00923nam0-22002891i-450 99000446603040332120171003104030.0000446603FED0100044660319990530d1867----km-y0itay50------baitay-------001yyPio IX ed il suo secolodalla rivoluzione francese del 1789 alla proclamazione del regno d'italiaBiagio CognettiNapoliStab. Tip. di P. Androsio18672 v. (XXIV,505; 558 p.)23 cmPio <papa ; 9.>Stato della Chiesa - Storia - 1789-1861945.6322.10945Cognetti,Biagio<sec. 19.sacerdote>741278ITUNINAREICATUNIMARCBK990004466030403321SG 200/B 184R.Bibl. 14572FLFBCFLFBCPio IX ed il suo secolo1471107UNINA02503oam 2200469 450 991082376220332120190911103508.01-4166-2410-41-4166-2409-0(OCoLC)987437180(MiFhGG)GVRL000P(EXLCZ)99434000000019216820170511h20172017 uy 0engurun|---uuuuardacontentrdamediardacarrierHow to use grading to improve learning /Susan M. BrookhartAlexandria, Virginia :ASCD,[2017]�20171 online resource (xi, 171 pages) illustrationsGale eBooksPreviously titled Grading and Learning.1-4166-2407-4 Includes bibliographical references and index.Part I: The basics of grading for learning : All students can learn ; Grading on standards for achievement ; Grading strategies that support and motivate student effort and learning -- Part II. Twelve grading strategies that support student learning : Designing and grading assessments to reflect student achievement ; Designing report card grading policies to reflect student achievement -- Part III. Reforming grading policies and practices to support student learning : Beginning and implementing learning-focused report card grading policies ; Communicating with students and parents ; Assessing readiness for grading reform.This book guides educators at all levels in figuring out how to produce grades for single assignments and report cards that accurately communicate student achievement of learning goals. It explores topics that are fundamental to effective grading and learning practices, including acknowledging that all students can learn, supporting and motivating student effort and learning, designing and grading appropriate assessments, and implementing learning-focused grading policies.Grading and marking (Students)Educational tests and measurementsAcademic achievementGrading and marking (Students)Educational tests and measurements.Academic achievement.371.260973Brookhart Susan M. 915299MiFhGGMiFhGGBOOK9910823762203321How to use grading to improve learning4126319UNINA03201nam 2200493Ia 450 991073943320332120200520144314.01-4614-6797-710.1007/978-1-4614-6797-7(OCoLC)851482334(MiFhGG)GVRL6YIE(CKB)2670000000388019(MiAaPQ)EBC1317556(EXLCZ)99267000000038801920130708d2013 uy 0engurun|---uuuuatxtccrNonlinear optimization applications using the GAMS technology /Neculai Andrei1st ed. 2013.New York Springer20131 online resource (xxii, 340 pages) illustrations (some color)Springer optimization and its applications ;v. 81"ISSN: 1931-6828."1-4614-6796-9 Includes bibliographical references and index.Preface -- List of Figures -- List of Applications -- 1. Mathematical Modeling Using Algebraic Oriented Languages -- 2. Introduction to GAMS Technology -- 3. Nonlinear Optimization Applications in GAMS Technology -- References -- Subject Index -- Author Index.Nonlinear Optimization Applications Using the GAMS Technology develops a wide spectrum of nonlinear optimization applications expressed in the GAMS (General Algebraic Modeling System) language. The book is highly self-contained and is designed to present applications in a general form that can be easily understood and quickly updated or modified to represent situations from the real world. The book emphasizes the local solutions of the large-scale, complex, continuous nonlinear optimization applications, and the abundant examples in GAMS are highlighted by those involving ODEs, PDEs, and optimal control. The collection of these examples will be useful for software developers and testers. Chapter one presents aspects concerning the mathematical modeling process in the context of mathematical modeling technologies based on algebraic-oriented modeling languages. The GAMS technology is introduced in Chapter 2, mainly as a system for formulating and solving a large variety of general optimization models. The bulk of the 82 nonlinear optimization applications is given in Chapter 3. This book is primarily intended to serve as a reference for graduate students and for scientists working in various disciplines of industry/mathematical programming that use optimization methods to model and solve problems. It is also well suited as supplementary material for seminars in optimization, operations research, and decision making, to name a few.Springer optimization and its applications ;volume 81.Nonlinear theoriesMathematical analysisNonlinear theories.Mathematical analysis.003.75Andrei Neculai767620MiAaPQMiAaPQMiAaPQBOOK9910739433203321Nonlinear optimization applications using the GAMS technology3553832UNINA