Congratulations to Susu Zhang, Assistant Professor of Psychology and Statistics, who has been awarded an AERA-NSF grant!
Researchers from the University of Illinois at Urbana-Champaign and the University of Georgia propose to analyze the 2017 NAEP Grade 8 Mathematics process, outcome, and survey data to understand students' revision and review behavior in large-scale computer-based assessments. The 2017 NAEP Grade 8 Mathematics digital assessment allowed students to freely navigate between questions within a test form to review and revise previously visited problems. The process data, i.e., the computer logged events of the students' series of question navigations, clicks, entries, and the associated timestamps throughout the test, response data (e.g., final scores on each math problem), and the student, teacher, and school survey data were released by NCES as restricted-use data. This allows the analysis of individuals' revision and review behavior on each item throughout the test, which may contain meaningful information for both test design and instructions. The proposed project will couple statistical and machine learning methods for sequence data and psychometric theory to address the following research questions: (1) How to extract features and clusters from unstructured revision and review log data? (2) What tools can be deployed to interpret revision and review log features and clusters? (3) What are the typical patterns of revision and review behavior in large-scale, low-stakes computer-based math assessments? (4) What are the relationships between revision behavior and math proficiency and student self-reported noncognitive characteristics (e.g., motivation, persistence, interest, and pressure)? (5) What are the relationships between demographic and instructional covariates and revision and review behavior?