The Sensitivity of a Scenario-Based Assessment of Written Argumentation to School Differences in Curriculum and Instruction
Deane, P., Wilson, J., Zhang, M., Li, C., van Rijn, P., Guo, H., Roth, A., Winchester, E., & Richter, T. (2021). The sensitivity of a scenario-based assessment of written argumentation to school differences in curriculum and instruction. International Journal of Artificial Intelligence in Education, 31(1), 57-98. https://doi.org/10.1007/s40593-020-00227-x
This article examines whether a scenario-based assessment of written argumentation, supplemented with automated writing evaluation features and keystroke-log process measures, is sensitive to differences in curriculum and instruction across middle schools. Using data from one suburban and two urban schools, the authors found significant score gains and distinctive improvement patterns in the suburban school, suggesting the approach can provide actionable interim information about student progress.
Key takeaways
- Scenario-based assessments can be combined with writing-process data and automated features to support interim assessment.
- The assessment showed sensitivity to school-level differences in instruction and performance.
- One suburban school showed significant score increases and distinctive patterns of improvement.
- The approach may offer richer information for monitoring student writing development over a school year.
Why it matters
Presents and evaluates a multi-measure interim assessment approach for written argumentation, showing how scenario-based tasks, automated writing evaluation, and process data can detect differences in instructional impact.
Coauthors
Paul Deane, Joshua Wilson, Mo Zhang, Chen Li, Peter van Rijn, Hongwen Guo, Amanda Roth, Eowyn Winchester, Theresa Richter
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