A Continuous-Time Dynamic Choice Measurement Model for Problem-Solving Process Data

Yunxiao Chen ()
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Yunxiao Chen: London School of Economics and Political Science

Psychometrika, 2020, vol. 85, issue 4, No 13, 1052-1075

Abstract: Abstract Problem solving has been recognized as a central skill that today’s students need to thrive and shape their world. As a result, the measurement of problem-solving competency has received much attention in education in recent years. A popular tool for the measurement of problem solving is simulated interactive tasks, which require students to uncover some of the information needed to solve the problem through interactions with a computer-simulated environment. A computer log file records a student’s problem-solving process in details, including his/her actions and the time stamps of these actions. It thus provides rich information for the measurement of students’ problem-solving competency. On the other hand, extracting useful information from log files is a challenging task, due to its complex data structure. In this paper, we show how log file process data can be viewed as a marked point process, based on which we propose a continuous-time dynamic choice model. The proposed model can serve as a measurement model for scaling students along the latent traits of problem-solving competency and action speed, based on data from one or multiple tasks. A real data example is given based on data from Program for International Student Assessment 2012.

Keywords: problem solving; measurement; process data; choice model; marked point process (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11336-020-09734-1

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