German-speaking children between ages 2 and 3 mostly use the preposition ohne ('without') in an adult-like way, to express the absence of something. In this article we present surprising results from a corpus study suggesting that in this age group, absence can also be expressed using the sequence mit ohne 'with without'. We argue that this…

In this article, we investigate a systematic workflow that supports the learning engineering process of formulating the starting question for a conversational module based on existing learning materials, specifying the input that transformer-based language models need to function as classifiers, and specifying the adaptive dialogue structure,…

Although computational models can simulate aspects of human sentence processing, research on this topic has remained almost exclusively limited to the single language case. The current review presents an overview of the state of the art in computational cognitive models of sentence processing, and discusses how recent sentence-processing models…

Automatic essay scoring (AES) is an essential educational application in natural language processing. This automated process will alleviate the burden by increasing the reliability and consistency of the assessment. With the advances in text embedding libraries and neural network models, AES systems achieved good results in terms of accuracy.…

Purpose: This paper aims to critically review the intersection of searching and learning among children in the context of voice-based conversational agents (VCAs). This study presents the opportunities and challenges around reconfiguring current VCAs for children to facilitate human learning, generate diverse data to empower VCAs, and assess…

This study applies the Apriori algorithm to analyse patterns, syntactic structures, and thematic clusters in Chinese studies data from various genres. This study aims to identify recurring linguistic elements in order to shed light on the dynamic nature of the Chinese language across different contexts and time periods. The Apriori algorithm is…

Multisyllabic words constitute a large portion of children's vocabulary. However, the relationship between phonological neighborhood density and English multisyllabic word learning is poorly understood. We examine this link in three, four and six year old children using a corpus-based approach. While we were able to replicate the well-accepted…

Technological advances have made the ability to translate no longer exclusively belong to humans. Today, machine translation has turned into a tool with superior performance to convert text between languages without the need for human intervention. One of the translation research foci is the studies of causative translation, especially from…

The world's linguistic diversity is severely underrepresented in research on cognitive and neural aspects of language processing, with great consequences for our understanding of the relationship between language, cognition, and the human brain. The practical challenges of carrying out neurophysiological (but also behavioral) experiments under…

Learning analytics (LA) involves the measurement, collection, analysis, and reporting of data about learners and their contexts, aiming to understand and optimize both the learning process and the environments in which it occurs. Among many themes that the LA community considers, natural language processing (NLP) algorithms have been widely…

The phraseology of precipitation as a weather phenomenon occupies an important part in the Kazakh and Kyrgyz languages. Each phraseological fund encompasses rich imagery and specific cognitive characteristics. The objectives of this research were to discover the cognitive characteristics of rain, snow and hail based on their participation in…

Ambridge calls for exemplar-based accounts of language acquisition. Do modern neural networks such as transformers or word2vec -- which have been extremely successful in modern natural language processing (NLP) applications -- count? Although these models often have ample parametric complexity to store exemplars from their training data, they also…

Automating the classification of instructional strategies from a large-scale online tutorial dialogue corpus is indispensable to the design of dialogue-based intelligent tutoring systems. Despite many existing studies employing supervised machine learning (ML) models to automate the classification process, they concluded that building a…

Artificial intelligence has evolved since its inception in the 1950s, resulting in the creation of large language models that are trained on extensive data sets to understand and generate content, such as OpenAI's ChatGPT, which launched in November 2022. Modern technology that is easy to access and free to use, like ChatGPT, is changing the…

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…