With increasingly available computer-based or online assessments, researchers have shown keen interest in analyzing log data to improve our understanding of test takers’ problem-solving processes. In this paper, we propose a multi-state survival model (MSM) to action sequence data from log files, focusing on modeling test takers’ reaction times between actions, in order to investigate which factors and how they influence test takers’ transition speed between actions. We specifically identify the key actions that differentiate correct and incorrect answers, compare transition probabilities between these groups, and analyze their distinct problem-solving patterns. Through simulation studies and sensitivity analyses, we evaluate the robustness of our proposed model. We demonstrate the proposed approach using problem-solving items from the Programme for the International Assessment of Adult Competencies (PIAAC).

生成讲解博客的中文版本

生成AI智能校验的中文版本