Search Results (36)

The rapid proliferation of generative artificial intelligence (GenAI) in educational settings has created unprecedented opportunities for language instruction, yet empirical evidence regarding its efficacy in primary-level English as a Foreign Language contexts remains scarce, particularly concerning pre-service teachers’ implementation experiences during formative practicum periods. This investigation, conducted in a public school in a non-Anglophone country during the Spring of 2025, examined the impact of GenAI-driven gamified activities on elementary pupils’ English language competencies while exploring novice educators’ professional development trajectories through a mixed-methods quasi-experimental approach with comparison groups. Four third-grade classes (n = 119 individuals aged 8–9) in a public school were assigned to either ChatGPT-mediated voice-interaction games (n = 58) or conventional non-digital activities (n = 61) across six 45 min lessons spanning three weeks, with four female student-teachers serving as instructors during their culminating practicum. Quantitative assessments of grammar, listening comprehension, and pronunciation occurred at baseline, post-intervention, and one-month follow-up intervals, while reflective journals captured instructors’ evolving perceptions. Linear mixed-effects modeling revealed differential outcomes across linguistic domains: pronunciation demonstrated substantial advantages for GenAI-assisted learners at both immediate and delayed assessments, listening comprehension showed moderate benefits with superior overall performance in the experimental condition, while grammar improvements remained statistically equivalent between groups. Thematic analysis uncovered pre-service teachers’ progression from technical preoccupations toward sophisticated pedagogical reconceptualization, identifying connectivity challenges and assessment complexities as primary barriers alongside reduced performance anxiety and individualized pacing as key facilitators. These findings suggest selective efficacy of GenAI across language skills while highlighting the transformative potential and implementation challenges inherent in technology-enhanced elementary language education. Full article

Artificial Intelligence (AI) tools have transformed academic writing and literacy development in higher education. Students can now receive instant feedback on grammar, coherence, style, and argumentation using AI-powered writing assistants, like Grammarly, ChatGPT, and QuillBot. Moreover, these writing assistants can quickly produce completed essays and papers, leaving little else for the student to do aside from reading and perhaps editing the content. Many teachers are concerned that this erodes critical thinking skills and undermines ethical considerations since students are not performing the work themselves. This study addresses this concern by synthesizing and evaluating peer-reviewed literature on the effectiveness of AI in supporting writing pedagogy. Studies were selected based on their relevance and scholarly merit, following the Scale for the Assessment of Narrative Review Articles (SANRA) guidelines to ensure methodological rigor and quality. The findings reveal that although AI tools can be detrimental to the development of writing skills, they can foster self-directed learning and improvement when carefully integrated into coursework. They can facilitate enhanced writing fluency, offer personalized tutoring, and reduce the cognitive load of drafting and revising. This study also compares AI-assisted and traditional writing approaches and discusses best practices for integrating AI tools into curricula while preserving academic integrity and creativity in student writing. Full article

Some children with autism may require additional support to meet academic expectations for comprehension. Because an extensive set of research links oral narration to listening and reading comprehension, the promotion of narrative-based skills may be a viable intervention approach. The purpose of this study was to examine the effect of narrative intervention with explicit strategy instruction on the listening and reading retells of children with autism after hearing and decoding novel stories. Four children with autism aged 7 and 9 years old participated in this multiple baseline across participants single-case experimental design study. Behavioral therapists delivered the narrative intervention, which included explicit instruction on the use of story grammar icons, to each child individually within the course of their therapy. Results showed that all participants improved their listening (TauU ES range = 0.64–1.06) and reading (TauU ES range = 0.72–1.15) retells, but they required extended use of the icon strategy to achieve the most benefit. When icons were completely removed, three of the four participants performed above baseline levels on the listening and reading comprehension measures. Full article

Despite reaching intermediate English proficiency, many bilingual secondary students in Colombia struggle with academic writing due to difficulties in organizing ideas and expressing arguments coherently. To address this issue, this study explores the integration of AI-powered tools—Grammarly and ChatGPT—within the Writing Workshop Instructional Model (WWIM) to enhance students’ writing skills. Conducted at a bilingual secondary school, the intervention targeted 10th grade ESL learners and focused on improving grammar accuracy, textual coherence, and organizational structure. Drawing on Galbraith’s model of writing as content generation, the study adopted a design-based research methodology, incorporating iterations of implementation, feedback, and refinement. The results indicate that combining WWIM with AI feedback significantly improved students’ academic writing performance. Learners reported greater confidence and engagement when revising drafts using automated suggestions. These findings highlight the pedagogical potential of integrating AI tools into writing instructions and offer practical implications for enhancing academic writing curricula in secondary ESL contexts. Full article

The increasing demand for data-driven decision making to maintain the innovations and competitiveness of organizations highlights the need for data science educations across academia and industry. At its core is a solid understanding of statistics, which is necessary for conducting a thorough analysis of data and deriving valuable insights. Unfortunately, conventional statistics learning often lacks practice in real-world applications using computer programs, causing a separation between conceptual knowledge of statistics equations and their hands-on skills. Integrating statistics learning into Python programming can convey an effective solution for this problem, where it has become essential in data science implementations, with extensive and versatile libraries. In this paper, we present a self-learning method for fundamental statistics through Python programming for data science studies. Unlike conventional approaches, our method integrates three types of interactive problems—element fill-in-blank problem (EFP), grammar-concept understanding problem (GUP), and value trace problem (VTP)—in the Programming Learning Assistant System (PLAS). This combination allows students to write code, understand concepts, and trace the output value while obtaining instant feedback so that they can improve retention, knowledge, and practical skills in learning statistics using Python programming. For evaluations, we generated 22 instances using source codes for fundamental statistics topics, and assigned them to 40 first-year undergraduate students at UPN Veteran Jawa Timur, Indonesia. Statistics analytical methods were utilized to analyze the student learning performances. The results show that a significant correlation ($\rho <0.05$) exists between the students who solved our proposal and those who did not. The results confirm that it can effectively assist students in learning fundamental statistics self-learning using Python programming for data science implementations. Full article

Despite the growing number of bilinguals worldwide, research on how bilingualism influences grammatical development in children with learning disabilities remains limited. This may be due to challenges in assessing language in these children, given the heterogeneity of their disabilities, lack of appropriate tools, and variability in language background and exposure common in bilingual populations. This pilot study investigates grammatical abilities in bilingual versus monolingual children with Down syndrome using the LITMUS Sentence Repetition Task, specifically designed for bilingual populations. Sentence repetition tasks are widely used for assessing grammar in neurotypical children and children with language impairments and are part of many omnibus language assessments. Ten children with Down syndrome aged 5–8 were recruited: five bilingual, speakers of British English and various home languages, and five monolingual, age- and language-matched. Both groups produced a high proportion of ungrammatical repetitions, with more omissions of verbs than nouns, function words than content words, and significant difficulties producing complex structures such as relative clauses, wh-questions, and passives. However, qualitative analyses showed that bilingual children speaking morphologically rich home languages (e.g., Polish, Greek) appeared to have fewer difficulties with some function words (e.g., prepositions) and were able to produce complex structures like passives and wh-questions, unlike their monolingual peers. Although the small sample limits generalisability, two insights emerge: First, sentence repetition may be of limited use in assessing expressive grammar in children with Down syndrome due to frequent ungrammatical responses. Second, while both groups showed similar challenges, bilingualism—especially with richly inflected home languages—may support specific grammatical skills. These findings support existing evidence that bilingualism does not hinder grammatical development in children with Down syndrome and suggest that parents should not avoid dual-language input. Further research is needed to determine whether bilingualism confers specific benefits in grammatical morpheme use and complex syntactic constructions. Full article

Task repetition is a technique that promotes the development of utterance fluency, but the addition of an accuracy enhancement is necessary. The study tested the effects of an accuracy enhancement where a Target Structure was used in response to what a partner said, limiting cognitive load (group 1, n = 31), while group 2 (n = 29) had to independently produce an idea formulated by the structure, which represented an additional load that could negatively affect the processes of proceduralization. Group 3 (n = 26) constituted the control group. Group 1 outperformed group 2 in terms of the fluent use of the structure, with a large effect size. Regarding the accurate use of the Target Structure, group 1 also outperformed group 2, but with a smaller effect size. In a new task, group 1 used the structure more, and a significant correlation was observed between the number of uses of the structure and the degree of proceduralization. Full article

The present study aimed to enhance the understanding of the spelling processes used by young German-speaking learners of English as a foreign language (EFL). Specifically, we sought to (1) compare the children’s accuracy in spelling English real words versus pseudowords to elucidate the role of lexical and sublexical knowledge, and (2) determine which cognitive (phonological awareness, phonological short-term memory, working memory, nonverbal intelligence) and linguistic skills (English receptive grammar and vocabulary) underlie learners’ spelling abilities and misspellings (phonological and orthographic). We followed participants (N = 101) for two years, from the beginning of grade 3 to the end of grade 4. Cognitive skills and linguistic abilities were determined using standardized assessment procedures. Our results indicate that the learners in our study demonstrated greater accuracy in spelling English real words compared to pseudowords. English grammar knowledge significantly predicted real word and pseudoword spelling accuracy, as well as the number of phonological errors, which was the predominant error category. English vocabulary knowledge was a predictor for real word spelling, while nonverbal intelligence predicted pseudoword spelling accuracy. Phonological short-term memory positively predicted the number of orthographic errors (phonologically plausible misspellings but lacking orthographic conventions). Full article

Artificial intelligence (AI) in education has become increasingly common in higher education, particularly in learning English as a second language (ESL). ChatGPT is a conversational AI model frequently used to support language acquisition by creating personalized, interactive learning experiences. This narrative review explored the impact of ChatGPT on ESL in higher education within the past three years. It employed a qualitative literature review using EBSCOhost, ERIC, and JSTOR databases. A total of 29 peer-reviewed articles published between 2023 and 2025 were selected for review. The Scale for the Assessment of Narrative Review Articles (SANRA) was applied as an assessment tool for quality and reliability. The results indicated that ChatGPT enhances learning outcomes in ESL by helping students improve their writing skills, grammar proficiency, and speaking fluency. Moreover, it fostered student engagement due to its personalized feedback and accessible learning resources. There were, however, concerns about plagiarism, factual errors, and dependency on AI tools. Although ChatGPT and similar models present promising opportunities and benefits in ESL education, there is a need for structured implementation and ethical guidance. Full article

This study utilizes the danmaku on the Bilibili platform as the research subject to examine how their characteristics vary according to the nature or focus of English teaching videos. By employing social network analysis, the study reveals distinctive features in danmaku. For videos categorized under linguistic knowledge (phonetics, vocabulary, and grammar), the danmaku comments predominantly center around topics such as phonetics, vocabulary, and grammar. Conversely, in videos categorized under language skills (listening, speaking, reading and writing), the danmaku comments primarily reflect a vocabulary review for three of the four skills, with only the listening skill showing slight deviations. This underscores the centrality of vocabulary in skill-oriented videos. The findings highlight the unique role of danmaku in distinguishing between knowledge and skills within the context of English teaching videos. Full article

Background/Objectives: Developmental language disorders (DLD) are often associated with co-occurring neurodevelopmental difficulties, including attentional or social–emotional problems. Another nonverbal domain, i.e., visual cognition and its relationship to DLD, is virtually unexplored. However, learning visuospatial regularities—a scene-grammar—is crucial for navigating our daily environment. These regularities show certain similarities to the structure of language and there is preliminary evidence for a relationship between scene processing and language competence in preschoolers with and without DLD. This study compared implicit and explicit visuospatial knowledge of everyday indoor scenes in older children, aged 6 to 10 years, of both groups. Methods: We measured ‘dwell times’ on semantic and syntactic object—scene inconsistencies via eye-tracking and performance in an object-placement task, and their associations with children’s language, visual, and cognitive skills. Results: Visual attention towards object-scene inconsistencies was highly comparable between groups, but children with DLD scored lower in a visual perception test and higher language skills were associated with higher visuo-cognitive performance in both tasks. In the explicit scene-grammar measurement, this relationship only existed for children with DLD and disappeared when nonverbal cognitive performance was controlled. Conclusions: Our study suggests the existence of mild problems in visuospatial processing co-occurring with DLD, which is partly influenced by age and nonverbal cognitive ability. The acquisition of visual cognition and linguistic knowledge is an interactive, multimodal process where the perception of objects in scenes might affect how the words for these objects are learned and vice versa. A better understanding of this interplay could eventually have impact on the diagnosis and treatment of DLD. Full article

This study addresses the integration of Spanish for Specific Purposes in Agriculture (SSPA) into the curricula of English-speaking veterinary and animal sciences students at three collaborating universities (Texas Tech University School of Veterinary Medicine, North Carolina State University, and Tarleton State University), to bridge communication gaps in agricultural settings. We designed and implemented three SSPA courses focused on key areas such as animal health, welfare, and food safety, using insights from industry professionals. The courses incorporated contextualized language instruction, including vocabulary, grammar, and practical communication scenarios relevant to the field. Teaching materials including interactive resources and metacognitive strategies were developed to enhance learning and engagement. The results showed that while the courses improved students’ communication skills, challenges such as technical issues and balancing academic commitments required adjustments to course delivery. Significant differences in performance were observed between institutions, with a considerable impact on the course completion rates and final test scores. The study concludes that SSPA courses significantly enhance the ability of veterinary and animal sciences students to effectively communicate with the Hispanic workforce, providing a model for similar language integration efforts in specialized fields. Full article

Generative Intelligent Tutoring Systems (ITSs), powered by advanced language models like GPT-4, represent a transformative approach to personalized education through real-time adaptability, dynamic content generation, and interactive learning. This study presents a modular framework for designing and evaluating such systems, leveraging GPT-4’s capabilities to enable Socratic-style interactions and personalized feedback. A pilot implementation, the Socratic Playground for Learning (SPL), was tested with 30 undergraduate students, focusing on foundational English skills. The results showed significant improvements in vocabulary, grammar, and sentence construction, alongside high levels of engagement, adaptivity, and satisfaction. The framework employs lightweight JSON structures to ensure scalability and versatility across diverse educational contexts. Despite its promise, challenges such as computational demands and content validation highlight the main areas for future refinement. This research establishes a foundational approach for advancing Generative ITSs, offering key insights into personalized learning and the broader potential of Generative AI in education. Full article

Background. Language development in toddlers can be influenced by social interactions in environments and proximal contexts with mothers and fathers. We present the literature on mothers’ and fathers’ education level and socioeconomic status on the child’s language development; further evidence is needed in the Italian-speaking context. Aims. The study aims to confirm the role of mother and father education level on toddlers’ language skills assessed with direct and indirect measures. Methods and Procedures. Participants were 51 Italian-speaking children aged 33 to 41 months. Children were tested with a lexical test (PinG test) for comprehension and production of nouns and predicates and a morpho-syntactic test for grammar comprehension (PCGO). Parents of the children completed a demographic form and the Italian adaptation of the MacArthur-Bates CDI long version. Two series of one-way ANCOVAs were performed to study the role of mothers’ and fathers’ level of education on separate measures of their child’s language. Outcomes and Results. Findings suggest that in most families, mothers’ level of education is higher than fathers’ level of education. There was no significant difference between children of parents with low–middle level of education and children of parents with high level of education for the grammar comprehension tasks (PCGO) and indirect measure of vocabulary production (MacArthur-Bates CDI). However, both mothers’ and fathers’ level of education appears to be significant for the direct measurement of word production. Conclusions and Implications. This study provides new evidence for the role of mothers’ and fathers’ education on the development of word production in children aged 33 to 41 months, contributing to enriching the literature on the Italian context; it lays the groundwork for future research on the social and environmental factors that can affect language development. Full article

Nowadays, with the common use of smartphones in daily lives, mobile applications have become popular around the world, which will lead to a rise in Flutter framework. Developed by Google, Flutter with Dart programming provides a cross-platform development environment to create visually appealing and responsive user interfaces across mobile, web, and desktop platforms using a single codebase. However, due to time and staff limitations, the Flutter/Dart programming course is not included in curricula, even in IT departments in universities. Therefore, independent learning environments for students are essential to meet this growing popularity. Previously, we have developed programming learning assistant system (PLAS) as a web-browser-based self-learning platform for novice students. PLAS offers various types of exercise problems designed to cultivate programming skills step-by-step through a lot of code reading and code writing practices. Among them, one particular type is the code modification problem (CMP), which asks to modify the given source code to satisfy the new specifications. CMP is expected to be solved by novices with little effort if they have knowledge of other programming languages. Thus, PLAS with CMP will be an excellent platform for independent learning. In this paper, we present PLAS with CMP for the independent learning of Flutter/Dart programming. To improve the readability of the source code by students, we provided rich comments on grammar or behaviors. Besides, the code can be downloaded so that students can check and run it on an IDE. For evaluations, we generated 38 CMP instances for basic and multimedia/storage topics in Flutter/Dart programming and assigned them to 21 master students at Okayama University, Japan, who have never studied it. The results confirm the validity of the proposal. Full article