The rise of Artificial Intelligence technology has raised concerns about the potential compromise of privacy due to the handling of personal data. Private AI prevents cybercrimes and falsehoods and protects human freedom and trust. While Federated Learning offers a solution by model training across decentralized devices or servers, thereby…

Peer Evaluation Systems (PESs) allow members of student teams to provide one another with computer-mediated feedback in the form of qualitative, open-ended comments. The current research leverages unsupervised Natural Language Processing (NLP), namely Biterm Topic Modeling (BTM) and sentiment analysis, to uncover latent topics and degree of…

In this dissertation, I establish a research program that uses computational modeling as a testbed for theories of phonological learning. This dissertation focuses on a fundamental question: how do children acquire sound patterns from noisy, real-world data, especially in the presence of lexical exceptions that defy regular patterns? For instance,…

The past thirty years have shown a rise in models of language acquisition in which the state of the learner is characterized as a probability distribution over a set of non-stochastic grammars. In recent years, increasingly powerful models have been constructed as earlier models have failed to generalize well to increasingly complex and realistic…

Naturalistic language learning is contextually grounded. When people learn their first (L1) and often their second (L2) language, they do so in various contexts. In this dissertation I examine the effect of various contexts on language development. Part 1 describes the effects of textual, linguistic context in reading. I employed an eye-tracking…

This dissertation investigates how collective process-oriented documentation tools, combined with Natural Language Processing (NLP) techniques, can enhance knowledge construction in hands-on, open-ended learning environments, such as makerspaces. Through a three-year design-based research, the study developed and tested a collective documentation…

The current study tests the hypothesis that language comprehension is, in part, influenced by language exposure, and the biases that people develop are related to the frequency of exposure to different linguistic input, like, for instance, pronoun coreference. As comprehenders filter the linguistic input they encounter, we ask, what is the impact…

Natural language is highly complex and can be challenging for some learners, yet the contribution of complexity to individual differences in language learning remains poorly understood. This poor understanding appears due to both a lack of consensus among researchers regarding what complexity is, and to on-line language research often employing…

One of the fundamental questions in the field of language acquisition is a learnability problem, which considers how learners acquire certain aspects of language which are not directly provided in the input or whose referents are not readily observable. This dissertation investigates Japanese children's acquisition of various linguistic phenomena,…

How do children learn the meaning of words like "pretty" and "tall," which are not only gradable and context dependent (Kennedy & McNally 2005), but encode speaker subjectivity? Despite their complex semantics (Stephenson 2007; Lasersohn 2009; Bylinina 2014), these and other adjectives like them, are some of the most…

The long-term objective of this project was to better understand how shorter auditory experience and spectral degradation of the cochlear implant (CI) signal impact spoken language processing in deaf children with CIs. The specific objective of this research was to utilize psycholinguistic methods to investigate the mechanisms underlying observed…

While information theory is typically considered in the context of modern computing and engineering, its core mathematical principles provide a potentially useful lens through which to consider human language. Like the artificial communication systems such principles were invented to describe, natural languages involve a sender and receiver, a…

Data-driven learning uncontroversially plays a role in human language acquisition--how large a role is a matter of much debate. The success of artificial neural networks in NLP in recent years calls for a re-evaluation of our understanding of the possibilities for learning grammar from data alone. This dissertation argues the case for using…

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…

For many people, learning a second language as an adult is a challenging endeavor. Much interest in the study of adult second language learning has concerned the type of input that learners receive in their second language, with findings suggesting that second language learners are often exposed to a register of speech called 'foreigner talk' that…