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In recent decades, higher education systems and institutions have been called to respond to an unprecedented number of challenges. Major challenges emerged with the phenomenal increase in the demand for higher education and the associated massive expansion of higher education systems. In response universities were called to adopt planning and research methods that would enable them to identify and address the needs of a larger, more diverse student body. Higher education institutions began to place greater emphasis on planning and marketing, seeking to maintain their position in an increasingly competitive higher education market. Under the current economic downturn, universities are under pressure to further cut costs while maintaining their attractiveness to prospective students.As a result educational policy makers and administrators are called to select the 'right' alternatives, aiming for both efficiency and effectiveness in delivered outcomes. This book provides insights into the use of data as an input in planning and improvement initiatives in higher education. It focuses on uses (and potential abuses) of data in educational planning and policy formulation, examining several practices and perspectives relating to different types of data. The book is intended to address the need for the collection and utilization of data in the attempt to improve higher education both at the systemic and the institutional level.
Internal and external pressure continues to mount for college professionals to provide evidence of successful activities, programs, and services, which means that, going forward, nearly every campus professional will need to approach their work with a data-informed perspective.But you find yourself thinking “I am not a data person”.Yes, you are. Or can be with the help of Amelia Parnell.You Are a Data Person provides context for the levels at which you are currently comfortable using data, helps you identify both the areas where you should strengthen your knowledge and where you can use this knowledge in your particular university role.For example, the rising cost to deliver high-quality programs and services to students has pushed many institutions to reallocate resources to find efficiencies. Also, more institutions are intentionally connecting classroom and cocurricular learning experiences which, in some instances, requires an increased gathering of evidence that students have acquired certain skills and competencies. In addition to programs, services, and pedagogy, professionals are constantly monitoring the rates at which students are entering, remaining enrolled in, and leaving the institution, as those movements impact the institution’s financial position.From teaching professors to student affairs personnel and beyond, Parnell offers tangible examples of how professionals can make data contributions at their current and future knowledge level, and will even inspire readers to take the initiative to engage in data projects.The book includes a set of self-assessment questions and a companion set of action steps and available resources to help readers accept their identity as a data person. It also includes an annotated list of at least 20 indicators that any higher education professional can examine without sophisticated data analyses.
This book helps you make sense of the data your school district collects, including state student achievement results as well as other qualitative and quantitative data. Easy-to-use templates, tools, and examples are available on the accompanying downloadable resources.
This book helps you make sense of the data your school collects, including state student achievement results as well as other qualitative and quantitative data. Easy-to-use templates, tools, and examples are available on the accompanying downloadable resources. High stakes accountability requires that you develop your understanding of who your students are and how to get them where you want them to be.
Our fifth book in the International Research on School Leadership series focuses on the use of data in schools and districts as useful information for leadership and decision making. Schools are awash in data and information, from test scores, to grades, to discipline reports, and attendance as just a short list of student information sources, while additional streams of data feed into schools and districts from teachers and parents as well as local, regional and national policy levels. To deal with the data, schools have implemented a variety of data practices, from data rooms, to data days, data walks, and data protocols. However, despite the flood of data, successful school leaders are leveraging an analysis of their school’s data as a means to bring about continuous improvement in an effort to improve instruction for all students. Nevertheless, some drown, some swim, while others find success. Our goal in this book volume is to bring together a set of chapters by authors who examine successful data use as it relates to leadership and school improvement. In particular, the chapters in this volume consider important issues in this domain, including: • How educational leaders use data to inform their practice. • What types of data and data analysis are most useful to successful school leaders. • To what extent are data driven and data informed practices helping school leaders positively change instructional practice? • In what ways does good data collection and analysis feed into successful continuous improvement and holistic systems thinking? • How have school leadership practices changed as more data and data analysis techniques have become available? • What are the major obstacles facing school leaders when using data for decision making and how do they overcome them?
​This book focuses on the uses of big data in the context of higher education. The book describes a wide range of administrative and operational data gathering processes aimed at assessing institutional performance and progress in order to predict future performance, and identifies potential issues related to academic programming, research, teaching and learning​. Big data refers to data which is fundamentally too big and complex and moves too fast for the processing capacity of conventional database systems. The value of big data is the ability to identify useful data and turn it into useable information by identifying patterns and deviations from patterns​.
American higher education needs a major reframing of student learning outcomes assessment Dynamic changes are underway in American higher education. New providers, emerging technologies, cost concerns, student debt, and nagging doubts about quality all call out the need for institutions to show evidence of student learning. From scholars at the National Institute for Learning Outcomes Assessment (NILOA), Using Evidence of Student Learning to Improve Higher Education presents a reframed conception and approach to student learning outcomes assessment. The authors explain why it is counterproductive to view collecting and using evidence of student accomplishment as primarily a compliance activity. Today's circumstances demand a fresh and more strategic approach to the processes by which evidence about student learning is obtained and used to inform efforts to improve teaching, learning, and decision-making. Whether you're in the classroom, an administrative office, or on an assessment committee, data about what students know and are able to do are critical for guiding changes that are needed in institutional policies and practices to improve student learning and success. Use this book to: Understand how and why student learning outcomes assessment can enhance student accomplishment and increase institutional effectiveness Shift the view of assessment from being externally driven to internally motivated Learn how assessment results can help inform decision-making Use assessment data to manage change and improve student success Gauging student learning is necessary if institutions are to prepare students to meet the 21st century needs of employers and live an economically independent, civically responsible life. For assessment professionals and educational leaders, Using Evidence of Student Learning to Improve Higher Education offers both a compelling rationale and practical advice for making student learning outcomes assessment more effective and efficient.
In recent decades, higher education systems and institutions have been called to respond to an unprecedented number of challenges. Major challenges
Thanks to initiatives like the Common Core and Race to the Top, accountability requirements continue to be a reality for educators. Yet many are still unsure of how to use data to make well-informed instructional decisions. The Data-Driven Classroom comes to the rescue with a systematic, universal process that shows teachers how to: examine student assessment results to identify a curricular or skill area to target for individual intervention or large-group instructional revision; develop, implement, and assess the effectiveness of the intervention or revision; and develop an action plan for future instructional cycles. Author Craig A. Mertler sheds light on how teachers can make sense of overwhelming standardized test reports while avoiding pitfalls like over-interpreting data. In these pages you will also find practical classroom examples and templates designed to guide teachers of all grade levels and subject areas through the comprehensive decision-making framework.
Data 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.