Artificial intelligence (AI) has become an integral component of human existence, with individuals employing AI tools in various facets of life. Among the most significant applications of AI is its role in facilitating communication among humans. The present study focuses on the use of AI in translating a crucial type of text that falls within the…

Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…

Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…

Generative AIs such as Google Bard are known to be equipped with techniques and grammatical principles of human language based on a large corpus of text and code that allow them to generate natural-sounding language, and also identify and correct grammatical errors in human-written texts. Still, they are not perfect language generators, and this…

This paper explores the development of an intelligent translation system for spoken English using Recurrent Neural Network (RNN) models. The fundamental principles of RNNs and their advantages in processing sequential data, particularly in handling time-dependent natural language data, are discussed. The methodology for constructing the…

Current student-centred, multilingual, active teaching methodologies require that teachers have continuous access to texts that are adequate in terms of topic and language competence. However, the task of finding appropriate materials is arduous and time consuming for teachers. To build on automatic readability assessment research that could help…

Scientists use specific terms to denote concepts, objects, phenomena, etc. The terms are then connected with each other in sentences that are used in science-specific language. Representing these connections through term networks can yield valuable insights into central terms and properties of the interconnections between them. Furthermore,…

This article introduces a novel, holistic framework--named Dr. Mosaik--that encompasses explanations of the entire tense-aspect system, while highlighting eight comprehensive rules that explain the main workings of the system. In turn, this provides a limited number of "anchor points" on which to time-efficiently address instruction and…

Background or Context: Although many scholars have evaluated how Hispanic-serving institutions (HSIs) "serve" and can better "serve" Latinx students and their communities, scant research has integrated artificial intelligence (AI) technology within this evaluation of diversity and "servingness." With institutions of…

Numerous approaches have been introduced to automate the process of text summarization, but only few can be easily adapted to multiple languages. This paper introduces a multilingual text processing pipeline integrated in the open-source "ReaderBench" framework, which can be retrofit to cover more than 50 languages. While considering the…

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…

Multilingualism presents both a challenge and an opportunity for Natural Language Processing, with code-switching representing a particularly interesting problem for computational models trained on monolingual datasets. In this paper, we explore how code-switched data affects the task of Machine Translation, a task which only recently has started…

Second language learners constitute a significant and expanding portion of the global population and there is a growing demand for tools that facilitate language learning and instruction across various levels and in different countries. The development of large language models (LLMs) has brought about a significant impact on the domains of natural…

With artificial intelligence (AI) now producing human-quality text in seconds via natural language generation, urgent questions arise about the nature and purpose of the teaching of writing in English. Humans have already been co-composing with digital tools for decades, in the form of spelling and grammar checkers built into word processing…

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…