Accurate Assessment via Process Data

Susu Zhang, Zhi Wang, Jitong Qi, Jingchen Liu, Zhiliang Ying

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)76–97
Number of pages22
Issue number1
Early online dateAug 13 2022
StatePublished - Mar 2023


  • ability estimation
  • automated scoring
  • Process data
  • Rao–Blackwellization

ASJC Scopus subject areas

  • General Psychology
  • Applied Mathematics


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