Language is an essential component of human communication and interaction. Advances in Artificial Intelligence (AI) technology, specifically in Natural Language Processing (NLP) and speech-recognition, have made is possible for conversational agents, also known as chatbots, to converse with language learners in a way that mimics human speech.…

AI chatbots, e.g. ChatGPT, are becoming increasingly popular in education as a means to enhance student learning experiences and improve teaching efficiency. This study utilizes NVivo 12 Plus to examine the role of AI chatbots in education, ethical considerations, and sentimental analysis regarding the utilization of ChatGPT in education. ChatGPT…

Lexical frequency benchmarks have been extensively used to investigate second language (L2) lexical sophistication, especially in language assessment studies. However, indices based on semantic co-occurrence, which may be a better representation of the experience language users have with lexical items, have not been sufficiently tested as…

Recent years have seen a flourishing of Natural Language Processing models that can mimic many aspects of human language fluency. These models harness a simple, decades-old idea: It is possible to learn a lot about word meanings just from exposure to language, because words similar in meaning are used in language in similar ways. The successes of…

Given the importance of conversation practice in language learning, chatbots, especially ChatGPT, have attracted considerable attention for their ability to converse with learners using natural language. This review contributes to the literature by examining the currently unclear overall effect of using chatbots on language learning performance…

The linguistic input children receive across early childhood plays a crucial role in shaping their knowledge about the world. To study this input, researchers have begun applying distributional semantic models to large corpora of child-directed speech, extracting various patterns of word use/co-occurrence. Previous work using these models has not…

Purpose: This study examines the accuracy of Interaction Detection in Early Childhood Settings (IDEAS), a program that automatically transcribes audio files and estimates linguistic units relevant to speech-language therapy, including part-of-speech units that represent features of language complexity, such as adjectives and coordinating…

Natural language processing (NLP) has captivated the attention of educational researchers over the past three decades. In this study, a total of 2,480 studies were retrieved through a comprehensive literature search. We used neural topic modeling and pre-trained language modeling to explore the research topics pertaining to the application of NLP…

Amid the ongoing discussion about the potential of LLMs (Large Language Models) to facilitate language learning, there has been a broad spectrum of views in academia. However, little is known about the different viewpoints of students and what contributes to these differences. In light of this, this study adopts Q-methodology, a mixed-methods…

Traditional educational giants and natural language processing companies have launched several artificial intelligence (AI)-enabled digital learning applications to facilitate language learning. One typical application of AI in digital language education is the automatic scoring application that provides feedback on pronunciation repeat outcomes.…

This paper details the motivation for and the main characteristics of "An Scéalaí" ('The Storyteller'), an intelligent Computer Assisted Language Learning (iCALL) platform for autonomous learning that integrates the four skills; writing, listening, speaking, and reading. A key feature is the incorporation of speech technology. Speech…

Despite the promise of research conducted at the intersection of computer-assisted language learning (CALL), natural language processing, and second language acquisition, few studies have explored the potential benefits of using intelligent CALL systems to deepen our understanding of the process and products of second language (L2) learning. The…

Infants' disposition to learn repetitions in the input structure has been demonstrated in pattern generalization (e.g., learning the pattern ABB from the token "ledidi"). This study tested whether a repetition advantage can also be found in lexical learning (i.e., learning the word "lele" vs. "ledi"). Twenty-four…

We introduce a set of biologically and computationally motivated design choices for modeling the learning of language, or of other types of sequential, hierarchically structured experience and behavior, and describe an implemented system that conforms to these choices and is capable of unsupervised learning from raw natural-language corpora. Given…

The processes of infant word segmentation and infant word learning have largely been studied separately. However, the ease with which potential word forms are segmented from fluent speech seems likely to influence subsequent mappings between words and their referents. To explore this process, we tested the link between the statistical coherence of…