Responsible AI-Augmented Judgment and Productive Cognitive Friction in Higher Education: The RABJ Study
Abstract
This OSF project documents the Responsible AI-Augmented Judgment (RABJ) study, a multilevel field study examining productive cognitive friction and responsible human judgment under two active generative artificial intelligence (GenAI) conditions in higher education. The study involved 120 undergraduate students organized into 24 pre-existing teams across four course sections and two disciplinary contexts—Business and Engineering and Sciences. The repository provides the study documentation, authorized de-identified numerical data, measurement and scoring materials, technical-validation outputs, and reproducible analytical resources associated with the RABJ research program. Materials are organized to distinguish raw-like de-identified data, processed analysis-ready data, aggregate outputs, instruments and scoring documentation, and reproducibility resources. The public repository excludes direct identifiers, student-generated text, submitted student work, original institutional linkage keys, and the restricted master workbook. Public materials are released subject to institutional governance, disclosure-risk controls, and documented reuse conditions. RABJ is treated as a provisional multidimensional framework represented by a reliable overall indicator and theoretically specified domains. The study also includes neutral individual performance assessment, team-level rubric evaluation, expert content validation, numeric qualitative coding, implementation-fidelity documentation, cluster-aware analytical procedures, and exploratory analyses of performance–self-appraisal patterns. This project is intended to support transparent documentation, reproducibility, secondary analysis, methodological reuse, and future research derived from the RABJ study.
