Thinking beyond the score: Multidimensional analysis of student performance to inform the next generation of science assessments

Abstract

AbstractConventional assessment analysis of student results, referred to as rubric‐based assessments (RBA), has emphasized numeric scores as the primary way of communicating information to teachers about their students’ learning. In this light, rethinking and reflecting on not only how scores are generated but also what analyses are done with them to inform classroom practices is of utmost importance. Informed by Systemic Functional Linguistics and Latent Dirichlet Allocation analyses, this study utilizes an innovative bilingual (Spanish–English) constructed response assessment of science and language practices for middle and high school students to perform a multilayered analysis of student responses. We explore multiple ways of looking at students’ performance through their written assessments and discuss features of student responses that are made visible through these analyses. Findings from this study suggest that science educators would benefit from a multidimensional model which deploys complementary ways in which we can interpret student performance. This understanding leads us to think that researchers and developers in the field of assessment need to promote approaches that analyze student science performance as a multilayered phenomenon.