"This book provides a detailed description of the application of mathematical learning curve modeling to analyze the state of learning and memory in humans and animals. The purpose of the book is to enable the readers to apply the knowledge gained in their own research on learning and memory. The authors hope that the readers may achieve success in this field of knowledge, expand and advance mathematical modeling of the learning curve, and that this book may aid in this process. For this, the authors have developed their own mathematical model based on the systems theory and proved its advantage in relation to those previously proposed. The authors developed MS Windows application "Learning Curve Modeling Tool" to help the reader modeling the learning curve from raw learning data in the California Verbal Learning Test, the Rey Auditory Verbal Learning Test, and other similar memory tests. Moreover, the book describes in detail the Windows and Android application "Memory Monitoring Tool", developed by the authors, which is suited well for mathematical modeling of the learning curves. The application aims to reveal initial signs of memory impairment. Besides, the section APPENDIX A describes a Web application - "Learning curve simulator" - developed by the authors for helping readers to get started with practically modeling the learning curve and testing their memory. This application is included in the book. The book will be useful for undergraduate students, graduate students, advanced graduate students, and professors, especially for professors who work on learning in both humans and animals, and those interested in the memory of marijuana users, alcoholics, and those suffering from diabetes and multiple sclerosis, as well as other neurological and psychological diseases and their neurological complications including those after COVID-19"--

The application of mathematical models in the analysis of learning data has a rich tradition in experimental psychology. Such modeling is not only of scientific interest from psychophysiological point of view but very important from clinical point of view because memory impairment is a common symptom that is frequently diagnosed in elder people, persons after traumatic brain injury, patients with type 2 diabetes mellitus, Parkinson disease, multiple sclerosis, and other neurological and psychiatric diseases. Mild memory impairment might be one of the most important symptoms of a future Alzheimer's disease. Thus, early diagnosis of initial signs of memory impairment is of importance. The book offers the reader hands on practical experience using a mathematical model dveloped by the senior authors. Classroom tested experiments are provided which requires the reader to use the model under various conditions such as learning and memory in both humans and animals. Following an introduction to mathematical models, the book contains 13 experiments. These experiments include those related to animal learning in such organisms as snails, bees, and rats. A variety of human experiments are also presented including those related to short and long term memory, maze learning, classical salivary conditioning, evaluation of sound on memory, and the influence of dietary supplements on memory. We close the section on experiments with and analysis of machine learning curves. Appendices are provided on how to build apparatus and how to install the software.

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

This volume documents on-going research and theorising in the sub-field of mathematics education devoted to the teaching and learning of mathematical modelling and applications. Mathematical modelling provides a way of conceiving and resolving problems in the life world of people whether these range from the everyday individual numeracy level to sophisticated new problems for society at large. Mathematical modelling and real world applications are considered as having potential for multi-disciplinary work that involves knowledge from a variety of communities of practice such as those in different workplaces (e.g., those of educators, designers, construction engineers, museum curators) and in different fields of academic endeavour (e.g., history, archaeology, mathematics, economics). From an educational perspective, researching the development of competency in real world modelling involves research situated in crossing the boundaries between being a student engaged in modelling or mathematical application to real word tasks in the classroom, being a teacher of mathematical modelling (in or outside the classroom or bridging both), and being a modeller of the world outside the classroom. This is the focus of many of the authors of the chapters in this book. All authors of this volume are members of the International Community of Teachers of Mathematical Modelling (ICTMA), the peak research body into researching the teaching and learning of mathematical modelling at all levels of education from the early years to tertiary education as well as in the workplace.

Learning curves are now recognized throughout the business community as valuable aids to improving productivity in the workplace. This volume is a clear and concise handbook intended to provide both the technical and the non-technical reader with a basic understanding of the underlying theory of learning curves, as well as ready access to commonly used learning curve models, formulas, and tables. Since the book itself is meant to be a handy reference guide, it is organized to make needed information easily available. After a review of basic learning curve theory and a comparison of the most frequently used models, an extensive list of equations is accompanied by everyday examples that illustrate the correct application of learning curve theory as well as solutions to problems that may arise. Tables, graphs, and charts, easily located in the appendixes, can facilitate computations, and a bibliography lists articles, pamphlets, and books that describe learning curve theory and its various uses over the past fifty years. Learning curve analysis, simplified and presented here in a convenient manual, will enable accounting, financial, and purchasing specialists to improve not only employee proficiency forecasting, but also the efficiency of their own productivity.

Project Report from the year 2017 in the subject Engineering - General, , language: English, abstract: There exist some fields in which the learning curves can be applied; they have a much wider applications including manufacturing and marketing strategy. However, they underlay the concept of continuous improvement, pricing decisions, work scheduling, standard setting, direct labour budget etc. Learning curve states that decreasing man hours are required to accomplish any repetitive task as the operation is continued; then knowledge of learning curve can be useful both in planning and control. Estimates of learning curves are used in many applications in organizations and they can be effective with the job which is repetitive in nature particulars with same machinery and tools; thus this study aims at improving the application of the learning curve which describes how knowledge is acquired and retained when people repeat a process. The overall purpose of this report is to determine whether or not the learning curve theory can be replicated. Data will be gathered based on the England flyer folding instructions; thereafter we will be plotting the learning curve by calculating the cumulative average, estimating the table of unit improvement curves and determining the learning rate. When a new product or process is started, performance of worker is not at its best and learning phenomenon takes place. As the experience is gained, the performance of worker improves, time taken per unit reduces; and then his productivity goes up. Thus, people who learn always increase their experience, they gain skill and ability from their own experience and the results throughout processes are improved. The usual use of learning curves is to estimate the labor hours and thereby much of the cost, of a manufactured good that is built in significant quantities.

operations research and management science