As we become increasingly acquainted with the rich opportunities that analytics systems can provide, there is a commensurate need to consider the extent to which analytics tools are effectively integrated, with proper training, into the day-to-day functioning of higher education professionals. This chapter explores the extent to which predictive…

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…

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…

This chapter summarizes ten selected issues and common problems that arise in most assessment research projects. These include: (1) the uses of grades in assessment; (2) institutional review boards; (3) research design as a compromise; (4) standardized testing; (5) self-reported measures; (6) missing data; (7) weighting data; (8) conditional…

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…

The author introduces her critical and feminist perspective, elaborates on her critical approach, and discusses how this influenced the development of her research questions, methodology, data analysis, interpretation, and presentation of findings.

Institutional comparison groups can be selected in several ways, depending on the comparison issue. The method chosen involves both technical and political considerations. (Author/MSE)

This case study documents a successful application of data-mining techniques in enrollment management through a partnership between the admissions office, a business administration master's-degree program, and the institutional research office at Willamette University (Salem, Oregon). (Contains 1 table and 3 figures.)

Many do not consider the effect that missing data have on their survey results nor do they know how to handle missing data. This chapter offers strategies for handling item-missing data and provides a practical example of how these strategies may affect results. The chapter concludes with recommendations for preventing and dealing with missing…

Comparative data are relatively easy to obtain, but effective use of the information requires careful planning and may produce unanticipated results. (MSE)

Focusing on student retention and time to degree completion, this study illustrates how institutional researchers may benefit from the power of predictive analyses associated with data-mining tools. The following are appended: (1) Predictors; and (2) Variable Definitions. (Contains 5 figures.)