Typically, vocabulary instruction is associated as part of reading instruction. However, vocabulary instruction is also a necessary component of mathematics instruction. In fact, state and national standards (e.g., Common Core State Standards) require elementary students to communicate about mathematics to provide clear explanations, construct…

Vocabulary is a set of familiar words within a person's language. Typically developed with students' exposure and age, the focused instructional routine of Define, Example, Ask (DEA) is used for Wonders K-5 Curriculum from McGraw Hill. This routine serves as a fundamental tool for acquiring knowledge through vocabulary in real-life methods. This…

Language learners are underserved if there are unlearned meanings of a word that they think they have already learned. For example, "circle" as a noun is well known, whereas its use as a verb is not. For artificial-intelligence-based support systems for learning vocabulary, assessing each learner's knowledge of such atypical but common…

This paper explores the concept of dynamically generating definitions using a deep-learning model. We do this by creating a dataset that contains definition entries and contexts associated with each definition. We then fine-tune a GPT-2 based model on the dataset to allow the model to generate contextual definitions. We evaluate our model with…

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…

The present study seeks to evaluate a hybrid model of identification that incorporates response to instruction and intervention (RTI) as one of the key symptoms of reading disability. The 1-year stability of alternative operational definitions of reading disability was examined in a large-scale sample of students who were followed longitudinally…

The relation definition theory proposed in this paper is explicitly different from previous semantic memory theories since it is the first to make a relation's definition the basis of semantic processing. The paper suggests that this relation definition theory successfully predicts relation similarity on the basis of one key primary assumption:…