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1. |
Record Nr. |
UNINA9910464521703321 |
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Autore |
Cooper Hilary <1943, > |
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Titolo |
History in the early years / / Hilary Cooper |
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Pubbl/distr/stampa |
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London : , : Routledge, , 2013 |
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ISBN |
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1-138-17805-5 |
1-136-46690-8 |
1-315-01501-3 |
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Edizione |
[Second edition.] |
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Descrizione fisica |
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1 online resource (248 p.) |
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Collana |
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Teaching and learning in the first three years of school |
Teaching and learning in the early years |
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Disciplina |
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Soggetti |
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History - Study and teaching (Early childhood) |
History - Study and teaching (Elementary) |
History - Study and teaching (Preschool) |
Electronic books. |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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First published in 1995 by Routledge. |
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Nota di bibliografia |
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Includes bibliographical references (pages [221]-231) and index. |
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Nota di contenuto |
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Cover; Title Page; Copyright Page; Table of Contents; List of illustrations; Editor's preface; Acknowledgements; Introduction; Prologue; PART I An introduction to history: the Foundation Stage; 1 Understanding change over time; 2 Interpretations of the past; 3 Deductions and inferences from sources; PART II History during the first three years of school; 4 Teaching children to understand concepts of time and change; 5 Interpretations; 6 Deductions from sources; PART III Organisation, planning and assessment; 7 Long-term planning; 8 Planning a unit of study; PART IV Three case studies |
9 Case study 1: 'Toys and Games, Now and Then'10 Case study 2: year 1- 'Castles'; 11 Case study 3: year 2 - 'A class museum'; PART V In-service workshops; 12 In-service workshops: some examples; Resources referred to in the text; Bibliography; Index |
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Sommario/riassunto |
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History in the Early Years is an innovative and accessible guide to helping young children explore the past through their environment, family history and story. This fully revised edition includes guidance on introducing children to the past at the Foundation Stage in school and pre-school settings. Throughout it shows how the requirements of the |
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early years curriculum can be met in innovative ways, and is fully illustrated by case study examples of children's learning and also supported by recent research.The book will support both new and experienced early years practitioners in |
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2. |
Record Nr. |
UNINA9910957680403321 |
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Titolo |
Environmental modelling : new research / / Paul N. Findley, editor |
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Pubbl/distr/stampa |
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New York, : Nova Science Publishers, c2009 |
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ISBN |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (250 p.) |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Environmental sciences - Mathematical models |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Intro -- ENVIRONMENTAL MODELLING:NEW RESEARCH -- CONTENTS -- PREFACE -- EXPERT COMMENTARY -- ADVANCES IN SPACE-TIME TECHNOLOGY FORASSESSING HUMAN EXPOSURE TO ENVIRONMENTALCONTAMINANTS -- Abstract -- Introduction -- Space-Time Software Systems -- Space-Time Datasets for Exposure Assessment -- Example Applications of Space-Time Exposure Reconstruction -- Conclusion -- References -- RESEARCH AND REVIEW STUDIES -- BAYESIAN BELIEF NETWORKS IN ENVIRONMENTALMODELLING: A REVIEW OF RECENT PROGRESS -- Abstract -- Introduction -- Description of a BBN -- Literature Search Methods -- Domains -- Network Structure -- Obtaining Conditional Probabilities -- Model Testing -- Sensitivity Analysis -- Use of BBNs to Support Decision-Making -- Advantages of BBNs -- Limitations of BBNs -- Conclusions and Forward Look -- Acknowledgements -- References -- EOF REGRESSION ANALYTICAL MODELWITH APPLICATIONS TO THE RETRIEVALOF ATMOSPHERIC TEMPERATURE AND GASCONSTITUENTS CONCENTRATION FROM HIGHSPECTRAL RESOLUTION INFRAREDOBSERVATIONS -- Abstract -- 1. Introduction -- 2. Mathematical Theory -- 3. EOF Based Regression Algorithm -- 3.1. |
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Data and Parameters Space, Training Data Set and Basic Definitions -- 3.2. How Many Principal Components Do We Need to Extract? -- 3.3. The System of Regression Coefficients -- 3.3.1. Bias and Second Order Statistics of the Retrieval -- 3.3.2. Assessing the Vertical Spatial Resolution of the Retrieval, the Index iD -- 4. Implementation with Simulated Data and Assessment of theRetrieval Performance -- 4.1. More on "How Many Components doWe Need to Extract?" -- 4.2. Values of the Retrieval Interdependency Index, iD -- 5. Application to Real Observations -- 5.1. CAMEX/3 Experiment -- 5.2. EAQUATE Experiment -- 5.3. IASI Tropical Soundings -- 6. Conclusion -- Acknowledgment -- References. |
COMOVEMENT AND CYCLICAL PATTERNSOF SOUTHERN PINE BEETLE OUTBREAKS -- Abstract -- 1. Introduction -- 2. Methods and Data -- 2.1. Measuring Infestation Risk -- 2.2. Assessing Comovement -- 2.3. Assessing Cyclical Patterns -- 3. Results -- 3.1. Infestation Risk -- 3.2. Comovement -- 3.3. Cyclical Patterns -- 4. Concluding Remarks -- References -- TRENDS IN MODELLING OF RADIONUCLIDESUPTAKE BY PARTICULATE MATTER IN THE MARINEENVIRONMENT USING BOX MODELS -- Abstract -- I. Introduction -- II. Theory of Ion Exchange between Water and SuspendedParticles -- III. Development of Kinetic Box Models -- III.1. The One-Step Reversible Reaction -- II. Theory of Ion Exchange between Water and SuspendedParticles -- III. Development of Kinetic Box Models -- III.1. The One-Step Reversible Reaction -- III.2. The Two-Step Model -- III.3. The Three-Step Model -- IV. Applicability of Box Models -- Strontium -- Americium -- Plutonium -- V. Conclusion -- References -- SPATIAL DOWN-SCALING AS A TOOL TO IMPROVEMULTIFUNCTIONALITY INDICATORS IN ECONOMICMODELS -- Abstract -- 1. Introduction -- 2. Methods -- 2.1. The CAPRI Model1 -- 2.2. Regional Down-Scaling 3 -- 2.3. Meta-model of DNDC -- 2.3. Meta-model of DNDC -- 3. Indicators -- 4. Indicator Performance -- 5. Technical Solution -- 6. Conclusion -- Acknowledgements -- References -- ADAPTIVE CONTROL METHODOLOGY AND SOMEAPPLICATIONS IN ENVIRONMENTAL MODELLING -- Abstract -- 1. Introduction -- 2. Adaptive Control Methodology -- 2.1. The Methodology -- 2.2. Environmental Modelling with ACM -- 3. A Sustainability Case Study -- 3.1. Background -- 3.2. The Initial Policies in 'NOW - 5 years' -- 3.3. Monitoring 'NOW' the Initial Policies -- 3.4. Revisiting 'NOW' the Initial Policies -- 4. Conclusion -- References -- PREDICTION OF SEDIMENT SOURCE AREASWITHIN WATERSHEDS AS AFFECTED BY SOIL DATARESOLUTION -- Abstract -- Introduction. |
Description of SWAT -- STATSGO versus SSURGO -- Study Area within the Elm River Watershed -- Study Area within the Cowhouse Creek Watershed -- Model Set up -- Assessment Method -- Results and Discussion -- Calibrated Models -- Predicted Sediment -- Conclusions -- Acknowledgement -- References -- LANDSLIDE MODELING -- Abstract -- 1. Introduction -- 2. Landslide Mapping -- 3. Physically-Based Landslide Models -- 3.1. Factor of Safety (FS) -- 3.2. Critical Rainfall Model -- 4. Statistical Landslide Model -- 4.1. Bivariate Analysis -- 4.2. Multivariate Analysis -- 5. Model Validation -- 6. Examples of Landslide Models -- 6.1. A Critical Rainfall Model -- 6.2. A Certainty Factor Model -- 6.3. A Logistic Regression Model -- 7. Conclusion -- References -- SPATIAL MODELLING OF GROUNDWATERPOLLUTION USING A GIS -- Abstract -- Introduction -- Study Area -- Geology and Hydrogeology -- Materiel and Methods -- Sampling and Analysis -- GIS Approaches -- Multivariate Analysis -- Results -- 1. Physico-Chemical Parameters -- 2. Cation Chemistry -- 3. Anion Chemistry -- 4. Heavy Metals Distributions in Groundwater |
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Samples -- 5. Multivariate Analysis -- 6. GIS Analysis -- Conclusion -- References -- INDEX. |
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Sommario/riassunto |
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Environment models seek to re-create what occurs during some event in nature. It is much easier and practical to create computer models to run certain experiments than it is to go out and do the same experiment again and again. Computer models take equations which were usually formulated through testing under natural conditions, and put them into computer programs where they can be run quickly and easily. A model can then output the results of doing these equations into a form which can be output to a screen for the user to view. The aim is to improve the capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales. This new book presents the latest research from around the globe. |
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