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Hazelton, Lynette; Nastal, Jessica; Elliot, Norbert; Burstein, Jill; McCaffrey, Daniel F. – Grantee Submission, 2021
In writing studies research, automated writing evaluation technology is typically examined for a specific, often narrow purpose: to evaluate a particular writing improvement measure, to mine data for changes in writing performance, or to demonstrate the effectiveness of a single technology and accompanying validity arguments. This article adopts a…
Descriptors: Formative Evaluation, Writing Evaluation, Automation, Natural Language Processing
Rhodes, Katherine T.; Lukowski, Sarah; Branum-Martin, Lee; Opfer, John; Geary, David C.; Petrill, Stephen A. – Grantee Submission, 2018
The strategy choice model (SCM) is a highly influential theory of human problem-solving. One strength of this theory is the allowance for both item and person variance to contribute to problem-solving outcomes, but this central tenet of the model has not been empirically tested. Explanatory item response theory (EIRT) provides an ideal approach to…
Descriptors: Learning Strategies, Addition, Problem Solving, Item Response Theory
Katz, Sandra; Albacete, Patricia L. – Grantee Submission, 2013
For some time, it has been clear that students who are tutored generally learn more than students who experience classroom instruction (e.g., Bloom, 1984). Much research has been devoted to identifying features of tutorial dialogue that can explain its effectiveness, so that these features can be simulated in natural-language tutoring systems. One…
Descriptors: Rhetorical Theory, Tutoring, Intelligent Tutoring Systems, Secondary School Science