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ETS R&D

Quality assessments, groundbreaking research and measurement, and user-driven educational solutions

Learn more about ETS Research & Development.

 

Psychometric and Data Science Modeling Group

Guided by learning science principles, members in the Psychometric and Data Science Modeling group innovate and apply methods from psychometrics, data science and artificial intelligence to big educational data. The group applies these methods to evaluate and predict how learners:

  • process and interpret information
  • interact with tasks, technology and other learners

Current projects

The current research of the PDSM group focuses on:

  • process data mining and modeling, collaborative problem-solving, learner behavior analytics and test security
  • response process data mining, analytics and modeling
  • assessment of 21st-century skills, such as collaborative problem-solving

Sample publications

Gong, T., Jiang, Y., Saldivia, L. E., & Agard, C. (in press). Using Sankey diagrams to visualize drag and drop action sequences in technology-enhanced items. Behavior Research Methods.

He, Q., Borgonovi, F., Paccagnella, M. (2021). Leveraging process data to assess adults' problem-solving skills: Identifying generalized behavioral patterns with sequence miningComputers and Education, 166, 104170.

Jiang, Y., Gong, T., Saldivia, L. E., Cayton-Hodges, G., & Agard, C. (2021). Using process data to understand problem-solving strategies and processes for drag-and-drop items in a large-scale mathematics assessment. Large-scale Assessments in Education, 9(1), 1–31.

Zhang, M., Bennett, R., Deane, P., & van Rijn, P. (2019). Are there gender differences in how students write their essays? An analysis of writing processes. Educational Measurement: Issues and Practice, 38, 12–26.

Hao, J., & Mislevy, R. J. (2019). Characterizing interactive communications in computer-supported collaborative problem-solving tasks: A conditional transition profile approach. Frontiers in Psychology, 10, 1011.