Measuring Student Success in an Era of Heightened Accountability and Big Data

Measuring Student Success in an Era of Heightened Accountability and Big Data

Jennifer L. Ivie
Copyright: © 2020 |Pages: 22
DOI: 10.4018/978-1-7998-2410-7.ch006
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Higher education in the United States has been called to the mat to prove the return on investment by students, taxpayers, governments, and other funding sources. This call for accountability requires the use of “big” data to demonstrate student success, continuous improvement, and stewardship. However, using big data in the U.S. higher education system is still a newer concept. The available research and tools for this work is growing as institutions embrace this new era. This chapter explores the use of big data in higher education in the United States through the framework of the historical perspective, current trends, and changing needs and demographics of the nation.
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Gravetter and Wallnau (2013) define data simply as “measurements or observations” (p. 7). Data is the information gathered about the world. Data can come in the form of numbers (quantitative data) or words, images, etc. (qualitative data) and can be used to describe phenomena or make inferences about the why or how about phenomena. In higher education, data is collected about our students, employees, courses, services, facilities, institutions, competition, partners, and community. In today’s digital world, there are endless measurements and observations on each and every person. In higher education, the plethora of data available on our students is growing exponentially on an almost daily basis. The challenge is reigning in these data points to create usable information to make decisions on how to best serve our students and communities.

This chapter explores the use of data in higher education in the United States. The chapter will examine the historical perspective of higher education, accreditation, assessment, and reporting of data, as well as current measures of student success employed by national, regional, and state entities to hold postsecondary institutions accountable for creating an educated workforce. Finally, this work will discuss some movements within the United States to change the conversation around defining and measuring student success due to shortfalls of current measures.

To begin a discussion of data trends in American higher education, it is important to understand the history of this higher education system, and how it has shaped our policies, procedures, and practices around accountability, data use, assessment, and equity.

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