activity
20112021
most citedItem Response Theory -- A Statistical Framework for Educational and Psychological Measurement

17 citations · 46 across the 8 of their papers we have counts for

collaborators

9 papers

stat.ME202117 cited

Item Response Theory -- A Statistical Framework for Educational and Psychological Measurement

Yunxiao Chen, Xiaoou Li, Jingchen Liu +1

Item response theory (IRT) has become one of the most popular statistical models for psychometrics, a field of study concerned with the theory and techniques of psychological measu…

stat.AP20215 cited

External Correlates of Adult Digital Problem-Solving Behavior: Log Data Analysis of a Large-Scale Assessment

Susu Zhang, Xueying Tang, Qiwei He +2

Using the action sequence data (i.e., log data) from the problem-solving in technology-rich environments assessment on the 2012 Programme for the International Assessment of Adult…

cs.HC20201 cited

Subtask Analysis of Process Data Through a Predictive Model

Zhi Wang, Xueying Tang, Jingchen Liu +1

Response process data collected from human-computer interactive items contain rich information about respondents' behavioral patterns and cognitive processes. Their irregular forma…

stat.CO20201 cited

ProcData: An R Package for Process Data Analysis

Xueying Tang, Susu Zhang, Zhi Wang +2

Process data refer to data recorded in the log files of computer-based items. These data, represented as timestamped action sequences, keep track of respondents' response processes…

stat.ML2019

An Exploratory Analysis of the Latent Structure of Process Data via Action Sequence Autoencoder

Xueying Tang, Zhi Wang, Jingchen Liu +1

Computer simulations have become a popular tool of assessing complex skills such as problem-solving skills. Log files of computer-based items record the entire human-computer inter…

stat.ME20174 cited

Optimal Stopping and Worker Selection in Crowdsourcing: an Adaptive Sequential Probability Ratio Test Framework

Xiaoou Li, Yunxiao Chen, Xi Chen +2

In this paper, we aim at solving a class of multiple testing problems under the Bayesian sequential decision framework. Our motivating application comes from binary labeling tasks…