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Author: Paul Preuss
Publisher: Routledge
ISBN: 1317924134
Category : Education
Languages : en
Pages : 143
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Book Description
This 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.
Author: Chris O'Neal
Publisher: International Society for Technology in Education
ISBN: 1564844609
Category : Education
Languages : en
Pages : 142
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Book Description
This workbook will serve as your guide to incorporating the data-driven decision making process into your organization’s culture and behavior. O’Neal leads you through setting up teams; warehousing, accessing, and examining data; and finally reflecting on your process. Understand what’s happening in your school environment and how you can make better decisions that will keep you on a path to success.
Author: Theodore J. Kowalski
Publisher: Pearson
ISBN: 9780205496686
Category : Education
Languages : en
Pages : 0
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Book Description
This book integrates theory and practice in decision-making, with a specific focus on data-driven decision making. Applications are demonstrated in the contexts of administration, supervision, and teaching. The book provides a unique contribution to the literature in this field in that the studies of decision theory and data-based decision making are integrated. Focusing on educators assuming leadership roles in school improvement, the book's content is equally relevant for administrators, supervisors, and teachers. The book, however, is centered on data-driven decision making, both as a requirement of the No Child Left Behind Act and as a normative professional standard. Issues related to accumulating, storing, and protecting data in districts and schools also are covered. Applications in administration, supervision, and teaching are demonstrated.
Author: Kim Schildkamp
Publisher: Springer Science & Business Media
ISBN: 9400748159
Category : Education
Languages : en
Pages : 221
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Book Description
In 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.
Author: Paul Preuss
Publisher: Routledge
ISBN: 1317924134
Category : Education
Languages : en
Pages : 143
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Book Description
This 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.
Author: Anthony G. Picciano
Publisher: Prentice Hall
ISBN:
Category : Education
Languages : en
Pages : 260
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Book Description
Brief ContentsPrefacePrologue Concepts and Foundations of Data-Driven Decision Making Introduction to Data-Driven Decision Making Planning and Developing Information Resources Hardware, Software, and People Educational Research Methods and Tools Teachers and Administrators as Researchers Basic Applications Student Data, Demographics, and Enrollments School and the Community Financial Management and Budgeting Supporting Teaching and Learning Supporting Teachers and Their Professional Development Technical Support Review of Statistical Routines Used in this Book Introduction to Spreadsheet Software Introduction to the Statistical Package for the Social Sciences (SPSS) Database Management Terms and Sample Outline Internet Resources for Data-Driven Decision MakingGlossaryIndex Contents PrefacePrologue Concepts and Foundations of Data-Driven Decision Making Introduction to Data-Driven Decision Making Rationale for Adopting Data-Driven Decision Making Purpose of This Book Defining Data-Driven Decision Making An Old Idea: Knowledge Is Power Need for Planning The Systems Approach Organization of This Book SummaryReferences Planning and Developing Information Resources School Districts Take the Lead Defining Information Needs Database Management Systems Long-Term and Short-Term Data Resources SummaryCase StudyReferences Hardware, Software, and People A Brief Look at Infrastructure Hardware for Effective Data Management and Access Client-Server Architecture Software for Data Analysis Developing People Resources The Data Analyst SummaryCase StudyReferences Educational Research Methods and Tools The Scientific Method and Educational Research Educational Research Methods Ethnographic Research Historical Research Descriptive Research Correlational Research Causal Comparative Research Experimental Research Action Research Data Collection Tools Direct Observation Structured Interviews Document Analysis Surveys Test Instruments SummaryCase StudyReferences Teachers and Administrators as Researchers Learning Communities Action Research in Action Trial Testing a Peer Tutoring Program Multiple Intelligences in a Foreign Language Program Advancing to an Inclusion Program SummaryActivitiesReferences Basic Applications Student Data, Demographics, and Enrollments Student Data Enrollment Projections at the District Level Attendance Zones and Individual Schools Taking a Census Special Student Populations SummaryActivitiesReferences School and the Community Partnering with the Community: Broad-Based Surveys Anatomy of a Survey Who Will Participate in the Survey? What Data Will Be Collected? Data Analysis Is the Sample Representative of the High School Population? Do Students Have Access to the Internet? The Committee's Next Steps SummaryActivitiesReferences Financial Management and Budgeting Basic Terminology School District Budget School Budget The Canton Alternative School Budget Emergency SummaryActivitiesReferences Supporting Teaching and Learning States, Cities, Districts, Schools, Classes, Teachers, Students Improving Teaching and Learning Jefferson Middle School Developing a Plan Information Overload: A Caution SummaryActivitiesReferences Supporting Teachers and Their Professional Development Summative and Formative Evaluation Collecting Personnel Data Kingsland School District Case Study Keeping Track of Professional Development SummaryActivitiesReferences Technical Support Review of Statistical Routines Used in this Book Key Terms Descriptive Statistical Procedures Frequency Distributions Contingency Tables (Crosstabulations) Measures of Central Tendency Measures of Dispersion Measures of Relationship Correlational Coefficient Linear Regression Caution Introduction to Spreadsheet Software Overview and Key Terms Spreadsheet Structure Data Types and Data Manipulation Charts and Graphics Introduction to the Statistical Package for the Social Sciences (SPSS) Overview The Data Editor Creating a Data Set Defining Variables Transforming Data Options Data Analysis Procedures and the Output Viewer Graphs and Charts Database Management Terms and Sample Outline Internet Resources for Data-Driven Decision MakingGlossaryIndex.
Author: Thomas C. Redman
Publisher: Harvard Business Press
ISBN: 1422163644
Category : Business & Economics
Languages : en
Pages : 257
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Book Description
Your company's data has the potential to add enormous value to every facet of the organization -- from marketing and new product development to strategy to financial management. Yet if your company is like most, it's not using its data to create strategic advantage. Data sits around unused -- or incorrect data fouls up operations and decision making. In Data Driven, Thomas Redman, the "Data Doc," shows how to leverage and deploy data to sharpen your company's competitive edge and enhance its profitability. The author reveals: · The special properties that make data such a powerful asset · The hidden costs of flawed, outdated, or otherwise poor-quality data · How to improve data quality for competitive advantage · Strategies for exploiting your data to make better business decisions · The many ways to bring data to market · Ideas for dealing with political struggles over data and concerns about privacy rights Your company's data is a key business asset, and you need to manage it aggressively and professionally. Whether you're a top executive, an aspiring leader, or a product-line manager, this eye-opening book provides the tools and thinking you need to do that.
Author: Rajkumar Venkatesan
Publisher: University of Virginia Press
ISBN: 081394516X
Category : Business & Economics
Languages : en
Pages : 278
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Book Description
The authors of the pioneering Cutting-Edge Marketing Analytics return to the vital conversation of leveraging big data with Marketing Analytics: Essential Tools for Data-Driven Decisions, which updates and expands on the earlier book as we enter the 2020s. As they illustrate, big data analytics is the engine that drives marketing, providing a forward-looking, predictive perspective for marketing decision-making. The book presents actual cases and data, giving readers invaluable real-world instruction. The cases show how to identify relevant data, choose the best analytics technique, and investigate the link between marketing plans and customer behavior. These actual scenarios shed light on the most pressing marketing questions, such as setting the optimal price for one’s product or designing effective digital marketing campaigns. Big data is currently the most powerful resource to the marketing professional, and this book illustrates how to fully harness that power to effectively maximize marketing efforts.
Author: Subhashish Samaddar
Publisher:
ISBN: 9780999766965
Category :
Languages : en
Pages :
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Book Description
This book is intended for the students and teachers of evidence based decision making, especially when the evidences are obtained from numerical facts. It specifically covers business modeling, decision analytics, and forecasting. All planning and decision making start with some estimation of what the future holds for a business and thus, we need to forecast the future. Generally, there can be more than one forecast for most real situations based on the model one uses to forecast them. Business modeling can help us with calculating what those multiple forecasts of the future mean for the things that the business is interested in, such as profit, costs, pay off, returns etc. These are also called outcomes. Once we get the forecasts depicting the future, we can devise and assess multiple actions, and choose one of them that get the best outcome for the business. Decision analytics help us with this assessment. This book is best used for problem based learning and instruction. Problem based learning introduces the problem first for the students to work on, along with the instructor. Students learn by doing. They can practice multiple problems for practice until the underlying principles and lessons are understood and absorbed. Then the formal theories and principles are presented to make sense of what the students have already done and learned. This can also be called reversed learning because it reverses the process of the traditional learning method of theory first and problem solving later. The first of the book provides the problem and the second half of the book provides brief theories and principles, and solutions of the problems.
Author: Ellen B. Mandinach
Publisher: Corwin Press
ISBN: 1452279667
Category : Education
Languages : en
Pages : 281
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Book Description
Connect data and instruction to improve practice Gathering data and using it to inform instruction is a requirement for many schools, yet educators are not necessarily formally trained in how to do it. This book helps bridge the gap between classroom practice and the principles of educational psychology. Teachers will find cutting-edge advances in research and theory on human learning and teaching in an easily understood and transferable format. The text’s integrated model shows teachers, school leaders, and district administrators how to establish a data culture and transform quantitative and qualitative data into actionable knowledge based on: Assessment Statistics Instructional and differentiated psychology Classroom management
Author: Mario Vanhoucke
Publisher: Apress
ISBN: 1484234987
Category : Business & Economics
Languages : en
Pages : 164
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Book Description
Discover solutions to common obstacles faced by project managers. Written as a business novel, the book is highly interactive, allowing readers to participate and consider options at each stage of a project. The book is based on years of experience, both through the author's research projects as well as his teaching lectures at business schools. The book tells the story of Emily Reed and her colleagues who are in charge of the management of a new tennis stadium project. The CEO of the company, Jacob Mitchell, is planning to install a new data-driven project management methodology as a decision support tool for all upcoming projects. He challenges Emily and her team to start a journey in exploring project data to fight against unexpected project obstacles. Data-driven project management is known in the academic literature as “dynamic scheduling” or “integrated project management and control.” It is a project management methodology to plan, monitor, and control projects in progress in order to deliver them on time and within budget to the client. Its main focus is on the integration of three crucial aspects, as follows: Baseline Scheduling: Plan the project activities to create a project timetable with time and budget restrictions. Determine start and finish times of each project activity within the activity network and resource constraints. Know the expected timing of the work to be done as well as an expected impact on the project’s time and budget objectives. Schedule Risk Analysis: Analyze the risk of the baseline schedule and its impact on the project’s time and budget. Use Monte Carlo simulations to assess the risk of the baseline schedule and to forecast the impact of time and budget deviations on the project objectives. Project Control: Measure and analyze the project’s performance data and take actions to bring the project on track. Monitor deviations from the expected project progress and control performance in order to facilitate the decision-making process in case corrective actions are needed to bring projects back on track. Both traditional Earned Value Management (EVM) and the novel Earned Schedule (ES) methods are used. What You'll Learn Implement a data-driven project management methodology (also known as "dynamic scheduling") which allows project managers to plan, monitor, and control projects while delivering them on time and within budget Study different project management tools and techniques, such as PERT/CPM, schedule risk analysis (SRA), resource buffering, and earned value management (EVM) Understand the three aspects of dynamic scheduling: baseline scheduling, schedule risk analysis, and project control Who This Book Is For Project managers looking to learn data-driven project management (or "dynamic scheduling") via a novel, demonstrating real-time simulations of how project managers can solve common project obstacles
