As institutions of higher education increasingly look to data as evidence to support planning, allocate resources, and inform teaching and pedagogy, ethical considerations regarding learning analytics have evolved from being on the margins to more central in the conversations surrounding institutional uses of student data. After outlining this…

In this chapter, we explore the contexts within which institutional researchers must try to ensure the ethical use of data. We also identify challenges institutional research professionals can face when navigating college culture while trying to ensure the ethical use of data. Finally, we identify potential solutions for improving institutional…

The resources needed to conduct high-quality and large-scale survey research are often beyond the reach of institutional researchers and higher education analysts. However, the National Center for Education Statistics (NCES) provides many national student surveys that researchers can utilize. We outline four NCES studies--the High School…

This chapter will address the importance of intercampus involvement in reporting of gainful employment student-level data that will be used in the calculation of gainful employment metrics by the U.S. Department of Education. The authors will discuss why building relationships within the institution is critical for effective gainful employment…

Decades of research in survey methodology and psychology have yielded important insights about how to create effective and valid survey instruments. As Porter (in press) has argued convincingly, college student surveys often fall well short of these standards by placing unrealistic demands on students' memory and by assuming that students readily…

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…

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…

Most assessment arguments are about measurement. When is it better to use direct versus indirect measures of student learning? Is one standardized test of critical thinking better than another? Is applying rubrics to student work better than using standardized tests? How valid are self-reported measures of learning? Although these arguments are…

In this chapter, the authors explore the effect of incentives on attrition and nonresponse in a multi-institutional longitudinal study. They organize this chapter into three sections. First, they review the literature regarding nonresponse among students and the effects of incentives on attrition and nonresponse in studies that employ…

This article highlights the utility of disaggregating qualitative research and assessment data on Asian American college students. Given the complexity of and diversity within the Asian American population, scholars have begun to underscore the importance of disaggregating data in the empirical examination of Asian Americans, but most of those…

Research studies show that high school experiences, engagement, and academic achievement, as well as entering expectations and attitudes, are important predictors of student success. Therefore, to better understand first-year student engagement, it makes sense to consider the backgrounds and precollege characteristics of entering college students.…

In this article, the author argues that current strategies to study and understand students' identities fall short of fully capturing their complexity. A multi-dimensional perspective and a mixed-methods approach can reveal nuance that is missed with current approaches. The author offers an illustration of how mixed-methods research can promote a…

Data-mining technology's predictive modeling was applied to enhance the prediction of enrollment behaviors of admitted applicants at a large state university. (Contains 4 tables and 6 figures.)

The Wabash National Study of Liberal Arts Education presents a longitudinal analysis of how students change on a number of scales that purport to measure many of the outcomes of liberal learning over the span of a college education. The Wabash Study is designed to collect information longitudinally from students at the beginning and end of their…

This chapter explores how multiple approaches including data mining can help examine how the lengths of student enrollment are associated with varying numbers of advanced placement units. (Contains 3 tables and 5 figures.)