The Analytics Revolution In Higher Education

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.

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.

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

Co-published with the Association for State Colleges and Universities (AASCU), which sponsored the project from which the book emerged.This book answers the question “What would your institution look like if students really mattered?” The authors argue that really putting student success at the center of attention will require a radical reimagining of higher education. Much of what is presented here is grounded in the findings of the American Association of State Colleges and Universities’ (AASCU’s) Re-Imagining the First Year (RFY) initiative, which brought together 44 member institutions over a three-year period to identify and test programs, strategies, and tools aimed at improving retention rates for first-year students. The book makes a provocative set of arguments about what is possible if campuses radically reimagine their culture, practices, structures, and rules with the primary purpose of helping students succeed in college and beyond.

Gain an overview of learning analytics technologies in higher education, including broad considerations and the barriers to introducing them. This volume features the work of practitioners who led some of the most notable implementations, like: the Open Learning Initiative now at Stanford University, faculty-led projects at the University of Michigan, including ECoach and SLAM, the University of Maryland, Baltimore Countys Check My Activity and Indiana Universitys FLAGS early warning system and e-course advising initiatives. Readers will glean from these experiences, as well as from a national project in Australia on innovative approaches for enhancing student experience, an informed description of the role of feedback within these technologies, and a thorough discussion of ethical and social justiceissues related to the use of learning analytics, and why higher education institutions should approach such initiatives cautiously, intentionally, and collaboratively. This is the 179th volume of the Jossey-Bass quarterly report series New Directions for Higher Education. Addressed to presidents, vice presidents, deans, and other higher education decision makers on all kinds of campuses, it provides timely information and authoritative advice about major issues and administrative problems confronting every institution.

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.

Learning analytics (or educational big data) tools are increasingly being deployed on campuses to improve student performance, retention and completion, especially when those metrics are tied to funding. Providing personalized, real-time, actionable feedback through mining and analysis of large data sets, learning analytics can illuminate trends and predict future outcomes. While promising, there is limited and mixed empirical evidence related to its efficacy to improve student retention and completion. Further, learning analytics tools are used by a variety of people on campus, and as such, its use in practice may not align with institutional intent. This monograph delves into the research, literature, and issues associated with learning analytics implementation, adoption, and use by individuals within higher education institutions. With it, readers will gain a greater understanding of the potential and challenges related to implementing, adopting, and integrating these systems on their campuses and within their classrooms and advising sessions. This is the fifth issue of the 43rd volume of the Jossey-Bass series ASHE Higher Education Report. Each monograph is the definitive analysis of a tough higher education issue, based on thorough research of pertinent literature and institutional experiences. Topics are identified by a national survey. Noted practitioners and scholars are then commissioned to write the reports, with experts providing critical reviews of each manuscript before publication.

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.