This chapter demonstrates that the effects of good teaching and academic challenge on leadership and psychological well-being during the first year of college differ for African-American and White students, which suggests that institutional researchers should disaggregate data by race or other relevant student characteristics when trying to…

Item Response Theory (IRT) is a measurement theory that is ideal for scale and test development in institutional research, but it is not without its drawbacks. This chapter provides an overview of IRT, describes an example of its use, and highlights the pros and cons of using IRT in applied settings.

The goal of this chapter is to provide a brief introduction to one of the most rigorous nonexperimental analytical methods currently employed by education researchers: regression discontinuity.

This chapter is a case study of one institution's effort to institutionalize a process through which student development is promoted through active engagement with the community.

Faculty and staff at Indiana University-Purdue University Indianapolis (IUPUI) have developed several tools to assess campus civic engagement initiatives. This chapter describes the IUPUI Faculty Survey and the Civic-Minded Graduate Scale, and reports on findings from campus-based assessment and research.

Efforts to develop common higher education data standards are expanding both within and across countries. The institutional research (IR) community plays a critical role in assuring that these efforts capture the diverse manifestations of the postsecondary and tertiary education systems and promote responsible comparisons. This chapter provides…

This chapter presents a synthesis of the conceptualization and practice of institutional research (IR) in higher education (HE) in emerging countries across Southern Africa, Latin America and the Middle East and North Africa (MENA) regions. The chapter contextualizes the growing need for IR in these regions, identifies problems and challenges…

The upcoming challenge for higher education institutions (HEIs) globally is how to respond to an increasing variety of societal needs but with fewer public resources and increased accountability demands. In this chapter we draw attention to the central role institutional research (IR) professionals play in positioning HEIs in a competitive and…

Although institutional research has been a significant feature of U.S. higher education for more than 50 years, it is not so well understood in other parts of the world. As higher education around the world faces increasingly challenging times in responding to pressures of massification and globalization, increasing forms of accountability and…

While individuals in each country or part of the world face unique issues, many challenges facing higher education today are similar across the world. The great majority of higher education systems have grown in recent decades, enrolling far more students than they did in prior years and expanding their activities into new spheres such as economic…

Multilevel modeling offers researchers a rich array of tools that can be used for a variety of purposes, such as analyzing specific institutional issues, looking for macro-level trends, and helping to shape and inform educational policy. One of the more complex multilevel modeling tools available to institutional researchers is cross-classified…

Multilevel modeling (MLM), also referred to as hierarchical linear modeling (HLM) or mixed models, provides a powerful analytical framework through which to study colleges and universities and their impact on students. Due to the natural hierarchical structure of data obtained from students or faculty in colleges and universities, MLM offers many…

Understanding the suitability of multilevel modeling in the context of institutional research (IR) may ease the doubts of some IR professionals. However, the need for training on how to conduct and report multilevel modeling analysis remains. A major roadblock hindering the proliferation of multilevel modeling in IR is the perception that…

This article is designed to give the reader a conceptual, nontechnical overview of estimation and model fit issues in multilevel modeling (MLM). The process of MLM generally involves fitting a series of multilevel models that increase in complexity. When conducting multilevel analyses, it is important to balance the need for complexity and the…

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…