28 resultados para Learning process of arithmetic

em Cambridge University Engineering Department Publications Database


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Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics, however, the representations can be engaged based on visual context, and are updated by a single-rate process.

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Today's fast-paced, dynamic environments mean that for organizations to keep "ahead of the game", engineering managers need to maximize current opportunities and avoid repeating past mistakes. This article describes the development study of a collaborative strategic management tool - the Experience Scan to capture past experience and apply learning from this to present and future situations. Experience Scan workshops were held in a number of different technology organizations, developing and refining the tool until its format stabilized. From participants' feedback, the workshop-based tool was judged to be a useful and efficient mechanism for communication and knowledge management, contributing to organizational learning.

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Abstract: Starting in the 1980s, household-level water treatment and safe storage systems (HWTS) have been developed as simple, local, user-friendly, and low cost options to improve drinking water quality at the point of use. However, despite conclusive evidence of the health and economic benefits of HWTS, and promotion efforts in over 50 countries in the past 20 years, implementation outcomes have been slow, reaching only 5-10 million regular users. This study attempts to understand the barriers and drivers affecting HWTS implementation. Although existing literature related to HWTS and innovation diffusion theories proposed ample critical factors and recommendations, there is a lack of holistic and systemic approach to integrate these findings. It is proposed that system dynamics modelling can be a promising tool to map the inter-relationships of different critical factors and to understand the structure of HWTS dissemination process, which may lead to identifying high impact, leveraged mitigation strategies to scale-up HWTS adoption and sustained use.