753 resultados para Knowledge of mathematics learning


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Se reportan avances de una investigación que se interesa por determinar las características del conocimiento matemático para la enseñanza del concepto de límite al infinito de una función que pone en acción el profesor en la planificación del tópico. El estudio se fundamenta en el modelo Conocimiento Matemático para la Enseñanza (MKT). En el estudio participan dos profesores de matemáticas de España y uno de México. Los datos se obtienen mediante una entrevista semiestructurada que involucró aspectos sobre los datos personales, el aula de clases, la planificación del profesor y del investigador sobre el tópico. El análisis de los daros se realiza en tres fases: generación de las unidades de análisis, agrupamiento en categorías de dichas unidades y determinación de las características del conocimiento del profesor. Los resultados evidencian que el profesor pone en acción los subdominios del MKT cuando planifica la enseñanza del concepto de límite al infinito de una función.

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Teacher training processes, initial and continuing, and professional practice of teachers who teach Mathematics in the early years are highlighted in the literature as complex, but also are regarded as the way to overcome many difficulties in teaching this component curriculum in the school stage in question. The aim of the study was to investigate how the training needs in Mathematics are represented by a group of teachers in the early years of elementary school of public health system of the city of Uberlândia, State of Minas Gerais. The research, qualitative approach, had as object of study the training needs, in Mathematics, of teachers in the early years. The research involved 16 teachers from two schools in the municipal public schools of that city. Data were collected through questionnaires, non-participant observations, semi-structured interviews followed by group and individual. Analyses were performed by means of thematic categories, founded by content analysis. Data interpretation allowed to understand training needs in mathematics that are presented to the collaborating group from their professional practice, considering the knowledge and skills necessary to teaching. It is understood that the teachers of the study group have major limitations in relation to the specific content and didactic knowledge of Mathematics content, however, the concern is that demonstrated not always being aware of it. Moreover, the difficulties experienced in teaching practice proven to be overcome by sources and non-formal training activities, primarily through more experienced colleagues in the profession. Thus, it becomes difficult to think the initial and continuing training courses for teachers without the training needs of the teaching practice is appreciated as an object of study.

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Relatório de Estágio apresentado à Escola Superior de Educação do Instituto Politécnico de Castelo Branco para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Educação Pré-Escolar e Ensino do Primeiro Ciclo do Ensino Básico.

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A década de 90 inscreveu as organizações num novo cenário caracterizado pelo aparecimento da denominada nova economia. Outros desafios se colocaram e a luta pela sobrevivência tornou- se uma constante diária para as empresas que operam em actividades altamente competitivas. O presente artigo visa analisar este contexto. Discutem-se as novas preocupações e problemáticas, designadamente as novas competências-chave, a moldagem de futuros competitivos, onde o conhecimento e a aprendizagem são as principais armas de diferenciação entre as organizações. Consequentemente, a informação, a capacidade de absorção e adaptação incessantes e o fascínio pela inovação fazem o diferencial competitivo de algumas empresas centenárias.

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ICEMST 2014 INTERNATIONAL CONFERENCE ON EDUCATION IN MATHEMATICS, SCIENCE & TECHNOLOGY PROCEEDING BOOK (pp.865-869). Disponível em http://www.2014.icemst.com/

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Paper presented at the 8th European Conference on Knowledge Management, Barcelona, 6-7 Sep. 2008 URL: http://www.academic-conferences.org/eckm/eckm2007/eckm07-home.htm

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Paper presented at the 8th European Conference on Knowledge Management, Barcelona, 6-7 Sep. 2008 URL: http://www.academic-conferences.org/eckm/eckm2007/eckm07-home.htm

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This chapter appears in Encyclopaedia of Distance Learning 2nd Edition edit by Rogers, P.; Berg, Gary; Boettecher, Judith V.; Howard, Caroline; Justice, Lorraine; Schenk, Karen D.. Copyright 2009, IGI Global, www.igi-global.com. Posted by permission of the publisher. URL: http://www.igi-global.com/reference/ details.asp?ID=9703&v=tableOfContents

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This research attempted to address the question of the role of explicit algorithms and episodic contexts in the acquisition of computational procedures for regrouping in subtraction. Three groups of students having difficulty learning to subtract with regrouping were taught procedures for doing so through either an explicit algorithm, an episodic content or an examples approach. It was hypothesized that the use of an explicit algorithm represented in a flow chart format would facilitate the acquisition and retention of specific procedural steps relative to the other two conditions. On the other hand, the use of paragraph stories to create episodic content was expected to facilitate the retrieval of algorithms, particularly in a mixed presentation format. The subjects were tested on similar, near, and far transfer questions over a four-day period. Near and far transfer algorithms were also introduced on Day Two. The results suggested that both explicit and episodic context facilitate performance on questions requiring subtraction with regrouping. However, the differential effects of these two approaches on near and far transfer questions were not as easy to identify. Explicit algorithms may facilitate the acquisition of specific procedural steps while at the same time inhibiting the application of such steps to transfer questions. Similarly, the value of episodic context in cuing the retrieval of an algorithm may be limited by the ability of a subject to identify and classify a new question as an exemplar of a particular episodically deflned problem type or category. The implications of these findings in relation to the procedures employed in the teaching of Mathematics to students with learning problems are discussed in detail.

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Learning Disability (LD) is a general term that describes specific kinds of learning problems. It is a neurological condition that affects a child's brain and impairs his ability to carry out one or many specific tasks. The learning disabled children are neither slow nor mentally retarded. This disorder can make it problematic for a child to learn as quickly or in the same way as some child who isn't affected by a learning disability. An affected child can have normal or above average intelligence. They may have difficulty paying attention, with reading or letter recognition, or with mathematics. It does not mean that children who have learning disabilities are less intelligent. In fact, many children who have learning disabilities are more intelligent than an average child. Learning disabilities vary from child to child. One child with LD may not have the same kind of learning problems as another child with LD. There is no cure for learning disabilities and they are life-long. However, children with LD can be high achievers and can be taught ways to get around the learning disability. In this research work, data mining using machine learning techniques are used to analyze the symptoms of LD, establish interrelationships between them and evaluate the relative importance of these symptoms. To increase the diagnostic accuracy of learning disability prediction, a knowledge based tool based on statistical machine learning or data mining techniques, with high accuracy,according to the knowledge obtained from the clinical information, is proposed. The basic idea of the developed knowledge based tool is to increase the accuracy of the learning disability assessment and reduce the time used for the same. Different statistical machine learning techniques in data mining are used in the study. Identifying the important parameters of LD prediction using the data mining techniques, identifying the hidden relationship between the symptoms of LD and estimating the relative significance of each symptoms of LD are also the parts of the objectives of this research work. The developed tool has many advantages compared to the traditional methods of using check lists in determination of learning disabilities. For improving the performance of various classifiers, we developed some preprocessing methods for the LD prediction system. A new system based on fuzzy and rough set models are also developed for LD prediction. Here also the importance of pre-processing is studied. A Graphical User Interface (GUI) is designed for developing an integrated knowledge based tool for prediction of LD as well as its degree. The designed tool stores the details of the children in the student database and retrieves their LD report as and when required. The present study undoubtedly proves the effectiveness of the tool developed based on various machine learning techniques. It also identifies the important parameters of LD and accurately predicts the learning disability in school age children. This thesis makes several major contributions in technical, general and social areas. The results are found very beneficial to the parents, teachers and the institutions. They are able to diagnose the child’s problem at an early stage and can go for the proper treatments/counseling at the correct time so as to avoid the academic and social losses.

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Sociable robots are embodied agents that are part of a heterogeneous society of robots and humans. They Should be able to recognize human beings and each other, and to engage in social, interactions. The use of a robotic architecture may strongly reduce the time and effort required to construct a sociable robot. Such architecture must have structures and mechanisms to allow social interaction. behavior control and learning from environment. Learning processes described oil Science of Behavior Analysis may lead to the development of promising methods and Structures for constructing robots able to behave socially and learn through interactions from the environment by a process of contingency learning. In this paper, we present a robotic architecture inspired from Behavior Analysis. Methods and structures of the proposed architecture, including a hybrid knowledge representation. are presented and discussed. The architecture has been evaluated in the context of a nontrivial real problem: the learning of the shared attention, employing an interactive robotic head. The learning capabilities of this architecture have been analyzed by observing the robot interacting with the human and the environment. The obtained results show that the robotic architecture is able to produce appropriate behavior and to learn from social interaction. (C) 2009 Elsevier Inc. All rights reserved.

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Based on a review of literature of conceptual and procedural knowledge in relation to intrinsic and extrinsic motivation, the purpose of this study was to test the relationship between conceptual and procedural knowledge and intrinsic and extrinsic motivation. Thirty-eight education students with a mathematics focus (elementary or secondary) in their junior, senior, or fifth year completed a survey with a Likert scale measuring their preference to learning (conceptual or procedural) and their motivation type (intrinsic or extrinsic). Findings showed that secondary mathematics focused students were more likely to prefer learning mathematics conceptually than elementary mathematics focused students. However, secondary and elementary mathematics focused students showed an equal preference for learning mathematics procedurally and sequentially. Elementary and secondary students reported similar intrinsic and extrinsic motivation. Extrinsically motivated students preferred procedural learning more than conceptual learning. While there was no statistically significant preference with intrinsically motivated students, there was a trend favoring preference of conceptual learning over procedural learning. These results tend to support the hypothesis that mathematics focused students who prefer conceptual learning are more intrinsically motivated, and mathematics focused students who prefer procedural learning are more extrinsically motivated.

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Another ed. of v. 1, containing only the articles of De Morgan and Parker, was issued in 1836.

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This article considers the question of what specific actions a teacher might take to create a culture of inquiry in a secondary school mathematics classroom. Sociocultural theories of learning provide the framework for examining teaching and learning practices in a single classroom over a two-year period. The notion of the zone of proximal development (ZPD) is invoked as a fundamental framework for explaining learning as increasing participation in a community of practice characterized by mathematical inquiry. The analysis draws on classroom observation and interviews with students and the teacher to show how the teacher established norms and practices that emphasized mathematical sense-making and justification of ideas and arguments and to illustrate the learning practices that students developed in response to these expectations.

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This article presents the principal results of the doctoral thesis “Semantic-oriented Architecture and Models for Personalized and Adaptive Access to the Knowledge in Multimedia Digital Library” by Desislava Ivanova Paneva-Marinova (Institute of Mathematics and Informatics), successfully defended before the Specialised Academic Council for Informatics and Mathematical Modelling on 27 October, 2008.