Every Learner Everywhere

Toward Ending the Monolithic View of “Underrepresented Students”

Why Higher Education Must Account for Racial, Ethnic, and Economic Variations In Barriers to Equity

Higher education in the United States has a tendency to treat all “underrepresented” students as a monolith in ways that are counterproductive to the cause of equity. This aggregation of racially and ethnically minoritized, poverty-affected, and first-generation students obscures significant variations in admissions, course-level outcomes, persistence, graduation, and career success. Digital learning is particularly lacking in disaggregated data. To make progress on equity, educators and institutional leaders must be able to balance seeing and examining the patterns of lived experience among people in specific student populations with hearing how every student’s experience is unique.

Toward Ending the Monolithic View of “Underrepresented Students”: Why Higher Education Must Account for Racial, Ethnic, and Economic Variations in Barriers to Equity, synthesizes commentary, research, and programmatic activity on how higher education has grappled with disaggregating and using student data to confront and close equity gaps for particular student populations. A literature review of relevant studies and commentary was complemented by original interviews with 17 experts, including faculty, administrators, researchers, advocates, and students. Those experts are quoted at length throughout the report. The purpose of the report is to advance high-level evidence-based conversation about equity and learning — especially digital learning — in U.S. colleges and universities.

Toward Ending the Monolithic View of “Underrepresented Students” is organized into two parts:

  • Part 1: Why and How Accounting for Variations in Student Populations Matters for Equity
  • Part 2: What Works to Remove Barriers to Equity for Unique Populations

Interwoven into those parts are sections with background and related information including:

  • the history and context of these racial, ethnic, and economic categories;
  • the various ways first generation is defined;
  • how historically Black colleges and universities (HBCUs) and tribal colleges and universities (TCUs) provide models for equity-centered institutional culture;
  • exemplar programs; and 
  • resources and tools for creating equity-centered educational institutions.

An Appendix details where disaggregated student data does exist and provides a sampling of how that data could create more precise profiles of racially and ethnically minoritized students. 

Download the full report Download the executive summary

Recommended citatation:

McGuire, R. (2022, September, 1) Toward Ending the Monolithic View of “Underrepresented Students”: Why Higher Education Must Account for Racial, Ethnic, and Economic Variations in Barriers to Equity. Every Learner Everywhere. https://www.everylearnereverywhere.org/resources/toward-ending-the-monolithic-view-of-underrepresented-students

Other Related Resources

Pillar Resource
Report cover with title, Annual Impact Report 2024, with photo of black female student smiling under a tree holding a laptop.

May 2025

In this annual impact report, read about the network’s impact in areas of the services we provide institutions, our thought leadership in the field, and engagements with students. In addition, we recap our 2024 network convening, spotlight institutional services, feature our student interns, and give readers a preview of what’s next for the network in 2025.

Pillar Resource
Cover of Accessible AI resource. Title: Where AI Meets Accessibility Report with title and photo of female student on laptop taking notes. Every Learner logo and Teach access logo at the bottom.

March 2025

As AI becomes increasingly embedded into educational settings and practices, it offers both opportunities and challenges. This comprehensive resource will help navigate both aspects — demonstrating how AI can help overcome technology barriers, including various recommendations for integrating accessible AI across different areas of higher education.