01468nam a2200313 i 4500991003736009707536 9788809859678b1437903x-39ule_instDip.to di Storia, Società e Studi sull'Uomoita372.4076153.93Cornoldi, Cesare437867Prove MT - Kit scuola classi 3-4-5 primaria :dalla valutazione degli apprendimenti di lettura e comprensione al potenziamento : prove di valutazione /Cesare Cornoldi, Giovanni Colpo, Barbara Carretti ; con la collaborazione di Maria Luisa Gola, Cosmiana Saponaro e Francesco ViolaFirenze :Giunti Edu,c2017155 p. :ill. ;30 cmLetturaApprendimentoValutazioneScuola elementareTest psicologiciColpo, Giovanniauthorhttp://id.loc.gov/vocabulary/relators/aut159779Carretti, Barbaraauthorhttp://id.loc.gov/vocabulary/relators/aut479929Gola, Maria LuisaSaponaro, CosmianaViola, Francesco.b1437903x07-01-2007-01-20991003736009707536LE023 372.407 COR 1 212023000179246le023pE30.00-l- 01010.i1591174307-01-20Prove MT - Kit scuola classi 3-4-5 primaria1751766UNISALENTOle023 - - ma -itait 0003647nam 22006135 450 991041609030332120250609111404.09783030473921303047392910.1007/978-3-030-47392-1(CKB)4100000011384180(MiAaPQ)EBC6296001(DE-He213)978-3-030-47392-1(MiAaPQ)EBC6295962(EXLCZ)99410000001138418020200810d2020 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierAdoption of Data Analytics in Higher Education Learning and Teaching /edited by Dirk Ifenthaler, David Gibson1st ed. 2020.Cham :Springer International Publishing :Imprint: Springer,2020.1 online resource (464 pages)Advances in Analytics for Learning and Teaching,2662-21309783030473914 3030473910 Part I. Theoretical Foundations and Frameworks -- Part II. Technological Infrastructure and Staff Requirements -- Part III. Institutional Governance and Policy Implementation -- Part IV. Case Studies.The book aims to advance global knowledge and practice in applying data science to transform higher education learning and teaching to improve personalization, access and effectiveness of education for all. Currently, higher education institutions and involved stakeholders can derive multiple benefits from educational data mining and learning analytics by using different data analytics strategies to produce summative, real-time, and predictive or prescriptive insights and recommendations. Educational data mining refers to the process of extracting useful information out of a large collection of complex educational datasets while learning analytics emphasizes insights and responses to real-time learning processes based on educational information from digital learning environments, administrative systems, and social platforms. This volume provides insight into the emerging paradigms, frameworks, methods and processes of managing change to better facilitate organizational transformation toward implementation of educational data mining and learning analytics. It features current research exploring the (a) theoretical foundation and empirical evidence of the adoption of learning analytics, (b) technological infrastructure and staff capabilities required, as well as (c) case studies that describe current practices and experiences in the use of data analytics in higher education.Advances in Analytics for Learning and Teaching,2662-2130Educational technologyLearning, Psychology ofEducation, HigherDigital Education and Educational TechnologyInstructional PsychologyHigher EducationEducational technology.Learning, Psychology of.Education, Higher.Digital Education and Educational Technology.Instructional Psychology.Higher Education.378.007378.007Ifenthaler Dirkedthttp://id.loc.gov/vocabulary/relators/edtGibson Davidedthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK9910416090303321Adoption of Data Analytics in Higher Education Learning and Teaching2057313UNINA05139nam 22007333u 450 991067988180332120230120010437.00-12-800000-71-60119-624-5(CKB)1000000000744548(EBL)1687326(OCoLC)880058183(SSID)ssj0000072601(PQKBManifestationID)11969652(PQKBTitleCode)TC0000072601(PQKBWorkID)10102756(PQKB)11723052(MiAaPQ)EBC1687326(EXLCZ)99100000000074454820140825d2013|||| u|| |engur|n|---|||||txtccrNatural Gas Measurement HandbookBurlington Elsevier Science20131 online resource (497 p.)Description based upon print version of record.1-306-77083-1 1-933762-00-4 Front Cover; Natural Gas Measurement Handbook; Copyright Page; Dedication; Table of Contents; List of Tables; List of Figures; Preface; Symbols; Unit Conversions; CHAPTER ONE. Introduction; 1.1 Transportation System; 1.2 Measurement; 1.3 Fluid Classification, Commercial; 1.4 Material Quality; 1.5 Risk Management; CHAPTER TWO. Composition and Quality; 2.1 Assay; 2.2 Quality Parameters and Tolerances; 2.3 Potential Impacts of Gas Quality; 2.4 Typical Streams; CHAPTER THREE. Physical Properties and Process Conditions; 3.1 Natural Gas; 3.2 Fluid Classification: Technical; 3.3 Phase Envelope3.4 Fluid Properties3.5 Process (or Operating) Conditions; 3.6 Typical Natural Gas Physical Properties; CHAPTER FOUR. Measurement Concepts; 4.1 Applicable Fluids; 4.2 Base Conditions; 4.3 Flowmeters (or Primary Devices); 4.4 Flowmeter Calibration Concepts; 4.5 Law of Similarity; 4.6 Single-Phase Fluid Flow in Pipes; 4.7 Multiphase Fluid Flow in Pipes; 4.8 Secondary Devices; 4.9 Tertiary Device; 4.10 Uncertainty; 4.11 Total Cost of Measurement; CHAPTER FIVE. Orifice Flowmeter; 5.1 General Principles; 5.2 Mass Flow Equation; 5.3 Artifact Calibration; 5.4 Uncertainty Roadmap5.5 Sources of Error5.6 Risk Management; CHAPTER SIX. Ultrasonic Flowmeter; 6.1 General Principles; 6.2 Mass Flow Equation; 6.3 Central Facility Calibration; 6.4 In Situ Calibration; 6.5 Uncertainty Roadmap; 6.6 Sources of Error; 6.7 Risk Management; CHAPTER SEVEN. Turbine Flowmeter; 7.1 General Principles; 7.2 Mass Flow Equation; 7.3 Central Facility Calibration; 7.4 In Situ Calibration; 7.5 Uncertainty Roadmap; 7.6 Sources of Error; 7.7 Risk Management; CHAPTER EIGHT. Rotary Displacement Flowmeter; 8.1 General Principles; 8.2 Mass Flow Equation; 8.3 Central Facility Calibration8.4 In Situ Calibration8.5 Uncertainty Roadmap; 8.6 Sources of Error; 8.7 Risk Management; CHAPTER NINE. Calculations; 9.1 Base Conditions; 9.2 Physical Properties; 9.3 Natural Gas Density; 9.4 GPA 2172 versus A.G.A.8; 9.5 Mass Flow Rate in Pipes; 9.6 Mass Flow Rate for Orifice Flowmeter; 9.7 Mass Flow Rate for Ultrasonic Flowmeter; 9.8 Mass Flow Rate for Turbine Flowmeter; 9.9 Mass Flow Rate for Rotary Displacement Flowmeter; 9.10 Volumetric Flow Rate at Base Conditions; 9.11 Energy Flow Rate at Base Condtions; 9.12 Quantities; CHAPTER TEN. Secondary and Tertiary Devices; 10.1 General10.2 Differential Pressure (dP)10.3 Static Pressure; 10.4 Temperature; 10.5 Multivariable Transmitter; 10.6 Online Densitometer; 10.7 Moisture Analyzer; 10.8 Online Gas Chromatograph; 10.9 Other Analyzers; 10.10 Flow Computers; 10.11 Gas Sampling Systems; CHAPTER ELEVEN. Electronic Gas Measurement; 11.1 Description of an Electronic Gas Measurement System; 11.2 System Accuracy; 11.3 Definitions; 11.4 Sampling Flow Variables; 11.5 Low Flow Detection; 11.6 Averaging Techniques; 11.7 Compressibility, Density, and Heating Values; 11.8 Hourly and Daily Quantity Calculations; 11.9 Data Availability11.10 Audit and Reporting RequirementsThis information-packed volume covers all aspects of natural gas measurement.Gas-meters -- Handbooks, manuals, etcNatural gas -- HistoryNatural gas -- MeasurementNatural gasMeasurementHandbooks, manuals, etcGas-metersCivil & Environmental EngineeringHILCCEngineering & Applied SciencesHILCCCivil EngineeringHILCCGas-meters -- Handbooks, manuals, etc.Natural gas -- History.Natural gas -- Measurement.Natural gasMeasurementGas-meters.Civil & Environmental EngineeringEngineering & Applied SciencesCivil Engineering665.74665.74Gallagher James E1007044AU-PeELAU-PeELAU-PeELBOOK9910679881803321Natural Gas Measurement Handbook2318939UNINA