LEADER 04576oam 2200673I 450 001 9910792380403321 005 20230504180802.0 010 $a1-135-14620-9 010 $a1-135-14621-7 010 $a1-282-57002-1 010 $a9786612570025 010 $a0-203-85587-6 024 7 $a10.4324/9780203855874 035 $a(CKB)2670000000009305 035 $a(EBL)484730 035 $a(OCoLC)609427282 035 $a(SSID)ssj0000363568 035 $a(PQKBManifestationID)11260184 035 $a(PQKBTitleCode)TC0000363568 035 $a(PQKBWorkID)10387897 035 $a(PQKB)10944214 035 $a(MiAaPQ)EBC484730 035 $a(Au-PeEL)EBL484730 035 $a(CaPaEBR)ebr10371510 035 $a(CaONFJC)MIL257002 035 $a(OCoLC)647887390 035 $a(EXLCZ)992670000000009305 100 $a20180706d2010 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aNegotiating language education policies $eeducators as policymakers /$fedited by Kate Menken, Ofelia Garcia 210 1$aNew York :$cRoutledge,$d2010. 215 $a1 online resource (xiii, 278 pages) 300 $aDescription based upon print version of record. 311 0 $a0-415-80208-3 311 0 $a0-415-80207-5 320 $aIncludes bibliographical references and index. 327 $aBook Cover; Title; Copyright; Dedication; Contents; Foreword; Chapter 1 Introduction; Part I: Negotiation of Language Education Policies Guided by Educators' Experiences or Identity (Individual); Chapter 2 Appropriating Language Policy on the Local Level: Working the Spaces for Bilingual Education; Chapter 3 Two-Teacher Classrooms, Personalized Learning and the Inclusion Paradigm in the United Kingdom: What's in it for Learners of EAL?; Chapter 4 "Tu Sais Bien Parler Mai?tresse!": Negotiating Languages other than French in the Primary Classroom in France 327 $aChapter 5 "Angles Make Things Difficult": Teachers' Interpretations of Language Policy and Quechua Revitalization in Peru; Chapter 6 Towards Normalizing South African Classroom Life: The Ongoing Struggle to Implement Mother-Tongue Based Bilingual Education; Chapter 7 Enacting Language Policy through the Facilitator Model in a Monolingual Policy Context in the United States; Chapter 8 Between Intended and Enacted Curricula: Three Teachers and a Mandated Curricular Reform in Mainland China 327 $aPart II: Educators' Negotiation of Language Education Policies Influenced by Situation/Context/Community (Social); Chapter 9 Maori Language Policy and Practice in New Zealand Schools: Community Challenges and Community Solutions; Chapter 10 (Re)Constructing Language Policy in a Shi'i School in Lebanon; Chapter 11 Cases of Language Policy Resistance in Israel's Centralized Educational System; Chapter 12 Traversing the Linguistic Quicksand in Ethiopia; Chapter 13 Language Policy in Education and Classroom Practices in India: Is the Teacher a Cog in the Policy Wheel? 327 $aChapter 14 Chilean Literacy Education Policies and Classroom Implementation; Part III: Moving Forward; Chapter 15 Stirring the Onion: Educators and the Dynamics of Language Education Policies (Looking Ahead); Chapter 16 Moving Forward: Ten Guiding Principles for Teachers; Contributors; Author Index; Subject Index 330 $aEducators are at the epicenter of language policy in education. This book explores how they interpret, negotiate, resist, and (re)create language policies in classrooms. Bridging the divide between policy and practice by analyzing their interconnectedness, it examines the negotiation of language education policies in schools around the world, focusing on educators' central role in this complex and dynamic process.Each chapter shares findings from research conducted in specific school districts, schools, or classrooms around the world and then details how educators negotiate policy in 606 $aLanguages, Modern$xStudy and teaching$vCross-cultural studies 606 $aLanguage policy$xStudy and teaching$vCross-cultural studies 615 0$aLanguages, Modern$xStudy and teaching 615 0$aLanguage policy$xStudy and teaching 676 $a379.24 701 $aGarcia$b Ofelia$0175920 701 $aMenken$b Kate$f1968-$01547620 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910792380403321 996 $aNegotiating language education policies$93804095 997 $aUNINA LEADER 05032nam 22006855 450 001 9910484264703321 005 20251113181725.0 010 $a3-030-61943-5 024 7 $a10.1007/978-3-030-61943-5 035 $a(CKB)4100000011679197 035 $a(MiAaPQ)EBC6455888 035 $a(DE-He213)978-3-030-61943-5 035 $a(PPN)252515331 035 $a(EXLCZ)994100000011679197 100 $a20201223d2021 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aProbabilistic Graphical Models $ePrinciples and Applications /$fby Luis Enrique Sucar 205 $a2nd ed. 2021. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021. 215 $a1 online resource (XXVIII, 355 p. 167 illus., 144 illus. in color.) 225 1 $aAdvances in Computer Vision and Pattern Recognition,$x2191-6594 311 08$a3-030-61942-7 327 $aIntroduction -- Probability Theory -- Graph Theory -- Bayesian Classifiers -- Hidden Markov Models -- Markov Random Fields -- Bayesian Networks: Representation and Inference -- Bayesian Networks: Learning -- Dynamic and Temporal Bayesian Networks -- Decision Graphs -- Markov Decision Processes -- Partially Observable Markov Decision Processes -- Relational Probabilistic Graphical Models -- Graphical Causal Models -- Causal Discovery -- Deep Learning and Graphical Models -- A Python Library for Inference and Learning -- Glossary -- Index. 330 $aThis fully updated new edition of a uniquely accessible textbook/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective. It features new material on partially observable Markov decision processes, graphical models, and deep learning, as well as an even greater number of exercises. The book covers the fundamentals for each of the main classes of PGMs, including representation, inference and learning principles, and reviews real-world applications for each type of model. These applications are drawn from a broad range of disciplines, highlighting the many uses of Bayesian classifiers, hidden Markov models, Bayesian networks, dynamic and temporal Bayesian networks, Markov random fields, influence diagrams, and Markov decision processes. Topics and features: Presents a unified framework encompassing all of the main classes of PGMs Explores the fundamental aspects of representation, inference and learning for each technique Examines new material on partially observable Markov decision processes, and graphical models Includes a new chapter introducing deep neural networks and their relation with probabilistic graphical models Covers multidimensional Bayesian classifiers, relational graphical models, and causal models Provides substantial chapter-ending exercises, suggestions for further reading, and ideas for research or programming projects Describes classifiers such as Gaussian Naive Bayes, Circular Chain Classifiers, and Hierarchical Classifiers with Bayesian Networks Outlines the practical application of the different techniques Suggests possible course outlines for instructors This classroom-tested work is suitable as a textbook for an advanced undergraduate or a graduate course in probabilistic graphical models for students of computer science, engineering, andphysics. Professionals wishing to apply probabilistic graphical models in their own field, or interested in the basis of these techniques, will also find the book to be an invaluable reference. Dr. Luis Enrique Sucar is a Senior Research Scientist at the National Institute for Astrophysics, Optics and Electronics (INAOE), Puebla, Mexico. 410 0$aAdvances in Computer Vision and Pattern Recognition,$x2191-6594 606 $aComputer science$xMathematics 606 $aMathematical statistics 606 $aArtificial intelligence 606 $aPattern recognition systems 606 $aProbabilities 606 $aElectrical engineering 606 $aProbability and Statistics in Computer Science 606 $aArtificial Intelligence 606 $aAutomated Pattern Recognition 606 $aProbability Theory 606 $aElectrical and Electronic Engineering 615 0$aComputer science$xMathematics. 615 0$aMathematical statistics. 615 0$aArtificial intelligence. 615 0$aPattern recognition systems. 615 0$aProbabilities. 615 0$aElectrical engineering. 615 14$aProbability and Statistics in Computer Science. 615 24$aArtificial Intelligence. 615 24$aAutomated Pattern Recognition. 615 24$aProbability Theory. 615 24$aElectrical and Electronic Engineering. 676 $a003.54 700 $aSucar$b Luis Enrique$01060261 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484264703321 996 $aProbabilistic Graphical Models$92512048 997 $aUNINA