The productivity of a specific research field hinges on the periodic examination of both the knowledge produced and the knowledge production activities. By harnessing the strength of traditional bibliometric analyses and a variety of Natural language processing (NLP) techniques, this study portrayed a holistic landscape of higher education…

The aim of this study was to share our experience of developing a digital Natural Language Processing Tool and its implementation in the process of training future linguists. In this article, we demonstrate the process of creating the web application SENTIALIZER, which is a multilingual Sentiment Analysis Tool developed with the help of the Python…

The significance of interdisciplinary learning has been well-recognized by higher education institutions. However, when teaching interdisciplinary learning to junior undergraduate students, their limited disciplinary knowledge and underrepresentation of students from some disciplines can hinder their learning performance. ChatGPT's ability to…

The launch of OpenAI ChatGPT's language-generation model has raised alarms within many sectors, especially the academic sector. Several academicians have urged universities to develop new forms of assessment after the launch of ChatGPT, which solves academic questions in less than a few minutes. Academic cheating is not a new phenomenon, and the…

The release of ChatGPT in 2022 has generated extensive speculation about how Artificial Intelligence (AI) will impact the capacity of institutions for higher learning to achieve their central missions of promoting learning and certifying knowledge. Our main questions were whether people could identify AI-generated text and whether factors such as…

Course planning is essential for academic success and the achievement of personal goals. Although universities provide course syllabi and curriculum maps for course planning, integrating and understanding these resources by the learners themselves for effective course planning is time-consuming and difficult. To address this issue, this study…

In this dissertation, I investigate how people navigate ambiguity in everyday speech, with a focus on quantifier-negation sentences. Combining corpus analysis, behavioral experiments, and computational modeling in the Rational Speech Act framework, I explore preferred interpretations of quantifier-negation and examine the contexts and prosodies…

The rapid advancement of artificial intelligence (AI) has outpaced existing research and regulatory frameworks in higher education, leading to varied institutional responses. Although some educators and institutions have embraced AI and generative AI (GenAI), other individuals remain cautious. This systematic literature review explored teaching…

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,…

Children achieve better long-term language outcomes than adults. However, it remains unclear whether children actually learn language "more quickly" than adults during real-time exposure to input--indicative of true superior language learning abilities--or whether this advantage stems from other factors. To examine this issue, we…

Artificial intelligence (AI) has been evolving since the mid-twentieth-century when luminaries such as Alan Turing, Herbert Simon, and Marvin Minsky began developing rudimentary AI applications. For decades, AI programs remained pretty much in the realm of computer science and experimental game playing. This changed radically in the 2020s when…

A robust finding in psycholinguistics is that prior language experience influences subsequent language processing. This phenomenon is known as syntactic priming. Most of the empirical support for L2 syntactic priming comes from lab-based experiments. However, this evidence might not reflect how priming occurs in typical language activities in the…

In the history of psycholinguistics, there are traditional accounts that have been told about language learning and processing. These accounts revolve around the constraints imposed by the age of language learning and by universal principles that are assumed to be natively given. The contribution of Brian MacWhinney and his collaborators has been…

It is widely assumed that subliminal word priming is case insensitive and that a short SOA (< 100 ms) is required to observe any effects. Here we attempted to replicate results from an influential study with the inclusion of a longer SOA to re-examine these assumptions. Participants performed a semantic categorisation task on visible word…

Classical quantifiers (like "all," "some," and "none") express relationships between two sets, allowing us to make generalizations (like "no elephants fly"). Devices like these appear to be universal in human languages. Is the ubiquity of quantification due to a universal property of the human mind or is it…