Computer-assisted Language Learning Research Articles

Analysis of the sensitization spectrum in patients with severe allergic diseases using the ImmunoCAP ISAC method

BACKGROUND: An important advance in modern allergology has been made by the introduction of allergenic molecules/components, including their detection by the ImmunoCAP ISAC method. This method is useful in patients with a complex spectrum of sensitization and severe forms of allergic diseases, where various predictors of severe course are actively searched for.
 AIM: To evaluate the informativeness of component resolved diagnostic by ISAC ImmunoCAP method in patients with severe bronchial asthma and severe atopic dermatitis.
 MATERIALS AND METHODS: A single-center retrospective study was conducted from January to August 2023. 100 patients who were candidates for biologicals for severe bronchial asthma (group 1; 63 patients), severe atopic dermatitis (group 2; 20 patients), or their combination (group 3; 17 patients) were included. Component restlved diagnostic was performed by ImmunoCAP ISAC method.
 RESULTS: Polysensitization and high occurrence of food and fungal allergens were more frequently detected in the groups of patients with severe atopic dermatitis. When analyzing the pollen sensitization spectrum in groups 2 and 3, Bet v 1 and PR-10 family cross-linked molecules (Mal d 1, Pru p 1, Ara h 8, Gly m 4, Cor a 1.04), as well as Ole e 9, Cyn d 1, Ph p 1 and Par j 2 were the most common. Epidermal allergens were common in all three groups. Lipocains (Can f 1, Can f 4, Can f 6, Ecu q 1, Mus m 1), kallikreins (Can f 5), and albumin (Fel d 2) dominated among them. The presence of sensitization to household allergens was detected only in group 2 and only to the molecule Der p 23. Among fungal allergens, the allergen Asp f 6 was predominant in the groups with severe atopic dermatitis, and the component Alt a 1 in patients with severe bronchial asthma. Among food allergens, one of the most common allergens was the molecule Gad c 1, Gal d 1, Gal d 2, Gal d 5 and Bos d 6.
 CONCLUSION: Component resolved diagnostic is an accurate assay suitable for determining the spectrum of sensitization in patients; its result can serve as a distinct biomarker for severe allergic diseases.

The Impact of Technology-Enhanced Language Learning on Bilingual Education

Bilingual education stands as a pivotal approach in contemporary educational landscapes, aiming to cultivate bilingualism and enhance academic achievement among students. In recent years, technology-enhanced language learning (TELL) has emerged as a promising avenue to augment bilingual education efforts. This paper presents a thorough examination of the impact of TELL on bilingual education, synthesizing theoretical frameworks, exploring various technologies utilized, assessing effectiveness, and addressing challenges and future directions. The theoretical underpinnings of TELL encompass constructivism, sociocultural theory, and cognitive load theory. Drawing from constructivist principles, TELL engages learners actively in constructing knowledge through meaningful interactions with technology-mediated learning environments. Sociocultural theory accentuates the socio-cultural context of language learning, underscoring TELL's potential to foster collaboration and cultural exchange among bilingual learners. Cognitive load theory informs the design of TELL materials to optimize learning outcomes by managing cognitive resources effectively. Technologies employed in bilingual education span diverse platforms, including computer-assisted language learning (CALL), mobile applications, virtual reality (VR), augmented reality (AR), and online collaboration tools. CALL platforms offer interactive exercises and personalized feedback, while mobile applications afford ubiquitous access to language learning resources. VR and AR technologies provide immersive experiences, enriching cultural understanding and language proficiency. Online collaboration tools facilitate synchronous and asynchronous communication, fostering peer interaction and collaboration. Research findings underscore the effectiveness of TELL in enhancing language proficiency, cultural understanding, and overall learning outcomes in bilingual education settings. TELL interventions have demonstrated significant improvements across language skills, motivating learners and fostering positive attitudes toward language learning. However, challenges such as limited access to technology, digital literacy skills, and the need for teacher training persist, hindering widespread implementation. Addressing these challenges requires concerted efforts to promote equitable access to technology, enhance digital literacy skills, and provide ongoing professional development for educators. Collaborative endeavors among stakeholders are essential to develop inclusive strategies for leveraging technology to support bilingual learners effectively. Future research should focus on innovative TELL approaches, long-term impact evaluation, and best practices for technology integration in bilingual education. TELL holds immense promise in enriching bilingual education by providing interactive, engaging, and culturally relevant learning experiences. By leveraging theoretical frameworks and diverse technologies, TELL has the potential to transform language learning practices and cultivate global citizens proficient in multiple languages. However, concerted efforts are needed to overcome challenges and maximize the benefits of TELL for all bilingual learners, emphasizing the importance of collaboration, research, and advocacy in advancing bilingual education in the digital age.

STUDY OF PREFRONTAL OXYGENATION DURING EMOTIONAL THINKING USING FUNCTIONAL NEAR-INFRARED SPECTROSCOPY (FNIRS)

Introduction: This section provides an overview of the project and introduces the topic. It should include the background, objectives, and scope of the research. Literature Review: This section reviews relevant literature related to the topic to provide a better understanding of the existing research and technology available. It should include sources such as books, academic journals, and online articles. Methodology: This section outlines the methodology used to design and develop the project, including the hardware and software components, programming languages and tools used, and testing procedures. System Design: This section describes the architecture and design of the system, including the hardware and software components, communication protocols, and interfaces. It should provide a detailed explanation of how the system is structured. Implementation: This section details the process of implementing the system, including the setup of the hardware and software components, programming of the microcontroller and sensors, and integration of any external platforms. Results and Evaluation: This section presents the results of the testing and evaluation of the system, including the performance, efficiency, and effectiveness of the system in achieving its objectives. It should also discuss any limitations or challenges encountered during testing. Conclusion and Future Work: This section summarizes the research findings and provides recommendations for future work. It should discuss any potential for further development and improvement of the system.

Effects of flipped English learning designs on learning outcomes and cognitive load: Workload of out‐of‐class activities versus during‐class activities

AbstractBackgroundSome studies have researched the correlation between flipped learning and cognitive learning outcomes; however, there is a paucity of research elaborating on the effects of flipped language learning on cognitive load (CL).ObjectivesThis study investigates the effects of using flipped learning designs (student‐led, teacher‐led and collaboration‐led) on learning outcomes and CL management during out‐of‐class activities versus during‐class activities.MethodsA mixed methods research was used to concurrently triangulate different strands of data on the effects of flipped learning designs on English as foreign language (EFL) learners' learning outcomes and CL. A total of 122 EFL learners were randomly assigned to either the control or experimental group and participated in the study. The interpretations were made based on running one‐way analysis of variance between four groups.Results and ConclusionThis study evidenced the efficacy of the interactive use of collaboration‐led flipped learning design over student‐led and teacher‐led designs for improving learning outcomes and lowering CL during computer‐assisted language learning (CALL) course.Pedagogically, CALL practitioners need to develop and integrate a well‐organized combination of student‐led and teacher‐led flipped learning activities for during‐class and out‐of‐class phases with respect to the CL and learning material complexity, while also considering the specific contexts and goals of their instructional settings. Theoretically, the results indicate the necessity of merging active learning and sociocultural theories into an instructional design to take advantage of the identified affordances of flipped language learning approach in terms of psychological effects (CL management) and learning effects (CALL outcomes).

A Study on Using Computer-Assisted Language Learning to Shape a Real Environment for Learning Chinese as a Foreign Language

With the development of technology, more and more technologies are being applied to the teaching of essential Chinese. This study will investigate whether technology can be applied in the process of teaching Chinese as a foreign language, creating a Chinese learning environment through Computer-Assisted Language Learning (CALL), etc. to assist learners in better learning Chinese. CALL can provide learners with a more immersive learning environment through virtual reality, artificial intelligence, online classrooms, and other means. Instead of a teacher-centered classroom centered on students, the focus is on cultivating their language abilities, not just for paper-based dumb Chinese, striving to focus on vocabulary, sentence grammar and cultural aspects to assist learners in better learning Chinese. Multiple studies have also shown that the use of technology to create a Chinese learning environment is beneficial for Chinese learners to learn Chinese. At the same time, this learning method is beneficial for reducing learners' pressure and enhancing their interest. In addition, learning Chinese in such a language environment which is more beneficial for learners to deepen their impression of the content they are learning, understand Chinese culture, better use Chinese for communication, and enhance their Chinese language proficiency.

Plus noise unlock

Abstract What happens when speech synthesis applications are incompatible with certain software? This essay considers how inaccessibility within the software and programming language Max is sonically, aesthetically, culturally, and ideologically amplified through a case study of “plus noise unlock,” which is the sound made by the author’s computer when she attempts to use a screen reader within a patcher window.

Characteristics of Postoperative Heart Failure in Older Hip Fractures Patients Combined with Coronary Heart Disease and Construction of a Prediction Model of Nomogram, a Retrospective Cohort Study.

Older patients combined with coronary heart disease (CHD) develop acute heart failure (AHF) after hip fracture surgery is common, and this study aimed to investigate the risk factors of postoperative AHF in older hip fracture patients and to construct a nomogram prediction model. We retrospectively collected older hip fracture patients with CHD who underwent hip fracture surgery at the Third Hospital of Hebei Medical University from January 2017 to December 2021. We divided them into a training set and a validation set. We collected the demographic data, laboratory indicators and imaging examination results. We identified risk factors for postoperative AHF and used R language software to establish a nomogram prediction model, plot ROC curves, calibration curves and DCA decision curves. We retrospectively collected 1288 older hip fractures patients with CHD. After excluding 214 patients who did not meet the criteria, 1074 patients were included in our research and we divided them into the training set and the validation set. In the training set, a total of 346 (42.8%) patients developing postoperative AHF. Through univariate and multivariate logistic regression analysis, we identified the risk factors for postoperative AHF and constructed a nomogram prediction model. The AUC of the prediction model is 0.778. The correction curve shows that the model has good consistency. The decision curve analysis shows that the model has good clinical practicality. There were 42.8% older patients combined with CHD develop postoperative AHF. Among them, fracture type, age, anemia at admission, combined with COPD, ASA ≥ 3, and preoperative waiting time >3 days are risk factors for postoperative AHF. We constructed a nomogram prediction model that can effectively predict the risk of postoperative AHF in older hip fracture patients combined with CHD.

Evaluating the efficacy of Kahoot as a computer-assisted language learning tool in higher education

This study aimed to analyse the effectiveness of using the computer tool Kahoot for foreign language learning in higher education, as well as to address the problem of students' lack of motivation in learning English. This study hypothesised that using the Kahoot app in foreign language classes would improve students' motivation through its engaging approach. To test this hypothesis, a survey was conducted among students who had studied English using this tool. The results showed that students who used the Kahoot app in the classroom were significantly more motivated to learn English. This was made possible by the app's ability to vary the learning tool depending on the needs of the students, which encouraged their active participation in the learning process. The effectiveness of Kahoot as a tool in higher education for learning foreign languages is promising. Its engaging and interactive format, instant feedback, and collaborative learning opportunities make it a valuable tool for enhancing language learning. However, it is important for teachers to be aware of its limitations and complement it with other activities to ensure comprehensive language development. Overall, Kahoot can be a valuable addition to the language learning toolkit in higher education.

Generating Genre-Based Automatic Feedback on English for Research Publication Purposes

Artificial intelligence (AI) for supporting second language (L2) writing processes and practices has garnered increasing interest in recent years, establishing AI-mediated L2 writing as a new norm for many multilingual classrooms. As such, the emergence of AI-mediated technologies has challenged L2 writing instructors and their philosophies regarding computer-assisted language learning (CALL) and teaching. Technologies that can combine principled pedagogical practices and the benefits of AI can help to change the landscape of L2 writing instruction while maintaining the integrity of knowledge production that is so important to CALL instructors. To align L2 instructional practices and CALL technologies, we discuss the development of an AI-mediated L2 writing technology that leverages genre-based instruction (GBI) and large language models to provide L2 writers and instructors with tools to enhance English for research publication purposes. Our work reports on the accuracy, precision, and recall of our network classification, which surpass previously reported research in the field of genre-based automated writing evaluation by offering a faster network training approach with higher accuracy of feedback provision and new beginnings for genre-based learning systems. Implications for tool development and GBI are discussed.

ChatGPT as a CALL tool in language education: A study of hedonic motivation adoption models in English learning environments

AbstractThe advancement of information technologies has led to increased attention to AI chatbots as valuable tools for computer-assisted language learning (CALL), drawing the attention of both academic scholars and industry practitioners. However, there remains limited understanding regarding the adoption of AI chatbots, specifically within the context of the English language. To address this existing research gap and examine the perception and motivation of usage of ChatGPT, this research employed the hedonic motivation system adoption model (HMSAM) to examine the adoption of ChatGPT. Employing structural equation modelling (SEM), a comprehensive investigation was conducted using data sourced from 189 valid responses obtained through an online survey administered to Chinese international students who are currently enrolled in British universities. The findings reveal that the research model effectively elucidates the elements influencing the adoption of ChatGPT in English learning. Notably, boredom, joy, focused immersion, and control emerged as significant mediating factors pertaining to the link between perceived ease of use and behavioural intention. These findings offer meaningful perspectives for upcoming researchers and practitioners in English language teaching and learning, contributing to promoting innovation in this domain.

Assessing Intercultural Communicative Competence in British Council Algeria

Due to globalization and technological advancement, the world has become open and people have unrestricted access to an infinite amount of resources. Computer technology and web-based gadgets are hereby considered imperative for personal, educational, and professional development. Reliance on computer-based instruction has rendered the teaching and the learning processes appealing and rarefied. The result, or the basic outcome, would be individuals able to fit in the ever-changing globalized world and who are able to transcend far beyond content users to content creators. The purpose of this study is to demonstrate what contributions computer assisted language learning (CALL) has on the educational system in general and on students in particular, and how effective teaching and learning can be optimized. Another aim of this research is to recognize how CALL contributes to the behavioral, cognitive, and meta-cognitive development of the learners. British Council is a web-based platform that offers varied instructional contents for learners from across the globe. This paper seeks to show how British Council, as a form of CALL, contributes in developing learners’ communicative competence and intercultural skills.

A craniometric study of the Medieval sample from Deraheib (Northern Sudan)

The history of North Africa has been always tightly connected to events occurring in Eurasia. Human migra-tions in both directions are well-documented in written sources and archaeological records. To gain a comprehen-sive understanding of historical processes, it is essential to study the remains of individuals who inhabited this region during various time periods. A lack of cranial metric data on the Medieval population of North Africa im-pedes thorough investigation of the population history of the region. This paper presents a craniometric study of the sample from the Southern necropolis at Deraheib. This study contributes to filling the existing void in the un-derstanding of the Medieval population of North Africa. According to written sources, the site was a center of gold mining, known as the city of al-Allaki, dated to the 9th to 15th centuries AD. The city attracted a diverse population seeking economic opportunities. Besides this, Al-Allaki served as an important point on the caravan route which was utilized by merchants and pilgrims traversing the Nubian Desert on their way to Jeddah. The study analyzes cranial metrics of a total of 23 individuals (14 male and 9 female) skulls recovered from the southern necropolis Deraheib sample and employs 55 linear dimensions, following Martin's/Howells craniometric protocol as well as some additional measurements. Statistical analyses were performed using the R language packages and the Multican software. Our results revealed heterogeneity of the sample in male and female parts of the sample at the intra-group level: an observation aligning with existing archaeological and historical evidence. The limited size of the sample warns against any firm conclusions regarding affinities of the Deraheib population. Our intergroup comparison has shown that the cranial sample from the Southern Necropolis of the Deraheib site displays morphological features that are more similar to neighboring Caucasoid populations rather than equatorial groups from East Africa.

Network pharmacology and molecular docking studies on the mechanism of action of moist exposed burn ointment for treatment of diabetic foot ulcer

Purpose: To investigate the bioactive components and mechanism of action of moist exposed burn ointment (MEBO) for treatment of diabetic foot ulcers using network pharmacology (NP) and molecular docking technology 
 Methods: Through pharmacology database of traditional Chinese medicine (TCM) systems (TCMSP), analysis platform and symptom mapping (SymMap) database, the bioactive components of MEBO were screened for and protein binding to bioactive components was predicted. Proteins related to Diabetic foot ulcer (DFU) were collected from GeneCards, OMIM, PharmGkb and TTD disease databases. With R language software, the binding proteins of bioactive components of MEBO intersected with the proteins related to occurrence of DFU. Proteins of DFU linked to treatment with MEBO were subjected to analysis using gene ontology (GO) and KEGG with R language software. AutoDock and PyMOL software were employed to dock active components of MEBO and major proteins of DFU. Targeted binding potential of bioactive compounds in MEBO to core proteins of DFU was analyzed. 
 Results: One hundred and five (105) bioactive ingredients and 246 likely therapeutic proteins were obtained. Proteins were mainly involved in biological processes in wound healing, oxidative stress, and lipopolysaccharide. The enriched signaling pathway focused on lipid metabolism and the process of atherosclerosis which involved PI3K and Akt, advanced glycation end-products (AGE)-receptor (RAGE) and mitogen-activated protein kinase (MAPK). The absolute values of these proteins were screened out with a docking score greater than 5 kcal/mol. 
 Conclusion: The biological effects of MEBO are related to multiple proteins and multiple signaling pathways. Therefore, healing effect of MEBO on DFU occurs via multiple pathways. The biological characteristics of MEBO need to be fully elucidated in further studies.

Performance of Two Artificial Intelligence Generative Language Models on the Orthopaedic In-Training Examination.

Artificial intelligence (AI) generative large language models are powerful and increasingly accessible tools with potential applications in health care education and training. The annual Orthopaedic In-Training Examination (OITE) is widely used to assess resident academic progress and preparation for the American Board of Orthopaedic Surgery Part 1 Examination. Open AI's ChatGPT and Google's Bard generative language models were administered the 2022 OITE. Question stems that contained images were input without and then with a text-based description of the imaging findings. ChatGPT answered 69.1% of questions correctly. When provided with text describing accompanying media, this increased to 77.8% correct. In contrast, Bard answered 49.8% of questions correctly. This increased to 58% correct when text describing imaging in question stems was provided (P<.0001). ChatGPT was most accurate in questions within the shoulder category, with 90.9% correct. Bard performed best in the sports category, with 65.4% correct. ChatGPT performed above the published mean of Accreditation Council for Graduate Medical Education orthopedic resident test-takers (66%). There is significant variability in the accuracy of publicly available AI models on the OITE. AI generative language software may play numerous potential roles in the future in orthopedic education, including simulating patient presentations and clinical scenarios, customizing individual learning plans, and driving evidence-based case discussion. Further research and collaboration within the orthopedic community is required to safely adopt these tools and minimize risks associated with their use. [Orthopedics. 2024;47(3):e146-e150.].

Improving the Load Carrying Capacity through Asymmetric Spur Gear using WC-Fe Metal Matrix Composite for Automobile Applications

Gears are the components that have been used for a century to transmit power from one place to another place. Symmetric spur gears are commonly used in the gearbox to transmit power between two parallel shafts. In order to increase the load carrying capacity of the spur gear with reduced noise and vibration, its profile can be modified. This can be achieved by changing the gear tooth design into asymmetric form. Asymmetrically toothed gears are used in power transmission for transmitting the power in one direction. These teeth help to improve the load carrying and power transmitting capacity of the gear. The strength can be further increased by changing the material used in gears. This can be made possible by using Metal Matrix Composite as a gear material. The metal matrix composites have high stiffness and strength to weight ratio compared to the Alloy Steel. The main objective of this project is to increase the load carrying capacity of the spur gear by using WC-Fe metal matrix composite material. The symmetric and asymmetric gear modeling has been done for existing car gear (Maruthi 800) using Ansys parametric design language software. The contact stress, bending stress and von Mises stress of the composite, as well as conventional gear material, is analyzed and the results are compared to find the percentage increase in strength of the gear.

LncRNAs associated with lymph node metastasis in thyroid cancer based on TCGA database

ObjectiveLong non-coding RNA (lncRNA), especially RNA associated with lymph node metastasis, plays an important role in the development of cancer. Identifying metastasis related lncRNAs and exploring their clinical significance can guide the treatment and prognosis of thyroid cancer patients. MethodsRNA expression and clinical data of thyroid cancer was derived from The Cancer Genome Atlas (TCGA) database, while the survival data was obtained from the ULCAN database. R language and SPSS software were used to analyze the correlation between lncRNA and lymph node metastasis of thyroid cancer and the lncRNAs associated with lymph node metastasis were screened. Result10 lncRNAs showed significant differential expression in thyroid cancer with and without lymph node metastasis. Four lncRNAs (LRRC52-AS1, AP002358.1, AC004847.1, and AC254633.1) were overexpressed in metastatic thyroid cancer, while six lncRNAs (SLC26A4-AS1, LINC01886, LINC01789, AF131216.3, AC062015.1, and AL031710.1) were underexpressed. The expression levels of these lncRNAs were associated with the clinical staging of tumors. Cox regression analysis further showed that elevated expression levels of AP002358.1 and LRRC52-AS1 were associated with poor prognosis in patients with thyroid cancer. In addition, analysis of the UALCAN database indicated that these two lncRNAs were significantly overexpressed in thyroid cancer compared to other cancers, and the expression levels of AF131216.3 and AL031710.1 were associated with progression-free survival in thyroid cancer patients. ConclusionThese lncRNAs may play crucial roles in the development and progression of thyroid cancer and could serve as potential markers for predicting tumor metastasis, clinical stage, and patient prognosis.

Developing Multimedia-Call in Writing Using Field Trip Animation Model for the Eight - Graders at SMPIT Al Mumtaz, Indonesia

This research aimed to develop Multimedia Computer Assisted Language Learning (Multimedia CALL) using a field trip animation model (FTA model) into supplementary material for the eighth graders in writing recount text. It was a research and development study. The research subjects were 8th-graders from both homogeneous gender classes of SMPIT Al Mumtaz Pontianak. The research procedure systematically comprised need analysis, needs exploration, the contextual realization of the materials, pedagogical materials development, the physical materials design, and materials evaluation. The needs analysis results revealed that they needed the supplementary writing material, providing integrated reading and listening practices, along with multi facilities so that they were able to compose a topic about a sightseeing trip for 200 words or above. Therefore, the researcher designed four serial and contextual writing learning units, enhanced by the enriched multimedia CALL tools in the material. Besides, the material evaluation found the material was appropriate and practical for the students to write a recount text.Keywords: Development, writing learning material, recount text, field trip animation based model, and Multimedia CALL

Digital Technologies in Language Education: A Comprehensive Review and Analysis

This systematic literature review examines the role and efficacy of digital storytelling (DST), the robot-DST strategy, and the normalization of computer-assisted language learning (CALL) in language education. The review is based on a range of studies published between 2019 and 2023 and follows the PRISMA approach for systematic reviews and meta-analysis. The analysis includes the evaluation of training, validation, and testing stages, with the search employing the keywords "educational technologies" to identify relevant articles. The review's findings highlight the potential of digital storytelling as a multimodal approach to language education. However, the limitations of traditional DST methods are also scrutinized. To address these limitations, the study proposes a robot-based DST approach, robot-DST, to enhance student engagement and promote interaction. The effectiveness of this approach is evaluated through a quasi-experimental study conducted in an English as a Foreign Language (EFL) course, comparing it with the conventional animation-based DST approach. Furthermore, the review explores the normalization of computer-assisted language learning (CALL) and the evolving communicative competencies needed for the digital generation. It also delves into the role of digital technology in reshaping academic journals and emphasizes the importance of integrating digital tools in reading instruction within university curricula. While acknowledging the existing inadequacies in current methodologies, the study serves as an inspiration for future researchers. It provides a solid foundation for developing and implementing innovative solutions in language education. In conclusion, this systematic literature review sheds light on the transformative role of digital technologies in language education. It highlights the potential of digital storytelling, introduces the robot-DST strategy as an alternative approach, and explores the normalization of CALL. The review emphasizes the need for integrating digital tools and fostering evolving communicative competencies to meet the demands of the digital generation. It also underscores the importance of further research and innovation in developing effective solutions for language education.

Effectiveness of AI Integration into Computer-Assisted Language Learning (CALL) on Student Writing Skills Based on Gender

This research has evaluated the efficacy of AI in CALL to improve writing among students by gender. The analysis involved a literature review on how AI and processing have made an impact on writing and it’s utilized to augment writing of the English language learners. It has reviewed an inspection of how educational technology affects men and women disparately. The result proved that integrating AI in technology enhances writing quality of language learners, regardless of their sex. It has exposed the nitty-gritty of gender, technology use and its effectiveness. It stipulates that in the imbuing of CALL on the basis of student demographics, gender-tailored approaches are essential. Moreover, policies and interventions in CALL, need to accommodate gender discrepancies to allow for maximum effectiveness. It is also crucial to delve more deeply into the after-effects of AI infused CALL over time, such as constructing intervention tools attuned with genders. Also, inspecting the fine-tuned effects of integrating AI on student writing, over longer periods would yield insights, into fashioning optimal CALL strategies, suited to learner populations.

FPGAs memory synchronization and performance evaluation using the open computing language framework

&lt;p&gt;One advantage of the open computing language (OpenCL) software framework is its ability to run on different architectures. Field programmable gate arrays (FPGAs) are a high-speed computing architecture used for computation acceleration. This work develops a set of eight benchmarks (memory synchronization functions, explained in this study) using an OpenCL framework to study the effect of memory access time on overall performance when targeting the general FPGA computing platform. The results indicate the best synchronization mechanism to be adopted to synthesize the proposed design on the FPGA computation architecture. The proposed research results also demonstrate the effectiveness of using a task-parallel model approach to avoid using high-cost synchronization mechanisms within proposed designs that are constructed on the general FPGA computation platform.&lt;/p&gt;