20 resultados para learning for change

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Conversation is central to the process of organizational learning and change. Drawing on the notion of reflective conversation, we describe an action research project, "learning through listening" in Omega, a residential healthcare organization. In this project, service users, staff, members of management committees, trustees, managers, and central office staff participated in listening to each other and in working together towards building capacity for creating their own vision of how the organization could move into the future, according to its values and ethos. In doing so they developed ways of engaging in reflective conversation that enabled progress towards a strategic direction.

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The increasing practice of offshore outsourcing software maintenance has posed the challenge of effectively transferring knowledge to individual software engineers of the vendor. In this theoretical paper, we discuss the implications of two learning theories, the model of work-based learning (MWBL) and cognitive load theory (CLT), for knowledge transfer during the transition phase. Taken together, the theories suggest that learning mechanisms need to be aligned with the type of knowledge (tacit versus explicit), task characteristics (complexity and recurrence), and the recipients’ expertise. The MWBL proposes that learning mechanisms need to include conceptual and practical activities based on the relative importance of explicit and tacit knowledge. CLT explains how effective portfolios of learning mechanisms change over time. While jobshadowing, completion tasks, and supportive information may prevail at the outset of transition, they may be replaced by the work on conventional tasks towards the end of transition.

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The aim of this paper is investigate the role of conversation in strategic change so as to enhance both theory and practice in this respect. As an investigation on how conversations shape change processes in practice, we reflect on an interpretive case study in a health care organization. Through an OD project complemented by semi-structured interviews with participants, we gained a set of data and experiences that allows us to inquire into the relationship between conversations and change in more depth.

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Over the last decade, the end-state comfort effect (e.g., Rosenbaum et al., 2006) has received a considerable amount of attention. However, some of the underlying mechanisms are still to be investigated, amongst others, how sequential planning affects end-state comfort and how this effect develops over learning. In a two-step sequencing task, e.g., postural comfort can be planned on the intermediate position (next state) or on the actual end position (final state). It might be hypothesized that, in initial acquisition, next state’s comfort is crucial for action planning but that, in the course of learning, final state’s comfort is taken more and more into account. To test this hypothesis, a variant of Rosenbaum’s vertical stick transportation task was used. Participants (N = 16, right-handed) received extensive practice on a two-step transportation task (10,000 trials over 12 sessions). From the initial position on the middle stair of a staircase in front of the participant, the stick had to be transported either 20 cm upwards and then 40 cm downwards or 20 cm downwards and then 40 cm upwards (N = 8 per subgroup). Participants were supposed to produce fluid movements without changing grasp. In the pre- and posttest, participants were tested on both two-step sequencing tasks as well as on 20 cm single-step upwards and downwards movements (10 trials per condition). For the test trials, grasp height was calculated kinematographically. In the pretest, large end/next/final-state comfort effects for single-step transportation tasks and large next-state comfort effects for sequenced tasks were found. However, no change in grasp height from pre- to posttest could be revealed. Results show that, in vertical stick transportation sequences, the final state is not taken into account when planning grasp height. Instead, action planning seems to be solely based on aspects of the next action goal that is to be reached.

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Like other mountain areas in the world, the Hindu Kush-Himalayan (HKH) region is particularly vulnerable to climate change. Ongoing climate change processes are projected to have a high impact on the HKH region, and accelerated warming has been reported in the Himalayas. These climate change impacts will be superimposed on a variety of other environmental and social stresses, adding to the complexity of the issues. The sustainable use of natural resources is crucial to the long-term stability of the fragile mountain ecosystems in the HKH and to sustain the socio-ecological resilience that forms the basis of sustainable livelihoods in the region. In order to be prepared for these challenges, it is important to take stock of previous research. The ‘People and Resource Dynamics Project’ (PARDYP), implemented by International Centre for Integrated Mountain Development (ICIMOD), provides a variety of participatory options for sustainable land management in the HKH region. The PARDYD project was a research for development project that operated in five middle mountain watersheds across the HKH – two in Nepal and one each in China, India, and Pakistan. The project ran from 1996 to 2006 and focused on addressing the marginalisation of mountain farmers, the use and availability of water, issues relating to land and forest degradation and declining soil fertility, the speed of regeneration of degraded land, and the ability of the natural environment to support the growing needs of the region’s increasing population. A key learning from the project was that the opinion of land users is crucial to the acceptance (and, therefore, successful application) of new technologies and approaches. A major challenge at the end of every project is to promote knowledge sharing and encourage the cross-fertilization of ideas (e.g., in the case of PARDYP, with other middle mountain inhabitants and practitioners in the region) and to share lessons learned with a wider audience. This paper will highlight how the PARDYP findings, including ways of addressing soil fertility and water scarcity, have been mainstreamed in the HKH region through capacity building (international, regional, and national training courses), networking, and the provision of backstopping services. In addition, in view of the challenges in watershed management in the HKH connected to environmental change, the lessons learned from the PARDYP are now being used by ICMOD to define and package climate change proof technology options to address climate change adaptation.

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Humans and animals face decision tasks in an uncertain multi-agent environment where an agent's strategy may change in time due to the co-adaptation of others strategies. The neuronal substrate and the computational algorithms underlying such adaptive decision making, however, is largely unknown. We propose a population coding model of spiking neurons with a policy gradient procedure that successfully acquires optimal strategies for classical game-theoretical tasks. The suggested population reinforcement learning reproduces data from human behavioral experiments for the blackjack and the inspector game. It performs optimally according to a pure (deterministic) and mixed (stochastic) Nash equilibrium, respectively. In contrast, temporal-difference(TD)-learning, covariance-learning, and basic reinforcement learning fail to perform optimally for the stochastic strategy. Spike-based population reinforcement learning, shown to follow the stochastic reward gradient, is therefore a viable candidate to explain automated decision learning of a Nash equilibrium in two-player games.

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We present a model of spike-driven synaptic plasticity inspired by experimental observations and motivated by the desire to build an electronic hardware device that can learn to classify complex stimuli in a semisupervised fashion. During training, patterns of activity are sequentially imposed on the input neurons, and an additional instructor signal drives the output neurons toward the desired activity. The network is made of integrate-and-fire neurons with constant leak and a floor. The synapses are bistable, and they are modified by the arrival of presynaptic spikes. The sign of the change is determined by both the depolarization and the state of a variable that integrates the postsynaptic action potentials. Following the training phase, the instructor signal is removed, and the output neurons are driven purely by the activity of the input neurons weighted by the plastic synapses. In the absence of stimulation, the synapses preserve their internal state indefinitely. Memories are also very robust to the disruptive action of spontaneous activity. A network of 2000 input neurons is shown to be able to classify correctly a large number (thousands) of highly overlapping patterns (300 classes of preprocessed Latex characters, 30 patterns per class, and a subset of the NIST characters data set) and to generalize with performances that are better than or comparable to those of artificial neural networks. Finally we show that the synaptic dynamics is compatible with many of the experimental observations on the induction of long-term modifications (spike-timing-dependent plasticity and its dependence on both the postsynaptic depolarization and the frequency of pre- and postsynaptic neurons).

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PURPOSE: Understanding the learning styles of individuals may assist in the tailoring of an educational program to optimize learning. General surgery faculty and residents have been characterized previously as having a tendency toward particular learning styles. We seek to understand better the learning styles of general surgery residents and differences that may exist within the population. METHODS: The Kolb Learning Style Inventory was administered yearly to general surgery residents at the University of Cincinnati from 1994 to 2006. This tool allows characterization of learning styles into 4 groups: converging, accommodating, assimilating, and diverging. The converging learning style involves education by actively solving problems. The accommodating learning style uses emotion and interpersonal relationships. The assimilating learning style learns by abstract logic. The diverging learning style learns best by observation. Chi-square analysis and analysis of variance were performed to determine significance. RESULTS: Surveys from 1994 to 2006 (91 residents, 325 responses) were analyzed. The prevalent learning style was converging (185, 57%), followed by assimilating (58, 18%), accommodating (44, 14%), and diverging (38, 12%). At the PGY 1 and 2 levels, male and female residents differed in learning style, with the accommodating learning style being relatively more frequent in women and assimilating learning style more frequent in men (Table 1, p < or = 0.001, chi-square test). Interestingly, learning style did not seem to change with advancing PGY level within the program, which suggests that individual learning styles may be constant throughout residency training. If a resident's learning style changed, it tended to be to converging. In addition, no relation exists between learning style and participation in dedicated basic science training or performance on the ABSIT/SBSE. CONCLUSIONS: Our data suggests that learning style differs between male and female general surgery residents but not with PGY level or ABSIT/SBSE performance. A greater understanding of individual learning styles may allow more refinement and tailoring of surgical programs.

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The purpose of this study was to investigate the role of the fronto–striatal system for implicit task sequence learning. We tested performance of patients with compromised functioning of the fronto–striatal loops, that is, patients with Parkinson's disease and patients with lesions in the ventromedial or dorsolateral prefrontal cortex. We also tested amnesic patients with lesions either to the basal forebrain/orbitofrontal cortex or to thalamic/medio-temporal regions. We used a task sequence learning paradigm involving the presentation of a sequence of categorical binary-choice decision tasks. After several blocks of training, the sequence, hidden in the order of tasks, was replaced by a pseudo-random sequence. Learning (i.e., sensitivity to the ordering) was assessed by measuring whether this change disrupted performance. Although all the patients were able to perform the decision tasks quite easily, those with lesions to the fronto–striatal loops (i.e., patients with Parkinson's disease, with lesions in the ventromedial or dorsolateral prefrontal cortex and those amnesic patients with lesions to the basal forebrain/orbitofrontal cortex) did not show any evidence of implicit task sequence learning. In contrast, those amnesic patients with lesions to thalamic/medio-temporal regions showed intact sequence learning. Together, these results indicate that the integrity of the fronto–striatal system is a prerequisite for implicit task sequence learning.

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Experts working on behalf of international development organisations need better tools to assist land managers in developing countriesmaintain their livelihoods, as climate change puts pressure on the ecosystemservices that they depend upon. However, current understanding of livelihood vulnerability to climate change is based on a fractured and disparate set of theories andmethods. This reviewtherefore combines theoretical insights from sustainable livelihoods analysis with other analytical frameworks (including the ecosystem services framework, diffusion theory, social learning, adaptive management and transitions management) to assess the vulnerability of rural livelihoods to climate change. This integrated analytical framework helps diagnose vulnerability to climate change,whilst identifying and comparing adaptation options that could reduce vulnerability, following four broad steps: i) determine likely level of exposure to climate change, and how climate change might interact with existing stresses and other future drivers of change; ii) determine the sensitivity of stocks of capital assets and flows of ecosystem services to climate change; iii) identify factors influencing decisions to develop and/or adopt different adaptation strategies, based on innovation or the use/substitution of existing assets; and iv) identify and evaluate potential trade-offs between adaptation options. The paper concludes by identifying interdisciplinary research needs for assessing the vulnerability of livelihoods to climate change.

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There is empirical evidence showing that positive emotional and motivational factors in formal learning contexts decrease at the stage of young adolescence. According to Stage-Environment-Fit Theory and Self-Determination Theory, this change should be explained by a non-fulfilment of students' needs. By combining two different methods (questionnaires and day-to-day diaries) and applying a longitudinal design, this study aimed to explore the change in and the determinants of habitual and actual learning enjoyment. The sample consisted of 356 students. Quantitative results indicated that learning enjoyment and classroom practices decreased between Grades 6 and 7. Path analyses revealed that classroom practices are the source of students' learning enjoyment, while self-efficacy functions as a partial mediator. Data from students' diaries showed that a teacher's neglect of students' needs for competence and relatedness were significant sources of impeded learning enjoyment. Practical implications suggest the relevance of adjusting learning conditions to the needs of young adolescents in order to provide a facilitating basis for learning enjoyment.

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Throughout their history mountain communities have had to adapt to changing environmental and socio-economic conditions. They have developed strategies and specialized knowledge to sustain their livelihoods in a context of adverse climatic events and constant change. As negotiations and discussions on climate change emphasize the critical need for locally relevant and community owned adaptation strategies, there is a need for new tools to capitalize on this local knowledge and endogenous potential for innovation. The toolkit Promoting Local Innovation (PLI) was designed by the Centre for Development and Environment (CDE) of the University of Bern, Switzerland, to facilitate a participatory social learning process which identifies locally available innovations that can be implemented for community development. It is based on interactive pedagogy and joint learning among different stakeholders in the local context. The tried-and-tested tool was developed in the Andean region in 2004, and then used in International Union for Conservation of Nature (IUCN) climate change adaptation projects in Thailand, Burkina Faso, Senegal, and Chile. These experiences showed that PLI can be used to involve all relevant stakeholders in establishing strategies and actions needed for rural communities to adapt to climate change impacts, while building on local innovation potential and promoting local ownership

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This paper studies the relation between coalition structures in policy processes and policy change. While different factors such as policy images, learning processes, external events, or venue shopping are important to explain policy change, coalition structures within policy processes are often neglected. However, policy change happens as a result of negotiations and coordination among coalitions within policy processes. The paper analyzes how conflict, collaboration, and power relations among coalitions of actors influence policy change in an institutional context of a consensus democracy. Empirically, I rely on a Qualitative Comparative Analysis to conduct a cross-sector comparison of the 11 most important policy processes in Switzerland between 2001 and 2006. Coalition structures with low conflict and strong collaboration among coalitions as well as structures with dominant coalitions and weak collaboration both facilitate major policy change. Competing coalitions that are separated by strong conflict but still collaborate strongly produce policy outputs that are close to the status quo.