Accurate Assessment via Process Data

Susu Zhang, Zhi Wang, Jitong Qi, Jingchen Liu () and Zhiliang Ying
Additional contact information
Susu Zhang: University of Illinois at Urbana-Champaign
Zhi Wang: Citadel Securities
Jitong Qi: Columbia University
Jingchen Liu: Columbia University
Zhiliang Ying: Columbia University

Psychometrika, 2023, vol. 88, issue 1, No 4, 76-97

Abstract: Abstract Accurate assessment of a student’s ability is the key task of a test. Assessments based on final responses are the standard. As the infrastructure advances, substantially more information is observed. One of such instances is the process data that is collected by computer-based interactive items and contain a student’s detailed interactive processes. In this paper, we show both theoretically and with simulated and empirical data that appropriately including such information in the assessment will substantially improve relevant assessment precision.

Keywords: Process data; ability estimation; automated scoring; Rao–Blackwellization (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11336-022-09880-8

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