Humans can attribute beliefs to others. However, it is unknown to what extent this ability results from an innate biological endowment or from experience accrued through child development, particularly exposure to language describing others' mental states. We test the viability of the language exposure hypothesis by assessing whether models…

Automated scoring of student language is a complex task that requires systems to emulate complex and multi-faceted human evaluation criteria. Summary scoring brings an additional layer of complexity to automated scoring because it involves two texts of differing lengths that must be compared. In this study, we present our approach to automate…

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…

University classrooms are increasingly populated by students with diverse nationalities and native languages (L1). The growing number of students in English-led classrooms who speak English as a second or lower language (L2) may face added difficulties in understanding the specific task objectives or directions, as explained by native-…

There are many ways to learn how to be entrepreneurs and one of the powerful ways is to learn from successful entrepreneurs. However, it is difficult to reach and interview those entrepreneurs about their best practices in doing business in real lives. Chatbot technology can come into play in mimicking conversation of successful entrepreneurs 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…

Given the novelty of human--machine communication (HMC) in task-based language learning (TBLL), we conducted a multimethodological pilot study to explore the use of Alexa in out-of-class task-based learning to mediate texts in English as a foreign language. Fourteen Polish intermediate learners participated in the quasi-experiment and programme…

"Natural language understanding" (NLU) of text is a fundamental challenge in AI, and it has received significant attention throughout the history of NLP research. This primary goal has been studied under different tasks, such as Question Answering (QA) and Textual Entailment (TE). In this thesis, we investigate the NLU problem through…

Learning to paraphrase supports both writing ability and reading comprehension, particularly for less skilled learners. As such, educational tools that integrate automated evaluations of paraphrases can be used to provide timely feedback to enhance learner paraphrasing skills more efficiently and effectively. Paraphrase identification is a popular…

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…

In this investigation we propose new machine learning methods for automated scoring models that predict the vocabulary acquisition in science and social studies of second grade English language learners, based upon free-form spoken responses. We evaluate performance on an existing dataset and use transfer learning from a large pre-trained language…

In phonetics research, language alternation--including code switching (speaker-initiated) and cued switching (researcher-prompted)--can be used as a tool to investigate various aspects of speech production and perception in bilingual or multilingual speakers (Bullock & Toribio, 2009a). Studies on the production of voice onset time (VOT) during…

Machine translation is currently undergoing a paradigm shift from statistical to neural network models. Neural machine translation (NMT) is difficult to conceptualise for translation students, especially without context. This article describes a short in-class evaluation exercise to compare statistical and neural MT, including details of student…

We have developed a process model that learns in multiple ways while finding faults in a simple control panel device. The model predicts human participants' learning through its own learning. The model's performance was systematically compared to human learning data, including the time course and specific sequence of learned behaviors. These…