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[null,"1.","Record Nr.",null,"UNINA9910452089703321"]
[null,null,"Autore",null,"Wolsey Thomas DeVere"]
[null,null,"Titolo",null,"Transforming writing instruction in the digital age [[electronic resource] ] : techniques for grades 5-12 / / Thomas DeVere Wolsey, Dana L. Grisham ; series editors' note by Diane Lapp and Douglas Fisher ; foreword by Bridget Dalton"]
[null,null,"Pubbl/distr/stampa",null,"New York, : Guilford Press, 2012"]
[null,null,"ISBN",null,"1-280-48410-1"]
[{"$nulls":4},"9786613579089"]
[{"$nulls":4},"1-4625-0468-X"]
[null,null,"Descrizione fisica",null,"1 online resource (258 p.)"]
[null,null,"Collana",null,"Teaching practices that work"]
[null,null,"Disciplina",null,"428.0071/2"]
[null,null,"Soggetti",null,"English language - Composition and exercises - Study and teaching (Secondary) - Computer-assisted instruction"]
[{"$nulls":4},"Internet in education"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Machine generated contents note: IntroductionHashtags by Technique<b>I. Getting Started with Tools and Teaching </b>Technique 1. Resources: Anytime, AnywhereTechnique 2. Management: Computers in the ClassroomTechnique 3. Management: The HardwareTechnique 4. Direct InstructionTechnique 5. A Word about Differentiation<b>II. Writing and Thinking</b>Technique 6. Embracing Writing: Knowledge-Transforming WritingTechnique 7. Why Writing Is a Process, and How Technology Can HelpTechnique 8. Working with Sources: Keeping Track of Learning, and Leaving a Path for Others to FollowTechnique 9. Working with Sources: Using Style Guides<b>III. Writing to Understand: It's All about the Discipline</b>Technique 10. Discussion and WritingTechnique 11. Writing Short PiecesTechnique 12. Short Writing: Electronic JournalsTechnique 13. Blogs and Classroom Websites for WritingTechnique 14. Online Literature Discussion (Threaded Discussion)Technique 15. Vocabulary and WritingTechnique 16. Collaborative WritingTechnique 17. Are Those Kids Texting Again?<b>IV. Inquiry and Long Thinking Meet the Disciplines</b>Technique 18. FAQs about Writing in the DisciplinesTechnique 19. It's All the "]
[{"$nulls":4},"Same, or Maybe Not?Technique 20. What Was That Essential Question Again?Technique 21. Learning Because I'm Writing: Logs and JournalsTechnique 22. Writing Is (Hard) Cognitive Work: Bloom's Taxonomy MattersTechnique 23. Internet InquiryTechnique 24. PromptsTechnique 25. Prewriting: Composing before Writing with Pen or KeyboardTechnique 26. Prewriting with Graphic OrganizersTechnique 27. Feedback, Assessment, and Technology<b>V. What about Literature and English Language Arts?</b>Technique 28. Short Writing: Summaries in Response to ReadingTechnique 29. The Zen of Writing about LiteratureTechnique 30. Persuasion: In This Essay, I'm Going to Convince You...Technique 31. Prompts for Writing: Language Arts<b>VI. Composing with Multimedia</b>Technique 32. Visualize It!Technique 33. Podcasting: It's Ear-resistible<b>VII. Wrapping It Up </b>Technique 34. Advocacy for Technology and New LiteraciesTechnique 35. High-Stakes Writing AssessmentsTechnique 36. Automated ToolsTechnique 37. PublicationAppendix: Common Core Content Standards for Writing, Grades 6-12Glossary."]
[null,null,null,"Sommario/riassunto","\"An innovative, practical guide for middle and high school teachers, this book is packed with specific ways that technology can help serve the goals of effective writing instruction. It provides ready-to-implement strategies for teaching students to compose and edit written work electronically; conduct Internet inquiry; create blogs, websites, and podcasts; and use text messaging and Twitter productively. The book is grounded in state-of-the-art research on the writing process and the role of writing in content area learning. Teacher-friendly features include vivid classroom examples, differentiation tips, links to online resources, and reproducible worksheets and forms\"-- Provided by publisher."]
[null,"2.","Record Nr.",null,"UNINA9910955546603321"]
[null,null,"Autore",null,"Goos Peter"]
[null,null,"Titolo",null,"Optimal design of experiments : a case study approach / / Peter Goos, Bradley Jones"]
[null,null,"Pubbl/distr/stampa",null,"Hoboken, N.J., : Wiley, 2011"]
[null,null,"ISBN",null,"9781119976165"]
[{"$nulls":4},"1119976162"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (305 p.)"]
[null,null,"Disciplina",null,"670.285"]
[null,null,"Soggetti",null,"Industrial engineering - Experiments - Computer-aided design"]
[{"$nulls":4},"Experimental design - Data processing"]
[{"$nulls":4},"Industrial engineering"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Optimal Design of Experiments : A Case Study Approach; Contents; Preface; Acknowledgments; 1 A simple comparative experiment; 1.1 Key concepts; 1.2 The setup of a comparative experiment; 1.3 Summary; 2 An optimal screening experiment; 2.1 Key concepts; 2.2 Case: an extraction experiment; 2.2.1 Problem and design; 2.2.2 Data analysis; 2.3 Peek into the black box; 2.3.1 Main-effects models; 2.3.2 Models with two-factor interaction effects; 2.3.3 Factor scaling; 2.3.4 Ordinary least squares estimation; 2.3.5 Significance tests and statistical power calculations; 2.3.6 Variance inflation"]
[{"$nulls":4},"2.3.7 Aliasing2.3.8 Optimal design; 2.3.9 Generating optimal experimental designs; 2.3.10 The extraction experiment revisited; 2.3.11 Principles of successful screening: sparsity, hierarchy, and heredity; 2.4 Background reading; 2.4.1 Screening; 2.4.2 Algorithms for finding optimal designs; 2.5 Summary; 3 Adding runs to a screening experiment; 3.1 Key concepts; 3.2 Case: an augmented extraction experiment; 3.2.1 Problem and design; 3.2.2 Data analysis; 3.3 Peek into the black box; 3.3.1 Optimal selection of a follow-up design; 3.3.2 Design construction algorithm; 3.3.3 Foldover designs"]
[{"$nulls":4},"3.4 Background reading3.5 Summary; 4 A response surface design with a categorical factor; 4.1 Key concepts; 4.2 Case: a robust and optimal process experiment; 4.2.1 Problem and design; 4.2.2 Data analysis; 4.3 Peek into the black box; 4.3.1 Quadratic effects; 4.3.2 Dummy variables for multilevel categorical factors; 4.3.3 Computing D-"]
[{"$nulls":4},"efficiencies; 4.3.4 Constructing Fraction of Design Space plots; 4.3.5 Calculating the average relative variance of prediction; 4.3.6 Computing I-efficiencies; 4.3.7 Ensuring the validity of inference based on ordinary least squares; 4.3.8 Design regions"]
[{"$nulls":4},"4.4 Background reading4.5 Summary; 5 A response surface design in an irregularly shaped design region; 5.1 Key concepts; 5.2 Case: the yield maximization experiment; 5.2.1 Problem and design; 5.2.2 Data analysis; 5.3 Peek into the black box; 5.3.1 Cubic factor effects; 5.3.2 Lack-of-fit test; 5.3.3 Incorporating factor constraints in the design construction algorithm; 5.4 Background reading; 5.5 Summary; 6 A \"mixture\" experiment with process variables; 6.1 Key concepts; 6.2 Case: the rolling mill experiment; 6.2.1 Problem and design; 6.2.2 Data analysis; 6.3 Peek into the black box"]
[{"$nulls":4},"6.3.1 The mixture constraint6.3.2 The effect of the mixture constraint on the model; 6.3.3 Commonly used models for data from mixture experiments; 6.3.4 Optimal designs for mixture experiments; 6.3.5 Design construction algorithms for mixture experiments; 6.4 Background reading; 6.5 Summary; 7 A response surface design in blocks; 7.1 Key concepts; 7.2 Case: the pastry dough experiment; 7.2.1 Problem and design; 7.2.2 Data analysis; 7.3 Peek into the black box; 7.3.1 Model; 7.3.2 Generalized least squares estimation; 7.3.3 Estimation of variance components; 7.3.4 Significance tests"]
[{"$nulls":4},"7.3.5 Optimal design of blocked experiments"]
[null,null,null,"Sommario/riassunto","\"This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples. These examples address questions such as the following: How can I do screening inexpensively if I have dozens of factors to investigate? What can I do if I have day-to-day variability and I can only perform 3 runs a day? How can I do RSM cost effectively if I have categorical factors? How can I design and analyze experiments when there is a factor that can only be changed a few times over the study? How can I include both ingredients in a mixture and processing factors in the same study? How can I design an experiment if there are many factor combinations that are impossible to run? How can I make sure that a time trend due to warming up of equipment does not affect the conclusions from a study? How can I take into account batch information in when designing experiments involving multiple batches? How can I add runs to a botched experiment to resolve ambiguities?While answering these questions the book also shows how to evaluate and compare designs. This allows researchers to make sensible trade-offs between the cost of experimentation and the amount of information they obtain. The structure of the book is organized around the following chapters: 1) Introduction explaining the concept of tailored DOE. 2) Basics of optimal design. 3) Nine case studies dealing with the above questions using the flow: description &rarr; design &rarr; analysis &rarr; optimization or engineering interpretation. 4) Summary. 5) Technical appendices for the mathematically curious\"--"]
[{"$nulls":4},"\"This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples\"--"]