Computer-assisted Language Learning Research Articles

Smart Operation Control of Power and Heat Demands in Active Distribution Grids Leveraging Energy Flexibility

Demand flexibility plays a crucial role in mitigating the intermittency of renewable power sources. This paper focuses on an active distribution grid that incorporates flexible heat and electric demands, specifically heat pumps (HPs) and electric vehicles (EVs). Additionally, it addresses photovoltaic (PV) power generation facilities and electrical batteries to enhance demand flexibility. To exploit demand flexibility from both heat and electric demand, along with the integration of PVs and batteries, Control and Communication Mechanisms (CCMs) are formulated. These CCMs integrate demand flexibility into the distribution grids to obtain economic benefits for private households and, at the same time, facilitate voltage control. Concerning EVs, the paper discusses voltage-based droop control, scheduled charging, priority charging, and up-/down-power regulation to optimize the charging and discharging operations. For heat demands, the on-off operation of the HPs integrated with phase change material (PCM) storage is optimized to unlock heat-to-power flexibility. The HP controllers aim to ensure as much self-consumption as possible and provide voltage support for the distribution grid while ensuring the thermal comfort of residents. Finally, the developed CCMs are implemented on a small and representative community of an active distribution grid with eight houses using Power Factory software and DIgSILENT simulation language (DSL). This scalable size of the active distribution network facilitates the careful study of symbiotic interaction among the flexible load, generation, and different houses thoroughly. The simulation results confirm that the integration of flexible demands into the grid using the designed CCMs results in the grid benefiting from stabilized voltage control, especially during peak demand hours.

Methodological characteristics in technology-mediated task-based language teaching research: Current practices and future directions

Abstract In the past two decades, the synergistic relationship among task-based language teaching (TBLT), instructed second language acquisition, and computer-assisted language learning has gained increasing interest.Technology-mediated TBLT combines these three research domains by integrating the use of technology with task-based approaches for second language (L2) learning purposes. Since the emergence of this framework, empirical studies have increasingly explored the incorporation of tasks with technology-mediated settings for L2 learning and teaching purposes. To understand the methodological characteristics of technology-mediated TBLT research to date, we conducted a systematic search and reviewed 254 technology-mediated TBLT studies published between 2000 and 2022 in peer-reviewed journals and book chapters. These studies were coded for methodological features, research foci, and types of technology. We further examined the role of technologies in task performance to identify their effectiveness in creating authentic tasks. The findings revealed that technology-mediated TBLT research investigated a rather limited scope of contexts, learner groups, and linguistic features, with little attention paid to evaluating the quality of task outcomes. The types of technology used were skewed toward computer-mediated communication. The results also showed that studies examined various interactional features, and the majority reported both quantitative and qualitative data. Furthermore, technologies were integrated into task design to create meaningful language use contexts. Based on these findings, we share suggestions for future technology-mediated TBLT research.

SMS based reservoir condition monitoring sensor system for pumped hydro storage in mini-grids

Solar mini-grids are a cost-effective and efficient method of improving energy access in sub-Saharan Africa, particularly in low-income communities. However, conventional battery storage systems have reduced the affordability of solar mini-grid-generated electricity, necessitating the development of alternative energy storage systems such as pumped hydro storage to replace lithium-ion batteries. This paper introduces a model for an SMS-based fluid parameter monitoring system to provide visibility of reservoir conditions during peak and off-peak periods. The model uses hardware such as voltage regulators, sensors, microcontrollers, and C- programming language software. Sensors monitor various parameters in the reservoir and penstock, transmitting signals to a microcontroller for analysis. The results are relayed to a display unit and personnel's mobile phones for alert notifications, ensuring precise and accurate reporting. Simulation results show the reliability of the design to monitor water levels, water temperature, flow rate, and transmission through SMS to mobile devices for timely reporting. The paper recommends the development and commercialization of this model for larger applications, such as monitoring dams for irrigation and power generation.

Optimization Through Artificial Neural Network and Compare with Response Surface Methodology for Multiples Yield

Cotton slub yarn is widely used in denomination and any other casual, physical and mechanical Conditions. The data for the underlying purpose was collected from the Department of Polymer Engineering, National Textile University, and Faisalabad. R-Programming language software is used for analysis. The output of cotton depends on several factors whose cumulative influence on Process efficiency has a direct influence. The purpose of the research was to optimize the 100% cotton slub yarn model (slub length, slub thickness, pause length and linear density) for multiples yield (elongation, imperfection, strength, coefficient of mass variation and hairiness) as Optimizing is a way of identifying and enhancing the performance of the constructed framework by assessing a set of quality parameters, such as process efficiency using two methods response- surface methodology (RSM) and artificial neural network (ANN) and the results are compared using mean square error (MSE). Furthermore, coefficients of determination () and the mean square error root (RMSE) are used for greater accuracy. However, the ANN has consistently performed better than the RSM in all the aspects. The final selected ANN model was able to simultaneously predict the five output parameters with an RMSE of 0.229.

Effect of Mobile Assisted Language Learning (MALL) Attitude and Practices in University Students

This study explores how technology, particularly mobile devices, is changing the landscape of foreign language learning. Traditionally, foreign language education relied on various methods and techniques, but the rise of technology and changing teacher attitudes have paved the way for innovative approaches. Mobile Assisted Language Learning (MALL) represents the latest evolution, following the earlier Computer Assisted Language Learning (CALL) approach. This research investigates the impact of MALL on student attitudes and practices in foreign language learning. The mixed study involved 40 university students from various majors. Data was collected through a 5-point Likert scale survey and follow-up semi structured interviews with some volunteers. The findings revealed a strong belief among students that mobile devices are highly effective for language learning. Students highlighted the advantage of instant access to target language input through mobile tools. Overall, participants' high mobile phone use, media preferences, and frequency of mobile phone usage all pointed towards a positive attitude towards the role of mobile phones in their foreign language development. The findings of this study extend beyond the immediate research and can be applied by future researchers, teachers, parents, and others interested in language learning.

Teaching and Learning English in the Digital Era: Opportunities and Challenges

This paper examines the opportunities, challenges, and perspectives of teaching and learning English in the digital era. With the rapid advancement of technology and its integration into educational settings, English language instruction has experienced significant transformations. The paper explores the potential benefits of digital tools and platforms in language learning while also addressing the challenges in the digital language classroom. Based on a review of previous studies and a comprehensive analysis, it further discusses the evolving roles of teachers and learners in this digital landscape and presents strategies for effective implementation and utilization of technology in English language education. The findings offer to share expertise, disseminate the lessons learned, and recommend best practices collected from scholarship. Sustainable solutions to specific problems and perspectives to cope with future challenges have been proposed with the recommendation of effective systems such as Computer Assisted Language Learning (CALL), Mobile Phone Assisted Language Learning (MPALL) and other sophisticated tools that fit some specific situations.

Hey <i>Google</i>, Let’s Write

Writing involves more than attention to form (e.g., orthography, grammar), since it requires attention to text type, content, and genre. However, most students of English as a second language (L2) tend to prioritize linguistic accuracy in their writing, to the detriment of the content of their texts. Automatic speech recognition (ASR) has the potential to mitigate this, as it reduces the cognitive burden of writing by facilitating the text input process (using a skill most humans possess—speaking), offering assistance in spelling, and allowing a focus on other aspects of the task (e.g., cohesion, content). Automatic speech recognition is not only accessible and free, but it also fulfills Chapelle’s (2001) criteria of an effective computer-assisted language learning tool (e.g., authenticity, learner fit). Despite these affordances, there is a dearth of studies examining the possible affordances of ASR for writing. This mixed methods, one-shot study examines L2 writers’ perceptions of using ASR to write using the technology acceptance model (TAM). Seventeen (N = 17) undergraduate students at a Canadian university were provided with training on Google Voice Typing (Google Docs) and carried out a series of ASR-based writing tasks over a two-hour period. In order to measure their perceptions of the target criteria, participants filled in a TAM-informed survey consisting of statements about their experience with ASR scored on a 7-point Likert scale. To further explore the participants’ perceptions, semi-structured interviews followed. Findings indicate positive perceptions of ASR’s usefulness in terms of language learning and its ease of use due to the user-friendly voice commands. This suggests that ASR has pedagogical potential, thus requiring further examination to determine its optimal use for L2 writing.

Adaptation of English Teachers to the Use of CALL in Technical Secondary Schools in Nyanza District, Rwanda, and Its Implications on Students’ Performance in English

In some Rwandan schools, the use of Computer-Assisted Language Learning (CALL) in English teaching has influenced students' English performance. In technical secondary schools, language teachers have begun utilizing new technologies as pedagogical tools to enhance students' English performance. The current study investigates how teachers adapt to the use of CALL and its implications for students' performance in English subjects in some Rwandan technical secondary schools. Sociocultural theory in language teaching guided this investigation. It used a descriptive research design with a sample of 24 English teachers from Nyanza Technical Secondary Schools. This study utilized a census of all 24 English teachers. Data were collected using questionnaires in the form of a Likert scale. Descriptive analyses indicate that 91% of respondents have a positive attitude towards CALL. The findings show that teachers of English use CALL in teaching English, which affects students’ performance in English. The inferential analysis results show a P value of 0.020, which is lower than the significant correction of 0.05. Therefore, the study findings confirm the teachers’ positive attitude towards CALL. According to the research, the Rwanda TVET Board should train new teachers and continue updating existing English teachers with new CALL technologies.

Risk factors and prognosis of postoperative acute myocardial infarction in elderly hip fracture patients combined with coronary heart disease

IntroductionThis article mainly studies the risk factors for postoperative acute myocardial infarction (AMI) in elderly hip fracture patients combined with coronary heart disease (CHD), constructs a prediction model, and evaluates the prognosis of all the patients.MethodsThis article retrospectively collected elderly patients with hip fracture and CHD who underwent hip fracture surgery at the Third Hospital of Hebei Medical University from January 2019 to December 2021. Demographic data, laboratory indicators, and imaging examination results were collected from the medical case system. The risk factors of postoperative AMI were determined by univariate and multivariate logistic regression, and a nomogram prediction model was established. The ROC curve, calibration curve and DCA decision curve were plotted by R language software. The patients in the training set were followed up for 2 years to evaluate their survival situation.Results1094 eligible patients were divided into a training set (n = 824 from January 1, 2019 to September 31, 2021) and a validation set (n = 270 from October 1, 2021 to December 31, 2022). In the training set, women accounted for 58.6%; The average age of the patients was 79.45 years old; The main type of fracture was intertrochanteric fracture. There were 64.7% patients taken B receptor blockers; A total of 166 (20.1%) patients underwent percutaneous coronary intervention (PCI); Hypertension accounted for 55.5%; 520 (63.1%) patients had a preoperative waiting time greater than 3 days; The average hemoglobin value upon admission was 101.36 g/L; The average intraoperative bleeding volume was 212.42 ml; The average surgical time was 2.5 ± 0.3 h; Reginal anesthesia accounted for 29.7%; 63 (68.5%) AMI patients had no obvious clinical symptoms; 68 (73.9%) AMI patients did not show ST-segment elevation in ECG; The risk factors of postoperative AMI were age, hemoglobin at admission, diabetes, chronic kidney disease, intraoperative bleeding, and reginal anesthesia. The AUC of the nomogram prediction model was 0.729. The AUC in the validation set was 0.783. Survival analysis showed a significant statistical difference in 2-year mortality between patients with AMI and without AMI, among all the patients with AMI, patients with ECG ST-segment elevation has higher mortality than patients without ECG ST-segment elevation.ConclusionOur research results found that the incidence of postoperative AMI in elderly patients with hip fractures and CHD was 11.1%. Age, diabetes, hemoglobin at admission, regional anesthesia, chronic kidney disease, and intraoperative bleeding are risk factors. The AUC of the nomogram in training set is 0.729. The 2-year mortality rate of the patients with AMI is higher than that of patients without AMI.

Network pharmacology and molecular docking technology for exploring the effect and mechanism of high-dose vitamin c on ferroptosis of tumor cells: A review.

To investigate the mechanism by which high-dose vitamin C (HVC) promotes ferroptosis in tumor cells via network pharmacology, vitamin C-related and ferroptosis-related targets were obtained from the PharmMapper and GeneCards databases, respectively, and their common targets were compared using the Venn diagram. Common targets were imported into the STRING database for protein-protein interaction analysis, and core targets were defined. Core targets were enriched for Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways using the R language packages. A map of the core target-based interaction network and a map of the mechanism by which HVC regulates ferroptosis were constructed. A total of 238 vitamin C-related and 721 ferroptosis-related targets were identified, of which 21 targets were common to both. Furthermore, ALDOA, AHCY, LDHB, HSPA8, LGALS3, and GSTP1 were identified as core targets. GO enrichment analysis suggested that the main biological processes included the extrinsic apoptotic signaling pathway and pyruvate metabolic process. KEGG enrichment analysis suggested that HVC regulates ferroptosis mainly through the amino acid and carbohydrate metabolic pathways. The targets were validated by molecular docking. In conclusion, HVC may promote ferroptosis in tumor cells by regulating metabolic pathways, and there is a synergistic effect between HVC and type I ferroptosis inducers. Glycolysis-dependent tumors may be beneficial for HVC therapy. Our study provides a reference for further clinical studies on HVC antitumor therapy.

Language Dissemination Paths and Modes Aided by Computer Technology

The expansion of technology and computer science, as well as advancements in language instruction and learning methodologies, has enabled computer-assisted language learning technologies to tackle this challenge. In the field of Chinese learning, a few language learning computerized systems in the country and abroad concentrate mainly on language, grammar acquisition only have one or two assessment indicators as basis of evaluation, that definite functional flaws provide a general assessment to learners' pronunciation. In this manuscript, Language Dissemination Paths and Modes Aided by Computer Technology (LDPM-QICCNN-KOA) are proposed. The input data are collected from Chinese Corpus dataset. Then the data is given into unscented trainable kalman filter for preprocessing the input data. Then the preprocessed data are provided to QICCNN for Language Dissemination. In general, the based Quantum-inspired Complex Convolutional Neural Network doesn’t express adapting optimization approaches to determine optimal parameters to ensure exact identification. Hence, KOA utilized to enhance Quantum-inspired Complex Convolutional Neural Network, which accurately done the Language Dissemination Paths and Modes. The proposed LDPM-QICCNN-KOA method is executed on python. Then performance of proposed technique is analyzed with other existing methods. The proposed technique attains 26.36%, 20.69% and 35.29% higher accuracy; 19.23%, 23.56%, and 33.96% higher F1-Score; 26.28%, 31.26%, and 19.66% higher precision when comparing with the existing methods such as research on network oral English teaching system depend on machine learning (LDPM-DBN), nonlinear network speech recognition structure in deep learning algorithm (LDPM-DNN), research on open oral English scoring system depend on neural network (LDPM-BPNN).

Promoting critical reading instruction in higher education: a three-step training scheme facilitated by using corpus technology

Abstract This study examines the development of students’ cognitive skills through hands-on concordancing, also known as the inductive Data-driven learning (DDL) method (Cobb, T. 1997. Is there any measurable learning from hands-on concordancing? System 25(3). 301–315). This method involves learners directly using concordance software to identify language rules by observing and working with concordance results. While previous research has explored DDL’s role in language acquisition, its impact on cognitive growth has received less attention. Building on a corpus-based language pedagogy (CBLP) (Ma, Q., J. Tang & S. Lin. 2022a. The development of corpus-based language pedagogy for TESOL teachers: A two-step training approach facilitated by online collaboration. Computer Assisted Language Learning 35(9). 2731–2760, Ma, Q., R. Yuan, L. M. E. Cheung & J. Yang. 2022b. Teacher paths for developing corpus-based language pedagogy: A case study. Computer Assisted Language Learning. 1–32), we designed a three-step training scheme that included an online task, a computer lab lesson, and a student independent corpus exploration task. The study involved 45 second-year English majors. The data were collected through surveys, interviews, and written reports, focusing on student learning of cognitive skills such as speculating, noticing, inferring, and verifying, as synthesized by Chun (2011. Learners as corpus researchers: Developing cognitive skills through hands-on concordancing. Foreign Languages Education 18(3). 73–103). The results indicate a positive response to the CBLP, with students’ independent exploration task contributing to improved critical reading and thinking skills. This highlights the effectiveness of our three-step CBLP scheme in developing cognitive skills and enhancing independent research. Overall, the study emphasizes the potential of hands-on concordancing and CBLP in fostering critical reading skills.

The agency development of teachers of an additional language via immersive VR telecollaboration

Teacher agency is essential for professional growth and teachers’ ability to support transformative student learning. This study looks into the potential of virtual reality (VR) as a joint practice teaching and reflective discussion environment for achieving language teacher agency. A group of teachers of an additional language (LX) participated in a telecollaborative project. They were provided with VR devices and language learning software, Immerse, for practice teaching and reflective discussions after each VR teaching. The data of this qualitative study were video recordings of the teaching and discussion sessions and the participants’ answers to an end-of-project questionnaire based on the Cognitive Affective Model of Immersive Learning (CAMIL) by Makransky and Petersen in 2021. The video recording analysis results showed that the participants used almost all the teaching facilitation functions (e.g., tools that allowed teachers to present content, conduct classroom management, and monitor students) provided by Immerse. The themes that emerged from the participants’ reflective discussions analysis also indicated mutual support for teacher agency development. Their responses to the questionnaire revealed that taking advantage of the teaching facilitation functions reflected the factors affecting learner agency as outlined in the CAMIL model. The findings of this study provided empirical evidence that VR environments can be a viable choice for teacher intercultural collaboration in which teachers of different backgrounds and experiences could together explore the potentiality of VR for teaching an additional language, sustain one another’s growth, and achieve teacher agency.

Exploring memory synchronization and performance considerations for FPGA platform using the high-abstracted OpenCL framework: Benchmarks development and analysis.

A key benefit of the Open Computing Language (OpenCL) software framework is its capability to operate across diverse architectures. Field programmable gate arrays (FPGAs) are a high-speed computing architecture used for computation acceleration. This study investigates the impact of memory access time on overall performance in general FPGA computing environments through the creation of eight benchmarks within the OpenCL framework. The developed benchmarks capture a range of memory access behaviors, and they play a crucial role in assessing the performance of spinning and sleeping on FPGA-based architectures. The results obtained guide the formulation of new implementations and contribute to defining an abstraction of FPGAs. This abstraction is then utilized to create tailored implementations of primitives that are well-suited for this platform. While other research endeavors concentrate on creating benchmarks with the Compute Unified Device Architecture (CUDA) to scrutinize the memory systems across diverse GPU architectures and propose recommendations for future generations of GPU computation platforms, this study delves into the memory system analysis for the broader FPGA computing platform. It achieves this by employing the highly abstracted OpenCL framework, exploring various data workload characteristics, and experimentally delineating the appropriate implementation of primitives that can seamlessly integrate into a design tailored for the FPGA computing platform. Additionally, the results underscore the efficacy of employing a task-parallel model to mitigate the need for high-cost synchronization mechanisms in designs constructed on general FPGA computing platforms.

Conceptualising language MOOC diversity: The creation of a defined taxonomy through the analysis of course indicators

Abstract Language MOOC research has experienced a notable evolution from practice to conceptuality since its emergence as a subdiscipline of computer-assisted language learning. The versatility of the MOOC format for language learning has led to experimental designs that combine linguistic acquisition with other educational activities. This has been considered to be conducive to new ways of understanding how language learning occurs in LMOOCs, although there is no solid classification of LMOOCs subtypes to date based on course design. This study aimed to contribute to the conceptualisation of the field by creating a taxonomy for existing LMOOCs. Grounded theory strategies were adopted, so evidence was systematically collected to develop conceptual categories based on a thorough analysis process of the syllabus and short description of 432 courses. As a result, six LMOOC modalities emerged from the analysis: general language learning LMOOCs, LMOOCs for academic purposes, LMOOCs for professional purposes, LMOOCs focused on a specific language skill development, cultural-oriented LMOOCs, and meta-language learning LMOOCs. This study means a significant contribution to the LMOOC research field inasmuch as it is one of the first empirical-based attempts to broaden the definition of LMOOC.

Themes and trends in marathon performance research: a comprehensive bibliometric analysis from 2009 to 2023.

Background: When marathon runners break the 2-h barrier at the finishing line, it attracts global attention. This study is aimed to conduct a bibliometric analysis of publications in the field of marathon running, analyze relevant research contributors, and visualize the historical trends of marathon performance research over the past 15years. Methods: On 8 December 2023, we extracted high-quality publication data from the Web of Science Core Collection spanning from 1 January 2009 to 30 November 2023. We conducted bibliometric analysis and research history visualization using the R language packages biblioshiny, VOSviewer, and CiteSpace. Results: A total of 1,057 studies were published by 3,947 authors from 1,566 institutions across 63 countries/regions. USA has the highest publication and citation volume, while, the University of Zurich being the most prolific research institution. Keywords analysis revealed several hotspots in marathon research over the past 3years: (1) physiology of the elite marathon runners, (2) elite marathon training intensity and pacing strategies, (3) nutritional strategies for elite marathon runners, (4) age and sex differences in marathon performance, (5) recovery of inflammatory response and muscle damage. Conclusion: This study presents the first comprehensive bibliometric analysis of marathon performance research over the past 15years. It unveils the key contributors to marathon performance research, visually represents the historical developments in the field, and highlights the recent topical frontiers. The findings of this study will guide future research by identifying potential hotspots and frontiers.

Informal digital learning of English and EFL learners’ willingness to communicate: investigating the mediating role of L2 grit

ABSTRACT Informal digital learning of English (IDLE) has recently become a heated debate in the realm of computer-assisted language learning. Despite the potential benefits of IDLE, the mediating role of English as a foreign language (EFL) learners’ domain-specific grit in the relationship between IDLE and willingness to communicate (WTC) has yet to receive due attention. Therefore, the current study explored how L2 grit mediated the relationship between IDLE and WTC. A sample of 313 Iranian EFL learners filled out three questionnaires. The results of the mediation model analysis conducted with AMOS indicated that L2 grit fully mediated the association between IDLE and WTC. In other words, it was figured out that IDLE impacts learners’ L2 WTC indirectly through their grit. The findings of this study implied that enhancing perseverance and passion for pursuing long-term goals can help EFL learners benefit from IDLE-based activities for communicative purposes. Ultimately, suggestions for future research are offered.

Risk Factors of Chemotherapy-Induced Thrombocytopenia After Oxaliplatin-Containing Chemotherapy for Gastrointestinal Malignancies.

Thrombocytopenia is among the most common chemotherapy-related hematologic toxicities. We aim to determine the predictors of oxaliplatin chemotherapy-induced thrombocytopenia in patients with gastrointestinal tumors to guide the clinic. Clinical data of 750 patients with a malignant gastrointestinal tumor were included as the primary cohort. Basic clinical data, serological indices, and anthropometric indices of these patients were collected. According to the presence or absence of CIT, univariate analysis was performed to identify significant factors for multivariate analysis. In R language software, nomogram was constructed based on the results of multi-factor analysis, and the calibration curve and ROC curve were drawn. Univariate analysis identified 17 factors as closely related to CIT occurrence, namely age, lymph node metastasis (N) stage, metastasis (M) stage, lung metastasis, other site metastasis, chemotherapy regimen, course of treatment, total dose of oxaliplatin, AST, albumin, neutrophils, monocytes, baseline platelets, transferrin, natural killer (NK) cell, phase angle, and SMI (P < 0.10). The binary logistic multivariate regression analysis revealed five independent risk factors for developing CIT (P < 0.05), including the M stage, total dose of oxaliplatin, albumin, baseline thrombocyte count, and NK cell. Based on the results of multivariate logistic regression analysis, R software was used to establish a nomogram model. The calibration curve shows that the combined predictor has good consistency. The area under the ROC curve was 0.877 and the best cut-off value was 0.3579613 (sensitivity, 78.9%; specificity, 81.8%), which showed the better prediction efficiency. The total dose of oxaliplatin, M stage, albumin, baseline platelet count, and NK cell was independent risk factors for CIT. The sequentially constructed histogram model had a good predictive effect on the risk of thrombocytopenia caused by oxaliplatin chemotherapy in patients with gastrointestinal malignancies.

Implementing smart technologies for teaching Ukrainian language across secondary and higher education: case studies and practical recommendations

The article is dedicated to exploring SMART technologies in the process of teaching the Ukrainian language to students in general secondary and higher education institutions. Specifically, methodical recommendations are formulated to enhance the effectiveness of utilizing these technologies in the modern educational process. The significance of SMART technologies is substantially increasing in the innovative paradigm of the educational process under the influence of integration, globalization, and the transition to an information society. The article employs a comparative and content analysis of distance and electronic learning of the Ukrainian language. It delves into the theoretical foundations of computer-assisted language teaching as a distinct methodological approach based on “smart” technologies. The authors emphasize the effectiveness of using interactive whiteboards and multimedia presentations to implement the principle of visualizing language elements and structures, facilitating students' acquisition of lexical-grammatical material. It is identified that creating mental maps is an effective SMART teaching technology for the Ukrainian language. To this end, computer services such as MindMeister, Mindomo, Cliffy, Spinscape, Bubbl.us, MAPMYself, SpiderScribe, and others are recommended. The research concludes that the use of SMART technologies by students in general secondary and higher education institutions contributes to increased motivation for language learning, improved literacy levels, facilitates independent research efforts aimed at enhancing professional-communicative competence, and streamlines the process of knowledge assessment by educators.

Computer-Assisted Language Learning: Pros and Cons from the Perspective of Moroccan EFL Instructors

The fast advancement of technology has profoundly impacted how we live, work, and even learn. In the education sector, technology plays a significant role as it has transformed the traditional methods of teaching and learning processes. Computer-assisted language learning and teaching is a concrete example of how technological development has revolutionised the field of education. Computers are incredibly powerful teaching instruments that can support many learning objectives. Therefore, the current study aims to investigate Moroccan high school teachers' perceptions about the potential pros and cons of computer technology in learning English as a foreign language (EFL). To attain the study's objective, the researchers employed a self-developed online questionnaire involving 112 participants. The research results indicate that EFL instructors in Fes-Meknes, Morocco, have positive perceptions regarding implementing CALL in their classrooms. The results suggest that the programs can motivate the learners, enhance their confidence, motivate them, and allow access to diversified educational material. Still, constraints related to financing, uneven access to technology, and scarcity of professional training for teachers are hindering the full implementation of CALL. The research recommends improving financial investment in the educational field, guaranteeing impartial access to technology and providing human resources with professional training to ensure the effective integration of CALL.