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Using Data to Improve Teacher Education by Charles A. Peck,Kristen Cuthrell,Désirée H. Pointer Mace,Tine Sloan,Diana B. Lys Pdf
"A collaborative effort between researchers and practitioners, this volume presents lessons learned to assist teacher educators who are engaged daily with the challenges of making data useful and used in their programs. Readers will see how the work carried out in "high data use" teacher education programs strengthened local program identity and coherence"--
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.
The Analytics Revolution in Higher Education by Jonathan S. Gagliardi,Amelia Parnell,Julia Carpenter-Hubin Pdf
Co-published with and In this era of “Big Data,” institutions of higher education are challenged to make the most of the information they have to improve student learning outcomes, close equity gaps, keep costs down, and address the economic needs of the communities they serve at the local, regional, and national levels. This book helps readers understand and respond to this “analytics revolution,” examining the evolving dynamics of the institutional research (IR) function, and the many audiences that institutional researchers need to serve.Internally, there is a growing need among senior leaders, administrators, faculty, advisors, and staff for decision analytics that help craft better resource strategies and bring greater efficiencies and return-on-investment for students and families. Externally, state legislators, the federal government, and philanthropies demand more forecasting and more evidence than ever before. These demands require new and creative responses, as they are added to previous demands, rather than replacing them, nor do they come with additional resources to produce the analysis to make data into actionable improvements. Thus the IR function must become that of teacher, ensuring that data and analyses are accurate, timely, accessible, and compelling, whether produced by an IR office or some other source. Despite formidable challenges, IR functions have begun to leverage big data and unlock the power of predictive tools and techniques, contributing to improved student outcomes.
Adoption of Data Analytics in Higher Education Learning and Teaching by Dirk Ifenthaler,David Gibson Pdf
The book aims to advance global knowledge and practice in applying data science to transform higher education learning and teaching to improve personalization, access and effectiveness of education for all. Currently, higher education institutions and involved stakeholders can derive multiple benefits from educational data mining and learning analytics by using different data analytics strategies to produce summative, real-time, and predictive or prescriptive insights and recommendations. Educational data mining refers to the process of extracting useful information out of a large collection of complex educational datasets while learning analytics emphasizes insights and responses to real-time learning processes based on educational information from digital learning environments, administrative systems, and social platforms. This volume provides insight into the emerging paradigms, frameworks, methods and processes of managing change to better facilitate organizational transformation toward implementation of educational data mining and learning analytics. It features current research exploring the (a) theoretical foundation and empirical evidence of the adoption of learning analytics, (b) technological infrastructure and staff capabilities required, as well as (c) case studies that describe current practices and experiences in the use of data analytics in higher education.
Using Data to Improve Student Learning in School Districts by Victoria Bernhardt Pdf
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.
Using Data to Improve Student Learning by Graham S. Maxwell Pdf
This book offers a coherent research-based overview and analysis of theories and practices in using data to improve student learning. It clarifies what 'use of data' means and differentiates the different levels of decision-making in education (relating to the system, district, school, classroom, or individual student). The relationship between data and decision-making is considered and various movements in the use of data to improve student learning are analysed, especially from the perspective of their assumptions and effects. This leads to a focus on effective educational decision-making as a social process requiring collaboration among all relevant participants. It also requires a clear understanding of educational aims, and these are seen to transcend what can be assessed by standardised tests. The consequences of this analysis for decision processes are explored and conclusions are drawn about what principles might best guide educational practice as well as what ambiguities remain. Throughout, the focus is on what existing research says about each of the issues explored. .
How Colleges Use Data by Jonathan S. Gagliardi Pdf
What does a culture of evidence really look like in higher education? The use of big data and the rapid acceleration of storage and analytics tools have led to a revolution of data use in higher education. Institutions have moved from relying largely on historical trends and descriptive data to the more widespread adoption of predictive and prescriptive analytics. Despite this rapid evolution of data technology and analytics tools, universities and colleges still face a number of obstacles in their data use. In How Colleges Use Data, Jonathan S. Gagliardi presents college and university leaders with an important resource to help cultivate, implement, and sustain a culture of evidence through the ethical and responsible use and adoption of data and analytics. Gagliardi provides a broad context for data use among colleges, including key concepts and use cases related to data and analytics. He also addresses the different dimensions of data use and highlights the promise and perils of the widespread adoption of data and analytics, in addition to important elements of implementing and scaling a culture of evidence. Demystifying data and analytics, the book helps faculty and administrators understand important topics, including: • How to define institutional aspirations using data • Equity and student success • Strategic finance and resource optimization • Academic quality and integrity • Data governance and utility • Implicit and explicit bias in data • Implementation and planning • How data will be used in the future How Colleges Use Data helps college and university leaders understand what a culture of evidence in higher education truly looks like.
Using Data to Improve Learning for All by Nancy Love Pdf
Collaborative inquiry + effective use of data = significant leaps in learning and achievement! This resource combines a powerful collaborative inquiry process, reflective dialogue, and rigorous use of data to improve outcomes for all students. The editor and contributors provide detailed examples of schools that have demonstrated dramatic gains by building collaborative cultures, nurturing ongoing inquiry, and using data systematically. The book shows school leaders how to: Implement collaborative inquiry to meet accountability mandates Build and support a high-performing data culture Establish a school climate characterized by collective responsibility for student learning and a respect for students’ cultures
George D. Kuh,Stanley O. Ikenberry,Natasha A. Jankowski,Timothy Reese Cain,Peter T. Ewell,Pat Hutchings,Jillian Kinzie
Author : George D. Kuh,Stanley O. Ikenberry,Natasha A. Jankowski,Timothy Reese Cain,Peter T. Ewell,Pat Hutchings,Jillian Kinzie Publisher : John Wiley & Sons Page : 309 pages File Size : 52,5 Mb Release : 2015-01-20 Category : Education ISBN : 9781118903391
Using Evidence of Student Learning to Improve Higher Education by George D. Kuh,Stanley O. Ikenberry,Natasha A. Jankowski,Timothy Reese Cain,Peter T. Ewell,Pat Hutchings,Jillian Kinzie Pdf
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.
Using Data to Improve Teacher Education by Charles Peck,Kristen Cuthrell,Désirée H. Pointer Mace,Tine Sloan,Diana Lys Pdf
This book offers concrete examples of how data can be used by faculty, staff, and program leaders to improve their collective work as teacher educators. Strong external accountability mandates often lead to tensions that undermine local morale and motivation. This volume focuses on the practical work of navigating these tensions so that valuable programmatic change can happen. It describes policies and practices drawn from a study of “high data use” teacher education programs from around the country that have strategically engaged the challenges of learning to use data for program improvement. Readers will see how the data-use work carried out in these programs strengthened local program identity and coherence. Representing a collaborative effort between researchers and practitioners, this volume presents lessons learned to assist teacher educators who are engaged daily with the challenges of making data useful and used in their programs. Book Features: Examples of how tensions between external mandates for accountability and program improvement can be navigated in ways that are grounded in local program values.Detailed case study portraits of individual programs that offer a full and action-oriented sense of data use work.Strategies for ensuring that data systems are responsive to multiple stakeholders, such as faculty, administrators, students, and policymakers.A diversity of perspectives and experiences from small liberal arts colleges, large teacher preparation institutions, and research-intensive universities.
Cultivating a Data Culture in Higher Education by Kristina Powers,Angela E. Henderson Pdf
Higher education institutions have experienced a sharp increase in demand for accountability. To meet the growing demand by legislators, accreditors, consumers, taxpayers, and parents for evidence of successful outcomes, this important book provides higher education leaders and practitioners with actionable strategies for developing a comprehensive data culture throughout the entire institution. Exploring key considerations necessary for the development of an effective data culture in colleges and universities, this volume brings together diverse voices and perspectives, including institutional researchers, senior academic leaders, and faculty. Each chapter focuses on a critical element of managing or influencing a data culture, approaches for breaking through common challenges, and concludes with practical, research-based implementation strategies. Collectively, these strategies form a comprehensive list of recommendations for developing a data culture and becoming a change agent within your higher education institution.
Learning Analytics in Higher Education by Jaime Lester,Carrie Klein,Aditya Johri,Huzefa Rangwala Pdf
Learning Analytics in Higher Education provides a foundational understanding of how learning analytics is defined, what barriers and opportunities exist, and how it can be used to improve practice, including strategic planning, course development, teaching pedagogy, and student assessment. Well-known contributors provide empirical, theoretical, and practical perspectives on the current use and future potential of learning analytics for student learning and data-driven decision-making, ways to effectively evaluate and research learning analytics, integration of learning analytics into practice, organizational barriers and opportunities for harnessing Big Data to create and support use of these tools, and ethical considerations related to privacy and consent. Designed to give readers a practical and theoretical foundation in learning analytics and how data can support student success in higher education, this book is a valuable resource for scholars and administrators.
Big Data on Campus by Karen L. Webber,Henry Y. Zheng Pdf
How data-informed decision making can make colleges and universities more effective institutions. The continuing importance of data analytics is not lost on higher education leaders, who face a multitude of challenges, including increasing operating costs, dwindling state support, limits to tuition increases, and increased competition from the for-profit sector. To navigate these challenges, savvy leaders must leverage data to make sound decisions. In Big Data on Campus, leading data analytics experts and higher ed leaders show the role that analytics can play in the better administration of colleges and universities. Aimed at senior administrative leaders, practitioners of institutional research, technology professionals, and graduate students in higher education, the book opens with a conceptual discussion of the roles that data analytics can play in higher education administration. Subsequent chapters address recent developments in technology, the rapid accumulation of data assets, organizational maturity in building analytical capabilities, and methodological advancements in developing predictive and prescriptive analytics. Each chapter includes a literature review of the research and application of analytics developments in their respective functional areas, a discussion of industry trends, examples of the application of data analytics in their decision process, and other related issues that readers may wish to consider in their own organizational environment to find opportunities for building robust data analytics capabilities. Using a series of focused discussions and case studies, Big Data on Campus helps readers understand how analytics can support major organizational functions in higher education, including admission decisions, retention and enrollment management, student life and engagement, academic and career advising, student learning and assessment, and academic program planning. The final section of the book addresses major issues and human factors involved in using analytics to support decision making; the ethical, cultural, and managerial implications of its use; the role of university leaders in promoting analytics in decision making; and the need for a strong campus community to embrace the analytics revolution. Contributors: Rana Glasgal, J. Michael Gower, Tom Gutman, Brian P. Hinote, Braden J. Hosch, Aditya Johri, Christine M. Keller, Carrie Klein, Jaime Lester, Carrie Hancock Marcinkevage, Gail B. Marsh, Susan M. Menditto, Jillian N. Morn, Valentina Nestor, Cathy O'Bryan, Huzefa Rangwala, Timothy Renick, Charles Tegen, Rachit Thariani, Chris Tompkins, Lindsay K. Wayt, Karen L. Webber, Henry Y. Zheng, Ying Zhou
