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The analytics revolution in higher education : big data, organizational learning, and student success /
Co-published with AIR. Co-published with ACE. 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...
| Clasificación: | Libro Electrónico |
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| Otros Autores: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Sterling, Virginia :
Stylus Publishing, LLC.,
2018.
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| Edición: | First edition. |
| Temas: | |
| Acceso en línea: | Texto completo |
| Sumario: | Co-published with AIR. Co-published with ACE. 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. |
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| Descripción Física: | 1 online resource (xv, 220 pages) |
| Bibliografía: | Includes bibliographical references and index. |
| ISBN: | 9781620365786 1620365782 9781620365793 1620365790 |