Improving Educational Assessment: Multivariate Statistical Methods

Abstract

This review presents two case studies that illustrate how multivariate statistical modeling applies to the specific goal of improving educational assessment. The first case study involves the development of a new large-scale English language proficiency assessment system (called the English Language Proficiency Assessment for the 21st Century; ELPA21). The second application concerns efforts to quantify student progress in learning using conditional growth models, a topic of current debate about assessment policy. A popular measure, Student Growth Percentile (SGP), is explored through the lens of multivariate statistical analysis. It is concluded that collaboration between researchers and practice stakeholders can improve assessments that benefit student learning.