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Activity Number: 394 - Recent Advances in Cognitive Diagnosis Modeling
Type: Topic Contributed
Date/Time: Tuesday, July 31, 2018 : 2:00 PM to 3:50 PM
Sponsor: Mental Health Statistics Section
Abstract #329080
Title: An Exploration of Latent Structure in Process Data
Author(s): Jingchen Liu* and Yunxiao Chen and Xueying Tang and Zhi Wang
Companies: Columbia University and Emory University and Columbia University and Columbia University
Keywords:
Abstract:

In classic tests, item responses are often expressed as univariate categorical variables. Computer-based tests allow us to track students' entire problem solving processes through log files. In this case, the response to each item is a time-stamped process containing students' detailed behaviors and their interaction with the simulated environment. The key questions are whether and how much more information are contained in the detailed response processes additional to the traditional responses (yes/no or partial credits). Furthermore, we also need to develop methods to systematically extract such information from the process responses that often contain a substantial amount of noise. In this talk, I present exploratory analysis of process data in PIAAC and PISA. The results confirm that the process data do contain a significant amount of additional information and they also provide guideline on efficient item design for future studies.


Authors who are presenting talks have a * after their name.

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