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Fully Latent Principal Stratification with Misspecified Measurement Models in Intelligent Tutoring Systems
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Yanping Pei; Adam C. Sales; Hyeon-Ah Kang; Tiffany A. Whittaker – International Educational Data Mining Society, 2025
Fully-Latent Principal Stratification (FLPS) offers a promising approach for estimating treatment effect heterogeneity based on patterns of students' interactions with Intelligent Tutoring Systems (ITSs). However, FLPS relies on correctly specified models. In addition, multiple latent variables, such as ability, participation, and epistemic…
Descriptors: Intelligent Tutoring Systems, Measurement, Computation, Simulation