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Data-Driven Instructional Leadership
by Rebecca J. BlinkWith real-world examples from actual schools, this book shows you how to nurture a culture of continuous improvement, meet the needs of individual students, foster an environment of high expectations, and meet the requirements of NCLB.
Data-Driven Instructional Leadership
by Rebecca J. BlinkWith real-world examples from actual schools, this book shows you how to nurture a culture of continuous improvement, meet the needs of individual students, foster an environment of high expectations, and meet the requirements of NCLB.
Data-Driven Leadership (Jossey-Bass Leadership Library in Education #12)
by Amanda Datnow Vicki ParkTools and techniques from the trailblazers in data-based education reform Over a period of several years, Amanda Datnow and Vicki Park visited public schools with a reputation for being ahead of the pack in data-driven decision making. The results of this pioneering study reveal how education leaders can make data work for students and teachers, rather than against them. This book is an essential guide to meeting the challenges of high-stakes accountability, building performance-based schools, and improving student outcomes. By following the advice in this book, you’ll be able to transform data overload into a data-positive school culture. You’ll learn the difference between “data-driven leadership” and “data-informed leadership,” and how to use distributed leadership to inspire collaboration and guided analysis. Incorporating narrative reflections drawn from real educators and administrators, the authors refine their observations and interviews into practical conclusions that leaders can put to use immediately. This book empowers leaders to support inquiry, build trust in data-based initiatives, establish goals for evidence use, and provide educators with the skills they need to mobilize data for the good of all stakeholders. “Datnow and Park’s ideas are easily accessible and grounded in clear examples, and their seven ‘calls’ about what needs to be done nail the problem and the solutions. Use this book as your action guide and you’ll be rewarded with better results in student learning.” —Michael Fullan, professor emeritus, University of Toronto “Datnow and Park uncover, at last, what it means to use data to inform leadership. Documenting the four P’s (people, policies, practices, and patterns) in schools, we learn about the organization and dynamics of reform informed by data. A must read!” —Ann Lieberman, senior scholar, Stanford University
Data-Driven Leadership (Jossey-Bass Leadership Library in Education #12)
by Amanda Datnow Vicki ParkTools and techniques from the trailblazers in data-based education reform Over a period of several years, Amanda Datnow and Vicki Park visited public schools with a reputation for being ahead of the pack in data-driven decision making. The results of this pioneering study reveal how education leaders can make data work for students and teachers, rather than against them. This book is an essential guide to meeting the challenges of high-stakes accountability, building performance-based schools, and improving student outcomes. By following the advice in this book, you’ll be able to transform data overload into a data-positive school culture. You’ll learn the difference between “data-driven leadership” and “data-informed leadership,” and how to use distributed leadership to inspire collaboration and guided analysis. Incorporating narrative reflections drawn from real educators and administrators, the authors refine their observations and interviews into practical conclusions that leaders can put to use immediately. This book empowers leaders to support inquiry, build trust in data-based initiatives, establish goals for evidence use, and provide educators with the skills they need to mobilize data for the good of all stakeholders. “Datnow and Park’s ideas are easily accessible and grounded in clear examples, and their seven ‘calls’ about what needs to be done nail the problem and the solutions. Use this book as your action guide and you’ll be rewarded with better results in student learning.” —Michael Fullan, professor emeritus, University of Toronto “Datnow and Park uncover, at last, what it means to use data to inform leadership. Documenting the four P’s (people, policies, practices, and patterns) in schools, we learn about the organization and dynamics of reform informed by data. A must read!” —Ann Lieberman, senior scholar, Stanford University
Data-Driven Learning for the Next Generation: Corpora and DDL for Pre-tertiary Learners
by Peter CrosthwaiteDespite advancements in and availability of corpus software in language classrooms facilitating data-driven learning (DDL), the use of such methods with pre-tertiary learners remains rare. This book specifically explores the affordances of DDL for younger learners, testing its viability with teachers and students at the primary and secondary years of schooling. It features eminent and up-and-coming researchers from Europe, Asia, and Australasia who seek to address best practice in implementing DDL with younger learners, while providing a wealth of empirical findings and practical DDL activities ready for use in the pre-tertiary classroom. Divided into three parts, the volume's first section focuses on overcoming emerging challenges for DDL with younger learners, including where and how DDL can be integrated into pre-tertiary curricula, as well as potential barriers to this integration. It then considers new, cutting-edge innovations in corpora and corpus software for use with younger learners in the second section, before reporting on actual DDL studies performed with younger learners (and/or their teachers) at the primary and secondary levels of education. This book will appeal to post-graduate students, academics and researchers with interests in corpus linguistics, second language acquisition, primary and secondary literacy education, and language and educational technologies.
Data-Driven Learning for the Next Generation: Corpora and DDL for Pre-tertiary Learners
by Peter CrosthwaiteDespite advancements in and availability of corpus software in language classrooms facilitating data-driven learning (DDL), the use of such methods with pre-tertiary learners remains rare. This book specifically explores the affordances of DDL for younger learners, testing its viability with teachers and students at the primary and secondary years of schooling. It features eminent and up-and-coming researchers from Europe, Asia, and Australasia who seek to address best practice in implementing DDL with younger learners, while providing a wealth of empirical findings and practical DDL activities ready for use in the pre-tertiary classroom. Divided into three parts, the volume's first section focuses on overcoming emerging challenges for DDL with younger learners, including where and how DDL can be integrated into pre-tertiary curricula, as well as potential barriers to this integration. It then considers new, cutting-edge innovations in corpora and corpus software for use with younger learners in the second section, before reporting on actual DDL studies performed with younger learners (and/or their teachers) at the primary and secondary levels of education. This book will appeal to post-graduate students, academics and researchers with interests in corpus linguistics, second language acquisition, primary and secondary literacy education, and language and educational technologies.
Data Elicitation for Second and Foreign Language Research (Second Language Acquisition Research Ser.)
by Susan M. Gass Alison MackeyThis timely reference guide is specifically directed toward the needs of second language researchers, who can expect to gain a clearer understanding of which techniques may be most appropriate and fruitful in given research domains. Data Elicitation for Second and Foreign Language Research is a perfect companion to the same author team‘s bestsellin
Data Elicitation for Second and Foreign Language Research
by Alison Mackey Susan M. GassThis timely reference guide is specifically directed toward the needs of second language researchers, who can expect to gain a clearer understanding of which techniques may be most appropriate and fruitful in given research domains. Data Elicitation for Second and Foreign Language Research is a perfect companion to the same author team’s bestselling Second Language Research: Methodology and Design. It is an indispensable text for graduate or advanced-level undergraduate students who are beginning research projects in the fields of applied linguistics, second language acquisition, and TESOL as well as a comprehensive reference for more seasoned researchers.
Data for Continuous Programmatic Improvement: Steps Colleges of Education Must Take to Become a Data Culture (Routledge Research in Higher Education)
by Ellen B. Mandinach Edith GummerThis book addresses the issue of data use in educator preparation programs towards continuous programmatic improvement. With an aim to increase the rigor in both research and practice in educational administration and teacher education, this volume will analyze the longstanding quality concerns about teacher and leadership preparation and standards for programs and educators, as well as controversies concerning national accreditation and federal efforts to mandate program reporting data. By exploring the policies and practices that influence departments of education, this volume examines the increasing pressures to improve institutional functioning, within a complex system of university, state, and national structures and organizations.
Data for Continuous Programmatic Improvement: Steps Colleges of Education Must Take to Become a Data Culture (Routledge Research in Higher Education)
by Ellen B. Mandinach Edith GummerThis book addresses the issue of data use in educator preparation programs towards continuous programmatic improvement. With an aim to increase the rigor in both research and practice in educational administration and teacher education, this volume will analyze the longstanding quality concerns about teacher and leadership preparation and standards for programs and educators, as well as controversies concerning national accreditation and federal efforts to mandate program reporting data. By exploring the policies and practices that influence departments of education, this volume examines the increasing pressures to improve institutional functioning, within a complex system of university, state, and national structures and organizations.
Data Management and Analysis: Case Studies in Education, Healthcare and Beyond (Studies in Big Data #65)
by Reda Alhajj Mohammad Moshirpour Behrouz FarData management and analysis is one of the fastest growing and most challenging areas of research and development in both academia and industry. Numerous types of applications and services have been studied and re-examined in this field resulting in this edited volume which includes chapters on effective approaches for dealing with the inherent complexity within data management and analysis. This edited volume contains practical case studies, and will appeal to students, researchers and professionals working in data management and analysis in the business, education, healthcare, and bioinformatics areas.
Data Management Technologies and Applications: 10th International Conference, DATA 2021, Virtual Event, July 6–8, 2021, and 11th International Conference, DATA 2022, Lisbon, Portugal, July 11-13, 2022, Revised Selected Papers (Communications in Computer and Information Science #1860)
by Alfredo Cuzzocrea Oleg Gusikhin Slimane Hammoudi Christoph QuixThis book constitutes the refereed post-proceedings of the 10th International Conference and 11th International Conference on Data Management Technologies and Applications, DATA 2021 and DATA 2022, was held virtually due to the COVID-19 crisis on July 6–8, 2021 and in Lisbon, Portugal on July 11-13, 2022.The 11 full papers included in this book were carefully reviewed and selected from 148 submissions. They were organized in topical sections as follows: engineers and practitioners interested on databases, big data, data mining, data management, data security and other aspects of information systems and technology involving advanced applications of data.
Data Management Technologies and Applications: 12th International Conference, DATA 2023, Rome, Italy, July 11–13, 2023, Revised Selected Papers (Communications in Computer and Information Science #2105)
by Alfredo Cuzzocrea Slimane Hammoudi Oleg GusikhinThis book constitutes the proceedings of the 12th International Conference on Data Management Technologies and Applications, DATA 2023 , held in Rome,Italy during July 11–13, 2023, Proceedings. The 6 full paper were carefully reviewed and selected from 106 submissions. The papers are organized in subject areas as follows: Big Data Applications, Data Analytics, Data Science, NoSQL Databases, Social Data Analytics, Dimensional Modelling, Deep Learning and Big Data, Decision Support Systems, Data Warehouse Management and Data Management for Analytics.
Data Management Technologies and Applications: 9th International Conference, DATA 2020, Virtual Event, July 7–9, 2020, Revised Selected Papers (Communications in Computer and Information Science #1446)
by Slimane Hammoudi Christoph Quix Jorge BernardinoThis book constitutes the thoroughly refereed proceedings of the 9th International Conference on Data Management Technologies and Applications, DATA 2020, which was supposed to take place in Paris, France, in July 2020. Due to the Covid-19 pandemic the event was held virtually. The 14 revised full papers were carefully reviewed and selected from 70 submissions. The papers deal with the following topics: datamining; decision support systems; data analytics; data and information quality; digital rights management; big data; knowledge management; ontology engineering; digital libraries; mobile databases; object-oriented database systems; data integrity.
Data Mining: 17th Australasian Conference, AusDM 2019, Adelaide, SA, Australia, December 2–5, 2019, Proceedings (Communications in Computer and Information Science #1127)
by Thuc D. Le Kok-Leong Ong Yanchang Zhao Warren H. Jin Sebastien Wong Lin Liu Graham WilliamsThis book constitutes the refereed proceedings of the 17th Australasian Conference on Data Mining, AusDM 2019, held in Adelaide, SA, Australia, in December 2019.The 20 revised full papers presented were carefully reviewed and selected from 56 submissions. The papers are organized in sections on research track, application track, and industry showcase.
Data Mining: 20th Australasian Conference, AusDM 2022, Western Sydney, Australia, December 12–15, 2022, Proceedings (Communications in Computer and Information Science #1741)
by Laurence A. F. Park Heitor Murilo Gomes Maryam Doborjeh Yee Ling Boo Yun Sing Koh Yanchang Zhao Graham Williams Simeon SimoffThis book constitutes the refereed proceedings of the 20th Australasian Conference on Data Mining, AusDM 2022, held in Western Sydney, Australia, during December 12–15, 2022. The 17 full papers included in this book were carefully reviewed and selected from 44 submissions. They were organized in topical sections as research track and application track.
Data Mining and Big Data: Third International Conference, DMBD 2018, Shanghai, China, June 17–22, 2018, Proceedings (Lecture Notes in Computer Science #10943)
by Ying Tan Yuhui Shi Qirong TangThis book constitutes the refereed proceedings of the Third International Conference on Data Mining and Big Data, DMBD 2018, held in Shanghai, China, in June 2018. The 74 papers presented in this volume were carefully reviewed and selected from 126 submissions. They are organized in topical sections named: database, data preprocessing, matrix factorization, data analysis, visualization, visibility analysis, clustering, prediction, classification, pattern discovery, text mining and knowledge management, recommendation system in social media, deep learning, big data, Industry 4.0, practical applications
Data Mining and Market Intelligence: Implications for Decision Making (Synthesis Lectures on Engineering)
by Mustapha AkinkunmiThis book is written to address the issues relating to data gathering, data warehousing, and data analysis, all of which are useful when working with large amounts of data. Using practical examples of market intelligence, this book is designed to inspire and inform readers on how to conduct market intelligence by leveraging data and technology, supporting smart decision making. The book explains some suitable methodologies for data analysis that are based on robust statistical methods. For illustrative purposes, the author uses real-life data for all the examples in this book. In addition, the book discusses the concepts, techniques, and applications of digital media and mobile data mining. Hence, this book is a guide tool for policy makers, academics, and practitioners whose areas of interest are statistical inference, applied statistics, applied mathematics, business mathematics, quantitative techniques, and economic and social statistics.
Data Modelling and Process Modelling using the most popular Methods: Covering SSADM, Yourdon, Inforem, Bachman, Information Engineering and 'Activity/Object' Diagramming Techniques
by Rosemary Rock-EvansComputer Weekly Professional Series: Data modeling and Process modeling: Using the Most Popular Methods focuses on the processes, methodologies, and approaches employed in data modeling and process modeling. The book first offers information on data modeling, how to do data modeling, and process modeling. Discussions focus on diagrammatic representation, main concepts of process modeling, merging the models, refining the data model, diagrammatic techniques, fundamental rules of data modeling, and other deliverables of data modeling. The text then examines how to do process modeling and improving a system using analysis deliverables. Topics include problems, causes and effects, events, obligations and objectives, verification methods, and refining the results. The manuscript reviews elementary activities, including structured text and access paths, updating the data model from the access paths and structured English, and other useful detailed deliverables of an elementary activity.The publication is a valuable source of data for researchers interested in data modeling and process modeling.
Data Science: 5th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2019, Guilin, China, September 20–23, 2019, Proceedings, Part II (Communications in Computer and Information Science #1059)
by Rui Mao Hongzhi Wang Xiaolan Xie Zeguang LuThis two volume set (CCIS 1058 and 1059) constitutes the refereed proceedings of the 5th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2019 held in Guilin, China, in September 2019. The 104 revised full papers presented in these two volumes were carefully reviewed and selected from 395 submissions. The papers cover a wide range of topics related to basic theory and techniques for data science including data mining; data base; net work; security; machine learning; bioinformatics; natural language processing; software engineering; graphic images; system; education; application.
Data Science: 8th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2022, Chengdu, China, August 19–22, 2022, Proceedings, Part I (Communications in Computer and Information Science #1628)
by Yang Wang Guobin Zhu Qilong Han Hongzhi Wang Xianhua Song Zeguang LuThis two volume set (CCIS 1628 and 1629) constitutes the refereed proceedings of the 8th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2022 held in Chengdu, China, in August, 2022. The 65 full papers and 26 short papers presented in these two volumes were carefully reviewed and selected from 261 submissions. The papers are organized in topical sections on: Big Data Mining and Knowledge Management; Machine Learning for Data Science; Multimedia Data Management and Analysis.
Data Science: 8th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2022, Chengdu, China, August 19–22, 2022, Proceedings, Part II (Communications in Computer and Information Science #1629)
by Yang Wang Guobin Zhu Qilong Han Liehui Zhang Xianhua Song Zeguang LuThis two volume set (CCIS 1628 and 1629) constitutes the refereed proceedings of the 8th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2022 held in Chengdu, China, in August, 2022. The 65 full papers and 26 short papers presented in these two volumes were carefully reviewed and selected from 261 submissions. The papers are organized in topical sections on: Big Data Management and Applications; Data Security and Privacy; Applications of Data Science; Infrastructure for Data Science; Education Track; Regulatory Technology in Finance.
Data Science: 9th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023, Harbin, China, September 22–24, 2023, Proceedings, Part I (Communications in Computer and Information Science #1879)
by Zhiwen Yu Qilong Han Hongzhi Wang Bin Guo Xiaokang Zhou Xianhua Song Zeguang LuThis two-volume set (CCIS 1879 and 1880) constitutes the refereed proceedings of the 9th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023 held in Harbin, China, during September 22–24, 2023. The 52 full papers and 14 short papers presented in these two volumes were carefully reviewed and selected from 244 submissions. The papers are organized in the following topical sections:Part I: Applications of Data Science, Big Data Management and Applications, Big Data Mining and Knowledge Management, Data Visualization, Data-driven Security, Infrastructure for Data Science, Machine Learning for Data Science and Multimedia Data Management and Analysis.Part II: Data-driven Healthcare, Data-driven Smart City/Planet, Social Media and Recommendation Systems and Education using big data, intelligent computing or data mining, etc.
Data Science: 9th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023, Harbin, China, September 22–24, 2023, Proceedings, Part II (Communications in Computer and Information Science #1880)
by Zhiwen Yu Qilong Han Hongzhi Wang Bin Guo Xiaokang Zhou Xianhua Song Zeguang LuThis two-volume set (CCIS 1879 and 1880) constitutes the refereed proceedings of the 9th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023 held in Harbin, China, during September 22–24, 2023.The 52 full papers and 14 short papers presented in these two volumes were carefully reviewed and selected from 244 submissions. The papers are organized in the following topical sections:Part I: Applications of Data Science, Big Data Management and Applications, Big Data Mining and Knowledge Management, Data Visualization, Data-driven Security, Infrastructure for Data Science, Machine Learning for Data Science and Multimedia Data Management and Analysis.Part II: Data-driven Healthcare, Data-driven Smart City/Planet, Social Media and Recommendation Systems and Education using big data, intelligent computing or data mining, etc.
Data Science – Analytics and Applications: Proceedings of the 1st International Data Science Conference – iDSC2017
by Peter Haber Thomas Lampoltshammer Manfred MayrThe iDSC Proceedings reports on state-of-the-art results in Data Science research, development and business. Topics and content of the IDSC2017 proceedings are• Reasoning and Predictive Analytics• Data Analytics in Community Networks• Data Analytics through Sentiment Analysis• User/Customer-centric Data Analytics• Data Analytics in Industrial Application ScenariosAdvances in technology and changes in the business and social environment have led to an increasing flood of data, fueling both the need and the desire to generate value from these assets. The emerging field of Data Science is poised to deliver theoretical and practical solutions to the pressing issues of data-driven applications.The 1st International Data Science Conference (iDSC2017 / http://www.idsc.at) organized by Salzburg University of Applied Sciences in cooperation with Information Professionals GmbH, established a new key Data Science event, by providing a forum for the international exchange of Data Science technologies and applications.