a neural system and a carefully formulated model of attention. It is the hope that this new synthesis will be informative in fields of cognition and other fields of brain sciences and will lead to new avenues for experimentation across domains. PMID:23267335
Bazos, Dorothy A; Schifferdecker, Karen E; Fedrizzi, Rudolph; Hoebeke, Jaime; Ruggles, Laural; Goldsberry, Yvonne
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.
Ball, Adam; Marcolli, Matilde
We present a model of (modified) gravity on spacetimes with fractal structure based on packing of spheres, which are (Euclidean) variants of the packed swiss cheese cosmology models. As the action functional for gravity we consider the spectral action of noncommutative geometry, and we compute its expansion on a space obtained as an Apollonian packing of three-dimensional spheres inside a four-dimensional ball. Using information from the zeta function of the Dirac operator of the spectral triple, we compute the leading terms in the asymptotic expansion of the spectral action. They consist of a zeta regularization of the divergent sum of the leading terms of the spectral actions of the individual spheres in the packing. This accounts for the contribution of points 1 and 3 in the dimension spectrum (as in the case of a 3-sphere). There is an additional term coming from the residue at the additional point in the real dimension spectrum that corresponds to the packing constant, as well as a series of fluctuations coming from log-periodic oscillations, created by the points of the dimension spectrum that are off the real line. These terms detect the fractality of the residue set of the sphere packing. We show that the presence of fractality influences the shape of the slow-roll potential for inflation, obtained from the spectral action. We also discuss the effect of truncating the fractal structure at a certain scale related to the energy scale in the spectral action.
To keep pace with our adversaries, we must expand the scope of machine learning and reasoning to address the breadth of possible attacks. One approach is to employ an algorithm to learn a set of causal models that describes the entire cyber network and each host end node. Such a learning algorithm would run continuously on the system and monitor activity in real time. With a set of causal models, the algorithm could anticipate novel attacks, take actions to thwart them, and predict the second-order effects flood of information, and the algorithm would have to determine which streams of that flood were relevant in which situations. This paper will present the results of efforts toward the application of a developmental learning algorithm to the problem of cyber security. The algorithm is modeled on the principles of human developmental learning and is designed to allow an agent to learn about the computer system in which it resides through active exploration. Children are flexible learners who acquire knowledge by actively exploring their environment and making predictions about what they will find,1, 2 and our algorithm is inspired by the work of the developmental psychologist Jean Piaget.3 Piaget described how children construct knowledge in stages and learn new concepts on top of those they already know. Developmental learning allows our algorithm to focus on subsets of the environment that are most helpful for learning given its current knowledge. In experiments, the algorithm was able to learn the conditions for file exfiltration and use that knowledge to protect sensitive files.
Monfardini, Elisabetta; Hadj-Bouziane, Fadila; Meunier, Martine
Monkeys readily learn to discriminate between rewarded and unrewarded items or actions by observing their conspecifics. However, they do not systematically learn from humans. Understanding what makes human-to-monkey transmission of knowledge work or fail could help identify mediators and moderators of social learning that operate regardless of language or culture, and transcend inter-species differences. Do monkeys fail to learn when human models show a behavior too dissimilar from the animals’ own, or when they show a faultless performance devoid of error? To address this question, six rhesus macaques trained to find which object within a pair concealed a food reward were successively tested with three models: a familiar conspecific, a ‘stimulus-enhancing’ human actively drawing the animal’s attention to one object of the pair without actually performing the task, and a ‘monkey-like’ human performing the task in the same way as the monkey model did. Reward was manipulated to ensure that all models showed equal proportions of errors and successes. The ‘monkey-like’ human model improved the animals’ subsequent object discrimination learning as much as a conspecific did, whereas the ‘stimulus-enhancing’ human model tended on the contrary to retard learning. Modeling errors rather than successes optimized learning from the monkey and ‘monkey-like’ models, while exacerbating the adverse effect of the ‘stimulus-enhancing’ model. These findings identify error modeling as a moderator of social learning in monkeys that amplifies the models’ influence, whether beneficial or detrimental. By contrast, model-observer similarity in behavior emerged as a mediator of social learning, that is, a prerequisite for a model to work in the first place. The latter finding suggests that, as preverbal infants, macaques need to perceive the model as ‘like-me’ and that, once this condition is fulfilled, any agent can become an effective model. PMID
Ramadiani; Rodziah, A.; Hasan, S. M.; Rusli, A.; Noraini, C.
E-learning is not going to work if the system is not used in accordance with user needs. User Interface is very important to encourage using the application. Many theories had discuss about user interface usability evaluation and technology acceptance separately, actually why we do not make it correlation between interface usability evaluation and user acceptance to enhance e-learning process. Therefore, the evaluation model for e-learning interface acceptance is considered important to investigate. The aim of this study is to propose the integrated e-learning user interface acceptance evaluation model. This model was combined some theories of e-learning interface measurement such as, user learning style, usability evaluation, and the user benefit. We formulated in constructive questionnaires which were shared at 125 English Language School (ELS) students. This research statistics used Structural Equation Model using LISREL v8.80 and MANOVA analysis.
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.
Roche, Anne; Clarke, Doug; Clarke, David; Chan, Man Ching Esther
A central premise of this project is that teachers learn from the act of teaching a lesson and that this learning is evident in the planning and teaching of a subsequent lesson. We are studying the knowledge construction of mathematics teachers utilising multi-camera research techniques during lesson planning, classroom interactions and…
Researchers posit that teachers' teaching and learning are improved by teachers' collective efforts to examine and reflect on practice. Yet the questions of what and how teachers learn when collaborating with colleagues remain unanswered: What kinds of knowledge and skills do teachers acquire in conjunction with their collaboration? What brings…
Vinera, Jennifer; Kermen, Florence; Sacquet, Joëlle; Didier, Anne; Mandairon, Nathalie; Richard, Marion
Noradrenaline contributes to olfactory-guided behaviors but its role in olfactory learning during adulthood is poorly documented. We investigated its implication in olfactory associative and perceptual learning using local infusion of mixed a1-ß adrenergic receptor antagonist (labetalol) in the adult mouse olfactory bulb. We reported that…
At the University of the Free State (UFS) in South Africa, professional development is characterised by its focus on the advancement of scholarly teaching in the disciplines. Practices followed are informed by the scholarship of teaching and learning movement. Within learning communities, special attention is given to the motivational conditions…
Stukey, Marisa Ramirez
During the last twenty years, professional learning for teachers has been promoted as a viable path for increased teacher effectiveness and student achievement. Because of the complexities of the school system and the diversity of the student population, designing quality professional learning opportunities that are meaningful for teachers can be…
Palotai, Miklós; Telegdy, Gyula; Ekwerike, Alphonsus; Jászberényi, Miklós
The extensive projection of orexigenic neurons and the diffuse expression of orexin receptors suggest that endogenous orexins are involved in several physiological functions of the central nervous system, including learning and memory. Our previous study demonstrated that orexin A improves learning, consolidation and retrieval processes, which involves α- and β-adrenergic, cholinergic, dopaminergic, GABA-A-ergic, opiate and nitrergic neurotransmissions. However, we have little evidence about the action of orexin B on memory processes and the underlying neuromodulation. Therefore, the aim of the present study was to investigate the action of orexin B on passive avoidance learning and the involvement of neurotransmitters in this action in rats. Accordingly, rats were pretreated with the selective orexin 2 receptor (OX2R) antagonist, EMPA; the γ-aminobutyric acid subunit A (GABA-A) receptor antagonist, the bicuculline; a D2, D3, D4 dopamine receptor antagonist, haloperidol; the nonselective opioid receptor antagonist, naloxone; the non-specific nitric oxide synthase (NOS) inhibitor, nitro-l-arginine; the nonselective α-adrenergic receptor antagonist, phenoxybenzamine and the β-adrenergic receptor antagonist, propranolol. Our results demonstrate that orexin B can improve learning, consolidation of memory and retrieval. EMPA reversed completely the action of orexin B on memory consolidation. Bicuculline blocked fully; naloxone, nitro-l-arginine, phenoxybenzamine and propranolol attenuated the orexin B-induced memory consolidation, whereas haloperidol was ineffective. These data suggest that orexin B improves memory functions through OX2R and GABA-ergic, opiate, nitrergic, α- and β-adrenergic neurotransmissions are also involved in this action.
Somogyvári, Zoltán; Zalányi, László; Ulbert, István; Erdi, Péter
A new model-based analysis method was set up for revealing information encrypted in extracellular spatial potential patterns of neocortical action potentials. Spikes were measured by extracellular linear multiple microelectrode in vivo cat's primary auditory cortex and were analyzed based on current source density (CSD) distribution models. Validity of the monopole and other point source approximations were tested on the measured potential patterns by numerical fitting. We have found, that point source models could not provide accurate description of the measured patterns. We introduced a new model of the CSD distribution on a spiking cell, called counter-current model (CCM). This new model was shown to provide better description of the spatial current distribution of the cell during the initial negative deflection of the extracellular action potential, from the onset of the spike to the negative peak. The new model was tested on simulated extracellular potentials. We proved numerically, that all the parameters of the model could be determined accurately based on measurements. Thus, fitting of the CCM allowed extraction of these parameters from the measurements. Due to model fitting, CSD could be calculated with much higher accuracy as done with the traditional method because distance dependence of the spatial potential patterns was explicitly taken into consideration in our method. Average CSD distribution of the neocortical action potentials was calculated and spatial decay constant of the dendritic trees was determined by applying our new method.
Yin, Henry H; Knowlton, Barbara J; Balleine, Bernard W
Although there is consensus that instrumental conditioning depends on the encoding of action-outcome associations, it is not known where this learning process is localized in the brain. Recent research suggests that the posterior dorsomedial striatum (pDMS) may be the critical locus of these associations. We tested this hypothesis by examining the contribution of N-methyl-D-aspartate receptors (NMDARs) in the pDMS to action-outcome learning. Rats with bilateral cannulae in the pDMS were first trained to perform two actions (left and right lever presses), for sucrose solution. After the pre-training phase, they were given an infusion of the NMDA antagonist 2-amino-5-phosphonopentanoic acid (APV, 1 mg/mL) or artificial cerebral spinal fluid (ACSF) before a 30-min session in which pressing one lever delivered food pellets and pressing the other delivered fruit punch. Learning during this session was tested the next day by sating the animals on either the pellets or fruit punch before assessing their performance on the two levers in extinction. The ACSF group selectively reduced responding on the lever that, in training, had earned the now devalued outcome, whereas the APV group did not. Experiment 2 replicated the effect of APV during the critical training session but found no effect of APV given after acquisition and before test. Furthermore, Experiment 3 showed that the effect of APV on instrumental learning was restricted to the pDMS; infusion into the dorsolateral striatum did not prevent learning. These experiments provide the first direct evidence that, in instrumental conditioning, NMDARs in the dorsomedial striatum are involved in encoding action-outcome associations.
Van den Bossche, Piet; Gijselaers, Wim; Segers, Mien; Woltjer, Geert; Kirschner, Paul
To gain insight in the social processes that underlie knowledge sharing in teams, this article questions which team learning behaviors lead to the construction of a shared mental model. Additionally, it explores how the development of shared mental models mediates the relation between team learning behaviors and team effectiveness. Analyses were…
Käser, Tanja; Busetto, Alberto Giovanni; Solenthaler, Barbara; Baschera, Gian-Marco; Kohn, Juliane; Kucian, Karin; von Aster, Michael; Gross, Markus
This study introduces a student model and control algorithm, optimizing mathematics learning in children. The adaptive system is integrated into a computer-based training system for enhancing numerical cognition aimed at children with developmental dyscalculia or difficulties in learning mathematics. The student model consists of a dynamic…
Heift, Trude; Schulze, Mathias
Provides examples of student modeling techniques that have been employed in computer-assisted language learning over the past decade. Describes two systems for learning German: "German Tutor" and "Geroline." Shows how a student model can support computerized adaptive language testing for diagnostic purposes in a Web-based language learning…
This qualitative case study explored a third grade bilingual teacher's transformative language ideologies through participating in a collaborative action research project. By merging language ideologies theory, Cultural Historical Activity Theory (CHAT), and action research, I was able to identify the analytic focus of this study. I analyzed how one teacher and I, the researcher, collaboratively reflected on classroom language practices during the video analysis meetings and focus groups. Further, I analyzed twelve videos that we coded together to see the changes in the teacher's language practices over time. My unit of analysis was the discourse practice mediated by additive language ideologies. Throughout the collaborative action research process, we both critically reflected on the classroom language use. We also developed a critical consciousness about the participatory shifts and learning of focal English Learner (EL) students. Finally, the teacher made changes to her classroom language practices. The results of this study will contribute to the literacy education research field for theoretical, methodological, and practical insights. The integration of language ideologies, CHAT, and action research can help educational practitioners, researchers, and policy makers understand the importance of transforming teachers' language ideologies in designing additive learning contexts for ELs. From a methodological perspective, the transformative language ideologies through researcher and teacher collaborated video analysis process provide a unique contribution to the language ideologies in education literature, with analytic triangulation. As a practical implication, this study suggests action research can be one of the teacher education tools to help the teachers transform language ideologies for EL education.
Teichmann, Jan; Broom, Mark; Alonso, Eduardo
An experience-based aversive learning model of foraging behaviour in uncertain environments is presented. We use Q-learning as a model-free implementation of Temporal difference learning motivated by growing evidence for neural correlates in natural reinforcement settings. The predator has the choice of including an aposematic prey in its diet or to forage on alternative food sources. We show how the predator's foraging behaviour and energy intake depend on toxicity of the defended prey and the presence of Batesian mimics. We introduce the precondition of exploration of the action space for successful aversion formation and show how it predicts foraging behaviour in the presence of conflicting rewards which is conditionally suboptimal in a fixed environment but allows better adaptation in changing environments.
Roy, Sushmita; Lane, Terran; Werner-Washburne, Margaret
In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the statistical dependency structure than directed graphical models. Unfortunately, structure learning of undirected graphs using likelihood-based scores remains difficult because of the intractability of computing the partition function. We describe a new Markov random field structure learning algorithm, motivated by canonical parameterization of Abbeel et al. We provide computational improvements on their parameterization by learning per-variable canonical factors, which makes our algorithm suitable for domains with hundreds of nodes. We compare our algorithm against several algorithms for learning undirected and directed models on simulated and real datasets from biology. Our algorithm frequently outperforms existing algorithms, producing higher-quality structures, suggesting that enforcing consistency during structure learning is beneficial for learning undirected graphs.
Collins, Anne G E; Frank, Michael J
The striatal dopaminergic system has been implicated in reinforcement learning (RL), motor performance, and incentive motivation. Various computational models have been proposed to account for each of these effects individually, but a formal analysis of their interactions is lacking. Here we present a novel algorithmic model expanding the classical actor-critic architecture to include fundamental interactive properties of neural circuit models, incorporating both incentive and learning effects into a single theoretical framework. The standard actor is replaced by a dual opponent actor system representing distinct striatal populations, which come to differentially specialize in discriminating positive and negative action values. Dopamine modulates the degree to which each actor component contributes to both learning and choice discriminations. In contrast to standard frameworks, this model simultaneously captures documented effects of dopamine on both learning and choice incentive-and their interactions-across a variety of studies, including probabilistic RL, effort-based choice, and motor skill learning.
The aims of this research were to determine the effect of cooperative learning model and learning styles on learning result. This quasi-experimental study employed a 2x2 treatment by level, involved independent variables, i.e. cooperative learning model and learning styles, and learning result as the dependent variable. Findings signify that: (1)…
Laber, Eric B; Linn, Kristin A; Stefanski, Leonard A
Evidence-based rules for optimal treatment allocation are key components in the quest for efficient, effective health care delivery. Q-learning, an approximate dynamic programming algorithm, is a popular method for estimating optimal sequential decision rules from data. Q-learning requires the modeling of nonsmooth, nonmonotone transformations of the data, complicating the search for adequately expressive, yet parsimonious, statistical models. The default Q-learning working model is multiple linear regression, which is not only provably misspecified under most data-generating models, but also results in nonregular regression estimators, complicating inference. We propose an alternative strategy for estimating optimal sequential decision rules for which the requisite statistical modeling does not depend on nonsmooth, nonmonotone transformed data, does not result in nonregular regression estimators, is consistent under a broader array of data-generation models than Q-learning, results in estimated sequential decision rules that have better sampling properties, and is amenable to established statistical approaches for exploratory data analysis, model building, and validation. We derive the new method, IQ-learning, via an interchange in the order of certain steps in Q-learning. In simulated experiments IQ-learning improves on Q-learning in terms of integrated mean squared error and power. The method is illustrated using data from a study of major depressive disorder.
Schnorr, Donna; Painter, Diane D.
This paper presents a collaborative action research partnership model that involved participation by graduate school of education preservice students, school and university teachers, and administrators. An elementary teacher-research group investigated what would happen when fourth graders worked in teams to research and produce a multimedia…
Turnbull, Ann P.; Friesen, Barbara J.; Ramirez, Carmen
This article discusses a participatory action research (PAR) approach to conducting family research. It proposes a model of PAR implementation level including the options of family members as research leaders and researchers as ongoing advisors, researchers and family members as coresearchers, and researches as leaders, and family members as…
Objectives This article reviews an evaluation vector model driven from a participatory action research leveraging a collective inquiry system named SMILE (Stanford Mobile Inquiry-based Learning Environment). Methods SMILE has been implemented in a diverse set of collective inquiry generation and analysis scenarios including community health care-specific professional development sessions and community-based participatory action research projects. In each scenario, participants are given opportunities to construct inquiries around physical and emotional health-related phenomena in their own community. Results Participants formulated inquiries as well as potential clinical treatments and hypothetical scenarios to address health concerns or clarify misunderstandings or misdiagnoses often found in their community practices. From medical universities to rural village health promotion organizations, all participatory inquiries and potential solutions can be collected and analyzed. The inquiry and solution sets represent an evaluation vector which helps educators better understand community health issues at a much deeper level. Conclusions SMILE helps collect problems that are most important and central to their community health concerns. The evaluation vector, consisting participatory and collective inquiries and potential solutions, helps the researchers assess the participants' level of understanding on issues around health concerns and practices while helping the community adequately formulate follow-up action plans. The method used in SMILE requires much further enhancement with machine learning and advanced data visualization. PMID:27525157
de Freitas, Angilberto Sabino; Bandeira-de-Mello, Rodrigo
The existing literature on e-learning implementation is either descriptive or normative and falls short on explaining how managers act in introducing and disseminating e-learning projects in school settings. In this paper, we follow a symbolic approach in order to offer a grounded model for explaining how managerial framing of the introduction of…
This case study, one of a series of publications exploring effective and inclusive models of work-based learning, finds that work-based courses bring college to the production line by using the job as a learning lab. Work-based courses are an innovative way to give incumbent workers access to community college credits and degrees. They are…
Gershman, Samuel J.; Moustafa, Ahmed A.; Ludvig, Elliot A.
Reinforcement learning (RL) models have been influential in understanding many aspects of basal ganglia function, from reward prediction to action selection. Time plays an important role in these models, but there is still no theoretical consensus about what kind of time representation is used by the basal ganglia. We review several theoretical accounts and their supporting evidence. We then discuss the relationship between RL models and the timing mechanisms that have been attributed to the basal ganglia. We hypothesize that a single computational system may underlie both RL and interval timing—the perception of duration in the range of seconds to hours. This hypothesis, which extends earlier models by incorporating a time-sensitive action selection mechanism, may have important implications for understanding disorders like Parkinson's disease in which both decision making and timing are impaired. PMID:24409138
Zhao, Kaili; Chu, Wen-Sheng; De la Torre, Fernando; Cohn, Jeffrey F.; Zhang, Honggang
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
Dobel, Christian; Enriquez-Geppert, Stefanie; Baumgaertner, Annette; Zwitserlood, Pienie; Gerloff, Christian; Hummel, Friedhelm C.; Liuzzi, Gianpiero
Despite a growing number of studies, the neurophysiology of adult vocabulary acquisition is still poorly understood. One reason is that paradigms that can easily be combined with neuroscientfic methods are rare. Here, we tested the efficiency of two paradigms for vocabulary (re-) acquisition, and compared the learning of novel words for actions and objects. Cortical networks involved in adult native-language word processing are widespread, with differences postulated between words for objects and actions. Words and what they stand for are supposed to be grounded in perceptual and sensorimotor brain circuits depending on their meaning. If there are specific brain representations for different word categories, we hypothesized behavioural differences in the learning of action-related and object-related words. Paradigm A, with the learning of novel words for body-related actions spread out over a number of days, revealed fast learning of these new action words, and stable retention up to 4 weeks after training. The single-session Paradigm B employed objects and actions. Performance during acquisition did not differ between action-related and object-related words (time*word category: p = 0.01), but the translation rate was clearly better for object-related (79%) than for action-related words (53%, p = 0.002). Both paradigms yielded robust associative learning of novel action-related words, as previously demonstrated for object-related words. Translation success differed for action- and object-related words, which may indicate different neural mechanisms. The paradigms tested here are well suited to investigate such differences with neuroscientific means. Given the stable retention and minimal requirements for conscious effort, these learning paradigms are promising for vocabulary re-learning in brain-lesioned people. In combination with neuroimaging, neuro-stimulation or pharmacological intervention, they may well advance the understanding of language learning
Freundlieb, Nils; Ridder, Volker; Dobel, Christian; Enriquez-Geppert, Stefanie; Baumgaertner, Annette; Zwitserlood, Pienie; Gerloff, Christian; Hummel, Friedhelm C; Liuzzi, Gianpiero
Despite a growing number of studies, the neurophysiology of adult vocabulary acquisition is still poorly understood. One reason is that paradigms that can easily be combined with neuroscientfic methods are rare. Here, we tested the efficiency of two paradigms for vocabulary (re-) acquisition, and compared the learning of novel words for actions and objects. Cortical networks involved in adult native-language word processing are widespread, with differences postulated between words for objects and actions. Words and what they stand for are supposed to be grounded in perceptual and sensorimotor brain circuits depending on their meaning. If there are specific brain representations for different word categories, we hypothesized behavioural differences in the learning of action-related and object-related words. Paradigm A, with the learning of novel words for body-related actions spread out over a number of days, revealed fast learning of these new action words, and stable retention up to 4 weeks after training. The single-session Paradigm B employed objects and actions. Performance during acquisition did not differ between action-related and object-related words (time*word category: p = 0.01), but the translation rate was clearly better for object-related (79%) than for action-related words (53%, p = 0.002). Both paradigms yielded robust associative learning of novel action-related words, as previously demonstrated for object-related words. Translation success differed for action- and object-related words, which may indicate different neural mechanisms. The paradigms tested here are well suited to investigate such differences with neuroscientific means. Given the stable retention and minimal requirements for conscious effort, these learning paradigms are promising for vocabulary re-learning in brain-lesioned people. In combination with neuroimaging, neuro-stimulation or pharmacological intervention, they may well advance the understanding of language learning
Amundsen, Ruth M.
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.
Telegdy, Gyula; Adamik, Ágnes
Kisspeptins are G protein-coupled receptor ligands originally identified as human metastasis suppressor gene products that have the ability to suppress melanoma and breast cancer metastasis and recently found to play an important role in initiating the secretion of gonadotropin-releasing hormone at puberty. Kisspeptin-13 is an endogenous isoform that consists of 13 amino acids. The action of kisspeptin in the regulation of gonadal function has been widely studied, but little is known as concerns its function in limbic brain structures. In the brain, the gene is transcribed within the hippocampal dentate gyrus. This paper reports on a study the effects of kisspeptin-13 on passive avoidance learning and the involvement of the adrenergic, serotonergic, cholinergic, dopaminergic and GABA-A-ergic, opiate receptors and nitric oxide in its action in mice. Mice were pretreated with a nonselective α-adrenergic receptor antagonist, phenoxybenzamine, an α2-adrenergic receptor antagonist, yohimbine, a β-adrenergic receptor antagonist, propranolol, a mixed 5-HT1/5-HT2 serotonergic receptor antagonist, methysergide, a nonselective 5-HT2 serotonergic receptor antagonist, cyproheptadine, a nonselective muscarinic acetylcholine receptor antagonist, atropine, D2, D3, D4 dopamine receptor antagonist, haloperidol, a γ-aminobutyric acid subunit A (GABAA) receptor antagonist, bicuculline, naloxone, a nonselective opioid receptor antagonist and nitro-l-arginine, a nitric oxide synthase inhibitor. Kisspeptin-13 facilitated learning and memory consolidation in a passive avoidance paradigm. Phenoxybenzamine, yohimbine, propranolol, methysergide, cyproheptadine, atropine, bicuculline and nitro-l-arginine prevented the action of kisspeptin-13 on passive avoidance learning, but haloperidol and naloxone did not block the effects of kisspeptin-13. The results demonstrated that the action of kisspeptin-13 on the facilitation of passive avoidance learning and memory consolidation is mediated
Rybak, I.; Henley, W.
Groundwater modeling was conducted to design, implement, modify, and terminate corrective action at several RCRA sites in EPA Region 4. Groundwater flow, contaminant transport and unsaturated zone air flow models were used depending on the complexity of the site and the corrective action objectives. Software used included Modflow, Modpath, Quickflow, Bioplume 2, and AIR3D. Site assessment data, such as aquifer properties, site description, and surface water characteristics for each facility were used in constructing the models and designing the remedial systems. Modeling, in turn, specified additional site assessment data requirements for the remedial system design. The specific purpose of computer modeling is discussed with several case studies. These consist, among others, of the following: evaluation of the mechanism of the aquifer system and selection of a cost effective remedial option, evaluation of the capture zone of a pumping system, prediction of the system performance for different and difficult hydrogeologic settings, evaluation of the system performance, and trouble-shooting for the remedial system operation. Modeling is presented as a useful tool for corrective action system design, performance, evaluation, and trouble-shooting. The case studies exemplified the integration of diverse data sources, understanding the mechanism of the aquifer system, and evaluation of the performance of alternative remediation systems in a cost-effective manner. Pollutants of concern include metals and PAHs.
Juhary, Jowati Binti
This paper aims at analysing the needs for a specific teaching and learning model for the National Defence University of Malaysia (NDUM). The main argument is that whether there are differences between teaching and learning for academic component versus military component at the university. It is further argued that in order to achieve excellence, there should be one teaching and learning culture. Data were collected through interviews with military cadets. It is found that there are variations of teaching and learning strategies for academic courses, in comparison to a dominant teaching and learning style for military courses. Thus, in the interest of delivering quality education and training for students at the university, the paper argues that possibly a hybrid model for teaching and learning is fundamental in order to generate a one culture of academic and military excellence for the NDUM.
Cherin, D; Enguidanos, S; Brumley, R
Currently, single loop learning is the predominant method of problem solving orientation engaged in by healthcare institutions. This mode of learning is not conductive to fostering needed communications between health care providers and terminal patients. Reflection in action, second loop learning, focuses on deep listening and dialogue and can be critical in opening communications paths between the dying patient and his or her caregivers. This article discusses organizational learning theory and applies the theories double loop learning technique of reflection in action to end-of-life care. The article further explores an exemplar of reflection in action in a Palliative Care Program, and end-of-life home care program at Kaiser Permanente. In order to more effectively meet the needs of terminally ill patients, greater efforts are needed to incorporate second loop learning into the practice of those caring for these patients.
Hsu, Chia-Cheng; Wang, Kun-Te; Huang, Yueh-Min
An innovative learning mechanism for identifying learners' learning styles to improve adaptive learning is proposed. Hypermedia-learning tools are highly interactive to learners in web-based environments that have become increasingly popular in the field of education. However, these learning tools are frequently inadequate for individualize learning because accessing adaptive learning content is required for learners to achieve objectives. For predicating adaptive learning, a neuron-fuzzy inference approach is used to model the diagnosis of learning styles. Then, according to the diagnosis results, a recommendation model is constructed to help learners obtain adaptive digital content. The proposed approach has the capability of tracking learning activities on-line to correspond with learning styles. The results show that the identified model successfully classified 102 learners into groups based on learning style. The implemented learning mechanism produced a clear learning guide for learning activities, which can help an advanced learning system retrieve a well-structure learning unit.
Torii, Daisuke; Bousquet, François; Ishida, Toru
Companion Modeling is a methodology of refining initial models for understanding reality through a role-playing game (RPG) and a multiagent simulation. In this research, we propose a novel agent model construction methodology in which classification learning is applied to the RPG log data in Companion Modeling. This methodology enables a systematic model construction that handles multi-parameters, independent of the modelers ability. There are three problems in applying classification learning to the RPG log data: 1) It is difficult to gather enough data for the number of features because the cost of gathering data is high. 2) Noise data can affect the learning results because the amount of data may be insufficient. 3) The learning results should be explained as a human decision making model and should be recognized by the expert as being the result that reflects reality. We realized an agent model construction system using the following two approaches: 1) Using a feature selction method, the feature subset that has the best prediction accuracy is identified. In this process, the important features chosen by the expert are always included. 2) The expert eliminates irrelevant features from the learning results after evaluating the learning model through a visualization of the results. Finally, using the RPG log data from the Companion Modeling of agricultural economics in northeastern Thailand, we confirm the capability of this methodology.
Gold, Carl; Henze, Darrell A; Koch, Christof
We investigate the use of extracellular action potential (EAP) recordings for biophysically faithful compartmental models. We ask whether constraining a model to fit the EAP is superior to matching the intracellular action potential (IAP). In agreement with previous studies, we find that the IAP method under-constrains the parameters. As a result, significantly different sets of parameters can have virtually identical IAP's. In contrast, the EAP method results in a much tighter constraint. We find that the distinguishing characteristics of the waveform--but not its amplitude-resulting from the distribution of active conductances are fairly invariant to changes of electrode position and detailed cellular morphology. Based on these results, we conclude that EAP recordings are an excellent source of data for the purpose of constraining compartmental models.
Andersson, Sten-Ove; Lundberg, Lars; Jonsson, Anders; Tingström, Pia; Dahlgren, Madeleine Abrandt
The objective of this study is to examine how medics within the Swedish Armed Forces perceive their learning outcome following military prehospital training. A qualitative study with a phenomenographic approach was used to investigate how learning is perceived among military medics. At meta level, the results can be viewed as an interaction, i.e., being able to collaborate in the medical platoon, including the ability to interact within the group and being able to lead; an action, i.e., being able to assess and treat casualties, including the ability to communicate with the casualty, to prioritize, and to be able to act; and a reflection, i.e., having confidence in one's own ability in first aid, including being prepared and feeling confident. Interaction during the period of education is important for learning. Action, being able to act in the field, is based on a drill in which the subject progresses from simple to complex procedures. Reflection, learning to help others, is important for confidence, which in turn creates preparedness, thereby making the knowledge meaningful.
Watanabe, Hama; Taga, Gentaro
To understand young infants' flexible changes of learned actions when abrupt environmental changes occur, we examined fifty-four 3-month-olds who performed a mobile task, in which they learned to move the mobile by a string attached to their arms or legs (arm-based or leg-based learning). We manipulated the order of tests-arm to leg (AL) and leg to arm (LA)-and observed the time course of motion of four limbs. The infants in the AL condition showed a differentiated movement pattern, in which the movement of the connected arm was dominant, and when the connected limb changed, they immediately inhibited the prior movement pattern. The infants in the LA condition produced undifferentiated movement pattern of multiple limbs, which was maintained even when the critical limb was changed. The results suggest that the infants' flexibility of actions in a novel situation depends on the prior experience. We speculate neural mechanisms, which may underlie the difference between the arm-based and leg-based learning.
Basu, Amrita; McFarlane, Hewlet G; Kopchick, John J
Growth hormone (GH) has a significant influence on cognitive performance in humans and other mammals. To understand the influence of altered GH action on cognition, we assessed spatial learning and memory using a Barnes maze (BM) comparing twelve-month old, male, bovine GH (bGH) and GH receptor antagonist (GHA) transgenic mice and their corresponding wild type (WT) littermates. During the acquisition training period in the BM, bGH mice showed increased latency, traveled longer path lengths and made more errors to reach the target than WT mice indicating significantly poorer learning. Short-term memory (STM) and long-term memory (LTM) trials showed significantly suppressed memory retention in bGH mice when compared to the WT group. Conversely, GHA mice showed significantly better learning parameters (latency, path length and errors) and increased use of an efficient search strategy than WT mice. Our study indicates a negative impact of GH excess and a beneficial effect of the inhibition of GH action on spatial learning and memory and, therefore, cognitive performance in male mice. Further research to elucidate GH's role in brain function will facilitate identifying therapeutic applications of GH or GHA for neuropathological and neurodegenerative conditions.
An intimate link exists between the predictive and learning processes in the brain. Perceptual/cognitive and spatial/motor processes use complementary predictive mechanisms to learn, recognize, attend and plan about objects in the world, determine their current value, and act upon them. Recent neural models clarify these mechanisms and how they interact in cortical and subcortical brain regions. The present paper reviews and synthesizes data and models of these processes, and outlines a unified theory of predictive brain processing. PMID:19528003
Fujisawa, Kazuko; Inoue, Tomoyoshi; Yamana, Yuko; Hayashi, Humirhiro
The purpose of the present study was to investigate whether participants with intellectual impairments could benefit from the movement associated with animated pictures while they were learning symbol names. Sixteen school students, whose linguistic-developmental age ranged from 38?91 months, participated in the experiment. They were taught 16 static visual symbols and the corresponding action words (naming task) in two sessions conducted one week apart. In the experimental condition, animation was employed to facilitate comprehension, whereas no animation was used in the control condition. Enhancement of learning was shown in the experimental condition, suggesting that the participants benefited from animated symbols. Furthermore, it was found that the lower the linguistic developmental age, the more effective the animated cue was in learning static visual symbols.
Russler, D C; Schadow, G; Mead, C; Snyder, T; Quade, L M; McDonald, C J
Modeling information for the electronic medical record (EMR) builds on a century of study on information and its relationship to cost and quality improvement. An initiative to examine the focus of cost and quality improvement and its relationship to information modeling resulted in the development of the Unified Service Action Model of healthcare processes, which focuses on the action as the center of cost accounting, quality accounting and privacy management. The application of this model to the HL7 Reference Information Model produced a simplification of the HL7 model at the cost of increased reliance on vocabulary terms for actions.
Gatti, R; Tettamanti, A; Gough, P M; Riboldi, E; Marinoni, L; Buccino, G
Both motor imagery and action observation have been shown to play a role in learning or re-learning complex motor tasks. According to a well accepted view they share a common neurophysiological basis in the mirror neuron system. Neurons within this system discharge when individuals perform a specific action and when they look at another individual performing the same or a motorically related action. In the present paper, after a short review of literature on the role of action observation and motor imagery in motor learning, we report the results of a kinematics study where we directly compared motor imagery and action observation in learning a novel complex motor task. This involved movement of the right hand and foot in the same angular direction (in-phase movement), while at the same time moving the left hand and foot in an opposite angular direction (anti-phase movement), all at a frequency of 1Hz. Motor learning was assessed through kinematics recording of wrists and ankles. The results showed that action observation is better than motor imagery as a strategy for learning a novel complex motor task, at least in the fast early phase of motor learning. We forward that these results may have important implications in educational activities, sport training and neurorehabilitation.
Balakrishnan, Sivaraman; Kamisetty, Hetunandan; Carbonell, Jaime G; Lee, Su-In; Langmead, Christopher James
We introduce a new approach to learning statistical models from multiple sequence alignments (MSA) of proteins. Our method, called GREMLIN (Generative REgularized ModeLs of proteINs), learns an undirected probabilistic graphical model of the amino acid composition within the MSA. The resulting model encodes both the position-specific conservation statistics and the correlated mutation statistics between sequential and long-range pairs of residues. Existing techniques for learning graphical models from MSA either make strong, and often inappropriate assumptions about the conditional independencies within the MSA (e.g., Hidden Markov Models), or else use suboptimal algorithms to learn the parameters of the model. In contrast, GREMLIN makes no a priori assumptions about the conditional independencies within the MSA. We formulate and solve a convex optimization problem, thus guaranteeing that we find a globally optimal model at convergence. The resulting model is also generative, allowing for the design of new protein sequences that have the same statistical properties as those in the MSA. We perform a detailed analysis of covariation statistics on the extensively studied WW and PDZ domains and show that our method out-performs an existing algorithm for learning undirected probabilistic graphical models from MSA. We then apply our approach to 71 additional families from the PFAM database and demonstrate that the resulting models significantly out-perform Hidden Markov Models in terms of predictive accuracy.
Martin, James A.
This paper reports the methods and philosophy used in developing a mastery learning model at the University of Missouri-Columbia to insure that allied health students in the physical therapy and occupational therapy programs learn the concepts of anatomy essential to the rest of the curriculum. (MF)
Montoro, Carlos; Hampel, Regine; Stickler, Ursula
This article presents the methods and results of a four-year-long research project focusing on the language learning activity of individual learners using online tasks conducted at the University of Guanajuato (Mexico) in 2009-2013. An activity-theoretical model (Blin, 2010; Engeström, 1987) of the typical language learning activity was used to…
Karmeshu; Raman, Raghu; Nedungadi, Prema
A new modelling approach for diffusion of personalized learning as an educational process innovation in social group comprising adopter-teachers is proposed. An empirical analysis regarding the perception of 261 adopter-teachers from 18 schools in India about a particular personalized learning framework has been made. Based on this analysis,…
Computer models can be powerful tools for addressing many problems in fishery management, but uncertainty about how to apply models and how they should perform can lead to a cautious approach to modeling. Within this approach, we expect models to make quantitative predictions but only after all model inputs have been estimated from empirical data and after the model has been tested for agreement with an independent data set. I review the limitations to this approach and show how models can be more useful as tools for organizing data and concepts, learning about the system to be managed, and exploring management options. Fishery management requires deciding what actions to pursue to meet management objectives. Models do not make decisions for us but can provide valuable input to the decision-making process. When empirical data are lacking, preliminary modeling with parameters derived from other sources can help determine priorities for data collection. When evaluating models for management applications, we should attempt to define the conditions under which the model is a useful, analytical tool (its domain of applicability) and should focus on the decisions made using modeling results, rather than on quantitative model predictions. I describe an example of modeling used as a learning tool for the yellow perch Perca flavescens fishery in Green Bay, Lake Michigan.
Haywood, Antwione Maurice
The Academy was an assessment enhancement program created by the HLC to help institutions strengthen and improve the assessment of student learning. Using a multiple case study approach, this study applies Argyis and Schon's (1976) Theory of Action to explore the espoused values and existence of Model I and II behavior characteristics. Argyis…
Liu, Pei-Lin; Chen, Chiu-Jung
This study investigated the impact of taking photos using mobile phones on the English phrase-learning performance of English as a second-language learners. A total of 116 students enrolled in a college in Central Taiwan participated in this study. The participants were divided randomly into two groups: a control group and an experimental group…
Jacob J. Jacobson; Leonard Malczynski
This paper provides lessons learned from developing several large system dynamics (SD) models. System dynamics modeling practice emphasize the need to keep models small so that they are manageable and understandable. This practice is generally reasonable and prudent; however, there are times that large SD models are necessary. This paper outlines two large SD projects that were done at two Department of Energy National Laboratories, the Idaho National Laboratory and Sandia National Laboratories. This paper summarizes the models and then discusses some of the valuable lessons learned during these two modeling efforts.
Al Musawi, A.; Asan, A.; Abdelraheem, A.; Osman, M.
This research seeks to (1) implement a model for an inquiry based learning environment using learning objects (LOs), and (2) apply the model to examine its impact on students' learning. This research showed that a well-designed learning environment can enhance students learning experiences. The proposed model was applied to an undergraduate course…
Ulusoy, Fatma Merve; Onen, Aysem Seda
This study is based on the generative learning model which involves context-based learning. Using the generative learning model, we taught the topic of Halogens. This topic is covered in the grade 10 chemistry curriculum using activities which are designed in accordance with the generative learning model supported by context-based learning. The…
Linden, Jérôme; Van de Beeck, Lise; Plumier, Jean-Christophe; Ferrara, André
Basal ganglia stroke is often associated with functional deficits in patients, including difficulties to learn and execute new motor skills (procedural learning). To measure procedural learning in a murine model of stroke (30min right MCAO), we submitted C57Bl/6J mice to various sensorimotor tests, then to an operant procedure (Serial Order Learning) specifically assessing the ability to learn a simple motor sequence. Results showed that MCAO affected the performance in some of the sensorimotor tests (accelerated rotating rod and amphetamine rotation test) and the way animals learned a motor sequence. The later finding seems to be caused by difficulties regarding the chunking of operant actions into a coherent motor sequence; the appeal for food rewards and ability to press levers appeared unaffected by MCAO. We conclude that assessment of motor learning in rodent models of stroke might improve the translational value of such models.
Luchi, Kelly Cristina Gaviao; Montrezor, Luís Henrique; Marcondes, Fernanda K
The aim of this study was to evaluate the effect of an educational game that is used for teaching the mechanisms of the action potentials in cell membranes. The game was composed of pieces representing the intracellular and extracellular environments, ions, ion channels, and the Na(+)-K(+)-ATPase pump. During the game activity, the students arranged the pieces to demonstrate how the ions move through the membrane in a resting state and during an action potential, linking the ion movement with a graph of the action potential. To test the effect of the game activity on student understanding, first-year dental students were given the game to play at different times in a series of classes teaching resting membrane potential and action potentials. In all experiments, students who played the game performed better in assessments. According to 98% of the students, the game supported the learning process. The data confirm the students' perception, indicating that the educational game improved their understanding about action potentials.
Koponen, I. T.; Kokkonen, T.; Nousiainen, M.
We present a computational model of sociocognitive aspects of learning. The model takes into account a student's individual cognition and sociodynamics of learning. We describe cognitive aspects of learning as foraging for explanations in the epistemic landscape, the structure (set by instructional design) of which guides the cognitive development through success or failure in foraging. We describe sociodynamic aspects as an agent-based model, where agents (learners) compare and adjust their conceptions of their own proficiency (self-proficiency) and that of their peers (peer-proficiency) in using explanatory schemes of different levels. We apply the model here in a case involving a three-tiered system of explanatory schemes, which can serve as a generic description of some well-known cases studied in empirical research on learning. The cognitive dynamics lead to the formation of dynamically robust outcomes of learning, seen as a strong preference for a certain explanatory schemes. The effects of social learning, however, can account for half of one's success in adopting higher-level schemes and greater proficiency. The model also predicts a correlation of dynamically emergent interaction patterns between agents and the learning outcomes.
classification [23, 24], hyperspectral imag- ing [5, 6], among numerous other applications. It has also been applied recently for motion imagery analysis... CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same as Report (SAR) 18. NUMBER OF PAGES 26 19a. NAME OF RESPONSIBLE PERSON a. REPORT...Actions from Motion Imagery Alexey Castrodad and Guillermo Sapiro ∗ September 2, 2011 Abstract An efficient sparse modeling pipeline for the classification
Colombano, Silvano P.; Compton, Michael; Raghavan, Bharathi; Lum, Henry, Jr. (Technical Monitor)
Goal Directed Model Inversion (GDMI) is an algorithm designed to generalize supervised learning to the case where target outputs are not available to the learning system. The output of the learning system becomes the input to some external device or transformation, and only the output of this device or transformation can be compared to a desired target. The fundamental driving mechanism of GDMI is to learn from success. Given that a wrong outcome is achieved, one notes that the action that produced that outcome "would have been right if the outcome had been the desired one." The algorithm makes use of these intermediate "successes" to achieve the final goal. A unique and potentially very important feature of this algorithm is the ability to modify the output of the learning module to force upon it a desired syntactic structure. This differs from ordinary supervised learning in the following way: in supervised learning the exact desired output pattern must be provided. In GDMI instead, it is possible to require simply that the output obey certain rules, i.e., that it "make sense" in some way determined by the knowledge domain. The exact pattern that will achieve the desired outcome is then found by the system. The ability to impose rules while allowing the system to search for its own answers in the context of neural networks is potentially a major breakthrough in two ways: 1) it may allow the construction of networks that can incorporate immediately some important knowledge, i.e. would not need to learn everything from scratch as normally required at present, and 2) learning and searching would be limited to the areas where it is necessary, thus facilitating and speeding up the process. These points are illustrated with examples from robotic path planning and parametric design.
Colombano, Silvano P.; Compton, Michael; Raghavan, Bharathi; Friedland, Peter (Technical Monitor)
Goal Directed Model Inversion (GDMI) is an algorithm designed to generalize supervised learning to the case where target outputs are not available to the learning system. The output of the learning system becomes the input to some external device or transformation, and only the output of this device or transformation can be compared to a desired target. The fundamental driving mechanism of GDMI is to learn from success. Given that a wrong outcome is achieved, one notes that the action that produced that outcome "would have been right if the outcome had been the desired one." The algorithm makes use of these intermediate "successes" to achieve the final goal. A unique and potentially very important feature of this algorithm is the ability to modify the output of the learning module to force upon it a desired syntactic structure. This differs from ordinary supervised learning in the following way: in supervised learning the exact desired output pattern must be provided. In GDMI instead, it is possible to require simply that the output obey certain rules, i.e., that it "make sense" in some way determined by the knowledge domain. The exact pattern that will achieve the desired outcome is then found by the system. The ability to impose rules while allowing the system to search for its own answers in the context of neural networks is potentially a major breakthrough in two ways: (1) it may allow the construction of networks that can incorporate immediately some important knowledge, i.e., would not need to learn everything from scratch as normally required at present; and (2) learning and searching would be limited to the areas where it is necessary, thus facilitating and speeding up the process. These points are illustrated with examples from robotic path planning and parametric design.
Waismeyer, Anna; Meltzoff, Andrew N; Gopnik, Alison
How do young children learn about causal structure in an uncertain and variable world? We tested whether they can use observed probabilistic information to solve causal learning problems. In two experiments, 24-month-olds observed an adult produce a probabilistic pattern of causal evidence. The toddlers then were given an opportunity to design their own intervention. In Experiment 1, toddlers saw one object bring about an effect with a higher probability than a second object. In Experiment 2, the frequency of the effect was held constant, though its probability differed. After observing the probabilistic evidence, toddlers in both experiments chose to act on the object that was more likely to produce the effect. The results demonstrate that toddlers can learn about cause and effect without trial-and-error or linguistic instruction on the task, simply by observing the probabilistic patterns of evidence resulting from the imperfect actions of other social agents. Such observational causal learning from probabilistic displays supports human children's rapid cultural learning.
Bergsteiner, Harald; Avery, Gayle C.; Neumann, Ruth
Kolb's experiential learning theory has been widely influential in adult learning. The theory and associated instruments continue to be criticized, but rarely is the graphical model itself examined. This is significant because models can aid scientific understanding and progress, as well as theory development and research. Applying accepted…
Wu, Yun-Wu; Weng, Kuo-Hua; Young, Li-Ming
Generally, in the foundation course of architectural design, much emphasis is placed on teaching of the basic design skills without focusing on teaching students to apply the basic design concepts in their architectural designs or promoting students' own creativity. Therefore, this study aims to propose a concept transformation learning model to…
Izawa, Jun; Criscimagna-Hemminger, Sarah E; Shadmehr, Reza
When we use a novel tool, the motor commands may not produce the expected outcome. In healthy individuals, with practice the brain learns to alter the motor commands. This change depends critically on the cerebellum as damage to this structure impairs adaptation. However, it is unclear precisely what the cerebellum contributes to the process of adaptation in human motor learning. Is the cerebellum crucial for learning to associate motor commands with novel sensory consequences, called forward model, or is the cerebellum important for learning to associate sensory goals with novel motor commands, called inverse model? Here, we compared performance of cerebellar patients and healthy controls in a reaching task with a gradual perturbation schedule. This schedule allowed both groups to adapt their motor commands. Following training, we measured two kinds of behavior: in one case, people were presented with reach targets near the direction in which they had trained. The resulting generalization patterns of patients and controls were similar, suggesting comparable inverse models. In the second case, participants reached without a target and reported the location of their hand. In controls, the pattern of change in reported hand location was consistent with simulation results of a forward model that had learned to associate motor commands with new sensory consequences. In patients, this change was significantly smaller. Therefore, in our sample of patients, we observed that while adaptation of motor commands can take place despite cerebellar damage, cerebellar integrity appears critical for learning to predict visual sensory consequences of motor commands.
Hattie, John A. C.; Donoghue, Gregory M.
The purpose of this article is to explore a model of learning that proposes that various learning strategies are powerful at certain stages in the learning cycle. The model describes three inputs and outcomes (skill, will and thrill), success criteria, three phases of learning (surface, deep and transfer) and an acquiring and consolidation phase within each of the surface and deep phases. A synthesis of 228 meta-analyses led to the identification of the most effective strategies. The results indicate that there is a subset of strategies that are effective, but this effectiveness depends on the phase of the model in which they are implemented. Further, it is best not to run separate sessions on learning strategies but to embed the various strategies within the content of the subject, to be clearer about developing both surface and deep learning, and promoting their associated optimal strategies and to teach the skills of transfer of learning. The article concludes with a discussion of questions raised by the model that need further research.
Huang, Shuai; Li, Jing; Chen, Kewei; Wu, Teresa; Ye, Jieping; Wu, Xia; Yao, Li
Networks models have been widely used in many domains to characterize the interacting relationship between physical entities. A typical problem faced is to identify the networks of multiple related tasks that share some similarities. In this case, a transfer learning approach that can leverage the knowledge gained during the modeling of one task to help better model another task is highly desirable. In this paper, we propose a transfer learning approach, which adopts a Bayesian hierarchical model framework to characterize task relatedness and additionally uses the L1-regularization to ensure robust learning of the networks with limited sample sizes. A method based on the Expectation-Maximization (EM) algorithm is further developed to learn the networks from data. Simulation studies are performed, which demonstrate the superiority of the proposed transfer learning approach over single task learning that learns the network of each task in isolation. The proposed approach is also applied to identification of brain connectivity networks of Alzheimer’s disease (AD) from functional magnetic resonance image (fMRI) data. The findings are consistent with the AD literature. PMID:24526804
Hwang, Wu-Yuin; Chang, Chen-Bin; Chen, Gan-Jung
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…
Barbero G., J. Fernando; Villaseñor, Eduardo J.
We show that the Husain-Kuchař model can be described in the framework of BF theories. This is a first step towards its quantization by standard perturbative quantum field theory techniques or the spin-foam formalism introduced in the space-time description of general relativity and other diff-invariant theories. The actions that we will consider are similar to the ones describing the BF-Yang-Mills model and some mass generating mechanisms for gauge fields. We will also discuss the role of diffeomorphisms in the new formulations that we propose.
Boutant, Marie; Cantó, Carles
SIRT1 has attracted a lot of interest since it was discovered as a mammalian homolog of Sir2, a protein that influences longevity in yeast. Intensive early research suggested a key role of SIRT1 in mammalian development, metabolic flexibility and oxidative metabolism. However, it is the growing body of transgenic models that are allowing us to clearly define the true range of SIRT1 actions. In this review we aim to summarize the most recent lessons that transgenic animal models have taught us about the role of SIRT1 in mammalian metabolic homeostasis and lifespan.
Mesmer, Karen Luann
Students often have difficulty in learning natural selection, a major model in biology. This study examines what middle school students are capable of learning when taught about natural selection using a modeling approach. Students were taught the natural selection model including the components of population, variation, selective advantage, survival, heredity and reproduction. They then used the model to solve three case studies. Their learning was evaluated from responses on a pretest, a posttest and interviews. The results suggest that middle school students can identify components of the natural selection model in a Darwinian explanation, explain the significance of the components and relate them to each other as well as solve evolutionary problems using the model.
Brdiczka, Oliver; Crowley, James L; Reignier, Patrick
This paper addresses the problem of learning situation models for providing context-aware services. Context for modeling human behavior in a smart environment is represented by a situation model describing environment, users, and their activities. A framework for acquiring and evolving different layers of a situation model in a smart environment is proposed. Different learning methods are presented as part of this framework: role detection per entity, unsupervised extraction of situations from multimodal data, supervised learning of situation representations, and evolution of a predefined situation model with feedback. The situation model serves as frame and support for the different methods, permitting to stay in an intuitive declarative framework. The proposed methods have been integrated into a whole system for smart home environment. The implementation is detailed, and two evaluations are conducted in the smart home environment. The obtained results validate the proposed approach.
Gurvitch, Rachel; Metzler, Michael
Model-based instruction has been increasingly used in physical education for the past two decades. Metzler (2011) identified eight instructional models that are commonly used in physical education today. Each model is designed to promote certain kinds of learning outcomes for students and to address different combinations of the national…