@article {2624,
	title = {Latent Class Analysis of Recurrent Events in Problem-Solving Items},
	journal = {Applied Psychological Measurement},
	volume = {42},
	number = {6},
	year = {2018},
	pages = {478-498},
	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 {\textquotedblleft}Climate Control{\textquotedblright} 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.},
	doi = {10.1177/0146621617748325},
	url = {https://doi.org/10.1177/0146621617748325},
	author = {Haochen Xu and Guanhua Fang and Yunxiao Chen and Jingchen Liu and Zhiliang Ying}
}
