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Learning Process (learning + process)
Kinds of Learning Process Selected AbstractsExplaining the Good Friday Agreement: A Learning ProcessGOVERNMENT AND OPPOSITION, Issue 4 2001Etain Tannam First page of article [source] The Jammed Democracy: Bolivia's Troubled Political Learning ProcessBULLETIN OF LATIN AMERICAN RESEARCH, Issue 2 2006Ton Salman The fact that even the moderate and broadly respected president Carlos Mesa was forced to step down in Bolivia in June 2005 suggests that the country's crisis goes beyond a conflict on specific policies. A longstanding practice of excluding large sectors of the population from all real influence in politics, despite the existence of formal democracy, has produced a crisis of belief in democracy, affecting both governing bodies and the party system. President Mesa was unable to reverse the generalised distrust of politics. This distrust, combined with persisting political stalemate, is currently tending towards societal disintegration, which makes the recovery of genuine democratic practices even more difficult. [source] Customer Learning Processes, Strategy Selection, and Performance in Business-to-Business Service Firms,DECISION SCIENCES, Issue 2 2004Debra Zahay ABSTRACT Learning about customers takes place through relevant dialogues with those customers, also known as customer relationship management (CRM). As relationships develop, information about the customer is gathered in the firm's customer information systems (CIS): the content, processes, and assets associated with gathering and moving customer information throughout the firm. This research develops a measure of CIS management capabilities based on learning organization theory and measured by the ability to get, store, move, and use information throughout the business unit. This measure is then used to analyze customer learning processes and associated performance in the context of marketing strategic decision making. This study of 209 business services firms finds that generic marketing strategy positioning (low-cost and differentiation) and the marketing tactics of personalization and customization are related to CIS development. Customer information systems development in turn is associated with higher levels of customer-based performance, which in turn is associated with increased business growth. Since the strongest association with customer-based performance is strategy selection, the long-term benefits of the knowledge gained from the CIS may be in the ability to assist in measuring customer-based performance, rather than in the ability to immediately contribute to performance. Finally, for these firms, customization and personalization are not directly associated with performance and thus may not be necessary to support every firm's marketing strategy. [source] II. Study 1: Child Responses to Interparental Conflict: Comparing the Relative Roles Of Emotional Security and Social Learning ProcessesMONOGRAPHS OF THE SOCIETY FOR RESEARCH IN CHILD DEVELOPMENT, Issue 3 2002Patrick T. Davies [source] Learning to Cooperate: Learning Networks and the Problem of AltruismAMERICAN JOURNAL OF POLITICAL SCIENCE, Issue 3 2009John T. Scholz We explore how two populations learn to cooperate with each other in the absence of institutional support. Individuals play iterated prisoner's dilemmas with the other population, but learn about successful strategies from their own population. Our agent-based evolutionary models reconfirm that cooperation can emerge rapidly as long as payoffs provide a selective advantage for nice, retaliatory strategies like tit-for-tat, although attainable levels of cooperation are limited by the persistence of nonretaliatory altruists. Learning processes that adopt the current best response strategy do well only when initial conditions are very favorable to cooperation, while more adaptive learning processes can achieve high levels of cooperation under a wider range of initial conditions. When combined with adaptive learning, populations having larger, better connected learning relationships outperform populations with smaller, less connected ones. Clustered relationships can also enhance cooperation, particularly in these smaller, less connected populations. [source] LEARNING PRECONDITIONS FOR PLANNING FROM PLAN TRACES AND HTN STRUCTURECOMPUTATIONAL INTELLIGENCE, Issue 4 2005Okhtay Ilghami A great challenge in developing planning systems for practical applications is the difficulty of acquiring the domain information needed to guide such systems. This paper describes a way to learn some of that knowledge. More specifically, the following points are discussed. (1) We introduce a theoretical basis for formally defining algorithms that learn preconditions for Hierarchical Task Network (HTN) methods. (2) We describe Candidate Elimination Method Learner (CaMeL), a supervised, eager, and incremental learning process for preconditions of HTN methods. We state and prove theorems about CaMeL's soundness, completeness, and convergence properties. (3) We present empirical results about CaMeL's convergence under various conditions. Among other things, CaMeL converges the fastest on the preconditions of the HTN methods that are needed the most often. Thus CaMeL's output can be useful even before it has fully converged. [source] A software player for providing hints in problem-based learning according to a new specificationCOMPUTER APPLICATIONS IN ENGINEERING EDUCATION, Issue 3 2009Pedro J. Muñoz-Merino Abstract The provision of hints during problem solving has been a successful strategy in the learning process. There exist several computer systems that provide hints to students during problem solving, covering some specific issues of hinting. This article presents a novel software player module for providing hints in problem-based learning. We have implemented it into the XTutor Intelligent Tutoring System using its XDOC extension mechanism and the Python programming language. This player includes some of the functionalities that are present in different state-of-the-art systems, and also other new relevant functionalities based on our own ideas and teaching experience. The article explains each feature for providing hints and it also gives a pedagogical justification or explanation. We have created an XML binding, so any combination of the model hints functionalities can be expressed as an XML instance, enabling interoperability and reusability. The implemented player tool together with the XTutor server-side XDOC processor can interpret and run XML files according to this newly defined hints specification. Finally, the article presents several running examples of use of the tool, the subjects where it is in use, and results that lead to the conclusion of the positive impact of this hints tool in the learning process based on quantitative and qualitative analysis. © 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 17: 272,284, 2009; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20240 [source] An efficient concurrent implementation of a neural network algorithmCONCURRENCY AND COMPUTATION: PRACTICE & EXPERIENCE, Issue 12 2006R. Andonie Abstract The focus of this study is how we can efficiently implement the neural network backpropagation algorithm on a network of computers (NOC) for concurrent execution. We assume a distributed system with heterogeneous computers and that the neural network is replicated on each computer. We propose an architecture model with efficient pattern allocation that takes into account the speed of processors and overlaps the communication with computation. The training pattern set is distributed among the heterogeneous processors with the mapping being fixed during the learning process. We provide a heuristic pattern allocation algorithm minimizing the execution time of backpropagation learning. The computations are overlapped with communications. Under the condition that each processor has to perform a task directly proportional to its speed, this allocation algorithm has polynomial-time complexity. We have implemented our model on a dedicated network of heterogeneous computers using Sejnowski's NetTalk benchmark for testing. Copyright © 2005 John Wiley & Sons, Ltd. [source] An Emerging Market's Reaction to Initial Modified Audit Opinions: Evidence from the Shanghai Stock Exchange,CONTEMPORARY ACCOUNTING RESEARCH, Issue 3 2000CHARLES J. P. CHEN Abstract This study investigates the valuation effect of modified audit opinions (MAOs) on the emerging Chinese stock market. Here, the term MAO refers to both qualified opinions and unqualified opinions with explanatory notes. The latter can be considered an alternative form of a qualified opinion in China. The institutional setting in China enables us to find compelling evidence in support of the monitoring role of independent auditing as an institution. First, we find a significantly negative association between MAOs and cumulative abnormal returns after controlling for effects of other concurrent announcements. Further, results from a by-year analysis suggest that investors did not reach negative consensus about MAOs' valuation effect until the second year, exhibiting the learning process of a market without prior exposure to MAOs. Second, we do not observe significant differences between market reaction to non-GAAP- and GAAP-violation-related MAOs. Third, no significant difference is found between market reaction to qualified opinions and market reaction to unqualified opinions with explanatory notes. [source] Enhancing Knowledge Transfer in Classroom Versus Online Settings: The Interplay Among Instructor, Student, Content, and ContextDECISION SCIENCES JOURNAL OF INNOVATIVE EDUCATION, Issue 1 2009Louise Nemanich ABSTRACT This article integrates management education and organizational learning theories to identify the factors that drive the differences in student outcomes between the online and classroom settings. We draw upon theory on knowledge transfer barriers in organizations to understand the interlinking relationships among presage conditions, deep learning process, and product in the 3P model of student learning. We test our model in the context of undergraduate education and find that confidence in the instructor's expertise, perceived content relevance, and the social richness of the classroom learning environment enhance student enjoyment of the course. Confidence in instructor's expertise and perceived content relevance also contribute to greater understanding of causal relationships among course concepts. Enjoyment is positively associated with learning performance in the classroom, but not online, and student ability is positively associated with learning performance in the online context, but not in the classroom. Our results have implications for course designs in the traditional classroom context and the more innovative online environment. [source] Using the Malcolm Baldrige National Quality Award in Teaching: One Criteria, Several Perspectives,DECISION SCIENCES JOURNAL OF INNOVATIVE EDUCATION, Issue 2 2004James A. Belohlav ABSTRACT The Malcolm Baldrige National Quality Award (MBNQA) has influenced the thinking and operations within organizations from all sectors of the American economy. This paper presents the experiences of three faculty members who have used the Criteria for Performance Excellence and the underlying concepts of the MBNQA to enhance the learning experiences of their students. The authors discuss how Dale's Cone of Experience is employed, by means of concrete exercises and experiences, to better leverage the student's ability to understand the abstract concepts. The formal, end-of-term student evaluations indicate that the described approach has led to a higher level of student engagement in the learning process, as evidenced by more abundant and higher-quality feedback to the instructors. [source] Respiratory units of motor production and song imitation in the zebra finchDEVELOPMENTAL NEUROBIOLOGY, Issue 2 2002Michele Franz Abstract Juvenile male zebra finches (Taeniopygia guttata) learn a stereotyped song by imitating sounds from adult male tutors. Their song is composed of a series of syllables, which are separated by silent periods. How acoustic units of song are translated into respiratory and syringeal motor gestures during the song learning process is not well understood. To learn about the respiratory contribution to the imitation process, we recorded air sac pressure in 38 male zebra finches and compared the acoustic structures and air sac pressure patterns of similar syllables qualitatively and quantitatively. Acoustic syllables correspond to expiratory pressure pulses and most often (74%) entire syllables are copied using similar air sac pressure patterns. Even notes placed within different syllables are generated with similar air sac pressure patterns when only segments of syllables are copied (9%). A few of the similar syllables (17%) are generated with a modified pressure pattern, typically involving addition or deletion of an inspiration. The high similarity of pressure patterns for like syllables indicates that generation of particular sounds is constrained to a narrow range of air sac pressure conditions. Following presentation of stroboscope flashes, song was typically interrupted at the end of an expiratory pressure pulse, confirming that expirations and, therefore, syllables are the smallest unit of motor production of song. Silent periods, which separate syllables acoustically, are generated by switching from expiration to inspiration. Switching between respiratory phases, therefore, appears to play a dominant role in organizing the stereotyped motor program for song production. © 2002 Wiley Periodicals, Inc. J Neurobiol 51: 129,141, 2002 [source] Precise disturbance modeling for improvement of positioning performanceELECTRICAL ENGINEERING IN JAPAN, Issue 2 2010Masafumi Yamamoto Abstract This paper presents a modeling methodology for unknown disturbances in mechatronics systems, based on disturbance estimation using an iterative learning process. In disturbance modeling, nonlinear frictions are specially handled as disturbances in the mechanisms, which mainly degrade trajectory control performance. Friction can be mathematically modeled by using learned estimation data as a function of the displacement, velocity. acceleration, and jerk of the actuator. This model has the distinctive feature that friction compensation can be achieved with a generalization capability for different conditions. The proposed positioning control approach with disturbance modeling and compensation has been verified by experiments using a table drive system on a machine stand. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 171(2): 31,39, 2010; Published online in Wiley InterScience (www. interscience.wiley.com). DOI 10.1002/eej.20928 [source] The climate learning ladder.ENVIRONMENTAL POLICY AND GOVERNANCE, Issue 1 2010A pragmatic procedure to support climate adaptation Abstract We introduce a new pragmatic procedure called the ,climate learning ladder' to structure policy analysis, support reflection and identify critical decisions to support climate adaptation. This tool is the result of the reflexive learning process that occurred while developing innovative appraisal methods in the Alxa League of Inner Mongolia, China, and in the Guadiana river basin in the European Union. Building capacities to cope with climate change requires going beyond simply providing ,more knowledge' on climate impacts to policy makers. Instead, climate adaptation can be understood as a multi-step social process in which individuals and organizations need to learn how to (1) manage different framings of the issues at stake while raising awareness of climate risks and opportunities, (2) understand different motives for, and generate adequate incentives or sanctions to ensure, action, (3) develop feasible options and resources for individual and collective transformation and collaboration and (4) institutionalize new rights, responsibilities and feedback learning processes for climate adaptation in the long term. Copyright © 2010 John Wiley & Sons, Ltd and ERP Environment. [source] Climate proofing Scottish river basin planning, , a future challengeENVIRONMENTAL POLICY AND GOVERNANCE, Issue 6 2009Kirsty Blackstock Abstract Due to its cyclical planning process, River Basin Management Planning (RBMP) offers a route for adaptive management of a complex human,environment system. Considering how stakeholders speak about climate change provides a lens to examine social learning within RBMP. The paper explores how climate change emerged as a topic during our research and the trajectory of the social learning process. Participants were aware of the challenges that climate change might pose for achieving Good Ecological Status (GES), but as the deadline for the plans drew nearer the focus shifted from long-term issues to the current state of the environment and delivery of objectives. The degree of ,climate proofing' in RBMP depends on choices in future planning phases. We reflect on the potential for this to occur, putting our findings into the context of literature on social learning and adaptive management processes. Copyright © 2009 John Wiley & Sons, Ltd and ERP Environment. [source] Effect of augmented visual feedback from a virtual reality simulation system on manual dexterity trainingEUROPEAN JOURNAL OF DENTAL EDUCATION, Issue 1 2005E. Wierinck Little research has been published about the impact of simulation technology on the learning process of novel motor skills. Especially the role of augmented feedback (FB) on the quality of performance and the transfer of the acquired behaviour to a no-augmented FB condition require further investigation. Therefore, novice dental students were randomly assigned to one of three groups and given the task of drilling a geometrical class 1 cavity. The FB group trained under augmented visual FB conditions, provided by the virtual reality (VR) system (DentSimTM). The no-FB group practised under normal vision conditions, in the absence of augmented FB. A control group performed the test sessions without participating in any training programme. All preparations were evaluated by the VR grading system according to four traditional (outline shape, floor depth, floor smoothness and wall inclination), and two critical, criteria (pulp exposure and damage to adjacent teeth). Performance analyses revealed an overall trend towards significant improvement with training for the experimental groups. The FB group obtained the highest scores. It scored better for floor depth (P < 0.001), whilst the no-FB group was best for floor smoothness (P < 0.005). However, at the retention tests, the FB group demonstrated inferior performance in comparison with the no-FB group. The transfer test on a traditional unit revealed no significant differences between the training groups. Consequently, drilling experience on a VR system under the condition of frequently provided FB and lack of any tutorial input was considered to be not beneficial to learning. The present data are discussed in view of the guidance hypothesis of FB, which refers to the apprentice's dependence on FB. [source] Policy Learning: can Government discover the treasure within?EUROPEAN JOURNAL OF EDUCATION, Issue 2 2007GRAHAM LEICESTER We live in powerful times and are experiencing a conceptual emergency. The imperative to learn is evident. Yet in spite of advances in knowledge about how we learn, our application of that knowledge in practice remains patchy at best. A key part of the challenge is to encourage government itself to participate in the learning process, and to overcome the psychological and structural constraints it faces that militate against learning. The article suggests a number of measures to facilitate learning within the policy process: including first tackling denial, making space for reflection, empowering the boundary spanners and , most important , practising innovation as learning. The Delors Commission for UNESCO on education for the 21st century called learning ,the treasure within'. It is no longer possible for government to ignore the turbulence and complexity of its operating environment: it needs to find its own treasure within. This is the case for policy learning. [source] Blockade of NMDA receptors in the dorsomedial striatum prevents action,outcome learning in instrumental conditioningEUROPEAN JOURNAL OF NEUROSCIENCE, Issue 2 2005Henry H. Yin Abstract 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. [source] Inducing safer oblique trees without costsEXPERT SYSTEMS, Issue 4 2005Sunil Vadera Abstract: Decision tree induction has been widely studied and applied. In safety applications, such as determining whether a chemical process is safe or whether a person has a medical condition, the cost of misclassification in one of the classes is significantly higher than in the other class. Several authors have tackled this problem by developing cost-sensitive decision tree learning algorithms or have suggested ways of changing the distribution of training examples to bias the decision tree learning process so as to take account of costs. A prerequisite for applying such algorithms is the availability of costs of misclassification. Although this may be possible for some applications, obtaining reasonable estimates of costs of misclassification is not easy in the area of safety. This paper presents a new algorithm for applications where the cost of misclassifications cannot be quantified, although the cost of misclassification in one class is known to be significantly higher than in another class. The algorithm utilizes linear discriminant analysis to identify oblique relationships between continuous attributes and then carries out an appropriate modification to ensure that the resulting tree errs on the side of safety. The algorithm is evaluated with respect to one of the best known cost-sensitive algorithms (ICET), a well-known oblique decision tree algorithm (OC1) and an algorithm that utilizes robust linear programming. [source] Evolving modular networks with genetic algorithms: application to nonlinear time seriesEXPERT SYSTEMS, Issue 4 2004A.S. Cofiño Abstract: A key problem of modular neural networks is finding the optimal aggregation of the different subtasks (or modules) of the problem at hand. Functional networks provide a partial solution to this problem, since the inter-module topology is obtained from domain knowledge (functional relationships and symmetries). However, the learning process may be too restrictive in some situations, since the resulting modules (functional units) are assumed to be linear combinations of selected families of functions. In this paper, we present a non-parametric learning approach for functional networks using feedforward neural networks for approximating the functional modules of the resulting architecture; we also introduce a genetic algorithm for finding the optimal intra-module topology (the appropriate balance of neurons for the different modules according to the complexity of their respective tasks). Some benchmark examples from nonlinear time-series prediction are used to illustrate the performance of the algorithm for finding optimal modular network architectures for specific problems. [source] A metagenetic algorithm for information filtering and collection from the World Wide WebEXPERT SYSTEMS, Issue 2 2001Z.N. Zacharis This paper describes the implementation of evolutionary techniques for information filtering and collection from the World Wide Web. We consider the problem of building intelligent agents to facilitate a person's search for information on the Web. An intelligent agent has been developed that uses a metagenetic algorithm in order to collect and recommend Web pages that will be interesting to the user. The user's feedback on the agent's recommendations drives the learning process to adapt the user's profile with his/her interests. The software agent utilizes the metagenetic algorithm to explore the search space of user interests. Experimental results are presented in order to demonstrate the suitability of the metagenetic algorithm's approach on the Web. [source] Democracy, Islam and Dialogue: The Case of TurkeyGOVERNMENT AND OPPOSITION, Issue 4 2005Bora Kanra The November 2002 general elections in Turkey produced an Islamic-leaning government, supported by one of the biggest majorities, bringing the relationship between Islam and democracy under scrutiny. This paper examines the nature of this relationship and the current political situation in Turkey. It argues that Turkey's long-running aspiration for democratization has now a reasonable chance of success. This argument is supported by the findings of a Q study, conducted in Turkey during the 2002 election campaign, indicating strong support for dialogue, particularly within the Turkish Muslim community. Yet, it will also argue that turning this possibility into a success depends on the implementation of the right deliberative framework. Habermas's discourse theory of democracy provides the essentials for this. However, particularly in the context of a divided society, like Turkey, it has to be complemented with a better emphasis on deliberation as a social learning process, as in Dryzek's theory of discursive democracy. [source] Knowledge, Market Structure, and Economic Coordination: Dynamics of Industrial DistrictsGROWTH AND CHANGE, Issue 3 2002Ron A. Boschma The industrial rise of the Third Italy has been characterized by the growth of dynamic networks of flexible small and medium,sized enterprises (SMEs) that are spatially concentrated in specialized industrial districts. This network type of coordination has been associated with horizontal, trust,based relations rather than vertical relations of power and dependency between local organizations. This would lower transaction costs (essential for local systems with an extreme division of labor), facilitate the transmission and exchange of (tacit) knowledge (and thus, learning and innovation), encourage cooperation mechanisms (such as the establishment of research centers), and stimulate political,institutional performance (e.g. through regulation of potential social conflicts). From an evolutionary perspective, the focus is on the dynamics of industrial districts drawing from current experiences in Italy. In this respect, this paper concentrates on two main features of industrial districts that have largely contributed to their economic success in the past, that is, their network organization and the collective learning process. The evolution of industrial districts is described in terms of organizational adjustments to structural change. The way in which the size distribution of firms has changed is discussed (in particular the role of large companies), how the (power) relationships between local organizations have evolved, what are the current sources and mechanisms of learning, and to what extent institutional lock,in has set in. Finally, a number of trajectories districts may go through in the near future are presented. [source] Regulated competition and citizen participation: lessons from IsraelHEALTH EXPECTATIONS, Issue 2 2000David Chinitz PhD Objective To investigate the relationship between health system structure and citizen participation, in particular whether increased reliance on competition encourages or depresses citizen involvement. Setting The case of Israel's ongoing health reform, based on regulated competition among sick funds, is examined. Design Interviews with government officials and representatives of consumer groups; analysis of policy documents, judicial rulings, public surveys and journalistic accounts. Results The Israeli reform is based in large measure on a regulated competition model, in which citizens have free choice among highly regulated competing sick funds. At the same time, the reform process has been accompanied by legal, institutional and political frameworks, as well as significant interest group activity, all aimed at increasing public input into processes of health policy making and implementation. The Israeli case, it is argued, lends support to the proposition that citizen participation (voice) and individual choice (exit) are complementary, rather than alternative, modes of ensuring citizen influence over health services. The question is whether the development of multiple avenues for citizen involvement represents disarray or a healthy social learning process regarding the running of the health system. Conclusion This paper expresses cautious optimism that citizen participation is a projection of a healthy social learning process, and suggests directions for public policy to encourage this outcome. [source] An epigenetic induction of a right-shift in hippocampal asymmetry: Selectivity for short- and long-term potentiation but not post-tetanic potentiationHIPPOCAMPUS, Issue 1 2008Akaysha C. Tang Abstract In humans, it is well established that major psychological functions are asymmetrically represented between the left and right cerebral cortices. The developmental origin of such functional lateralization remains unknown. Using the rat as a model system, we examined whether exposing neonates briefly to a novel environment can differentially affect synaptic plasticity in the left and right hippocampi during adulthood. During the first 3 weeks of life, one half of the pups from a litter spent 3 min daily away from their familiar home environment (Novel) while their littermates remained in that familiar environment (Home). At adulthood (7-months old), post-tetanic potentiation (PTP) of excitatory post-synaptic potentials (EPSPs), a very short-lasting form of plasticity, was greater among the Novel than the Home rats in both left and right hippocampi. In contrast, the novelty-induced increases in short- and long-term potentiation (STP, LTP), two relatively longer-lasting forms of plasticity, were found only in the right hippocampus. These findings demonstrate that a phase-selective asymmetry in hippocampal synaptic plasticity can be induced epigenetically by seemingly small systematic differences in early life environment. The selectivity of this asymmetry for the longer-lasting forms of synaptic plasticity suggests that the observed asymmetry in plasticity may contribute specifically to an asymmetric learning process which, in turn, may contribute to a functional asymmetry in the neocortex. © 2007 Wiley-Liss, Inc. [source] How newcomers learn the social norms of an organization: A case study of the socialization of newly hired engineersHUMAN RESOURCE DEVELOPMENT QUARTERLY, Issue 3 2009Russell F. Korte Current scholarship views organizational socialization as a learning process that is primarily the responsibility of the newcomer. Yet recent learning research recognizes the importance of the social interactions in the learning process. This study investigated how newly hired engineers at a large manufacturing company learned job-related tasks and the social norms of the organization. From the perspective of social exchange theory, two major findings emerged from the data: (1) relationship building was the primary driver of socialization, and (2) the work group was the primary context for socialization. These findings challenge the current views of organizational socialization by accentuating the relational processes that mediate learning during socialization. [source] Learning in interactive work situations: It takes two to tango; why not invite both partners to dance?HUMAN RESOURCE DEVELOPMENT QUARTERLY, Issue 2 2006Hanneke Koopmans Learning that arises from interactions at work is the focus of this study. More specifically, the concrete activities of adult learners and their interaction partners were of interest because such learning activities largely determine the quality of learning outcomes. The results of the study are summarized in the form of a typology of interactive learning behaviors for adult learners (that is, workers) and their interaction partners at work. The similarities and differences among three occupational groups, teachers, financial service professionals, and police officers groups,were examined, and explanations were sought based on the nature of work and power. The results can help adult learners and their interaction partners enter into a more equal, dyadic, and reciprocal learning process and thereby contribute to a critical human resource development perspective. [source] Mediation in a sibling context: the relations of older siblings' mediating behaviour and younger siblings' task performanceINFANT AND CHILD DEVELOPMENT, Issue 4 2002Pnina S. Klein Abstract We investigated the sibling relationship as a context for cognitive development. Forty preschoolers (ages 5,6) and their younger siblings (ages 2,3) were visited at home. Four games were presented to the older siblings and they were asked (a) to estimate how well their younger sibling will perform on each game and (b) to teach the younger sibling how to use the games. The older siblings' mediating behaviours during the teaching session and the younger siblings' performance on the four tasks were coded. The frequency of mediating behaviours,including attention focusing, amplifying affect and providing meaning, fostering a sense of competence, regulating of the learning process, de-contextualization, and negative feedback in the form of mocking and laughing at errors, predicted the younger siblings' task performance. The older sibling's accurate perception of the younger child's competence was uniquely predictive of task performance. The highest amount of mediation was observed in older-brother,younger-brother pairs, in particular the behaviours of negative feedback and amplifying affect. Results contribute to the discussion on the role of siblings as moderators of cognitive development and are discussed in terms of Vygotsky's cultural,historical perspective on apprenticeship. Copyright © 2002 John Wiley & Sons, Ltd. [source] Learning cooperative linguistic fuzzy rules using the best,worst ant system algorithmINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 4 2005Jorge Casillas Within the field of linguistic fuzzy modeling with fuzzy rule-based systems, the automatic derivation of the linguistic fuzzy rules from numerical data is an important task. In the last few years, a large number of contributions based on techniques such as neural networks and genetic algorithms have been proposed to face this problem. In this article, we introduce a novel approach to the fuzzy rule learning problem with ant colony optimization (ACO) algorithms. To do so, this learning task is formulated as a combinatorial optimization problem. Our learning process is based on the COR methodology proposed in previous works, which provides a search space that allows us to obtain fuzzy models with a good interpretability,accuracy trade-off. A specific ACO-based algorithm, the Best,Worst Ant System, is used for this purpose due to the good performance shown when solving other optimization problems. We analyze the behavior of the proposed method and compare it to other learning methods and search techniques when solving two real-world applications. The obtained results lead us to remark the good performance of our proposal in terms of interpretability, accuracy, and efficiency. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 433,452, 2005. [source] Adaptive and Generative Learning: Implications from Complexity TheoriesINTERNATIONAL JOURNAL OF MANAGEMENT REVIEWS, Issue 2 2010Ricardo Chiva One of the most important classical typologies within the organizational learning literature is the distinction between adaptive and generative learning. However, the processes of these types of learning, particularly the latter, have not been widely analyzed and incorporated into the organizational learning process. This paper puts forward a new understanding of adaptive and generative learning within organizations, grounded in some ideas from complexity theories: mainly self-organization and implicate order. Adaptive learning involves any improvement or development of the explicate order through a process of self-organization. Self-organization is a self-referential process characterized by logical deductive reasoning, concentration, discussion and improvement. Generative learning involves any approach to the implicate order through a process of self-transcendence. Self-transcendence is a holo-organizational process characterized by intuition, attention, dialogue and inquiry. The main implications of the two types of learning for organizational learning are discussed. [source] | |||||||||||||||||||||||||||||||||||||||||||||||||