While hierarchical machine learning approaches have been used to classify texts into different content areas, this approach has, to our knowledge, not been used in the automated assessment of text difficulty. This study compared the accuracy of four classification machine learning approaches (flat, one-vs-one, one-vs-all, and hierarchical) using…

Self-explanations are commonly used to assess on-line reading comprehension processes. However, traditional methods of analysis ignore important temporal variations in these explanations. This study investigated how dynamical systems theory could be used to reveal linguistic patterns that are predictive of self-explanation quality. High school…

The current study explored relations between non-cognitive traits (Grit, Learning Orientation, Performance Orientation), reading skill, and performance across three experiments conducted in the context of two intelligent tutoring systems, iSTART and Writing Pal. Results showed that learning outcomes (comprehension score, holistic essay score) were…

Background knowledge is a strong predictor of reading comprehension; yet little is known about how different types of background knowledge affect comprehension. The study investigated the impacts of both domain and topic-specific background knowledge on students' ability to comprehend and learn from science texts. High school students (n = 3650)…

Research suggests that promoting metacognitive awareness can increase performance in, and learning from, intelligent tutoring systems (ITSs). The current work examines the effects of two metacognitive prompts within iSTART, a reading comprehension strategy ITS in which students practice writing quality self-explanations. In addition to comparing…

iSTART is an intelligent tutoring system designed to provide self-explanation instruction and practice to improve students' comprehension of complex, challenging text. This study examined the effects of extended game-based practice within the system as well as the effects of two metacognitive supports implemented within this practice. High school…

This paper introduces StairStepper, a new addition to Interactive Strategy Training for Active Reading and Thinking (iSTART), an intelligent tutoring system (ITS) that provides adaptive self-explanation training and practice. Whereas iSTART focuses on improving comprehension at levels geared toward answering challenging questions associated with…

Interactive Strategy Training for Active Reading and Thinking (iSTART) is an intelligent tutoring system that supports reading comprehension through self-explanation (SE) training. This study tested how two metacognitive features, presented in a 2 x 2 design, affected students' SE scores during training. The "performance notification"…

This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…

Intelligent tutoring systems for ill-defined domains, such as reading and writing, are critically needed, yet uncommon. Two such systems, the Interactive Strategy Training for Active Reading and Thinking (iSTART) and Writing Pal (W-Pal) use natural language processing (NLP) to assess learners' written (i.e., typed) responses and provide immediate,…