Latent Class Analysis of Recurrent Events in Problem-Solving Items
Abstract
Computer-based assessment of complex problem-solving abilities is becoming more and more popular. In such an assessment, the entire problem-solving process of an examinee is recorded, providing detailed information about the individual, such as behavioral patterns, speed, and learning trajectory. The problem-solving processes are recorded in a computer log file which is a time-stamped documentation of events related to task completion. As opposed to cross-sectional response data from traditional tests, process data in log files are massive and irregularly structured, calling for effective exploratory data analysis methods. Motivated by a specific complex problem-solving item “Climate Control” in the 2012 Programme for International Student Assessment, the authors propose a latent class analysis approach to analyzing the events occurred in the problem-solving processes. The exploratory latent class analysis yields meaningful latent classes. Simulation studies are conducted to evaluate the proposed approach.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Apr 09, 2018
- Source ID
- 10.1177/0146621617748325
Entities
People
- Guanhua Fang
- Haochen Xu
- Jingchen Liu
- Yunxiao Chen
- Zhiliang Ying
Organizations
- Army Research Office
- Columbia University
- Division of Information and Intelligent Systems
- Division of Social and Economic Sciences
- Emory University
- Fudan University
- National Institutes of Health