Self-explanation practice is an effective method to support students in better understanding complex texts. This study focuses on automatically assessing the comprehension strategies employed by readers while understanding STEM texts. Data from 3 datasets (N = 11,833) with self-explanations annotated on different comprehension strategies (i.e.,…

This article provides a commentary within the special issue, Integration: The Keystone of Comprehension. According to most contemporary frameworks, a driving force in comprehension is the reader's ability to generate the links among the words and sentences (ideas) in the texts and between the ideas in the text and what the readers already know. As…

This study investigated the presence of word reading difficulties in a sample of students in Grades 1-4 (n = 357) identified with language and reading comprehension difficulties. This study also examined whether distinct word reading and listening comprehension profiles emerged within this sample and the extent to which these groups varied in…

This study investigated the effect of cloze item practice on reading comprehension, where cloze items were either created by humans, by machine using natural language processing techniques, or randomly. Participants from Amazon Mechanical Turk (N = 302) took a pre-test, read a text, and took part in one of five conditions, Do-Nothing, Re-Read,…

An NLP algorithm was developed to assess question quality to inform feedback on questions generated by students within iSTART (an intelligent tutoring system that teaches reading strategies). A corpus of 4575 questions was coded using a four-level taxonomy. NLP indices were calculated for each question and machine learning was used to predict…

This study assesses the extent to which machine learning techniques can be used to predict question quality. An algorithm based on textual complexity indices was previously developed to assess question quality to provide feedback on questions generated by students within iSTART (an intelligent tutoring system that teaches reading strategies). In…

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,…

Current education standards in the U.S. require school students to read and understand complex texts from different subject areas (e.g., social studies). However, such texts usually contain figurative language, complex phrases and sentences, as well as unfamiliar discourse relations. This may present an obstacle to students whose native language…

This study expands upon an existing model of students' reading comprehension ability within an intelligent tutoring system. The current system evaluates students' natural language input using a local student model. We examine the potential to expand this model by assessing the linguistic features of self-explanations aggregated across entire…

In this chapter, we describe several intelligent tutoring systems (ITSs) designed to support student literacy through reading comprehension and writing instruction and practice. Although adaptive instruction can be a powerful tool in the literacy domain, developing these technologies poses significant challenges. For example, evaluating the…