Case study of the use of learner-centered assessment in the math school of a large university in the United States

ABSTRACT

This case study examined the current assessment practices in the math school of a large research university in the United States. After reviewing a sample of course syllabi offered in the spring 2021 semester, we descriptively summarized the use of 19 assessment methods in the school and examined the assessment patterns by subjects, class standings, and class size. Our study found that traditional homework and written tests were the most frequently used assessments in the school, while the use of learner-centered assessments was rare. Among the 19 assessment methods, we found significantly different usage of quizzes, participation scores, and projects by various course characteristics. Our case study demonstrates the gap between the recommended and actual assessment practice in U.S. higher education. We call for more future research that explores strategies to effect changes and increase the use of learner-centered assessment in higher education institutions.

KEYWORDS:

• Assessment practices
• learner-centered assessment
• higher education

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Notes

1 An “R1” university in the United States refers to “Doctoral Universities – Very High Research Activity”, as classified by the Carnegie Classification of Institutions of Higher Education.

2 A recitation refers to a type of instructional session that complements the main lecture course. Recitations are often smaller, more interactive classes where students have the opportunity to discuss the lecture material, ask questions, and engage in problem-solving activities.

3 Note that the focus of this article is synchronous lectures, which excludes asynchronous online courses. Within the broader scope of both synchronous and asynchronous courses, this category also includes self-paced participation in online course modules, such as logging into the online course platform and learn at least two topics on three different days per week.

Additional information

Notes on contributors

Yi Zheng

Yi Zheng, Ph.D., is an Associate Professor of Arizona State University, Tempe, Arizona, U.S.A. Her primary research interests include both the broader topics on educational measurement and assessment and the more specific topics on advancing methods and technology of test design, delivery, scoring, and analysis, especially adaptively testing.

Fern Van Vliet

Fern Van Vliet is a Mathematics Education Ph.D. student at the School of Mathematical and Statistical Sciences of Arizona State University. Her research focuses on student emotions and the relationship between emotions and problem-solving.

Jeong Im Jin

Jeongim Jin is a Ph.D. graduate in Quantitative Research Methods at Arizona State University. Her research focuses on quantitative research designs and methods, machine learning, and assessment and measurement.