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Novel Developments in the Use of Response Process Data in Assessment
Fri, April 17, 4:05 to 5:35pm, Virtual RoomSession Type: Paper Session
Abstract
The papers in this session use diverse methodological approaches to highlight new advances in the use of response process data in assessment. The authors cover a diverse array of topics including using IRT and Bayesian Network models to understand student learning via simulated process data; using the fully cross-loaded hierarchical model to simultaneously model response accuracy and response time; utilizing log files to understand students’ science inquiry; gathering response process data from assessments involving multiple people engaged in a dyadic interaction; and using Evidence Centered Design to assess teachers’ content knowledge.
Sub Unit
Chair
Papers
Modeling Complex Data From Simulations to Assess Middle School Students' Next Generation Science Standards–Aligned Science Learning - Emily Toutkoushian, The American Board of Anesthesiology; Kihyun "Kelly" Ryoo, University of North Carolina - Chapel Hill
The Influences of Ability on Response Accuracy: Using the Full Cross-Loadings Hierarchical Model - Maoxin Zhang, University of Oslo
Using PISA 2015 Log File Data to Identify Profiles of Students' Performance on Simulated Inquiry Tasks - Nani Teig, University of Oslo; Ronny Scherer, University of Oslo; Marit Kjaernsli, University of Oslo
Using Evidence-Centered Design to Develop Performance Assessments of Content Knowledge for Teaching - Geoffrey C. Phelps, Educational Testing Service; Brent Bridgeman, ETS