Verb-marking errors are a characteristic feature of the speech of typically-developing (TD) children and are particularly prevalent in the speech of children with Developmental Language Disorder (DLD). However, both the pattern of verb-marking error in TD children and the pattern of verb-marking deficit in DLD vary across languages and interact…

There is substantial evidence that children's apparent omission of grammatical morphemes in utterances such as "She play tennis" and "Mummy eating" is in fact errors of commission in which contextually licensed unmarked forms encountered in the input are reproduced in a context-blind fashion. So how do children stop making such…

Autograding short textual answers has become much more feasible due to the rise of NLP and the increased availability of question-answer pairs brought about by a shift to online education. Autograding performance is still inferior to human grading. The statistical and black-box nature of state-of-the-art machine learning models makes them…

Across many language backgrounds, a consistent hurdle to accessing United States higher education is understanding the basic information necessary to apply for admission and financial aid and complete the many enrollment management processes necessary to begin one's college career (apply for housing, receive and submit vaccinations, register for…

Linguistic category learning has been shown to be highly sensitive to linear order, and depending on the task, differentially sensitive to the information provided by preceding category markers ("premarkers," e.g., gendered articles) or succeeding category markers ("postmarkers," e.g., gendered suffixes). Given that numerous…

With recent improvements in machine translation (MT) accuracy, MT has gained unprecedented popularity in second language (L2) learning. Despite the significant number of studies on MT use, the effects of using MT on students' retention of learning or secondary school students' use of MT in L2 writing has rarely been researched. The current study…

Online assessment is an essential part of online education, and if conducted properly, has been found to effectively gauge student learning. Generally, textbased questions have been the cornerstone of online assessment. Recently, however, the emergence of generative artificial intelligence has added a significant challenge to the integrity of…

The analysis of spoken language has been integral to a breadth of research in social science and beyond. However, for analyses to occur with efficiency, language must be in the form of computer-readable text. Historically, the speech-to-text process has occurred manually using human transcriptionists. Automated speech recognition (ASR) is…

This study examines the impact of the College, Career, and Community Writers Program (C3WP) on upper-elementary students' first draft writing quality, addressing the challenges teachers face in providing timely and effective feedback on extensive student writing, particularly in spelling, grammar, mechanics, and cohesion. The hypothesis posits…

Purpose: ParAlg (Paraphasia Algorithms) is a software that automatically categorizes a person with aphasia's naming error (paraphasia) in relation to its intended target on a picture-naming test. These classifications (based on lexicality as well as semantic, phonological, and morphological similarity to the target) are important for…

It was observed from previous researches that Bloom's Taxonomy action verbs (BTAVs) are overlapping in multiple cognitive levels, causing ambiguity about the real sense of the word. A data set of BTAVs was ranked using a statistical classification. Four categories of BTAVs were identified, out of which 153 BTAVs (86.44%) are classified into a…

This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…

This dissertation developed a new learner corpus of Japanese and introduced an error and linguistic annotation scheme specifically designed for Japanese particles. The corpus contains texts written by learners who are in the first year to fourth year university level Japanese courses. The texts in the corpus were tagged with part-of-speech and…

Distributional models of semantics learn word meanings from contextual co-occurrence patterns across a large sample of natural language. Early models, such as LSA and HAL (Landauer & Dumais, 1997; Lund & Burgess, 1996), counted co-occurrence events; later models, such as BEAGLE (Jones & Mewhort, 2007), replaced counting co-occurrences…

Machine Translation (MT) has the potential to provide instant translation in times of crisis. MT provides real solutions that can remove borders between people and COVID-19 information. The widespread of MT system makes it worthy of scrutinizing the capacity of the most prominent MT system, Google Translate, to deal with COVID-19 texts into…