Search Results (184)

Augmented Reality (AR) has been found to produce significant effects on individual learning outcomes but its impact on collaborative applications remains moderate. Existing AR frameworks emphasize individual instructional design, whereas frameworks for collaborative learning rarely engage with the spatial and device-mediated affordances of mobile AR. In response to this inadequacy in the literature, we introduce the Mobile Augmented-Reality Storytelling for Vocational Education and Training (MARS-VET) framework, a four-dimensional conceptual architecture that integrates Computer-Supported Collaborative Learning (CSCL) scripting principles with mobile AR affordances for collaborative English as a Foreign Language (EFL) writing in Vocational Education and Training (VET) settings. MARS-VET synthesizes theoretical perspectives across four dimensions: contextual anchoring, which embeds activities within authentic workplace scenarios; collaborative orchestration, which structures group interaction through macro- and micro-level scripts; competency cultivation, which sequences writing progression from model-based reproduction toward autonomous professional text production; and capacity building, which addresses the professional-development requirements of implementing educators. Content validity was established through expert panel evaluation involving international specialists (N = 11) who rated the framework against 36 items using a four-point relevance scale and provided additional qualitative feedback. The Scale-level Content Validity Index (S-CVI/Ave = 0.91) exceeded established thresholds, with all four dimensions achieving satisfactory item-level indices. Experts reached unanimous agreement on items addressing workplace scenario identification and co-located access to linguistic resources. Qualitative feedback led to terminology refinements and clarification of orchestration mechanisms. The framework offers VET institutions and educators a reference for the design and evaluation of collaborative AR experiences in an area where integrative frameworks have so far been lacking. Full article

The study aimed to systematically analyze studies published between 2013 and 2025 on the second-grade primary school EFL curriculum in Türkiye. The study identified the strengths and weaknesses of the components of the English curriculum and examined the suggestions proposed regarding implementation issues. In order to answer the research questions, 27 studies were analyzed using content analysis, and their methodological characteristics were reviewed. The analysis revealed that the objectives constituted the strongest component of the second-grade English curriculum, whereas the assessment component was the weakest. The problems with the curriculum implementation include the incompatibility of the curriculum with the Common European Framework of Reference (CEFR) for Languages, insufficient class hours, teachers’ inclusion of reading and writing skills even though they are not included in the learning outcomes, individual differences between students, students’ unpreparedness for foreign language learning, inadequate instructional materials, and parents’ lack of interest in foreign language education. The findings revealed that, while the curriculum is well-structured in terms of its objectives, its effectiveness is hindered by persistent challenges in assessment and implementation. This underscores the importance of improving the alignment between curricular intentions and instructional practices, highlights the need for targeted improvements in assessment practices, and offers practical insights for ongoing curriculum development efforts. Full article

Writing-intensive courses help undergraduate students develop disciplinary knowledge and communication skills, yet many students, particularly first-generation college students and those writing in a second language, enter these courses with low confidence and high writing anxiety. Writing self-efficacy, or students’ beliefs about their ability to succeed as writers, is associated with motivation and academic success, but less is known about how instructional practices shape its development. This qualitative study examined how students experienced instructional practices in a writing-intensive public health course and how these experiences influenced writing self-efficacy. Data were collected through a focus group with six undergraduate students and analyzed using a deductive thematic approach guided by Bandura’s four sources of self-efficacy. Students identified scaffolded assignments, opportunities for revision, and explanatory feedback as key facilitators of writing self-efficacy. Supportive classroom relationships, including proactive instructor outreach and consistent feedback, also appeared to foster confidence. Barriers included linguistic challenges, limited academic role models, and negative experiences with writing support services. These findings suggest writing self-efficacy may develop through the interaction of structured instructional practices and supportive classroom environments. Full article

The Book of Margery Kempe is an extraordinary work of female visionary writing, in which Margery Kempe narrates her intimate and direct communications with Jesus Christ. The aim of this paper is to investigate how Kempe fashions herself into an authoritative religious figure and the impact of her self-fashioning. The study reveals that Kempe builds up her image as a chosen woman through a designed narrative discourse, which features disorder, imbalance, and homogeneity. To be specific, Kempe intentionally foregrounds her spiritual life endorsed by Christ and downplays her secular life in order to establish her authority. Moreover, Kempe’s work replicates the essential ingredients of hagiography, namely trials, divine intervention, and redemption, which naturally elevates Kempe to sainthood and therefore justifies her position of spiritual authority. Following on from this, Kempe, like other holy women, is well-qualified to instruct her fellow Christians to emulate her form of life, that is, to live a devout life. The establishment of Kempe’s spiritual authority is the epitome of women’s pursuit of spiritual leadership in the later Middle Ages, when they struggled with social conventions and ecclesiastical regulations. Full article

Generative AI (GenAI) is reshaping second language (L2) writing not only by altering how learners generate, revise, and refine text but also by changing how writers justify, disclose, and remain accountable for AI-mediated decisions. Yet much prompt-literacy work still treats prompting as output optimization or leaves it under-theorized as a general ability to “use AI well.” This conceptual article addresses that gap by reconceptualizing Fine-Tuned Prompt Literacy (FTPL) as an interaction-first learning-and-accountability framework for GenAI-mediated L2 writing. We argue that prompt literacy should be understood not simply as better prompting, but as the trained ability to set communicative and genre constraints, interrogate provisional AI outputs, corroborate claims, revise prompts and texts iteratively, and document accountable uptake decisions. To clarify FTPL’s theoretical distinctiveness, we position it in relation to AI literacy, critical GenAI literacy, and prompt literacy research, and define four interlocking dimensions—learner empowerment, prompt optimization, critical evaluation, and ethical responsibility. We further operationalize the framework through observable interactional indicators, process evidence, and assessment/accountability implications relevant to instructional and institutional contexts. By reframing prompt literacy as a genre-sensitive and ethically accountable interactional competence, this article offers a conceptual model for studying and designing GenAI-mediated writing beyond product improvement alone. Full article

In HPC systems and hyper-scale data centers, the adoption of high-performance NVMe SSDs and high-speed networks has shifted storage bottlenecks to the network stack. Under high-concurrency workloads, frequent interrupt processing exhausts CPU resources while protocol-level control–data dependencies in the NVMe over TCP write path introduce additional serialization penalties. Existing optimizations either require specialized hardware, dedicate CPU cores to user-space polling, or apply semantically blind batching that delays time-sensitive control messages. We present SENS, a Semantic-aware NVMe over TCP Scheduler embedded within the NVMe over TCP driver of the Linux kernel. SENS combines two mechanisms: (1) PDU vectorization, which aggregates discrete Protocol Data Units into memory vectors before network transmission, amortizing per-I/O system call overhead and reducing soft-interrupt frequency; and (2) instruction-aware dispatch, which detects control PDUs such as R2T and triggers an early flush of the aggregation window, mitigating the serialization penalty on the write path. A prototype evaluation with physical NVMe SSDs and 100 GbE networks shows that SENS saturates the SSD throughput ceiling using 4–5 CPU cores, halving the host-side core budget compared to the native TCP driver. With a RAMDisk backend that removes storage-media constraints, SENS sustains up to 2.5× higher concurrent IOPS. These results show that exposing storage-protocol semantics to the batching layer improves the scalability of NVMe over TCP without additional hardware. Full article

This study investigated the effects of computer-assisted writing on the written language production of secondary school students with Specific Learning Difficulties (SLD), particularly dyslexia. Writing is a complex cognitive process requiring the coordination of spelling, lexical retrieval, syntactic organization, transcription, and revision, areas in which students with SLD often experience persistent difficulties. The study compared handwritten and computer-based texts produced by 40 students with SLD and 20 students without learning difficulties using a counterbalanced design, with an interval of approximately two weeks between the two writing sessions. In the handwriting condition, students used printed reference materials, whereas in the computer-based condition they had access to general-purpose digital tools, including spell-checkers, electronic dictionaries, online resources, and word-processing software. Written texts were evaluated using the Spelling Accuracy Index and holistic scores assigned by independent raters. Data were analyzed using descriptive statistics and non-parametric tests (Mann–Whitney U and Wilcoxon signed-rank tests). The findings revealed statistically significant improvements in favor of computer-based writing for both groups, with particularly strong gains among students with SLD. Computer-written texts demonstrated higher spelling accuracy and received higher evaluation scores, indicating improved performance in the assessed writing outcomes. The findings suggest that computer-assisted writing may support written language production in secondary school students with SLD, particularly in relation to spelling accuracy and overall text evaluation, and may offer a useful avenue for more inclusive writing instruction. Full article

Syntactic complexity is a crucial aspect of assessing writing quality in Chinese as a second language. While existing literature predominantly focuses on synchronic features of syntactic complexity, particularly changes in complexity indices, less attention has been paid to its diachronic development and interactions among these indices. Drawing upon Dynamic Systems Theory, this exploratory longitudinal study traces the developmental trajectories of syntactic complexity indices and their interactions in CSL writings of 15 native Cambodian speakers within a single instructional context. The main results are as follows: (i) The syntactic complexity indices exhibited fluctuating and nonlinear growth. Among them, the length of topic chain clauses showed notable variation (range: 1.12 to 9.05), while relatively small changes (range: 0.4 to 2.39) occurred in the number of topic chain clauses. (ii) The development trends in the number of topic chains and the number of zero components showed no significant difference (p = 0.086, Cohen’s d = 0.31). In contrast, the development trends in the number of topic chain clauses and the length of topic chain clauses differed significantly (p = 0.039, Cohen’s d = 0.65). (iii) Individual differences in syntactic complexity were observed among learners in similar learning environments. These findings provide a detailed, context-bound description of the dynamic and complex syntactic development observed in the Chinese writing of 15 participants. The study highlights the value of employing multiple perspectives to capture such complexity and underscores the need for future research with more diverse samples and designs to test the generalizability of these patterns. Full article

This study investigated associations between a yearlong genre-based writing curriculum and students’ writing and self-efficacy outcomes. The curriculum had two stages: first, teaching genre elements without requiring use of sources and citations, and then integrating information from readings. Participants included 340 students and 3 teachers across 6th to 8th grades in a rural Title I middle school. Using a quasi-experimental, one-group pretest–posttest design with repeated measures, analysis showed significant improvements in writing quality across argumentative, compare-and-contrast, and narrative genres for all grades. Improvement patterns varied by grade and genre; self-efficacy and affect results were mixed—gains appeared in specific areas, but overall, self-efficacy decreased when reading was incorporated. Findings suggest the yearlong approach enhances writing quality but may require additional strategies to maintain student motivation. Full article

Positioned at the intersection of instructional mediation, Visual Education, and Universal Design for Learning (UDL), this research aims to ascertain whether the use of Artificial Intelligence (AI) enhances accessibility for students with sensory disabilities. The study involved 137 pre-service teachers attending the “Special Didactics and Learning for Sensory Disabilities” course within the teacher specialization program (TFA) at the University of Foggia. Although the hybridization of AI, UDL, and Visual Education was favourably received, its application remains sporadic, highlighting the challenge of balancing the need for simplification with requisite conceptual accuracy. This underscores the necessity of integrating more structured and continuous training pathways into teacher education, grounded in visual education and featuring micro-modules dedicated to specific skills such as writing alternative text, subtitling, and verifying color contrast according to recognized standards. Full article

Background/Objectives: Children develop the ability to construct meaning from language long before they learn to read. These foundational language processes support learning across academic contexts and form the basis for later reading and writing. However, many students, particularly those with Developmental Language Disorder (DLD), enter school with weaknesses in oral academic language that limit their ability to understand and express increasingly complex classroom discourse. Despite the central role of narrative and expository language in early instruction, explicit and systematic intervention targeting both discourse genres remains uncommon in the early grades. The purpose of this randomized controlled trial was to examine the immediate and maintained effects of a structured, small-group oral language intervention targeting both narrative and expository discourse for early elementary-age students with and without DLD. Methods: Participants (N = 80) were kindergarten through second-grade students identified as having DLD or significantly weak narrative language performance and were randomly assigned to an intervention condition or business-as-usual control. Narrative outcomes were collected for all participants at pretest, posttest, and a two-month follow-up, and expository outcomes were collected at posttest. Results: Results indicated statistically significant intervention effects for narrative language at posttest, with gains maintained at follow-up. Treatment effects were not moderated by language status, and subgroup analyses demonstrated large effects for students with DLD. Regression analyses indicated a non-significant intervention effect on expository outcomes. Conclusions: Findings provide experimental evidence that explicit, contextualized narrative and expository language instruction delivered in brief small-group sessions can produce meaningful and durable improvements in narrative language for young children, including those with DLD. Full article

As critical elements in argumentative writing, argument components and strategies significantly influence argument quality. However, the existing research lacks an in-depth exploration of how students construct and utilize these elements in argumentative writing. This study first evaluates the performance of leading large language models (LLMs) in identifying argument components and strategies using three approaches: single-task learning (STL), chain-of-thought (CoT), and multi-task learning (MTL). With the aid of learning analytics methods (Epistemic Network Analysis (ENA) and two-mode network), the study further reveals the intrinsic mechanisms linking argument components, strategies, and writing quality. Specifically, the research trains and evaluates LLMs on 226 argumentative essays, encompassing 4726 components and 4837 strategies. Compared to basic STL, the CoT and MTL methods significantly improve LLMs’ performance in both tasks. Moreover, learning analytics indicate that high-quality essays possess rich and complex logical relations, presenting multidimensional and multi-layered reasoning structures, whereas low-quality essays predominantly rely on simple and repetitive connections, lacking deeper logical support. These findings have significant implications for the automated analysis of argumentative writing and the sustainable development of education, not only providing valuable insights for educators in argumentation instruction but also contributing to the systematic enhancement of students’ argumentative abilities and critical thinking. Full article

Grammatical error correction (GEC) for Chinese learner English is still dominated by sentence-level modeling, which limits discourse-level consistency and weakens adaptation to learner-specific error profiles. From an instructional perspective, these limitations also reduce the value of automated feedback as a basis for spaced-repetition instructional structures sensitive to individual differences. This study proposes a symmetry-aware dual-encoder architecture for context-aware GEC in Chinese learner English. A context encoder captures preceding-sentence information, while a source encoder integrates BERT-based semantic representations with Bi-GRU-based syntactic features for the current sentence. A gated decoder performs asymmetric fusion of local and contextual evidence. To better reflect corpus-level tendencies in Chinese learner English, a CLEC-informed augmentation strategy generates synthetic errors using empirical category frequencies as a coarse sampling prior. Experiments on CoNLL-2014, JFLEG, and CLEC show consistent improvements over strong neural baselines in F_0.5 and GLEU under the current desktop-oriented implementation setting. Nevertheless, the integration of BERT, dual encoders, and gated decoding introduces non-negligible computational overhead, and the present system is therefore better suited to desktop writing-support scenarios than to strict real-time or large-scale online deployment. The proposed framework thus provides a practical technical basis for personalized grammar feedback and for future spaced-repetition instructional designs in ESL writing support. Full article

The processes of teaching and learning are primarily humanistic. However, contemporary artificial intelligence (AI) technology has significantly changed these processes. The current qualitative study aimed to explore this phenomenon by investigating the role that chatbots can play as language tutors in improving ESL students’ writing. Specifically, the study investigated students’ perceptions and experiences to assess the influence of ChatGPT-generated written communication on ESL writing improvement. Data were collected through semi-structured interviews with undergraduates from the College of Languages and Translation at a public university in Riyadh, Saudi Arabia. The emerging themes revealed that students held positive perceptions of the chatbot as a tutor, highlighting that collaborative learning with the chatbot facilitated the acquisition of writing skills and increased engagement in the writing process. Findings also showed noticeable improvement in language development, at lexical, syntactic, semantic, and pragmatic levels, as well as in the use of cognitive and metacognitive writing strategies. The study recommends reevaluating traditional writing instruction methodologies and highlights the benefits of integrating AI chatbots into second-language writing pedagogy. Furthermore, the study emphasises students’ need for accessible English-language tutoring, such as chatbots, which provide immediate, real-time writing instruction. The study also addresses the implications of incorporating AI-powered chatbots into writing curricula at Saudi universities. Full article

The rapid adoption of generative artificial intelligence tools such as ChatGPT in educational settings has generated both enthusiasm and concern regarding their influence on student learning. While several studies report improvements in efficiency, confidence, and perceived understanding, evidence for durable conceptual learning and knowledge transfer remains mixed. This article examines these tensions through the concept of fluency illusion, a cognitive phenomenon in which information that is easy to process is mistakenly judged as being well understood. Using a narrative conceptual review approach, this study synthesizes findings from 41 publications identified through searches of Google Scholar, Scopus, Web of Science, and ERIC covering the period from 2022 to early 2026. The reviewed literature includes 28 empirical studies, nine conceptual or theoretical analyses, and four review articles addressing the use of ChatGPT in educational contexts. Across domains such as writing and language learning, STEM problem solving, feedback and tutoring, and assessment, the literature shows a recurring pattern in which fluent AI-generated responses increase learners’ confidence without consistently improving deeper conceptual understanding. Drawing on research from cognitive psychology and metacognition, this review proposes an integrative conceptual account of how fluent AI output may shape learners’ judgments of understanding and influence their engagement with learning tasks. The paper concludes by discussing implications for instructional design, assessment practices, and metacognitive scaffolding, and outlines directions for future research aimed at empirically examining the proposed framework and identifying strategies to reduce fluency-driven misjudgments while preserving the potential benefits of generative AI in education. Full article