950 resultados para Graphics calculators


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Previous research on computers and graphics calculators in mathematics education has examined effects on curriculum content and students’ mathematical achievement and attitudes while less attention has been given to the relationship between technology use and issues of pedagogy, in particular the impact on teachers’ professional learning in specific classroom and school environments. This observation is critical in the current context of educational policy making, where it is assumed – often incorrectly – that supplying schools with hardware and software will increase teachers’ use of technology and encourage more innovative teaching approaches. This paper reports on a research program that aimed to develop better understanding of how and under what conditions Australian secondary school mathematics teachers learn to effectively integrate technology into their practice. The research adapted Valsiner’s concepts of the Zone of Proximal Development, Zone of Free Movement and Zone of Promoted Action to devise a theoretical framework for analysing relationships between factors influencing teachers’ use of technology in mathematics classrooms. This paper illustrates how the framework may be used by analysing case studies of a novice teacher and an experienced teacher in different school settings.

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This paper reports on the early stages of a three year study that is investigating the impact of a technology-enriched teacher education program on beginning teachers' integration of computers, graphics calculators, and the internet into secondary school mathematics classrooms. Whereas much of the existing research on the role of technology in mathematics learning has been concerned with effects on curriculum content or student learning, less attention has been given to the relationship between technology use and issues of pedagogy, in particular the impact on teachers' professional learning in the context of specific classroom and school environments. Our research applies sociocultural theories of learning to consider how beginning teachers are initiated into a collaborative professional community featuring both web-based and face to face interaction, and how participation in such a community shapes their pedagogical beliefs and practices. The aim of this paper is to analyse processes through which the emerging community was established and sustained during the first year of the study. We examine features of this community in terms of identity formation, shifts in values and beliefs, and interaction patterns revealed in bulletin board discussion between students and lecturers.

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Este estudo teve como objectivo compreender o desenvolvimento de tarefas de modelação, por parte de uma professora de Matemática e de uma professora de Física­ Química, no âmbito de trabalho colaborativo. Para tal foram formuladas três questões orientadoras: 1. Como é que os professores seleccionam e preparam as tarefas de modelação a colocar aos alunos em situação de sala de aula? Que características das tarefas de modelação se mostram fundamentais para a sua selecção? 2. como desenvolvem os professores as tarefas de modelação na sala de aula? Como gerem e dinamizam as aulas onde colocam tarefas de modelação aos alunos? Que papel reservam ao professor e ao aluno? 3. como exploram os professores as potencialidades das calculadoras gráficas no desenvolvimento das tarefas de modelação? Que questões se colocam à utilização de sensores? O estudo decorreu numa escola secundária, durante o ano lectivo de 2005/06, sob proposta e com a participação da investigadora, envolvendo uma professora de Matemática e uma professora de Física-Química de uma mesma turma de 100 ano. O grupo colaborativo reuniu regularmente e preparou e leccionou aulas com tarefas de modelação matemática, recorrendo a calculadoras gráficas e sensores, tarefas e tecnologias novas para ambas as professoras. A metodologia utilizada na investigação tem natureza qualitativa, tendo sido realizadas duas entrevistas longas a cada professora, uma no início e outra no fim do estudo, bem como entrevistas de curta duração às professoras após cada uma das aulas onde foram desenvolvidas as tarefas. Foram também recolhidos registos das sessões colectivas de trabalho e elaborado um "diário de bordo". O estudo permitiu formular as seguintes conclusões: - Quando as professoras seleccionavam as tarefas de modelação a propor aos seus alunos tinham em consideração o cumprimento dos programas, os conteúdos a abordar e a diversidade de questões que se podem formular sobre os mesmos e o interesse e significado da experiência para os alunos. - O tempo que é necessário para a preparação e execução das tarefas de modelação pareceu ser factor de grande peso na sua selecção. - O elevado número de alunos por turma pode ser factor um negativo para o desenvolvimento de tarefas de modelação na sala de aula. -Na opinião das professoras, o recurso à calculadora gráfica e aos sensores para realizar a recolha de dados relativos a uma tarefa de modelação tomou-as mais apelativas e ajudou os alunos a compreender a situação em causa assim como permitiu tomar mais nítida a relação entre a Matemática e a Física. ABSTRACT: This study aimed to understand the development of modelling tasks, by a Mathematics teacher and a Physics-Chemistry teacher, as part of collaborative work. For this study were formulated three guidelines: 1. How do teachers select and prepare the modelling tasks to present to the students in a classroom situation? What characteristics of these tasks are essential for their selection? 2. How do teachers develop the modelling tasks in the classroom? How do they manage and dynamize the classes where the modelling tasks took place? What role it's reserd to the teacher and the student? 3. How do teachers exploit the potential of graphics calculator in the development of the modelling tasks? What issues arise for the use of sensors? This study took place at a secundary school during the academic year 2005/06, as a suggestion and with the participation of the researcher, involving a Mathematics teacher and a Physics-Chemistry teacher of the same class (10th grade). The collaborative group had regular meetings and prepared and developed modellin tasks in the classroom using graphics calculator and sensors, which was a new activity for all the teachears. The methodology used has a qualitative nature. Two interviews were made to each teacher, one at baseline and another at the end of the study, fourteen work sections and three modelling tasks were explored in classroom context after which followed small interviews to the teacher that gave the class. ln addition records were also made in a small "log-book". This study allowed to reach the following conclusions: - When the teachers select the modelling tasks to offer its students they take into account the programs, the contents and the diversity of questions that can be made on it and the interest and significance of the experience for students. - The time needed for preparation and implementation of the modelling tasks is another factor of great weight in its selection. - The high number of student per class can be a negative factor for the development of modelling tasks in the classroom. Iii - ln the teacher’s opinion, the use of the graphics calculator and sensors to collect data on a modelling tasks makes its more attractive and helps students to understand the situation and makes clearer the link between Mathematics and Physics.

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Stipping, non-photorealistic rendering, non-photorealistic computer graphics

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Illustration Watermarks, Image annotation, Virtual data exploration, Interaction techniques

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Many multivariate methods that are apparently distinct can be linked by introducing oneor more parameters in their definition. Methods that can be linked in this way arecorrespondence analysis, unweighted or weighted logratio analysis (the latter alsoknown as "spectral mapping"), nonsymmetric correspondence analysis, principalcomponent analysis (with and without logarithmic transformation of the data) andmultidimensional scaling. In this presentation I will show how several of thesemethods, which are frequently used in compositional data analysis, may be linkedthrough parametrizations such as power transformations, linear transformations andconvex linear combinations. Since the methods of interest here all lead to visual mapsof data, a "movie" can be made where where the linking parameter is allowed to vary insmall steps: the results are recalculated "frame by frame" and one can see the smoothchange from one method to another. Several of these "movies" will be shown, giving adeeper insight into the similarities and differences between these methods

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Background In a previous study, the European Organisation for Research and Treatment of Cancer (EORTC) reported a scoring system to predict survival of patients with low-grade gliomas (LGGs). A major issue in the diagnosis of brain tumors is the lack of agreement among pathologists. New models in patients with LGGs diagnosed by central pathology review are needed. Methods Data from 339 EORTC patients with LGGs diagnosed by central pathology review were used to develop new prognostic models for progression-free survival (PFS) and overall survival (OS). Data from 450 patients with centrally diagnosed LGGs recruited into 2 large studies conducted by North American cooperative groups were used to validate the models. Results Both PFS and OS were negatively influenced by the presence of baseline neurological deficits, a shorter time since first symptoms (<30 wk), an astrocytic tumor type, and tumors larger than 5 cm in diameter. Early irradiation improved PFS but not OS. Three risk groups have been identified (low, intermediate, and high) and validated. Conclusions We have developed new prognostic models in a more homogeneous LGG population diagnosed by central pathology review. This population better fits with modern practice, where patients are enrolled in clinical trials based on central or panel pathology review. We could validate the models in a large, external, and independent dataset. The models can divide LGG patients into 3 risk groups and provide reliable individual survival predictions. Inclusion of other clinical and molecular factors might still improve models' predictions.

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Many multivariate methods that are apparently distinct can be linked by introducing oneor more parameters in their definition. Methods that can be linked in this way arecorrespondence analysis, unweighted or weighted logratio analysis (the latter alsoknown as "spectral mapping"), nonsymmetric correspondence analysis, principalcomponent analysis (with and without logarithmic transformation of the data) andmultidimensional scaling. In this presentation I will show how several of thesemethods, which are frequently used in compositional data analysis, may be linkedthrough parametrizations such as power transformations, linear transformations andconvex linear combinations. Since the methods of interest here all lead to visual mapsof data, a "movie" can be made where where the linking parameter is allowed to vary insmall steps: the results are recalculated "frame by frame" and one can see the smoothchange from one method to another. Several of these "movies" will be shown, giving adeeper insight into the similarities and differences between these methods.

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BACKGROUND: Prognostic models have been developed to predict survival of patients with newly diagnosed glioblastoma (GBM). To improve predictions, models should be updated with information at the recurrence. We performed a pooled analysis of European Organization for Research and Treatment of Cancer (EORTC) trials on recurrent glioblastoma to validate existing clinical prognostic factors, identify new markers, and derive new predictions for overall survival (OS) and progression free survival (PFS).¦METHODS: Data from 300 patients with recurrent GBM recruited in eight phase I or II trials conducted by the EORTC Brain Tumour Group were used to evaluate patient's age, sex, World Health Organisation (WHO) performance status (PS), presence of neurological deficits, disease history, use of steroids or anti-epileptics and disease characteristics to predict PFS and OS. Prognostic calculators were developed in patients initially treated by chemoradiation with temozolomide.¦RESULTS: Poor PS and more than one target lesion had a significant negative prognostic impact for both PFS and OS. Patients with large tumours measured by the maximum diameter of the largest lesion (⩾42mm) and treated with steroids at baseline had shorter OS. Tumours with predominant frontal location had better survival. Age and sex did not show independent prognostic values for PFS or OS.¦CONCLUSIONS: This analysis confirms performance status but not age as a major prognostic factor for PFS and OS in recurrent GBM. Patients with multiple and large lesions have an increased risk of death. With these data prognostic calculators with confidence intervals for both medians and fixed time probabilities of survival were derived.

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New emerging technologies in the recent decade have brought new options to cross platform computer graphics development. This master thesis took a look for cross platform 3D graphics development possibilities. All platform dependent and non real time solutions were excluded. WebGL and two different OpenGL based solutions were assessed via demo application by using most recent development tools. In the results pros and cons of the each solutions were noted.

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The purpose of this study was to determine the effect that calculators have on the attitudes and numerical problem-solving skills of primary students. The sample used for this research was one of convenience. The sample consisted of two grade 3 classes within the York Region District School Board. The students in the experimental group used calculators for this problem-solving unit. The students in the control group completed the same numerical problem-solving unit without the use of calculators. The pretest-posttest control group design was used for this study. All students involved in this study completed a computational pretest and an attitude pretest. At the end of the study, the students completed a computational posttest. Five students from the experimental group and five students from the control group received their posttests in the form of a taped interview. At the end of the unit, all students completed the attitude scale that they had received before the numerical problem-solving unit once again. Data for qualitative analysis included anecdotal observations, journal entries, and transcribed interviews. The constant comparative method was used to analyze the qualitative data. A t test was also performed on the data to determine whether there were changes in test and attitude scores between the control and experimental group. Overall, the findings of this study support the hypothesis that calculators improve the attitudes of primary students toward mathematics. Also, there is some evidence to suggest that calculators improve the computational skills of grade 3 students.