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Data Wise: A Step-By-Step Guide to Using Assessment Results to Improve Teaching and Learning
by Richard J. Murnane Kathryn Parker Boudett Elizabeth A. CityData Wise: A Step-by-Step Guide to Using Assessment Results to Improve Teaching and Learning presents a clear and carefully tested blueprint for school leaders. It shows how examining test scores and other classroom data can become a catalyst for important schoolwide conversations that will enhance schools' abilities to capture teachers' knowledge, foster collaboration, identify obstacles to change, and enhance school culture and climate. This revised and expanded edition captures the learning that has emerged in integrating the Data Wise process into school practice and brings the book up-to-date with recent developments in education and technology including: The shift to the Common Core State Standards. New material on the "ACE Habits of Mind": practices that prioritize Action, Collaboration, and Evidence as part of transforming school culture. A new chapter on "How We Improve," based on experiences implementing Data Wise and to address two common questions: "Where do I start?" and "How long will it take?" Other revisions take into account changes in the roles of school data teams and instructional leadership teams in guiding the inquiry process. The authors have also updated exhibits, examples, and terminology throughout and have added new protocols and resources.
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! Dialogue! Decisions!: The Data Difference
by Brian M. Pete Catherine A. DuncanLink relevant data to results instantly and consistently!This powerful text offers school leaders a process for data-based decision making that includes the critical elements of school improvement: collaborative teams, meaningful data, and measurable results. Administrators and instructors select the data, dialogue about the findings, and then make informed decisions about improving student performance. Educators will learn to:Select data that is easily accessible, collectible on an ongoing basis, and capable of impacting student achievementUse the three-step cyclical model of data analysisCreate and assess goals that are specific, measurable, and results-oriented
Data, Architecture and the Experience of Place
by Anastasia KarandinouThe notion of data is increasingly encountered in spatial, creative and cultural studies. Big data and artificial intelligence are significantly influencing a number of disciplines. Processes, methods and vocabularies from sciences, architecture, arts are borrowed, discussed and tweaked, and new cross-disciplinary fields emerge. More and more, artists and designers are drawing on hard data to interpret the world and to create meaningful, sensuous environments. Architects are using neurophysiological data to improve their understanding of people’s experiences in built spaces. Different disciplines collaborate with scientists to visualise data in different and creative ways, revealing new connections, interpretations and readings. This often demonstrates a genuine desire to comprehend human behaviour and experience and to – possibly – inform design processes accordingly. At the same time, this opens up questions as to why this desire and curiosity is emerging now, how it relates to recent technological advances and how it converses with the cultural, philosophical and methodological context of the disciplines with which it engages. Questions are also raised as to how the use of data and data-informed methods may serve, support, promote and/or challenge political agendas. Data, Architecture and the Experience of Place provides an overview of new approaches on this significant subject and is ideal for students and researchers in digital architecture, architectural theory, design, digital media, sensory studies and related fields.
Data, Data Everywhere: Bringing All the Data Together for Continuous School Improvement
by Victoria L. BernhardtThe latest book from best-selling author Victoria L. Bernhardt is an easy-to-read primer that describes what it takes to achieve student learning growth at every grade level, in every subject area, and with every student group. In this new edition, readers will learn how to use data to inform their continuous school improvement as they develop an appreciation of the various types of data, uses for data, and how data are involved in the process. This accessible, updated edition provides a wealth of straightforward and accessible strategies that will allow educators to become comfortable with the many uses of data in increasing student improvement. Data, Data Everywhere, 2nd edition, provides a framework and summary of the continuous school improvement framework. It is a perfect resource for teachers, administrators, support staff, and students of leadership to guide comprehensive school improvement that will make a difference for all students.
Data, Data, Everywhere: Bringing All the Data Together for Continuous School Improvement
by Victoria L. Bernhardt<p>The latest book from best-selling author Victoria L. Bernhardt is an easy-to-read primer that describes what it takes to achieve student learning growth at every grade level, in every subject area, and with every student group. In this new edition, readers will learn how to use data to inform their continuous school improvement as they develop an appreciation of the various types of data, uses for data, and how data are involved in the process. This accessible, updated edition provides a wealth of straightforward and accessible strategies that will allow educators to become comfortable with the many uses of data in increasing student improvement. <p>Data, Data Everywhere, 2nd edition, provides a framework and summary of the continuous school improvement framework. It is a perfect resource for teachers, administrators, support staff, and students of leadership to guide comprehensive school improvement that will make a difference for all students.</p>
Data-Driven Decision Making and Dynamic Planning: A School Leader's Guide
by Paul PreussThis book will help you understand how to integrate data-based decisions into the daily work of the school. It is a practical and relevant handbook for converting data into wise decision-making and planning. It will give you the skills to successfully make data-based decisions, measure student learning and program effectiveness, evaluate student progress, use data to improve instruction, integrate a "Dynamic Planning" process into the daily operation of your school.
Data-Driven Decision-Making in Schools: Lessons from Trinidad
by Jennifer Yamin-AliYamin-Ali shows how schools can undertake responsible decision-making through gathering and evaluating data, using as examples six fully developed case studies that shed light on common questions of school culture and student life, including student stress, subject selection, and the role of single-sex classes.
Data-Driven Design for Computer-Supported Collaborative Learning: Design Matters (Lecture Notes in Educational Technology)
by Lanqin ZhengThis book highlights the importance of design in computer-supported collaborative learning (CSCL) by proposing data-driven design and assessment. It addresses data-driven design, which focuses on the processing of data and on improving design quality based on analysis results, in three main sections. The first section explains how to design collaborative learning activities based on data-driven design approaches, while the second shares illustrative examples of computer-supported collaborative learning activities. In turn, the third and last section demonstrates how to evaluate design quality and the fidelity of enactment based on design-centered research.The book features several examples of innovative data-driven design approaches to optimizing collaborative learning activities; highlights innovative CSCL activities in authentic learning environments; demonstrates how learning analytics can be used to optimize CSCL design; and discusses the design-centered research approach to evaluating the alignment between design and enactment in CSCL. Given its scope, it will be of interest to a broad readership including researchers, educators, practitioners, and students in the field of collaborative learning, as well as the rapidly growing community of people who are interested in optimizing learning performance with CSCL.
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
by Amanda Datnow Vicki ParkTools and techniques from the trailblazers in data-based education reformOver 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-Enhanced Leadership
by Alan M. Blankstein Paul D. Houston Robert W. ColeThis compact volume combines research, practice, and innovative thinking to illustrate how strategic application of data enhances leadership practices and significantly improves curriculum, instruction, and schoolwide performance.
Data-Warehouse-Systeme kompakt: Aufbau, Architektur, Grundfunktionen (Xpert.press)
by Kiumars FarkischIn dem Buch werden Data-Warehouse-Systeme als einheitliche, zentrale, vollständige, historisierte und analytische IT-Plattform untersucht und ihre Rolle für die Datenanalyse und für Entscheidungsfindungsprozesse dargestellt. Dabei behandelt der Autor die einzelnen Komponenten, die für den Aufbau, die Architektur und den Betrieb eines Data-Warehouse-Systems von Bedeutung sind. Die multidimensionale Datenmodellierung, der ETL-Prozess und Analysemethoden werden erörtert und Maßnahmen zur Performancesteigerung von Data-Warehouse-Systemen diskutiert.
Data-based Decision Making in Education: Challenges and Opportunities (Studies in Educational Leadership #17)
by Mei Kuin Lai Lorna Earl Kim SchildkampIn a context where schools are held more and more accountable for the education they provide, data-based decision making has become increasingly important. This book brings together scholars from several countries to examine data-based decision making. Data-based decision making in this book refers to making decisions based on a broad range of evidence, such as scores on students' assessments, classroom observations etc. This book supports policy-makers, people working with schools, researchers and school leaders and teachers in the use of data, by bringing together the current research conducted on data use across multiple countries into a single volume. Some of these studies are 'best practice' studies, where effective data use has led to improvements in student learning. Others provide insight into challenges in both policy and practice environments. Each of them draws on research and literature in the field.
Database Systems for Advanced Applications: 25th International Conference, DASFAA 2020, Jeju, South Korea, September 24–27, 2020, Proceedings, Part I (Lecture Notes in Computer Science #12112)
by Bin Cui Yang-Sae Moon Jeffrey Xu Yu Yunmook Nah Sang-Won Lee Steven Euijong WhangThe 4 volume set LNCS 12112-12114 constitutes the papers of the 25th International Conference on Database Systems for Advanced Applications which will be held online in September 2020. The 119 full papers presented together with 19 short papers plus 15 demo papers and 4 industrial papers in this volume were carefully reviewed and selected from a total of 487 submissions. The conference program presents the state-of-the-art R&D activities in database systems and their applications. It provides a forum for technical presentations and discussions among database researchers, developers and users from academia, business and industry.
Database Systems for Advanced Applications: 25th International Conference, DASFAA 2020, Jeju, South Korea, September 24–27, 2020, Proceedings, Part III (Lecture Notes in Computer Science #12114)
by Bin Cui Yang-Sae Moon Jeffrey Xu Yu Yunmook Nah Sang-Won Lee Steven Euijong WhangThe 4 volume set LNCS 12112-12114 constitutes the papers of the 25th International Conference on Database Systems for Advanced Applications which will be held online in September 2020. The 119 full papers presented together with 19 short papers plus 15 demo papers and 4 industrial papers in this volume were carefully reviewed and selected from a total of 487 submissions. The conference program presents the state-of-the-art R&D activities in database systems and their applications. It provides a forum for technical presentations and discussions among database researchers, developers and users from academia, business and industry.
Database Systems for Advanced Applications: 27th International Conference, DASFAA 2022, Virtual Event, April 11–14, 2022, Proceedings, Part II (Lecture Notes in Computer Science #13246)
by Mukesh Mohania P. Krishna Reddy Anirban Mondal Arnab Bhattacharya Vikram Goyal Janice Lee Mong Li Divyakant Agrawal Rage Uday KiranThe three-volume set LNCS 13245, 13246 and 13247 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2022, held online, in April 2021. The total of 72 full papers, along with 76 short papers, are presented in this three-volume set was carefully reviewed and selected from 543 submissions. Additionally, 13 industrial papers, 9 demo papers and 2 PhD consortium papers are included. The conference was planned to take place in Hyderabad, India, but it was held virtually due to the COVID-19 pandemic.
Database Systems for Advanced Applications: DASFAA 2017 International Workshops: BDMS, BDQM, SeCoP, and DMMOOC, Suzhou, China, March 27-30, 2017, Proceedings (Lecture Notes in Computer Science #10179)
by Wen Hua Lijun Chang Zhifeng Bao Goce TrajcevskiThis two volume set LNCS 10177 and 10178 constitutes the refereed proceedings of the 22nd International Conference on Database Systems for Advanced Applications, DASFAA 2017, held in Suzhou, China, in March 2017. The 73 full papers, 9 industry papers, 4 demo papers and 3 tutorials were carefully selected from a total of 300 submissions. The papers are organized around the following topics: semantic web and knowledge management; indexing and distributed systems; network embedding; trajectory and time series data processing; data mining; query processing and optimization; text mining; recommendation; security, privacy, senor and cloud; social network analytics; map matching and spatial keywords; query processing and optimization; search and information retrieval; string and sequence processing; stream date processing; graph and network data processing; spatial databases; real time data processing; big data; social networks and graphs.
Databricks Certified Data Engineer Associate Study Guide
by Derar AlhusseinData engineers proficient in Databricks are currently in high demand. As organizations gather more data than ever before, skilled data engineers on platforms like Databricks become critical to business success. The Databricks Data Engineer Associate certification is proof that you have a complete understanding of the Databricks platform and its capabilities, as well as the essential skills to effectively execute various data engineering tasks on the platform.In this comprehensive study guide, you will build a strong foundation in all topics covered on the certification exam, including the Databricks Lakehouse and its tools and benefits. You'll also learn to develop ETL pipelines in both batch and streaming modes. Moreover, you'll discover how to orchestrate data workflows and design dashboards while maintaining data governance. Finally, you'll dive into the finer points of exactly what's on the exam and learn to prepare for it with mock tests.Author Derar Alhussein teaches you not only the fundamental concepts but also provides hands-on exercises to reinforce your understanding. From setting up your Databricks workspace to deploying production pipelines, each chapter is carefully crafted to equip you with the skills needed to master the Databricks Platform. By the end of this book, you'll know everything you need to ace the Databricks Data Engineer Associate certification exam with flying colors, and start your career as a certified data engineer from Databricks!You'll learn how to:Use the Databricks Platform and Delta Lake effectivelyPerform advanced ETL tasks using Apache Spark SQLDesign multi-hop architecture to process data incrementallyBuild production pipelines using Delta Live Tables and Databricks JobsImplement data governance using Databricks SQL and Unity CatalogDerar Alhussein is a senior data engineer with a master's degree in data mining. He has over a decade of hands-on experience in software and data projects, including large-scale projects on Databricks. He currently holds eight certifications from Databricks, showcasing his proficiency in the field. Derar is also an experienced instructor, with a proven track record of success in training thousands of data engineers, helping them to develop their skills and obtain professional certifications.
Databusting for Schools: How to Use and Interpret Education Data
by Richard Selfridge'In the increasingly data-swamped world of education, data literacy is no longer a desirable skill, it is essential. Databusting for Schools is part guide through the complexities, uses and limitations of data; and part challenge to those who too readily make assumptions and draw conclusions. This is an important book.' James Pembroke, independent data analyst Data rules schools and ignorance is far from bliss. From assessment results to questioning educational claims, there is a growing need to understand the numbers used in education. Education data blogger and teacher Richard Selfridge (aka Jack Marwood) unravels the complexities of dealing with educational data and explains statistics in an understandable, everyday way, relevant to your classroom and your school. He will take you through all you need to know about data and statistics in education including: · Where does education data come from? · The what, why and how of numbers. · Understanding different types of graphs and how to use them. · How to play around with data to see the bigger picture. · How to interpret data, does one thing really lead to another? · Using data to inform school policy. A must-read for all teachers, school leaders, data managers, school governors, and anyone in education who has ever looked at statistical data and broken out into a cold sweat. Richard Selfridge is a primary school teacher and writer on education. He is author of the popular datablog Icing on the Cake and tweets under the sometime pseudonym @Jack_Marwood.
Databusting for Schools: How to Use and Interpret Education Data
by Richard Selfridge'In the increasingly data-swamped world of education, data literacy is no longer a desirable skill, it is essential. Databusting for Schools is part guide through the complexities, uses and limitations of data; and part challenge to those who too readily make assumptions and draw conclusions. This is an important book.' James Pembroke, independent data analyst Data rules schools and ignorance is far from bliss. From assessment results to questioning educational claims, there is a growing need to understand the numbers used in education. Education data blogger and teacher Richard Selfridge (aka Jack Marwood) unravels the complexities of dealing with educational data and explains statistics in an understandable, everyday way, relevant to your classroom and your school. He will take you through all you need to know about data and statistics in education including: · Where does education data come from? · The what, why and how of numbers. · Understanding different types of graphs and how to use them. · How to play around with data to see the bigger picture. · How to interpret data, does one thing really lead to another? · Using data to inform school policy. A must-read for all teachers, school leaders, data managers, school governors, and anyone in education who has ever looked at statistical data and broken out into a cold sweat. Richard Selfridge is a primary school teacher and writer on education. He is author of the popular datablog Icing on the Cake and tweets under the sometime pseudonym @Jack_Marwood.
Dataproof Your School: How to use assessment data effectively (Corwin Ltd)
by Richard Selfridge James PembrokeCollecting and analysing data to monitor and challenge school standards is an increasingly important – and unavoidable – aspect of our education system. But how do we ensure we are generating useful information to support learning and make informed decisions, and not needlessly ramping up workload? This book will guide you through the different types of data schools can, and should, generate; how to make the best use of it, and what to avoid. From standardised tests and teacher assessment, to managing data and developing a data strategy, this book will equip you with the tools you need to dataproof your school. Richard Selfridge is a primary school teacher, data consultant and writer on education James Pembroke is a data analyst, blogger and consultant with 15 year’s experience working with education data. He now works for Insight Tracking.
Dataproof Your School: How to use assessment data effectively (Corwin Ltd)
by Richard Selfridge James PembrokeCollecting and analysing data to monitor and challenge school standards is an increasingly important – and unavoidable – aspect of our education system. But how do we ensure we are generating useful information to support learning and make informed decisions, and not needlessly ramping up workload? This book will guide you through the different types of data schools can, and should, generate; how to make the best use of it, and what to avoid. From standardised tests and teacher assessment, to managing data and developing a data strategy, this book will equip you with the tools you need to dataproof your school. Richard Selfridge is a primary school teacher, data consultant and writer on education James Pembroke is a data analyst, blogger and consultant with 15 year’s experience working with education data. He now works for Insight Tracking.
Datenbasierte Qualitätssicherung und -entwicklung in Schulen: Eine Bestandsaufnahme in den Ländern der Bundesrepublik Deutschland
by Felicitas Thiel Jasmin Tarkian Eva-Maria Lankes Norbert Maritzen Thomas Riecke-Baulecke Anna KroupaIm vorliegenden Buch werden auf der Grundlage einer systematischen Auswertung von Konzepten, Handreichungen, Gesetzen und Verwaltungsvorschriften die Verfahren und Regelungen zu drei zentralen Instrumenten schulischer Qualitätsentwicklung in den 16 deutschen Ländern beschrieben. Mehr als 1000 Dokumente wurden zu diesem Zweck analysiert. Damit liegt erstmals eine ländervergleichende Bestandsaufnahme vor, die für politisch-administrative Steuerungsentscheidungen sowie zukünftige Forschungsvorhaben gleichermaßen informativ ist. Der InhaltMethodische Grundlagen der Analyse bildungspolitischer und -rechtlicher Dokumente • Rahmenkonzepte zur Definition von Schulqualität • Konzeption und Implementation von Vergleichsarbeiten • Externe Evaluation • Interne Evaluation • Bildungsrechtliche Grundlagen datenbasierter Qualitätssicherung und -entwicklung • Strategien datenbasierter Steuerung zur Sicherung und Entwicklung von Schulqualität Die HerausgeberDr. Felicitas Thiel ist Professorin im Arbeitsbereich Schulpädagogik an der Freien Universität Berlin.Jasmin Tarkian und Anna Kroupa sind wissenschaftliche Mitarbeiterinnen im Arbeitsbereich Schulpädagogik an der Freien Universität Berlin.Dr. Eva-Maria Lankes ist Professorin für Schulpädagogik an der Technischen Universität München.Norbert Maritzen ist Direktor des Instituts für Bildungsmonitoring und Qualitätsentwicklung in Hamburg.Dr. Thomas Riecke-Baulecke ist Direktor des Instituts für Qualitätsentwicklung an Schulen Schleswig-Holstein.