This article analyses the significance of ideological and political education for college students in Tibet and proposes a natural language model for an ideological education curriculum to improve the accuracy of students' document search. The segmentation results are optimized to enhance literature search accuracy, promoting the development of…

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…

Building and checking concept maps is an active research topic in visual learning. Concept maps are intended to show visual representations of interrelated concepts in educational and professional settings. For the last decades, numerous formulas have been proposed to compute the semantic proximity between any pair of concepts in the map. A review…

Advances in machine learning (ML) are poised to contribute to our understanding of the linguistic processes associated with successful reading comprehension, which is a critical aspect of children's educational success. We used ML techniques to investigate and compare associations between children's reading comprehension and 260 linguistic…

This study examined the development of text complexity for the past 25 years of reading comprehension passages in the National Matriculation English Test (NMET) in China. Text complexity of 206 reading passages at lexical, syntactic, and discourse levels has been measured longitudinally and compared across the years. The natural language…

We examine the ability of supervised text classification models to identify several discourse properties from teachers' speech with an eye for providing teachers with meaningful automated feedback about the quality of their classroom discourse. We collected audio recordings from 28 teachers from 10 schools in 164 authentic classroom sessions,…

Using a natural language processing tool, this study examined participant discourse in personalized learning schools to better understand what personalized learning looks like in practice. Term frequency-inverse document frequency (tf-idf) was used to identify the significant words and potential emergent themes for 134 interview transcripts. This…

The paper advocates an approach to learning design that considers it as creating digital artefacts that can be extended, modified and used for different purposes. This is realised through an "act becoming artefact" cycle, where users' actions in the authors' software environment, named Learning Designer, are automatically interpreted on…

The goal of this dissertation is to introduce a method for deriving morphemes from Arabic words using stem patterns, a feature of Arabic morphology. The motivations are three-fold: modeling with morphemes rather than words should help address the out-of-vocabulary problem; working with stem patterns should prove to be a cross-dialectally valid…

The accelerating rate of data generation and resulting publications are taxing the ability of scientific investigators to stay current with the emerging literature. This problem, acute in science, is not uncommon in other areas. New approaches to managing this explosion of information are needed. While it is only possible to read one paper or…