When we examine the state of writing instruction in many schools and classrooms, we find that few teachers are actually teaching students to become better writers in large part because they are relying on process models that do not accurately reflect the complex task of creating good writing and that are out of step with current research. Merely…

Background: Federal law requires most school districts to develop school wellness policies (SWPs), which state agencies assist in by providing templates. Templates provide standard language, which districts may edit for numerous reasons. We aimed to identify the frequency/consistency of template usage and identify the types of edits districts make…

This paper presents WikiMorph, a tool that automatically breaks down words into morphemes, etymological compounds (morphemes from root languages), and generates contextual definitions for each component. It comes in two flavors: a dataset and a deep-learning-based model. The dataset was extracted from Wiktionary and contains over 450k entries. We…

Considering noticeable improvements in the accuracy of Google Translate recently, the aim of this study was to examine second language (L2) learners' ability to use post-editing (PE) strategies when applying AI tools such as the neural machine translator (MT) to solve their lexical and grammatical problems during L2 writing. This study examined 57…

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…