Learning Curves
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Learning Curves
Written by international contributors, Learning Curves: Theory, Models, and Applications first draws a learning map that shows where learning is involved within organizations, then examines how it can be sustained, perfected, and accelerated. The book reviews empirical findings in the literature in terms of different sources for learning and partia
Learning, Unlearning and Re-Learning Curves
Learning, Unlearning and Re-learning Curves (Volume IV of the Working Guides to Estimating & Forecasting series) focuses in on Learning Curves, and the various tried and tested models of Wright, Crawford, DeJong, Towill-Bevis and others. It explores the differences and similarities between the various models and examines the key properties that Estimators and Forecasters can exploit. A discussion about Learning Curve Cost Drivers leads to the consideration of a little used but very powerful technique of Learning Curve modelling called Segmentation, which looks at an organisation’s complex learning curve as the product of multiple shallower learning curves. Perhaps the biggest benefit is that it simplifies the calculations in Microsoft Excel where there is a change in the rate of learning observed or expected. The same technique can be used to model and calibrate discontinuities in the learning process that result in setbacks and uplifts in time or cost. This technique is compared with other, better known techniques such as Anderlohr’s. Equivalent Unit Learning is another, relative new technique that can be used alongside traditional completed unit learning to give an early warning of changes in the rates of learning. Finally, a Learning Curve can be exploited to estimate the penalty of collaborative working across multiple partners. Supported by a wealth of figures and tables, this is a valuable resource for estimators, engineers, accountants, project risk specialists, as well as students of cost engineering.
HUMAN LEARNING: From Learning Curves to Learning Organizations
Author: Ezey M. Dar-El
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-03-14
Learning plays a fundamental role in the production planning and growth of all organizations. With the need for more rapid changes in the global economy, the management of organizational change is a key factor in sustaining competitiveness in today's economy. This book has been developed with these `learning needs' in mind. Human Learning:From Learning Curves to Learning Organizations covers a broad range of learning models and related topics beginning with learning curves to recent research on learning organizations. The book's focus is to enable researchers and practitioners to forecast any organization's `learning needs' using the prediction aspects of an array of learning models. The book includes research and application discussions on topics such as accounting for previous experience; the `learning-forgetting-relearning' phenomenon; parameter estimation with no previous experience; DeJong's incompressibility model; predictive learning models requiring only two learning parameters; long learning cycle times; the speed-error relationship; evaluating the cost of learning from the point of view of safety; and an examination of Learning Organizations. Each chapter is developed from published research and worked examples are used throughout.