Computer-assisted Language Learning Research Articles

Implementation of data parsing technology using neural network and web driver

As a rule, data parsing is used to quickly obtain information from various web resources for further study and use. For parsing, you can use both specialized online services and desktop applications. Unfortunately, existing parsing technologies have some limitations. For example, it is often difficult to parse dynamic web pages and classify information obtained through parsing. New approaches are needed in implementing data collection and analysis - using language models and software (web driver) that simulate human actions when working with websites. The web driver assists in accessing data from dynamically updated sites, while artificial intelligence technologies help correctly recognize and classify data. This technology can be used to create parsers for real estate agencies, employment services, university admission committees, advertising campaigns, and financial organizations.

Development of a Nomogram Model to Predict the Risk of Stricture Recurrence after Urethroplasty: A Retrospective Study.

A retrospective study was performed to analyse the influencing factors of stricture recurrence after urethroplasty and to establish a predictive nomogram model. The clinical data of patients who underwent urethroplasty in our hospital from January 2021 to June 2023 were retrospectively analysed. Depending on whether stenosis occurs six months after surgery, the patients were divided into recurrence and nonrecurrence groups. Logistic regression analysis was performed on the indicators with statistically significant differences between the two groups in single factor analysis to analyse the influencing factors of postoperative recurrence risk of stricture. X64.4.1.3 version R language and external source packages were used to build the nomogram model. The nomogram was internally validated through 10-fold cross-validation, and C-index was calculated. The area under the curve (AUC) of the receiver operating characteristic curve was employed to evaluate the results of the internal validation. Amongst 105 patients who underwent urethroplasty in our hospital, 15 patients with recurrence were included in the recurrence group, and 90 patients without recurrence were included in the nonrecurrence group. The length of stricture segment, history of urethroplasty and smoking history within 3 months before surgery were risk factors for stricture recurrence, with odds ratio (OR) values of 1.874 (95% CI: 1.103-5.725), 1.670 (95% CI: 1.105-2.904) and 1.740 (95% CI: 1.456-5.785), respectively. The constructed nomogram obtained an average AUC of 0.842 and an average C-index of 0.794, calculated after 200 times of 10-fold cross-validation. From the data of this study, it can be deduced that the influencing factors of stricture recurrence after urethroplasty include the length of stricture segment, history of urethroplasty and smoking history of 3 months before surgery. Using the above factors as a basis to construct a predictive nomogram model is helpful to screen high-risk patients with recurrence of stricture after urethroplasty.

The ALICE Grid Workflow for LHC Run 3

The ALICE Grid Workflow for LHC Run 3

Angiopoietin-Like Protein 2 Serves as an Independent Prognostic Biomarker and Correlates with Immune Infiltration in Osteosarcoma

Osteosarcoma mostly occurs in adolescents, with high disability and mortality rates and poor prognosis. Angiopoietin-like protein 2 (ANGPTL2) is a secreted glycoprotein protein, which plays important roles in cellular processes and various diseases. Microarray gene expression data GSE16088 and GSE36001 were downloaded from Gene Expression Omnibus (GEO, <ext-link ext-link-type="uri" xlink:href="http://www.ncbi.nlm.nih.gov/geo">http://www.ncbi.nlm.nih.gov/geo</ext-link>). The Complex Heatmap package was used to construct heatmaps, the gglot2 R language package to plot volcanoes and differential expression data, and the “VennDiagram” R language package to plot Wayne plots. Western booting and qRT-PCR was used to detect ANGPTL2 expression in osteosarcoma tissues. proteins. In addition, the GeneMANIA database (<ext-link ext-link-type="uri" xlink:href="http://www.genemania.org">http://www.genemania.org</ext-link>) was cited to predict the ANGPTL2 interaction network. We used the single-sample gene-set enrichment analysis (ss GSEA) algorithm to quantify the immune infiltration of osteosarcoma. In the GSE16088 database there were 5005 that met the selected threshold of |log2(FC)| > 1 and P <0.05, of which 2719 were highly expressed and 2286 were lowly expressed. WB and qRT-PCR results showed that ANGPTL2 was significantly up-regulated in osteosarcoma tissues. ssGSEA showed that high ANGPTL2 expression in osteosarcoma patients had a worse prognosis. ssGSEA showed that high ANGPTL2 expression was correlated with Mast cells and Th1 cells. Collectively, ANGPTL2 can be an independent prognostic biomarker and correlated with immune infiltration in osteosarcoma.

The Effects of Computer-assisted Language Learning (CALL) and Different Interaction Patterns on Vocabulary Development of EFL Learners

Background: Research on the integration of Computer-assisted language learning (CALL) in EFL contexts has witnessed a significant advance due to the modern changes in language education and technology over the last decades. However, the effects of CALL on vocabulary development through different interaction patterns have not been investigated by researchers.
 Purpose: Attempts have been made to assess the effects of CALL and Memrise software on the vocabulary development of intermediate EFL learners through the three interaction patterns: 1) pair-work interaction, 2) small-group-work interaction, and 3) individual content.
 Method: A total of 100 male and female Iranian EFL learners were selected through convenience sampling and assigned into three experimental and one control groups, each consisting of 25 learners. The Oxford Quick Placement Test was taken to assure the homogeneity of the participants. Then, a multiple-choice vocabulary test was taken as a pretest. The three experimental groups learned vocabulary through Memrise desktop software with three different interaction patterns, while the control group learned the same through the conventional pattern. A reshuffled version of the pretest constitutes the subsequent posttest.
 Result: The results of the comparison between all pretests and posttests indicated that there was a significant difference between the vocabulary scores of the pretest and the posttest of the experimental groups, indicating the efficiency of these treatments. It was revealed that the pair work was slightly more effective than small-group work and that these two types of intervention were more effective than individual-content interaction, where the latter was more effective than conventional instruction.
 Conclusion: According to the findings, students are advised to take advantage of CALL-based facilities and participate in interactive activities.

The effect of evaluation and feedback in 360-degree video-based VR environments on language learning outcomes

Recently, 360-degree video technology (360VT) received considerable attention in the field of computer-assisted language learning as it creates authentic and immersive virtual reality environments to assist the language learning process. However, not many studies focused on applications of 360VT to assist the evaluation of learner’ performance and providing them with relevant feedback. Therefore, the present study was set to shed light on this aspect. We carried out an experiment to explore the effects of evaluation and feedback in two different video learning environments, i.e. a traditional video technology-based (TVT) and 360VT-based, on learning outcomes. In the context of the present study, evaluation referred to evaluating the content of videos created by students, and feedback referred to providing students with relevant feedback for further improvement of their videos. English as a foreign language (EFL) course was administered for 52 university students. The participants were equally divided into TVT and 360VT groups. They attended EFL classes, and after classes, they created videos using either a traditional video camera (TVT group) or a 360-degree video camera (360VT group) on four learning topics. The evaluators watched videos, evaluated them, and then provided feedback to students. Students then revised their works based on received feedback. The results showed an insignificant difference between the two groups in their pre-test scores when measuring prior knowledge. However, when measuring knowledge after the study, 360VT group students outperformed their counterparts in the post-test. According to the results, students in the 360VT group received significantly more feedback, and it was more detailed compared to that of their counterparts. In addition, the evaluators scored affordances of 360VT higher than those of TVT. The results showed many advantages of 360VT such as it was useful and easy to use during the evaluation process, 360VT created immersive environments so that the evaluators had a realistic experience and a high level of vividness when watching and evaluating videos. The results suggest that evaluation and feedback in 360VT environments had better effects on learning outcomes, and the evaluators positively perceived their experiences in 360VT settings. Therefore, it is suggested that educators and researchers consider implementing 360VT in situations when language learners are tasked with creating their own content, which can subsequently be evaluated with relevant feedback provided.

Expanding the functionality of IoT devices in conditions of emergency situations

The article is devoted to the expansion of functional devices of the Internet of Things (IoT) in order to increase the safety of the population in emergency situations, in particular in the context of natural disasters and military threats. After analyzing the latest research and publications, a conclusion was made about the relevance of the development of IoT technologies in the context of modern challenges for the safety of citizens. Special emphasis is placed on the use of innovative approaches to solving public safety problems, particularly for persons with disabilities, such as the hearing impaired or the elderly. The article describes the implementation of software in the Python programming language to visually display the status of a missile threat or artillery fire using Yeelight smart lamps, which use colored light to convey information about the presence or absence of danger messages. The proposed solutions include synchronous operation of devices in real time, connection to reliable sources of messages and provision of stable communication between devices and the server. The project demonstrated an innovative approach to solving security problems in crisis situations, in particular martial law, promoting a quick and accurate response to valuable threats and protecting the population.

EXPLORING THE USE OF PYTHON-BASED LANGUAGE LEARNING SOFTWARE TO IMPROVE THE VOCABULARY OF ENGINEERING STUDENTS

The paper examines the feasibility of using Python-based language learning software to improve the vocabulary of engineering students as a secondary language. The purpose of the paper is to investigate the following key parameters such as time frame, repeatability, ease of use of the software, and limited time for learning. Two student groups participated in this study – the first-year and the second-year students of engineering faculty. They showed a fluctuating trend in both groups, with the accuracy rate remaining the same for the first six weeks and then increasing as the students learned new words. Software like this could be used as a soft skill-based learning method to improve the language absorption of engineering-based students for non-English speaking student groups. The results indicated that both student groups increased the average vocabulary and had only 20 percent wrong answers by the end of the study programs compared to the 80 percent and 50 percent mistakes at the beginning of the study.

Remote methods of research assessment of the impact of agricultural economic processes on the environmental destruction of the territory

The research is about solving the problem of assessing the impact of agricultural processes on the environmental safety of territories. The research was carried out on the selection, uploading and processing of data from the aerial survey of the area. High-quality multispectral images of the study areas were selected in accordance with the time-related thematic tasks of aerospace research of agricultural plots. With the help of Google Earth Engine platform, JavaScript programming language, ENVI and ArcMap software complexes, segmentation of the image of space images was carried out on these images. Each of them has its own normalized color scale, and highlights certain objects with different colors. To improve the visualization of differences in images, the classification of index images using the Isodata method was studied.An Agrocontrol module for automated deciphering of agricultural was developed. The module allows to select agricultural land with further vectorization and the possibility of creating a geodatabase automatically. Based on results, preliminary cartographic models of the studied territories were created with the indication of land plots that are dangerous for the ecological state of the region and require more careful consideration.At the stage of practical research, an analysis of the received data, based on the agricultural holding "Mriya", was carried out on the scheme of crop rotation, hybrids of grain crops grown on the territory of the plots, the types and amount of fertilizers used, as well as the volume of the harvest for the last 5 years. This made it possible to prove the correlation between the chemical composition of the used fertilizers and the corresponding exceedances of the MPC norms of the soil samples chemical composition.

Analysis of Shared Mechanisms and Chinese Herbal Medicines Between Osteoporosis and Type 2 Diabetes

Background: Osteoporosis (OP) and type 2 diabetes (T2D) are commonly encountered metabolic disorders in clinical practice, but the comorbidity mechanism has not been clarified. This study explored the underlying mechanisms for utilizing bioinformatics methods. Furthermore, it predicted traditional Chinese medicines (TCMs) with preventive and therapeutic effects. Materials and Methods: GSE35958 and GSE43950 were retrieved and downloaded from the GEO database, and differential expression analysis was performed to identify differentially expressed genes (DEGs) with similar expression patterns in OP and T2D. Then, the common DEGs were uploaded to the STRING database to construct a protein interaction network. Enrichment analysis of the screened genes was conducted using R language packages. Relevant TCMs were searched and screened based on gene targets using the Encyclopedia of traditional Chinese medicine (ETCM) database. Molecular docking of active ingredients of the TCMs and related gene targets was performed using AutoDock Vina software. Results: By analyzing the gene expression microarrays, GSE35958 and GSE43950, 34 genes with the same expression pattern shared by OP and T2D were identified. Among these genes, 32 were upregulated and two were downregulated. Protein interaction network analysis revealed that tumor necrosis factor, vascular endothelial growth factor A, and CD44 might play key roles in the co-pathogenesis of T2D and OP. TCMs, including Wolfberry (枸杞), Ginseng (人参), and Yam (山药), were screened based on key genes. Molecular docking results demonstrated binding activity between all active ingredients and the related gene targets. Conclusion: This study explored the potential molecular co-pathogenesis of OP and T2D through bioinformatic analysis and preliminarily predicted traditional herbal medicines that may have preventive and therapeutic effects.

The multi-layer secure communication system based on 2D-OCDMA coding

Abstract This paper presents a novel multi-layer secure communication system that bases 2D-OCDMA technology to enhance the security and number of users of the system. The system innovatively combines RSA encryption, polarization multiplexing, and address coding techniques to protect and transmit the data. At the transmitting end, the data is encrypted by algorithm and then encoded by address code. The encoded optical data is split into two orthogonal polarization states and sent over the same channel. At the receiving end, only the optical signals in the matching polarization state can be retrieved by the polarizer with the right angle. The retrieved data is then decoded by the address code and decrypted by the algorithm to recover the original data. This system achieves multi-layer security and capacity enhancement by processing the information at different layers. The feasibility of the system is demonstrated by joint experimental simulation using Java programming language and Optisystem simulation software. In this paper, low BER transmission of 4 code words for 8 users 50 km 1Gbit/s is realized using optical orthogonal codes (OOC) with BER around 10−30. It realizes the enhancement of 4-user to 8-user without affecting the transmission effect.

Summary Report APE 2023, 10--12 January, Berlin, Germany Berlin Re-Visited: Building Technological Support for Scholarship and Scientific Publishing

This paper summarizes the 18th Academic Publishing in Europe (APE) Conference: Berlin Re-Visited: Building Technological Support for Scholarship and Scientific Publishing, held as a hybrid event 10 and 11 January 2023, and organized by the Berlin Institute of Scholarly Publishing (BISP), a not-for-profit organization dedicated to bringing publishers, researchers, funders, and policymakers together. This year’s conference theme “Out with the old, in with the new!” was discussed and presented in keynote speeches, the APE lecture, and several panel discussions. Current challenges within scholarly publishing, e.g., with research integrity, trust, and research assessment, have much to do with the old ways of doing things. To move science forward, new technologies and innovations, like the decentralized web, FAIR digital objects, and blockchain technology are needed to shape new paradigms. In many sessions it was stressed that not just new technologies are needed to move science forward, but human collaboration and partnerships as well. The changing role of the journal and the importance to recognize more diverse research outputs, beyond the journal article, was a topic of importance. Not only research assessment reforms and improved collaboration amongst different stakeholder groups are needed to address this, new publishing systems, better metadata, and open infrastructures as well. A session presenting different start-ups showcased how Artificial Intelligence, Natural Language Processing and software technology can be used to tackle problems in e.g., finding relevant funders and peer reviewers, and detecting image plagiarism. It was also discussed what publishers can do to help achieve the Sustainable Development Goals. Collaboration, data transparency and sharing best practices amongst researchers, funders, and policy makers are key. Another important topic during this year’s APE was how publishers can support Early Career Researchers: establishing new workflows and infrastructures that enable publication of a wider range of research outputs, and broader recognition of these outputs, will incentivize ECRs. This year’s APE was concluded with the APE Award Ceremony. The winner - Vsevolod Solovyov from Prophy - has used AI to enhance the current peer review system and made a very important contribution to improving the scholarly communication system.

Teachers’ Collaborative Reflections on Classroom Materials: From Traditional Consumers to Digital Materials Developers and Teacherpreneurs

L2 teachers, no longer considered to be predominantly passive coursebook consumers, act as mediators between pedagogy and materials in the current era of technology-assisted language instruction and should be empowered to digitalize language learning materials to meet the immediate needs of the digital generation. In this study, we aimed to investigate L2 teachers’ collaborative reflections on the current gaps in their classroom coursebook that could be bridged by the purposeful use of digital tools and address their attitudes towards their changing roles as digital materials developers. The findings demonstrated that, in their critical reflections, from a pedagogical perspective, the teachers pinpointed the dominance of passive language usage, the absence of personalized strategy-based instruction, and the lack of interactive content in the coursebook. From a task design perspective, they referred to the dominance of edutainment-free tasks, the prevalence of artificial peer tasks, the lack of multimodal scenario-based tasks, and the absence of adaptive feedback. The teachers further highlighted their shifting roles. As digital materials developers, they could create digital content for the “digital natives,” make digital mini-lessons for classrooms, attend project-based training courses, and co-produce digital content and tasks with students’ assistance. As digital teacherpreneurs, they could run private social media-based businesses, join Edu-Tech co-working spaces, and produce digital artifacts in edutainment centers. As digital materials designers, they could collaborate with computer-assisted language learning (CALL) stakeholders and do interdisciplinary projects in virtual communities. This study promises implications for L2 teachers, teacher educators, and materials developers.

Forty-two years of computer-assisted language learning research: A scientometric study of hotspot research and trending issues

AbstractFor years, computer-assisted language learning (CALL) has thrived as an interdisciplinary subfield, linking applied linguistics and educational technology. Despite its significance and a number of syntheses, CALL research has not yet undergone a comprehensive scientometric synthesis. This study synthesizes CALL research over a period of 42 years by employing a scientometric analysis of sources and document co-citation analyses. Scopus was used to retrieve original articles with a timespan limit from 1980 to 2021. Our records identified 4,631 articles representing CALL-based research, which were published in 63 peer-reviewed journals and collectively contained 186,589 references. The findings indicate that CALL research is supported by robust theoretical frameworks, grounded in socio-cultural and second language acquisition theories. Our research findings have revealed several significant clusters of interest within the realm of CALL, with a pronounced focus on writing among CALL scholars. Additionally, the study identified emerging research areas such as mobile-assisted language learning, synchronous computer-mediated communication, and data-driven learning in CALL literature. Notably, “CALL-core” journals exhibited high productivity, with Language Learning & Technology, Computer Assisted Language Learning, and Computers & Education standing out as top-ranked journals in terms of the Hirsch index (h-index) and co-citation. Suggestions for future research are outlined in the conclusion.

Construction of a prognostic nomogram combining PET/CT metabolic parameters and blood inflammatory markers for non-small cell lung cancer treated with first-line chemotherapy

To investigate the prognostic value of 18F-FDG-PET/CT metabolic parameters and blood inflammatory markers for advanced non-small cell lung cancer (NSCLC, stage Ⅳ/ⅢB) treated with first-line chemotherapy combined with immunotherapy and construct a nomogram prediction model for NSCLC. We retrospectively analyzed the metabolic parameters (SUVmax, MTV and TLG) and blood markers of inflammation (NLR, DNLR, PLR and SII) in 105 patients with advanced NSCLC receiving chemotherapy combined with baseline 18F-FDG-PET/CT prior to immunotherapy from March, 2019 to June, 2021. ROC curve was used to calculate the best cut-off points for grouping, and univariate and multivariate COX regression analyses were performed to screen the independent predictors of prognosis for a combined diagnostic analysis. The effective biomarkers were included in the prediction model, and the nomogram model was constructed using the cph function in the rms function package of R language software. The patients were followed up for a median of 17.5 months, and their median progression-free survival (PFS) was 16 months with a median overall survival (OS) of 13.6 months. A high PLR (≥151.050) and a high TLG (≥101.940) were significant independent prognostic factors for PFS, and a high SII (≥941.385) and a high TLG (≥101.940) were independent prognostic factors for OS. The nomogram combining PET and blood markers of inflammation showed a good performance for prognostic prediction (with C-index of 0.682 for PFS and of 0.727 for OS) and good fitting of the calibration curve. The clinical decision curve showed good clinical utility of the nomogram. The baseline PET/CT metabolic parameters and blood inflammatory markers are associated with PFS and OS of patients with advanced NSCLC receiving first-line chemotherapy, and the constructed nomogram based on these parameters has a good performance for prognostic prediction in these patients.

Sustainable Lessons Learnt from the Attitudes of Language Instructors toward Computer-Assisted Language Teaching

Technology has significantly influenced the educational field, including language teaching. However, some language instructors hold negative attitudes toward technology, particularly computer-assisted language teaching (CALT), which may affect the advancement of language teaching. This study examines the attitudes of language instructors toward CALT in some South African public universities and identifies sustainable lessons that could promote the use of CALT. The study employed a quantitative research approach using content analysis and surveys to comprehensively investigate language instructors’ attitudes toward CALT. Surveys provided the required information about the attitudes of language instructors toward CALT, and content analysis and descriptive statistics were used to analyze the data and identify sustainable lessons from the attitudes of the language instructors toward CALT. Descriptive statistics were used to summarize the survey results. The analysis revealed that some language instructors have negative attitudes toward CALT, suggesting that institutions require a fundamental approach to advance the use of CALT. Sustainable lessons learned from the attitudes of language instructors toward CALT are identified, and recommendations are made about how to implement effective CALT on a personal and institutional basis. This study highlights the importance of a positive attitude toward CALT and developing a fundamental approach to using CALT in language teaching. The sustainable lessons learned from this study could inform and advance language teaching practices that employ CALT, inform future research, and promote effective language teaching practices that use CALT.

Determining the parameters of the dynamic magnetic hysteresis loop of the structural materials by attachable primary transducers

Coercive force, which is one of the structure-sensitive characteristics of ferromagnetic materials, is most often used for magnetic analysis. This approach requires the use of powerful magnetization systems, which leads to an increase in the size of the attachable magnetic probe and, accordingly, to a decrease in the locality of control. The above-mentioned disadvantages can be eliminated by using the parameters of the dynamic magnetic hysteresis loop (MHL), which involves the use of variable magnetic fields. A device for studying the dynamic MHL during cyclic remagnetization for the tasks of testing ferromagnetic materials, namely structural analysis, is proposed. The device consists of a generator of sinusoidal signals, an amplifier, a cur¬rent sensor, an attachable magnetic probe, a two-channel analog-to-digital converter (ADC), and a computer. The attachable magnetic probe is proposed in the form of a U-shaped core with magnetization windings on one leg and measurement winding on the other leg. The signal from the generator through the amplifier and the current sensor enters the magnetization winding. The ADC receives two signals: first one – from the measurement winding, and second – from the current sensor. Both signals from the ADC output in digital form are processed and analyzed by the computer using the developed specialized software in the LabVIEW language. Due to the developed software the filtering and integration of the signal from the measuring winding as well as the MHL plotting and MHL parameters calculation was realized. To reduce interference when determining MHL parameters, averaging over 50 magnetization cycles was performed. The attachable magnetic probe with the dimensions of the contact part 30x17 mm created a field with a strength of 300 A/m at a frequency of 50 Hz. The device was tested on specimens of sheet steel of 09G2S type with a thickness of 4 mm, in which uniaxial tensile stresses were created. The obtained results show the sensitivity of the dynamic MHL area to mechanical tensile stresses, as it increases from 14.8 to 16.8 mT A/m during loading.

Four kinds of traditional Chinese exercise therapy in the treatment of type 2 diabetes: a systematic review and network meta-analysis

ObjectiveTo perform an evidence-based evaluation of the clinical efficacy of Taijiquan, Baduanjin, Yijinjing and Wuqinxi in interventions for type 2 diabetes.DesignA systematic review and network meta-analysis.MethodsThe comprehensive search included Chinese and other language databases such as the MEDLINE (PubMed), Web of Science, Excerpta Medica Database (Embase), The Cochrane Library, China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform, China Scientific Journal Database, VIP and China Biomedical Literature Database (CBM). Clinical randomized controlled trials of four traditional Chinese exercise therapies in the treatment of type 2 diabetes, including Taijiquan, Baduanjin, Yijinjing and Wuqinxi, were retrieved. The search time was conducted from the establishment of the database to 30 October 2022. Two researchers screened the documents that met the inclusion criteria, extracted data according to the preset table and evaluated the methodological quality of the included studies according to the quality evaluation tools recommended by the Cochrane System Reviewer Manual V.5.1. The R language, Stata and ADDIS statistical software programs were used to conduct statistics and analysis of intervention measures.ResultsA total of 33 randomized controlled trials with 2609 patients were identified. All patients were from China. The results of the network meta-analysis showed that Taijiquan ranked the best for improving HbA1c, 2-h postprandial blood glucose (2hPG), low-density lipoprotein cholesterol (LDL-C) and insulin sensitivity index indicator levels; Yijinjing reduced fasting plasma glucose (FPG) and total cholesterol (TC) indicator levels for the best probability ranking; Baduanjin improved the triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C) probability ranking the most. When the training period was less than 12 weeks, Baduanjin had better effects in improving 2hPG, TC, TG, HDL-C and LDL-C indicator levels. Taijiquan had better effects in reducing FPG levels. When the training period was 12 weeks, the effect of Yijinjing in improving FPG, HbAlc, TC and HDL-C levels was better than that in other traditional Chinese exercise, and Taijiquan had better effects in improving 2hPG, TG and LDL-C indicator levels. When the training period was longer than 12 weeks, Taijiquan had better effects in improving FPG, HbAlc, 2hPG and LDL-C indicator levels, and Baduanjin had better effects in improving TC, TG and HDL-C indicator levels.ConclusionThe four traditional Chinese exercise therapies can improve blood glucose levels, blood lipid levels and insulin-related indicators of type 2 diabetes to varying degrees. Studies have shown that Taijiquan has a better targeted treatment effect on type 2 diabetes.Systematic review registrationCRD42020214786.Protocol publishedWe published the protocol article “Network meta-analysis of four kinds of traditional Chinese exercise therapy in the treatment of type 2 diabetes: Protocol for a systematic review” in the BMJ Open magazine 2021, Issue 11, Volume 7.

Conceptualizing Corpus-Based Genre Pedagogy as Usage-Inspired Second Language Instruction

Abstract Corpus-based genre pedagogy (CBGP), the instructional integration of discourse-based rhetorical analysis and corpus-based linguistic analysis of diverse genres, has gained attention from English for Academic Purposes (EAP) researchers and practitioners aiming to cultivate the academic writing skills of second language (L2) learners. This has led to a need for the continuous conceptualization of CBGP (Lu, Xiaofei, J. Casal Elliott, and Yingying Liu. 2021. “Towards the Synergy of Genre- and Corpus-Based Approaches to Academic Writing Research and Pedagogy.” International Journal of Computer-Assisted Language Learning and Teaching 11 (1): 59–71). Additionally, usage-based approaches to L2 acquisition (U-SLA), a collection of cognitive and potentially sociocognitive theoretical approaches to language and language acquisition (Ellis, Nick C., Ute Römer, and Matthew Brook O’Donnell. 2016. Usage-Based Approaches to Language Acquisition and Processing: Cognitive and Corpus Investigations. Malden: Wiley-Blackwell; Wulff, Stepanie, and Nick C. Ellis. 2018. “Usage-Based Approaches to Second Language Acquisition.” In Bilingual Cognition and Language: The State of the Science across its Subfields, edited by D. Miller, F. Bayram, J. Rothman, and L. Serratrice, 37–56. Amsterdam: John Benjamins Publishing Company), have called for more pedagogically oriented research informed by usage-based principles (e.g., Tyler, Andrea E., Hae In Park, Mariko Uno, and Lourdes Ortega, eds. 2018. Usage-inspired L2 Instruction: Researched Pedagogy. Amsterdam: John Benjamins Publishing Company). Responding to such calls, we argue for conceptualizing CBGP as usage-inspired instruction given its intersections with key U-SLA instructional tenets. We first systematically review empirical studies on CBGP. Then, we introduce relevant U-SLA instructional tenets and interpret the CBGP studies to illuminate the extent to which CBGP resonates with different aspects of the U-SLA tenets. Eventually, we argue that CBGP can potentially unify the “social” and the “cognitive” in U-SLA’s accounts of L2 teaching and learning, making it a feasible way to materialize usage-inspired L2 instruction in actual classroom practice. Finally, we discuss future research and practical directions.

Exploring students’ acceptance of an artificial intelligence speech evaluation program for EFL speaking practice: an application of the Integrated Model of Technology Acceptance

Adapted from the Technology Acceptance Model (TAM), the Integrated Model of Technology Acceptance (IMTA) has been used to examine the perceptions and acceptance of computer-assisted language learning (CALL), such as online learning, mobile learning, and learning management systems. However, whether IMTA can be applied to empirical research on AI-assisted language learning remains unexplored. Therefore, this article intends to analyze an AI speech evaluation system for English speaking practice, in the context of higher education through the IMTA. Research instruments encompassed questionnaires (n = 218) and semi-structured interviews (n = 21). The participants were English as a foreign language (EFL) learners who had used an AI speech evaluation program to practice their speaking skills. The results suggested that (1) most participants found the AI program useful, pleasant, and easy to use. They also had a strong intention to continue using it; (2) perceived usefulness (PU) and perceived enjoyment (PE) are significant predictors of behavioural intention to use (BI). Meanwhile, problems related to user interface design, the accuracy of automatic feedback and especially the lack of face-to-face interaction were reported. This study demonstrates how IMTA could be applied to examine users’ acceptance of AI programs for EFL speaking practice. The findings also offer insights into further research and development in AI tools for EFL speaking practice.