对国际在线教育评估系统日志数据的分析：一种多状态生存模型方法用于行动序列间的反应时间
Analysis of Log Data from an International Online Educational Assessment System: A Multi-state Survival Modeling Approach to Reaction Time between and across Action Sequence
AI总结：
本文提出多状态生存模型分析在线教育评估系统日志数据，研究受试者在行动间的反应时间及影响因素。
摘要：
随着计算机基于或在线评估的日益可用，研究人员对分析日志数据以提高我们对受试者问题解决过程的理解表现出浓厚兴趣。在本文中，我们提出了一种多状态生存模型（MSM）来分析日志文件中的行动序列数据，重点是建模受试者在行动之间的反应时间，以研究哪些因素以及它们如何影响受试者在行动之间的转换速度。我们特别识别出区分正确和错误答案的关键行动，比较这些群体之间的转换概率，并分析其不同的问题解决模式。通过模拟研究和敏感性分析，我们评估了所提出模型的稳健性。我们使用国际成人能力计划（PIAAC）中的问题解决项目来展示所提出的方法。
英文摘要：
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).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
