A systematic review of the use of log-based process data in computer-based assessments
Surina He, Ying Cui
Abstract
In recent decades, log-based process data has been increasingly used in computer-based assessments to examine test-takers' response patterns and latent traits. This study provides a systematic review of the use of log-based process data in computer-based assessments. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guideline, we identified 2,548 publications, of which 330 were finally included in this study after careful screening and full-text review. The results of this study can assist researchers in better understanding: (1) what are the trends in using log-based process data in computer-based assessments, (2) which process indicators have been constructed from raw log files, (3) what latent constructs have been inferred from process indicators and at what inferential levels, and (4) what are the benefits, challenges, and future recommendations for using log-based process data. By examining these questions, we conclude that the use of log-based process data in computer-based assessment shows many potentials for enhancing the assessment. Therefore, more study using log-based process data in various fields is encouraged to better understand test-takers’ underlying response processes during assessments. Additionally, there is also a considerable demand for validating process indicators and the generalizability of findings. • Provides the overall trends in the use of log-based process data in computer-based assessments. • Categorized the types of process data that has been used in computer-based assessments. • Provided an overview of commonly investigated latent constructs based on process data. • Summarized benefits and challenges for using process data. • Suggested future directions for in-depth use of process data.