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Zhao, Siyuan; Heffernan, Neil – International Educational Data Mining Society, 2017
Personalized learning considers that the causal effects of a studied learning intervention may differ for the individual student. Making the inference about causal effects of studies interventions is a central problem. In this paper we propose the Residual Counterfactual Networks (RCN) for answering counterfactual inference questions, such as…
Descriptors: Computation, Outcomes of Treatment, Networks, Randomized Controlled Trials
Kurby, Christopher A.; Magliano, Joseph P.; Dandotkar, Srikanth; Woehrle, James; Gilliam, Sara; McNamara, Danielle S. – Journal of Educational Computing Research, 2012
This study assessed whether and how self-explanation reading training, provided by iSTART (Interactive Strategy Training for Active Reading and Thinking), improves the effectiveness of comprehension processes. iSTART teaches students how to self-explain and which strategies will most effectively aid comprehension from moment-to-moment. We used…
Descriptors: Computer Assisted Testing, Federal Aid, Control Groups, Experimental Groups

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