Computer-assisted Language Learning Research Articles

Research progress of breast cancer surgery during 2010–2024: a bibliometric analysis

PurposeThis study seeks to systematically analyze the research literature pertaining to breast cancer surgery from 2010 to 2024, as indexed in the PubMed database, employing bibliometric methodologies.MethodsEmploying the “bibliometrix” package in the R programming language, alongside VOSviewer and CiteSpace software, this research conducted a comprehensive visual analysis of 1,195 publications. The analysis encompassed publication trends, collaborative networks, journal evaluation, author and institutional assessments, country-specific analyses, keyword exploration, and the identification of research hotspots.ResultsThe study observed a rising trend in the number of publications related to breast cancer surgery. However, there was a concomitant decline in citation rates, potentially indicating either a saturation of the research field or a diminution in research quality. The United States, China, and Japan are the leading contributors to research output, with the United States showing the most extensive international collaboration. The University of California, University of Toronto, and University of Texas MD Anderson Cancer Center were the top institutions for the number of published papers. Through a comprehensive analysis of keywords, we have identified “breast cancer” “pain” “anxiety” “lymphedema” “mastectomy” and “surgery” as central research themes within this domain, the corresponding clusters were subjected to analysis.ConclusionThis study provides a comprehensive review of breast cancer surgery research, emphasizing major research areas and proposing future research directions. This study provides a significant resource for researchers and clinicians in the field.

SmCamera: all-in-one software package for single-molecule data acquisition and data analysis

AbstractIn the last decades, biological applications of single-molecule methods have grown rapidly and researchers with expertise in microscopy and instrumentation have adopted these techniques and advanced them even further. However, practicing single-molecule methods is still challenging for most because of the need for expensive equipments and instrumentation demands as well as complicated data acquisition and analysis workflow consisting of multiple steps using different software in each of them. smCamera is an all-in-one software package which aims to alleviate steep learning curves of the data acquisition and analysis. From recording movies through extraction of time series of single-molecule fluorescence resonance energy transfer (smFRET), everything can be done in a single program without any additional software or programming languages. Although smCamera has not been published before, it has been distributed to facilitate adaption of smFRET experiments and there has been requests for support for this software. We hope that this work answers questions from researchers using smCamera and also provides an opportunity to introduce and distribute smCamera for new users.

Lack of WDFY4 leads to impaired immune response and poor cancer prognosis.

WDFY4 plays an essential role in the immune system by regulating B-cell growth and development and participating in antigen processing during cross-presentation. WDFY4 is closely related to asthma and systemic lupus erythematosus; however, its role in cancer remains unclear. The purpose of this study is to use bioinformatics to determine whether abnormal expression of WDFY4 is a risk factor for cancer and to preliminarily analyze the ways in which WDFY4 affects cancer through experiments. R language packages and bioinformatic database were used to mine the potential carcinogenic effect of WDFY4 and analyze the differential WDFY4 expression in cancer, gene mutations, different tumor prognoses, immune cell infiltration, tumor microenvironment, and DNA methylation correlation. H1975 and A549 cell lines were infected with lentiviruses to overexpress WDFY4, and the effect of WDFY4 on the activity, proliferation, apoptosis, and cell cycle of lung cancer cells was analyzed. WDFY4 was differentially expressed in human tumors in unpaired and paired samples. The differential expression of WDFY4 in unpaired and paired or protein samples from the Clinical Proteome Tumor Analysis Consortium of eight cancers was consistent. WDFY4 methylation was downregulated in 17 cancer types and caused prognostic differences in different directions in some cancers. WDFY4 overexpression significantly inhibited the activity and proliferation of lung cancer cell lines, promoted apoptosis, and caused cell cycle arrest. Differential WDFY4 expression in cancers leads to differences in the prognosis of various cancers. WDFY4 can be an independent prognostic factor for glioma, KIRC, and LUSC.

Research on Computer-Assisted Task-Based Instruction in College English Writing Teaching

In the digital era, the application of Computer-Assisted Language Learning (CALL) in the field of foreign language teaching has been explored by many researchers. In addition, Task-based instruction (TBI) is also a widely accepted method in language teaching, which requires language learners to complete a series of meaningful tasks to improve their language abilities. In this research, I will combine the CALL and TBI teaching method, drawing on the advantages of both methods, aiming to enhance students' writing skills and studying interest by introducing technological means. This paper also explores the effectiveness of the application of a combination of CALL and TBI in improving college English writing teaching.

Clinical significance of Cyclin D1 by complete quantification detection in mantle cell lymphoma: positive indicator in prognosis

ObjectivesThe positive expression of Cyclin D1 in immunohistochemical (IHC) staining serves as the cornerstone for diagnosing mantle cell lymphoma (MCL). However, existing literature does not conclusively establish whether the expression ratio and staining intensity significantly influence diagnostic outcomes or patient prognosis. In this retrospective study, the correlation between comprehensive Cyclin D1 quantification and the prognosis of MCL patients was studied.MethodsThe Cyclin D1 protein level was assessed in 120 formalin-fixed paraffin-embedded samples from MCL patients using the quantitative dot blot (QDB) analysis technique. R language software was employed for statistical analysis to determine the optimal threshold with statistical significance. Additionally, Kaplan-Meier method was utilized to evaluate the relationship between the absolute level of Cyclin D1 protein and overall survival (OS) of patients. Furthermore, the Chi-square test was applied to analyze the causes of single and multiple fractures, with a significance level of p < 0.05. Finally, the Log-rank test was used to compare two survival curves, where a significance level of p < 0.05 was considered statistically significant.ResultsAt the optimized cutoff of 0.46 nmol/g, univariate analysis revealed a positive correlation between Cyclin D1 protein level and patient survival (OS). Specifically, in the subgroup with complete quantification of Cyclin D1 higher than the cutoff, the 5-year OS was 18%, whereas in the subgroup with complete quantification of Cyclin D1 lower than the cutoff, the 5-year OS was 4.8% (Log-rank test, P = 0.017). This indicates that patients with Cyclin D1 levels above the cutoff had significantly better overall survival compared to those below the cutoff. Additionally, in the Pearson distribution test, Ki-67 emerged as an independent prognostic factor for the complete quantification of Cyclin D1. Notably, Cyclin D1 complete quantification results remained unaffected by factors such as gender, age, LDH (Lactate Dehydrogenase) level, Ann Arbor stage(AAS), Ki-67, IPI(International prognostic index), MIPI(Mantle International prognostic index), and MIPI-c (MIPI Combined with Ki-67 Proliferation Index Chi-square test, p > 0.05).ConclusionsComprehensive Cyclin D1 quantification, especially above a threshold, significantly correlates with better overall survival in MCL. This highlights its prognostic importance in MCL management. Full quantification of CyclinD1 aids MCL prognosis, while QDB technology for biomarker quantification supports precise clinical prognostic stratification.

Examining the Impact of Online Help-Seeking Strategies on Promoting EFL learners’ Self-Regulated and Collaborative Learning Skills, Language Learning Outcomes, and Perceptions in CALL Environments

This research examines the impact of online help-seeking strategies—both adaptive and peer-based—on promoting self-regulated and collaborative learning skills, as well as language learning outcomes, among Chinese EFL learners in computer-assisted language learning (CALL) environments. Employing a mixed-methods approach, the study triangulates various data strands from 92 randomly selected EFL learners to explore how these strategies influence their learning outcomes. Through methodological triangulation and the execution of one-way ANOVA, the research demonstrates the superior effectiveness of combining adaptive and peer help-seeking strategies, compared to their isolated use, in enhancing self-regulated and collaborative learning skills and language learning outcomes. The findings reveal a significant positive correlation between learners’ interactive engagement with help-seeking strategies and their overall CALL outcomes, indicating that such strategies support the development of both collaborative and self-regulated learning skills. This study provides theoretical and practical insights into CALL, offering evidence-based guidance for researchers and practitioners on the nuanced impact of integrating dynamic and flexible help-seeking strategies to enhance EFL learners’ skills and outcomes.

Investigating young consumers’ acceptance of hemp fiber textiles and apparel: an analysis of Partial Least Squares Structural Equation Modeling

Purpose Concerns over environmental degradation, alongside the global legalization of hemp cultivation, have prompted applications of hemp-derived textile products. However, research examining consumers’ acceptance of such products is lacking. It is critical to understand how young consumers adopt these products as they prioritize sustainability and lead the future purchasing power. Thus, this study aims to investigate young consumers’ perceptions, attitudes, and purchase intentions regarding hemp fiber textiles and clothing based on the Theory of Consumption Value and the Spiral of Silence Theory. Design/methodology/approach A US-based research company was hired to recruit survey participants, yielding 314 valid data. Data analysis, including Exploratory Factor Analysis and Partial Least Squares Structural Equation Modeling, was conducted using the R programming language and RStudio software. Findings Purchase intentions of hemp-based clothing and textiles among young consumers are influenced by attitude, perceived social value and future trend perception. Perceived social value also impacts attitude and future trend perception. High environmental involvement correlates with positive attitudes. Consumers’ subjective knowledge of hemp and objective knowledge regarding hemp fiber impact their perceptions of future trends in such products. Originality/value This research represents a seminal consumer study focusing on the resurgence of industrial hemp fiber textiles and clothing. This study empirically validates the significant role of social factors in young consumer acceptance of such products at both personal and societal levels. This study expands current knowledge and provides actionable insights for practitioners.

Technological Interface Components That Support Accelerated Learning in the Acquisition of Foreign Language Vocabulary

There is a need to find innovative learning methods that enable accelerated learning of a foreign language. This study examined the effect of computer-assisted language learning (CALL) in acquiring a foreign language, which combines cognitive and emotional stimuli in the background. The study explored two factors related to the acquisition of a foreign language: the duration and scope of the learning process and the depth of internalization of the newly acquired language. Another objective was to assess the learning method in two learning environments, 2D and VR, to determine if the learning environment affects the learning results and leads to better vocabulary retention. One hundred native French speakers, with an average age of 47.5, participated in the study and had no prior knowledge of the newly acquired language. We randomly divided the participants into two groups (2D and VR). They studied 550 words in a new language for five days: 30 min each evening and 15 min in the morning. The post-learning test pointed out that both groups improved their vocabulary scores significantly. Approximately one month after the learning experience, we administered a knowledge retention test to 32 participants and found that the level of knowledge had been retained. Finally, background variables (e.g., gender, age, and previous knowledge of the newly acquired language) did not affect the learning results. The findings indicate that CALL, which integrates background cognitive and emotional stimuli in both learning environments, significantly accelerates learning pace, broadens the scope of newly acquired words, and ensures retention. The level of improvement observed in our study is notably higher than that reported in the literature for studies that had previously evaluated CALL and in-class language acquisition.

Global burden of low back pain and its attributable risk factors from 1990 to 2021: a comprehensive analysis from the global burden of disease study 2021.

This study aimed to examine the evolving trends in the global burden of low back pain (LBP) from 1990 to 2021 and predicted disease burden until 2035. LBP-related data were obtained from the Global Health Data Exchange (GHDx) query tool. All estimates and their 95% uncertainty intervals (UIs) were generated using DisMod-MR 2.1, a Bayesian meta-regression tool in Global Burden of Disease, Injury, and Risk Factor Study (GBD) 2021. Data processing and visualization were conducted using The R Programming Language software version 4.3.2 and Joinpoint 4.7. In 2021, approximately 628.8 million people worldwide were affected by LBP, with approximately 266.9 million new incident cases and age-standardized incidence rate (ASIR) of 3176.6 per 100,000. Compared with 1990, although the ASIR and age-standardized disability-adjusted life years rate (ASDALYsR) decreased, absolute numbers increased significantly. Projections for 2035 reveal a continued decline in ASIR and ASDALYsR for LBP. The LBP burden varied by the sociodemographic index quintile and GBD region, with the highest ASIR and ASDALYsR observed in Central Europe and the greatest decrease in East Asia. Globally, women bear a higher burden of LBP than men, with middle-aged populations experiencing the heaviest burden. Occupational ergonomic factors, high body mass index, and smoking remain the primary risk factors for LBP, with occupational ergonomic factors contributing the most to the overall burden. Despite a projected decline in incidence, the global burden of LBP persists, exhibiting significant regional and gender disparities. To mitigate its future burden, precise and effective prevention and control strategies targeting high-risk factors are imperative.

Entrenching CALL for English Language Multicultural Pedagogy in Nigerian Secondary Schools: Issues, Prospects and Perceptions of Critical Stakeholders in Osun State, Nigeria

This paper examines the possibility of adoption of computer-assisted language learning (CALL) in Nigerian secondary schools especially those in Osun State, Nigeria in the light of recent developments necessitating greater familiarity with the computer by the students for their external examinations. The paper argues that secondary school students are more positioned now than ever to harness the benefits of CALL in developing necessary competences to excel in their English language exams and generally develop adequate proficiency in the language for their growth in the Nigerian nation and beyond. Data for the study comprise responses to questionnaires designed for secondary school students, English language teachers and Ministry of Education senior officials in Osun State Nigeria. The sample comprised 120 teachers across the three senatorial districts in Osun State, 36 teachers and 15 Ministry of Education officials. Data analysis revealed that there is great awareness of CALL among all the categories of subjects. In addition, the subjects emphasise the potential agency of CALL for enhancing the delivery of English language topics and the professional development of teachers, even though about 30 percent of the teachers sampled doubted its feasibility. The study therefore concludes that given the positive disposition of students to the introduction of CALL for English language teaching and being primary actors in the education process, there is need for immediate full-fledged adoption for English language teaching in Nigerian secondary schools.

Advancing language learning: The impact and challenges of Computer-Assisted Language Learning (CALL)

Abstract. Computer-Assisted Language Learning (CALL) represents a transformative approach in modern education, integrating technology to enhance language acquisition effectively. This comprehensive review examines the various dimensions of CALL, focusing on its deployment through interactive software, online courses, mobile applications, and the accompanying challenges. Quantitative analyses reveal significant improvements in learner engagement and cognitive load management due to multimedia and interactive content. Moreover, the adaptability of CALL to cater to individual learning needs through personalized and adaptive learning systems demonstrates a superior proficiency acquisition rate. Despite these advancements, CALL implementation faces substantial barriers including technological limitations, the need for extensive teacher training, and concerns regarding data privacy and security. This article assesses the statistical impact of these elements on language learning outcomes and suggests strategies for overcoming the associated challenges. Through mixed-methods research and longitudinal studies, the effectiveness of CALL platforms is substantiated, highlighting their pivotal role in reshaping language education across diverse demographic and geographic spectrums.

Systematic review of Buzhong Yiqi method in alleviating cancer-related fatigue: a meta-analysis and exploratory network pharmacology approach.

Cancer-related fatigue (CRF) is a prevalent and distressing symptom experienced by many cancer patients, necessitating effective treatments. This study utilizes meta-analysis and network pharmacology to comprehensively assess the efficacy of the Buzhong Yiqi prescription in alleviating cancer-related fatigue and to preliminarily explore the mechanism of its core drugs. We included randomized controlled trials (RCTs) in cancer patients. The inclusion criteria encompassed a diagnosis of cancer-related fatigue, without limitation on cancer type, the experimental group receiving Buzhong Yiqi prescription, the control group receiving conventional treatment, patients awaiting treatment, and articles published in either English or Chinese. We conducted a search through 29 February 2024, across PubMed, Cochrane Database of Systematic Reviews, Cochrane Controlled Clinical Trials (CENTRAL), China Biomedical Literature Service (CBM), China National Knowledge Infrastructure (CNKI), WANFANG Database, and Weipu Database (VIP). Journal articles that met the inclusion criteria were selected for inclusion. Two independent investigators evaluated the quality of the included studies. A meta-analysis was performed utilizing the Stata 12.0 software package, where estimates of cancer-related fatigue were aggregated through the application of a random-effects model. We employed the Cochrane Risk of Bias Tool to evaluate potential biases in RCTs. The primary outcome measures utilized to assess the efficacy and safety of CRF treatment comprised the Revised Piper Fatigue Scale (PFS-R) and the Quality of Life Questionnaire Core 30 (EORTC QLQ-C30). The secondary outcomes encompassed the KPS score, the effective rate, the TCM syndrome score, and an evaluation of adverse reactions. The Traditional Chinese Medicine Systems Pharmacology (TCMSP) was utilized to identify the active ingredients and targets of BZD. Additionally, the Drug bank, Therapeutic Target Database (TTD), DiaGeNET, and GeneCards databases were utilized to retrieve relevant targets for CRC. The Venn diagram was employed to identify overlapping targets. Cytoscape software was utilized to construct a network of "herb-ingredient-target" and identify core targets. GO and KEGG pathway enrichment analyses were performed using R language software. In comparison to the control group, patients with CRF who received BZYQ prescription exhibited marked improvements in KPS score, QLQ-C30 quality of life score, and effective rate. Conversely, PFS, TCM syndrome score, and adverse reaction assessments significantly decreased. The primary active ingredients in its core drugs may exert a positive therapeutic effect on CRF by targeting molecules such as AKT1, IL6, IL1B, PTGS2, CASP3, ESR1, and BCL2, as well as through signaling pathways including TNF, IL17, TLR, NF-κB, and C-type lectin receptor. BZYQ demonstrates significant efficacy in treating CRF with minimal adverse reactions. It can serve as a fundamental treatment for CRF in clinical practice, and the medication can be tailored to individual patients for personalized therapy. The potential pharmacological mechanism of BZYQ in treating CRF, as predicted by network pharmacology, offers a molecular foundation for clinical CRF treatment. https://inplasy.com, identifier INPLASY202430025.

Gender Differences: The Impact of Gender Grouping on Egyptian STEM Undergraduates’ Online Group Work

This paper reports a study that compares teaching English as a foreign language (TEFL) through face-to-face (FTF) and CALL (Computer Assisted Language Learning) methods, comparing them with the interdisciplinary perspectives of sociology, social psychology, and educational technology. Based on the sociocultural theory, the influence of gender grouping on the academic performance of 141 English as a foreign language (EFL) Egyptian undergraduates enrolled in a technical writing course in the Faculty of Engineering was examined in a CALL context. Students’ academic performance was measured by overall grades on group work assignments and submitted peer evaluation forms. Sixty-six students were assigned to a FTF control group, and 75 students were included in the experimental online group. Findings suggested that the performance of the online group was superior to that of the FTF control group. There were highly significant differences in the online group between males and females in their academic performance with females being more successful. In addition, all female-only groups attained higher grades than mixed and male-only groups. These findings emphasize the importance of teaching EFL learners’ teamwork skills to complete their tasks successfully (Holmes, 2000).

A pathway from surface to deep online language learning approach: The crucial role of online self-regulation.

Students' approaches to online technologies (SAOLT) have garnered significant support among scholars from a variety of fields, particularly in the field of science, technology, engineering, and mathematics education (STEM). The humanistic field needs to explore learners' approaches to target learning contexts, especially in the fields of computer-assisted language learning (CALL) and psycholinguistics. To fill this gap, the researchers explored 686 Iranian high school EFL learners' approaches to online language learning (OLL) with regard to their pedagogical, technical, and peer support, as well as the mediation role of online self-regulation. The partial least squares modeling approach's (PLS-SEM) reflective analysis validated the factorial structure of the conceptual study framework in online language learning and secondary education. The formative model found that instructional and peer support positively impacted language learners' deep and surface approaches to online language learning, thereby maximizing and minimizing their online presence and meaningful language learning. Furthermore, the mediation analysis revealed the significant moderating influence of learners' online self-regulation, which shifted the correlations from relating both learners' perceived support to their surface and deep learning approaches to only relating to the deep learning approach. Consequently, this study has pedagogical implications as it introduces a new conceptual framework to the CALL and psycholinguistic domains, specifically incorporating a new psychological factor related to language learners' complex dynamic systems, known as Language Learners' Approaches to Online Language Learning (OLLA). To do so, the researchers suggested that instructors should design more practical activities for theoretical subjects such as English language learning in online learning and shift online teaching from teacher-centered to peer-centered so as to foster their learners' deep learning approach to online language learning.

Investigating the mediating role of Foreign Language Peace of mind and learning burnout in the relationship between Informal Digital Learning of English and willingness to communicate

Concurrent with the advancements of computer-assisted language learning (CALL), L2 researchers have started to pay more attention to the notion of informal digital learning of English (IDLE). A series of studies have already indicated its crucial role in linguistic achievements. However, the mediating role of positive and negative psychological states in the relationship between IDLE and willingness to communicate (WTC) has received scant research attention. Therefore, the present study explored whether foreign language peace of mind (FLPoM) and foreign language learning burnout (FLLB) mediated the relationship between IDLE and WTC among EFL learners. The participants were 316 Iranian EFL learners who completed four questionnaires. The results of structural equation modeling indicated that (a) IDLE did not have a direct impact on EFL learners’ WTC, (b) FLPoM fully mediated the relationship between IDLE and WTC, and (c) the relationship between IDLE and FLLB was fully mediated by FLPoM. This study suggests that L2 learners’ positive psychological state of FLPoM can direct their IDLE practices toward higher levels of willingness to interact in L2 and lower levels of negative syndrome of burnout. The findings of this study imply the significance of language learners’ psychological states in their digital language learning in out-of-class learning environments.

Assessing aortic morphology post aortic valve replacement using unsupervised hierarchical clustering and statistical shape modelling

Abstract Introduction There are different surgical procedures used to treat aortic valve disease such as aortic valve replacement (AVR), the Ozaki procedure, the Ross procedure, and the valve-sparing procedure. There may be postoperative side effects associated with aortic morphology. Computational analyses that assess morphology are thus necessary in such scenario. Statistical shape modelling is used to assess three-dimensional morphology, discover unique shape features, create mean shapes, and create shape modes that display morphological variability. Hierarchical cluster analysis is a machine learning method used to classify a population into subgroups. Both of these statistical methods were applied to aortic valve replacement patients to evaluate morphological variability after aortic valve replacement (AVR) surgery. Purpose The purpose of this study is to assess the aortic morphology of AVR patients, identify morphological differences between different surgical procedures, identify subgroups postoperatively using statistical shape modelling and hierarchical cluster analysis, and assessing possible correlations between the resultant clusters and function i.e. ejection fraction. Methods Computed tomography and cardiac magnetic resonance images were used to reconstruct aortas into 3D models using segmentation and 3D reconstruction software. For each patient, two models were created (i.e. ascending aorta only and aorta including the arch and the descending aorta). N=35 patients were included in the study. Statistical shape analysis was run to create templates and shape modes. Statistical environment and language software was used to run hierarchical cluster analysis. Results Overall, the hierarchical cluster analysis did not classify the aortas based on type of surgery, but most patients in the Ross group demonstrated morphological differences from the other surgical groups and many of the aortas belonging to the Ross group were clustered together in both clustering analyses. No significant differences between clusters were seen (p=0.47 for ascending, p=0.19 for whole aorta). No correlation was found between clusters and ejection fraction (p=0.75, r2&amp;lt;0.01), possibly indicating that post-AVR aortic morphology in this sample does not reflect overt functional changes. Conclusion Both statistical shape modelling and hierarchical cluster analyses were successful in assessing morphological variability and identifying subgroups in this population. This framework could therefore be extended to larger samples to inform on surgical decision-making allowing surgeons to choose the appropriate surgery for the patient or design prosthetic valves that are more customised to the patient’s anatomy.Cluster-Ejection Fraction Correlation

Teachers’ perceived perspective and selfefficacy in teaching EFL using Intelligent Computer-Assisted Language Learning (ICALL): A rigorous analysis

This study aims to describe Indonesian EFL teachers’ perceived perspective and self-efficacy in EFL teaching using ICALL, reveal the prominent factor influencing each variable, and examine the effect of the perceived perspective on their self-efficacy. This study used a cross-sectional survey design with a quantitative approach. There were 284 Indonesian EFL teachers taught in secondary schools chosen using a voluntary sampling technique as the respondents. Data were obtained by employing a Perceptify-ICALL questionnaire with forty items using a six-point Likert’s scaling method (α = .839). Data were analyzed using descriptive statistics, hierarchical multiple regression, and MANOVA. Results showed that teachers’ perceived perspective was in a very high category, but not for their self-efficacy. The prominent factor influencing their perspective was the support and facilities provided by the school and government in succeeding EFL teaching using ICALL. Whereas the most influencing factor of their self-efficacy was their skills in operating computers and AI. Another finding was the fact that the teachers’ perceived perspective significantly affected teachers’ mastery experience. 2Pratama, Lestari, Kirkgöz &amp; Imaniar: Intelligent Computer-Assisted Language Learning The JALT CALL Journal vol. 20 no.3 This study suggests that Indonesian EFL teachers’ perceived perspective in EFL teaching using ICALL is well constructed, but their efficacy is on the contrary due to lower skills in operating computers and AI-powered devices or programs. Future professional development programs in improving the teachers’ computer and AI-operation skills are suggested to be undertaken as well as bringing the ICALL-based approach to EFL learning.

AI Concepts Integration in Developing E-Muhadathat Kits For Non-Arabic Speakers

Recent educational reforms focus on strategically integrating technology into teaching, aligning with the principles of the fourth industrial revolution (IR 4.0). Among the swiftly evolving technologies in language learning is Artificial Intelligence (AI), particularly in the form of Natural Language Processing (NLP). This technology has been applied to create the E-Muhadathat kit, an interactive Arabic conversation simulation tool designed to enhance communication skills for non-Arabic speaking students in Malaysian public universities. This study aims to investigate the role of AI in education, address the challenges in developing AI-based Arabic language learning software, and propose a model for the E-Muhadathat kit tailored for non-Arabic speakers. This literature review uses documentary methods to gather information from journals, conference proceedings, articles, dissertations, and digital books from databases such as Google Scholar, Springer Link, Science Direct, and Research Gate. The collected data undergoes descriptive analysis based on thematic categorization. The findings indicate that the concept of AI consists of three core components: machine learning, deep learning, and neural networks. Arabic linguists have recognized several challenges in developing AI-based software, such as orthographic, morphological, syntactic, anaphoric, and semantic ambiguities. Moreover, the E-Muhadathat kit's design integrates machine learning and deep learning techniques, featuring applications for both spoken and written language. The study's findings support educators and researchers aiming to create Arabic language software tailored for non-native speakers in Malaysian higher education institutions. As a result, the study advocates for further investigation into the use of AI in Arabic language education to enhance the communication abilities of non-native speakers in Malaysia.

Quantifying the impact of ASR-based instruction: What does the iSpraak platform learner data show?

Computer-assisted Pronunciation Training (CAPT) tools have become increasingly dependent on Automatic Speech Recognition (ASR) technology to provide automated corrective pronunciation feedback to learners. The extent to which ASR-based tools measurably improve second language (L2) pronunciation is of great interest to language educators globally, and Computer-assisted Language Learning (CALL) researchers. Studies to date have largely been conducted by research practitioners with small-to-medium sized samples at single institutions. The findings and conclusions drawn from such small-scale data collection might be significantly bolstered by analysing the vast stores of learner data from large CAPT platforms. This study is informed by a sizable eight-year dataset from iSpraak, an open-source pronunciation tool designed to model and evaluate L2 speech. Quantitative analysis of anonymised learner interactions with this application reveals significant gains in intelligibility measures across multiple languages. Results also suggest that the extent of ASR’s ability to improve learner pronunciation may be L2 dependent.

Exploring collaborative writing among large groups in online distance learning through a public forum and private chat tool

Abstract This study explored how collaborative writing, an often-used instructional strategy in second language (L2) learning, intersects with large-group dynamics, and investigated their potential impact on the quality of writing outcomes in an online distance learning course. Using a mixed-methods approach, the research scrutinized intra-group interaction processes in two large groups undertaking a computer-assisted language learning writing assignment and evaluated the impact of these interaction processes on their writing products. Data from discussions in both a public online forum and a private social communication platform (WeChat) were collected, systematically coded, and analysed quantitatively and qualitatively based on language functions. Data collection also included an assessment of the written products and follow-up group interviews. The findings indicate distinct interaction patterns between high-performing and low-performing groups, characterised by an expert/participant pattern and a dominant/passive pattern, respectively. Additionally, insights from the interviews shed light on these interaction patterns and the potential impact on student learning outcomes. The study suggests practical implications, highlighting the importance of task design in promoting high levels of collaborative knowledge construction to enhance students’ writing skills and L2 language learning in large-group settings.