In this dissertation, I examine how fingerspelled words and core signs in American Sign Language (ASL) reduce as they are repeated. This investigation is motivated by theories of language production that posit that reduction may be shaped not only by reducing articulatory effort, but also by accommodation to an interlocutor's understanding of the…

The confusion between an EdD or PhD, the two terminal degrees in education, remains as current as it was at the beginning of the degrees' existence. The common belief is that the EdD is practitioner-oriented and the PhD research-oriented. The aim of present research is to clarify the confusion by conducting a corpus analysis of the aboutness of…

Since corpus linguistics gained popularity as a methodology in the latter half of the 20th century, second language acquisition research has seen the emergence of work investigating formulaic language, such as idioms, lexical bundles, and collocations. A collocation is a string of words that co-occur more routinely than probability would predict,…

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…

Dialogue act (DA) classification plays an important role in understanding, interpreting and modeling dialogue. Dialogue acts (DAs) represent the intended meaning of an utterance, which is associated with the illocutionary force (or the speaker's intention), such as greetings, questions, requests, statements, and agreements. In natural language…

There is a general consensus in theories of human speech recognition that humans engage in predictive processing during online speech processing. There are also claims that predictive processing indicates the operation of a predictive coding (PC) mechanism (Rao & Ballard, 1999). Formally, PC is a generative model where top-down signals consist…

Automated assessment using Natural Language Processing (NLP) has the potential to make English speaking assessments more reliable, authentic, and accessible. Yet without careful examination, NLP may exacerbate social prejudices based on gender or native language (L1). Current NLP-based assessments are prone to such biases, yet research and…

This dissertation investigates how bilinguals use their two grammars to comprehend written intra-sentential codeswitches. I focus on adjective/noun constructions in Spanish and English where I manipulate the congruence of grammatical word order in the two languages across the codeswitch boundary. This allows me to test three codeswitching…

The importance of input on language learning cannot be overstated. One method of providing input to learners at a level that is appropriate for them is called extensive reading, in which learners read an abundance of texts. In practice, for learners of English as a second or foreign language, these texts are often books that have been written and…

Discourse markers (DMs) are linguistic forms characterized by their use as conversation organizers or pause fillers (Fox Tree, 2010). Although used frequently in both speech and writing, DMs are not often taught in L2 classrooms, despite incorrect usage causing potential misunderstandings (Polat, 2011). Additionally, L2 learners have been observed…

When learning a language, typically-developing infants face the daunting task of learning both the sounds and the meanings of words. In this dissertation, we focus on a source of variability that complicates the one-to-one relationship between words and their meanings: wordform variability. In Chapter 1 we make a distinction between the micro…

Language is one of the hallmarks of intelligence, demanding explanation in a theory of human cognition. However, language presents unique practical challenges for quantitative empirical research, making many linguistic theories difficult to test at naturalistic scales. Artificial neural network language models (LMs) provide a new tool for studying…

Text classification typically performs best with large training sets, but short texts are very common on the World Wide Web. Can we use resampling and data augmentation to construct larger texts using similar terms? Several current methods exist for working with short text that rely on using external data and contexts, or workarounds. Our focus is…

Large scale product and service reviews proliferate and are commonly found across the web. The ability to harvest, digest and analyze a large corpus of reviews from online websites is still however a difficult problem. This problem is referred to as "opinion mining." Opinion mining is an important area of research as advances in the…

The dissertation paints a cultural-historical portrait of the New Criticism, a formalist school of twentieth-century literary criticism. My case study revisits the trajectory of this vital school of thought through a fine-grained textual comparison of critical essays produced by principal affiliates. Using "genre" as a guiding concept, I…