845 resultados para How Finns learn mathematics and science


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The U.S. Geological Survey (USGS) is committed to providing the Nation with credible scientific information that helps to enhance and protect the overall quality of life and that facilitates effective management of water, biological, energy, and mineral resources (http://www.usgs.gov/). Information on the Nation’s water resources is critical to ensuring long-term availability of water that is safe for drinking and recreation and is suitable for industry, irrigation, and fish and wildlife. Population growth and increasing demands for water make the availability of that water, now measured in terms of quantity and quality, even more essential to the long-term sustainability of our communities and ecosystems. The USGS implemented the National Water-Quality Assessment (NAWQA) Program in 1991 to support national, regional, State, and local information needs and decisions related to water-quality management and policy (http://water.usgs.gov/nawqa). The NAWQA Program is designed to answer: What is the condition of our Nation’s streams and ground water? How are conditions changing over time? How do natural features and human activities affect the quality of streams and ground water, and where are those effects most pronounced? By combining information on water chemistry, physical characteristics, stream habitat, and aquatic life, the NAWQA Program aims to provide science-based insights for current and emerging water issues and priorities. From 1991-2001, the NAWQA Program completed interdisciplinary assessments and established a baseline understanding of water-quality conditions in 51 of the Nation’s river basins and aquifers, referred to as Study Units (http://water.usgs.gov/nawqa/studyu.html).

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This action research study of twenty students in my sixth grade mathematics classroom examines the implementation of summarization strategies. Students were taught how to summarize concepts and how to explain their thinking in different ways to the teacher and their peers. Through analysis of students’ summaries of concepts from lessons that I taught, tests scores, and student journals and interviews, I discovered that summarizing mathematical concepts offers students an engaging opportunity to better understand those concepts and render that understanding more visible to the teacher. This analysis suggests that non-traditional summarization, such as verbal and written strategies, and strategies involving movement and discussions, can be useful in mathematics classrooms to improve student understanding, engagement in learning tasks, and as a form of formative assessment.

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In this action research study of my fifth grade high-ability mathematics class, I investigated student attitudes of mathematics and their confidence in mathematics. Student achievement was compared to two different confidence scales to identify a relationship between confidence and achievement. Six boys and eleven girls gave their consent to the study. I discovered there seems to be a connection between confidence and achievement and that boys are generally more confident than girls. Most students liked math and were comfortable sharing answers and methods of solving problems with other students. As a result of this study I plan to use my survey and interview questions at the beginning of the school year with my new class in order to assess their attitudes and confidence in math. I can use this information to identify potential struggles and better plan for student instruction.

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In this action research study of a district’s mathematics teachers, the researcher investigated how teachers interact with other teachers in their building and throughout the district. The researcher wanted to know how deeply teachers thought about teaching mathematics, and if they use other teachers in the district as a resource to help with unknown math problems. The researcher discovered that some teachers are willing to interact with others, but would like to have time supplied to them during the school year’s staff development meetings. The teachers involved were able to observe each other teaching and take valuable strategies back to their own classrooms. As a result of this research, the researcher would like to see this study continued next year during staff development time. The support of the district and staff development are key to the success of this study.

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Although praised for their rationality, humans often make poor decisions, even in simple situations. In the repeated binary choice experiment, an individual has to choose repeatedly between the same two alternatives, where a reward is assigned to one of them with fixed probability. The optimal strategy is to perseverate with choosing the alternative with the best expected return. Whereas many species perseverate, humans tend to match the frequencies of their choices to the frequencies of the alternatives, a sub-optimal strategy known as probability matching. Our goal was to find the primary cognitive constraints under which a set of simple evolutionary rules can lead to such contrasting behaviors. We simulated the evolution of artificial populations, wherein the fitness of each animat (artificial animal) depended on its ability to predict the next element of a sequence made up of a repeating binary string of varying size. When the string was short relative to the animats' neural capacity, they could learn it and correctly predict the next element of the sequence. When it was long, they could not learn it, turning to the next best option: to perseverate. Animats from the last generation then performed the task of predicting the next element of a non-periodical binary sequence. We found that, whereas animats with smaller neural capacity kept perseverating with the best alternative as before, animats with larger neural capacity, which had previously been able to learn the pattern of repeating strings, adopted probability matching, being outperformed by the perseverating animats. Our results demonstrate how the ability to make predictions in an environment endowed with regular patterns may lead to probability matching under less structured conditions. They point to probability matching as a likely by-product of adaptive cognitive strategies that were crucial in human evolution, but may lead to sub-optimal performances in other environments.

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We present the results of an operational use of experimentally measured optical tomograms to determine state characteristics (purity) avoiding any reconstruction of quasiprobabilities. We also develop a natural way how to estimate the errors (including both statistical and systematic ones) by an analysis of the experimental data themselves. Precision of the experiment can be increased by postselecting the data with minimal (systematic) errors. We demonstrate those techniques by considering coherent and photon-added coherent states measured via the time-domain improved homodyne detection. The operational use and precision of the data allowed us to check purity-dependent uncertainty relations and uncertainty relations for Shannon and Renyi entropies.

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This work reports the investigation on the structural differences between InAs quantum rings and their precursor quantum dots species as well as on the presence of piezoelectric fields and asymmetries in these nanostructures. The experimental results show significant reduction in the ring dimensions when the sizes of capped and uncapped ring and dot samples are compared. The iso-lattice parameter mapped by grazing-incidence x-ray diffraction has revealed the lateral extent of strained regions in the buried rings. A comparison between strain and composition of dot and ring structures allows inferring on how the ring formation and its final configuration may affect optical response parameters. Based on the experimental observations, a discussion has been introduced on the effective potential profile to emulate theoretically the ring-shape confinement. The effects of confinement and strain field modulation on electron and hole band structures are simulated by a multiband k.p calculation. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4733964]

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An operational method, already employed to formulate a generalization of the Ramanujan master theorem, is applied to the evaluation of integrals of various types. This technique provides a very flexible and powerful tool yielding new results encompassing different aspects of the special function theory. Crown Copyright (C) 2012 Published by Elsevier Inc. All rights reserved.

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In this paper we introduce a new class of abstract integral equations which enables us to study in a unified manner several different types of differential equations. (C) 2012 Elsevier Inc. All rights reserved.

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Interactive theorem provers (ITP for short) are tools whose final aim is to certify proofs written by human beings. To reach that objective they have to fill the gap between the high level language used by humans for communicating and reasoning about mathematics and the lower level language that a machine is able to “understandand process. The user perceives this gap in terms of missing features or inefficiencies. The developer tries to accommodate the user requests without increasing the already high complexity of these applications. We believe that satisfactory solutions can only come from a strong synergy between users and developers. We devoted most part of our PHD designing and developing the Matita interactive theorem prover. The software was born in the computer science department of the University of Bologna as the result of composing together all the technologies developed by the HELM team (to which we belong) for the MoWGLI project. The MoWGLI project aimed at giving accessibility through the web to the libraries of formalised mathematics of various interactive theorem provers, taking Coq as the main test case. The motivations for giving life to a new ITP are: • study the architecture of these tools, with the aim of understanding the source of their complexity • exploit such a knowledge to experiment new solutions that, for backward compatibility reasons, would be hard (if not impossible) to test on a widely used system like Coq. Matita is based on the Curry-Howard isomorphism, adopting the Calculus of Inductive Constructions (CIC) as its logical foundation. Proof objects are thus, at some extent, compatible with the ones produced with the Coq ITP, that is itself able to import and process the ones generated using Matita. Although the systems have a lot in common, they share no code at all, and even most of the algorithmic solutions are different. The thesis is composed of two parts where we respectively describe our experience as a user and a developer of interactive provers. In particular, the first part is based on two different formalisation experiences: • our internship in the Mathematical Components team (INRIA), that is formalising the finite group theory required to attack the Feit Thompson Theorem. To tackle this result, giving an effective classification of finite groups of odd order, the team adopts the SSReflect Coq extension, developed by Georges Gonthier for the proof of the four colours theorem. • our collaboration at the D.A.M.A. Project, whose goal is the formalisation of abstract measure theory in Matita leading to a constructive proof of Lebesgue’s Dominated Convergence Theorem. The most notable issues we faced, analysed in this part of the thesis, are the following: the difficulties arising when using “black box” automation in large formalisations; the impossibility for a user (especially a newcomer) to master the context of a library of already formalised results; the uncomfortable big step execution of proof commands historically adopted in ITPs; the difficult encoding of mathematical structures with a notion of inheritance in a type theory without subtyping like CIC. In the second part of the manuscript many of these issues will be analysed with the looking glasses of an ITP developer, describing the solutions we adopted in the implementation of Matita to solve these problems: integrated searching facilities to assist the user in handling large libraries of formalised results; a small step execution semantic for proof commands; a flexible implementation of coercive subtyping allowing multiple inheritance with shared substructures; automatic tactics, integrated with the searching facilities, that generates proof commands (and not only proof objects, usually kept hidden to the user) one of which specifically designed to be user driven.

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[EN]A new algorithm for evaluating the top event probability of large fault trees (FTs) is presented. This algorithm does not require any previous qualitative analysis of the FT. Indeed, its efficiency is independent of the FT logic, and it only depends on the number n of basic system components and on their failure probabilities. Our method provides exact lower and upper bounds on the top event probability by using new properties of the intrinsic order relation between binary strings. The intrinsic order enables one to select binary n-tuples with large occurrence probabilities without necessity to evaluate them. This drastically reduces the complexity of the problem from exponential (2n binary n-tuples) to linear (n Boolean variables)...

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The subject of this work concerns the study of the immigration phenomenon, with emphasis on the aspects related to the integration of an immigrant population in a hosting one. Aim of this work is to show the forecasting ability of a recent finding where the behavior of integration quantifiers was analyzed and investigated with a mathematical model of statistical physics origins (a generalization of the monomer dimer model). After providing a detailed literature review of the model, we show that not only such a model is able to identify the social mechanism that drives a particular integration process, but it also provides correct forecast. The research reported here proves that the proposed model of integration and its forecast framework are simple and effective tools to reduce uncertainties about how integration phenomena emerge and how they are likely to develop in response to increased migration levels in the future.

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Die Frage wie großmotorische Bewegungen gelernt werden beschäftigt nicht nur Sportler, Trainer und Sportlehrer sondern auch Ärzte und Physiotherapeuten. Die sportwissenschaftlichen Teildisziplinen Bewegungs- und Trainingswissenschaft versuchen diese Frage sowohl im Sinne der Grundlagenforschung (Wie funktioniert Bewegungslernen?) als auch hinsichtlich der praktischen Konsequenzen (Wie lehrt man Bewegungen?) zu beantworten. Innerhalb dieser Themenfelder existieren Modelle, die Bewegungslernen als gezielte und extern unterstützte Ausbildung zentralnervöser Bewegungsprogramme verstehen und solche, die Lernen als Selbstorganisationsprozess interpretieren. Letzteren ist das Differenzielle Lernen und Lehren (Schöllhorn, 1999) zuzuordnen, das die Notwendigkeit betont, Bewegungen durch die Steigerung der Variationen während der Aneignungsphase zu lernen und zu lehren. Durch eine Vielzahl an Variationen, so die Modellannahme, findet der Lernende ohne externe Vorgaben selbstorganisiert ein individuelles situatives Optimum. Die vorliegende Arbeit untersucht, welchen Einfluss Variationen verschiedener Art und Größe auf die Lern- und Aneignungsleistung großmotorischer Bewegungen haben und in wie fern personenübergreifende Optima existieren. In zwei Experimenten wird der Einfluss von räumlichen (Bewegungsausführung, Bewegungsergebnis) und zeitlichen Variationen (zeitliche Verteilung der Trainingsreize) auf die Aneignungs- und Lernleistung großmotorischer sportlicher Bewegungen am Beispiel zweier technischer Grundfertigkeiten des Hallenhockeys untersucht. Die Ergebnisse der Experimente stützen die bisherige Befundlage zum Differenziellen Lernen und Lehren, wonach eine Zunahme an Variation in der Aneignungsphase zu größeren Aneignungs- und Lernleistungen führt. Zusätzlich wird die Annahme bestätigt, dass ein Zusammenhang von Variationsbereich und Lernrate in Form eines Optimaltrends vorliegt. Neu sind die Hinweise auf die Dynamik von motorischen Lernprozessen (Experiment 1). Hier scheinen individuelle Faktoren (z. B. die Lernbiografie) als auch die Phase im Lernprozess (Aneignung, Lernen) Einfluss zu haben auf den Umfang und die Struktur eines für die optimale Adaptation notwendigen Variationsbereichs. Darüber hinaus weisen die Befunde auf verschiedene Aneignungs- und Lerneffekte aufgrund alleiniger Variation der zeitlichen Verteilung bei ansonsten gleichen Trainingsreizen hin (Experiment 2). Für zukünftige Forschungsarbeiten zum Erlernen großmotorischer Bewegungen und für die sportliche Praxis dürfte es daher erkenntnisreich sein, die Historie der intrinsischen Dynamik der lernenden Systeme stärker zu berücksichtigen. Neben Fragestellungen für die Grundlagenforschung zum (Bewegungs-)Lernen ließen sich hieraus unmittelbar praxisrelevante Erkenntnisse darüber ableiten, wie Bewegungslernprozesse mittels verschiedener Variationsbereiche strukturiert und gesteuert werden könnten.

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Performanzunterschiede zwischen verschiedenen Autokratietypen wie Monarchien, Militär-, Ein-Parteien- und begrenzten Mehr-Parteien-Regimen sind bis auf wenige Ausnahmen bisher relativ unerforscht. Deshalb widmet sich diese Arbeit folgenden Forschungsfragen: Gibt es Performanzunterschiede zwischen verschiedenen Autokratietypen? Wenn ja, wie gestalten sich diese und wie lassen sie sich erklären? Auf Grundlage der Selektoratstheorie von Bueno de Mesquite et al. wird die Hypothese aufgestellt, dass die Performanz politischer Regime mit der Größe der Winning Coalition steigt. Da verschiedene Autokratietypen unterschiedlich große Winning Coalitions haben, wird angenommen, dass es deutliche Performanzunterschiede zwischen diesen Typen gibt. Als Performanzkriterien dienen in dieser Arbeit wirtschaftlicher Wohlstand, soziale Sicherheit und ökologische Nachhaltigkeit. Aus diesen drei Kriterien wird zusätzlich ein Indikator allgemeiner Performanz gebildet. Die empirische Untersuchung erfolgt mit den Daten des Quality-of-Governement-Datensatzes und erstreckt sich über 140 autokratische Länder im Zeitraum von 1972 bis 2010. Die Daten werden mittels Time-Series-Cross-Section-Regressionen analysiert. Die Ergebnisse der Analysen entsprechen nur teilweise den Erwartungen. Die Größe der Winning Coalition wirkt positiv auf die wirtschaftliche Wohlfahrt und die soziale Sicherheit und damit auch auf die allgemeine Performanz aus. Entgegen den Erwartungen sinkt die ökologische Performanz jedoch mit steigender Größe der Winning Coalition. Auch die Befunde bezüglich der Performanz verschiedener Autokratietypen entsprechen nicht den Erwartungen. So sind Ein-Parteien-Regime insgesamt leistungsfähiger als Mehr-Parteien-Regime, Militär-Regime und Monarchien. Militär-Regime sind leistungsfähiger als Monarchien und tendenziell auch als Mehr-Parteien-Regime.

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As environmental problems became more complex, policy and regulatory decisions become far more difficult to make. The use of science has become an important practice in the decision making process of many federal agencies. Many different types of scientific information are used to make decisions within the EPA, with computer models becoming especially important. Environmental models are used throughout the EPA in a variety of contexts and their predictive capacity has become highly valued in decision making. The main focus of this research is to examine the EPA’s Council for Regulatory Modeling (CREM) as a case study in addressing science issues, particularly models, in government agencies. Specifically, the goal was to answer the following questions: What is the history of the CREM and how can this information shed light on the process of science policy implementation? What were the goals of implementing the CREM? Were these goals reached and how have they changed? What have been the impediments that the CREM has faced and why did these impediments occur? The three main sources of information for this research came from observations during summer employment with the CREM, document review and supplemental interviews with CREM participants and other members of the modeling community. Examining a history of modeling at the EPA, as well as a history of the CREM, provides insight into the many challenges that are faced when implementing science policy and science policy programs. After examining the many impediments that the CREM has faced in implementing modeling policies, it was clear that the impediments fall into two separate categories, classic and paradoxical. The classic impediments include the more standard impediments to science policy implementation that might be found in any regulatory environment, such as lack of resources and changes in administration. Paradoxical impediments are cyclical in nature, with no clear solution, such as balancing top-down versus bottom-up initiatives and coping with differing perceptions. These impediments, when not properly addressed, severely hinder the ability for organizations to successfully implement science policy.