For decades, colleges and universities have strived to use data to take bold actions and make big decisions. The result is an expanding community of higher education professionals who are leveraging analytics to deliver optimal learning experiences for students. This chapter will describe the evolution of data use in higher education with a focus…

The expansion of big data and analytics has led to the diffusion of institutional research functions across campus departments. In this new environment, IR professionals expect to lead and coordinate various institutional analyses. This article presents a four-quadrant framework to facilitate the dynamics between data analysis and decision-making.

We provide an overview of existing and emerging ways that institutional researchers can leverage National Student Clearinghouse data to expand a culture of data-driven decision-making across campus, with a focus on examples from the field.

In this chapter, we review the strengths of NCES survey data, provide an example of analyzing NCES survey data to explore the pathways between coursework in career and technical education in high school and postsecondary success, and offer suggestions for future data collection.

As institutions seek to shift into more advanced analytics and data-based decision-support, many institutional research offices face the challenge of meeting the office's current demands while taking on more intricate and specialized work to support decision-making. Given the great need organizations have for information that supports real-time…

The increasing volume of information and the intense pace of its circulation are changing the ways universities access, use, analyze, and provide data. Many have championed the use of large-scale databases to track student admissions and retention, faculty productivity, student wellness, and other phenomena that shape our understandings of higher…

This chapter describes how data analysis and data-driven decision making were critical for designing, developing, and assessing a new academic program. The authors--one, the program's founder; the other, an alumna--begin by highlighting some of the elements in the program's incubation and, subsequently, describe some of the components for data…

This chapter discusses issues and challenges encountered in using large-scale data sets to study educational experiences and subsequent outcomes for American Indian and Alaska Native (AI/AN) students. In this chapter, we argue that the linguistic and cultural diversity of Native peoples, coupled with the legal and political ways in which education…

This chapter provides examples of innovative methods and tools to collect, analyze, and report both quantitative and qualitative data in student affairs assessment.

The methods and models for categorical data analysis cover considerable ground, ranging from regression-type models for binary and binomial data, count data, to ordered and unordered polytomous variables, as well as regression models that mix qualitative and continuous data. This article focuses on methods for binary or binomial data, which are…

Multilevel modeling (MLM) gives researchers the ability to make inferences about organizations where nesting factors will bias results and the assumption of independence is not tenable. This article provides an overview of the variety of data sources that lend themselves to conducting institutional research (IR). It not only serves as a repository…

In this chapter, the author examines the adequacy and appropriateness of self-report data using the lens of construct validity (Kane, 2006; Messick, 1989). Because construct validity focuses on the appropriateness of data for specific uses or interpretations, he limits his discussion to the use of self-report data in scholarly research. Other…

In 2008-2009, the National Collegiate Athletic Association (NCAA) generated television and marketing revenues of approximately $591 million, college sports apparel sales topped $4 billion, and several schools signed multimedia-rights deals for more than $100 million (Berkowitz, 2009; National Collegiate Athletic Association, 2009). At the Division…

Multilevel modeling provides several advantages over traditional ordinary least squares regression analysis; however, reporting results to stakeholders can be challenging. This article suggests some strategies for presenting complex, multilevel data and statistical results to institutional and higher education decision makers. The article is…

Colleges and universities in the United States are being challenged to assess student outcomes and the quality of programs and services. One of the more widely used sources of evidence is student engagement as measured by a cluster of student engagement surveys administered by the Center for Postsecondary Research at Indiana University. They…