Language is one of the hallmarks of intelligence, demanding explanation in a theory of human cognition. However, language presents unique practical challenges for quantitative empirical research, making many linguistic theories difficult to test at naturalistic scales. Artificial neural network language models (LMs) provide a new tool for studying…

This dissertation presents various machine learning applications for predicting different cognitive states of students while they are using a vocabulary tutoring system, DSCoVAR. We conduct four studies, each of which includes a comprehensive analysis of behavioral and linguistic data and provides data-driven evidence for designing personalized…

As educational professionals strive to help students become efficient and effective learners, they must assist in the development of student learning strategies and a greater understanding of the learning process. The purpose of this study was to analyze and compare the learning pattern preferences of middle and high school students in general…

Three experiments investigated the effect of various kinds of reflection (within-task and post-task reflection) on learning a process control task. Also, two ways of providing learners with alternative ideas about task behavior, exposure to other's ideas and providing hints for task solution, were examined. The task involved a simulated…