Some Solutions to Help Students Enjoy Learning English More

When teaching a large class of students, the teacher's biggest concern is which method to use to partially satisfy the learning needs of the majority of students. Each class has its unique characteristics, different learning needs, and the same level of students between classes at Tan Trao University. Some methods work well for one class, but not for another. This concern becomes much greater when the level of the student and the level of the curriculum has quite a big difference. Teachers often have to add the function of "curriculum designer" for a particular class. In addition to teaching according to the school's general curriculum, teachers must prepare more types of exercises and support activities to help students become more interested in learning and learn English more effectively. In this research paper, the writer of this article would like to mention some solutions that I have applied to students of Kindergarten Class C K8 and their feedback on my solution

Utilizing Visual Stimuli to Foster Engagement Among English Speaking Skill Learners During Instructional Sessions

The utilization of imagery proves highly effective in stimulating interest and fostering motivation for learners during the process of honing English speaking skills. Through this approach, not only does it facilitate learners in easily conceptualizing and comprehending concepts visually, but it also provides a platform for them to discuss and articulate ideas with confidence and creativity. Imagery serves as a bridge between language and real-life experiences, thereby igniting learners' passion and curiosity, aiding in their rapid and effective progress in language acquisition. In the journey of refining English speaking skills, imagery transcends mere static pictures to become gateways to myriad worlds. When educators incorporate images into the classroom, they bring not only pictures but also emotions, stories, and even dreams. Each detail within an image serves as a key, unlocking the door to imagination, enabling learners to step into a rich world where language extends beyond words on paper to vibrant images within the mind. Through the integration of imagery, the learning process becomes vivid and captivating, transforming each lesson into an adventure, a voyage filled with exploration and anticipation.&nbsp

BARTPhoBEiT: Pre-trained Sequence-to-Sequence and Image Transformers Models for Vietnamese Visual Question Answering

Visual Question Answering (VQA) is an intricate and demanding task that integrates natural language processing (NLP) and computer vision (CV), capturing the interest of researchers. The English language, renowned for its wealth of resources, has witnessed notable advancements in both datasets and models designed for VQA. However, there is a lack of models that target specific countries such as Vietnam. To address this limitation, we introduce a transformer-based Vietnamese model named BARTPhoBEiT. This model includes pre-trained Sequence-to-Sequence and bidirectional encoder representation from Image Transformers in Vietnamese and evaluates Vietnamese VQA datasets. Experimental results demonstrate that our proposed model outperforms the strong baseline and improves the state-of-the-art in six metrics: Accuracy, Precision, Recall, F1-score, WUPS 0.0, and WUPS 0.9

Musculoskeletal Pain and Work-related Risk Factors among Waste Collectors in Hanoi, Vietnam: A Cross-sectional Study

BACKGROUND: Musculoskeletal disorders (MSDs) are prevalent among waste collectors (WCs) in developing countries. AIM: This study aimed to investigate the prevalence of MSDs and the factors associated with the risk of persistent musculoskeletal pain among WCs in Hanoi, Vietnam. METHODS: A cross-sectional survey was utilized to study 468 WCs in 2017. The Örebro Musculoskeletal Pain Questionnaire and a questionnaire on demographic and work conditions were used to collect data. Descriptive and multivariate logistics regression analyzes were applied at a significance level of 0.05 to examine the factors related to the risk of persistent pain. FINDINGS: About 74.4% of the participants of this study experienced MSDs in at least one body region and 9.4% reported MSDs in all 10 body sites. The lower back was reported to be the most affected followed by the neck and shoulders. The risk of persistent musculoskeletal pain was significantly associated with age (odds ratio (OR) = 2.31, confidence interval (CI) = 1.05–5.09), gender (OR = 3.29, CI = 1.28–8.44), work hours (OR = 2.35, CI = 1.12–4.92), work shift (OR = 0.48, CI = 0.26–0.92), duration of poor postures of the neck (OR = 0.31, CI = 0.13–0.76), bent back (OR = 0.4 CI = 0.18–0.92) and for medial rotation (OR = 3.01, CI = 1.42–6.36), carrying heavy objects (OR = 2.94, CI = 1.15–7.48), and experience of work dissatisfaction (OR = 3.31, CI = 1.46-7.52), stress (OR = 7.14, CI = 3.14–16.24), or anxiety (OR = 6.37, CI = 3.07–13.21). CONCLUSIONS: High prevalence of MSDs among WCs and its association with self-assessed unfavorable work postures and work-related stress implies the need of mechanical and social support at work for WC to prevent the development of MSDs and persistent pain

INTEGRATION OF CROSS-CULTURAL EXPERIENCES AND PROFESSIONAL COMPETENCIES: VIEWS FROM INTERNATIONAL EXCHANGE PROGRAMS IN HIGHER EDUCATION

Encouraging hospitality students in reflective and transformative learning toward a global mindset becomes an imperative for developing their cross-culturally professional competency in preparation of the future career path development. Oversea exchange programs are among the initiatives to raise personal, professional and cultural awareness for the hospitality students in a pathway to encourage cross-cultural learning among students in similar fields. However, to what extent the development of a global mindset gained from the cross-cultural experiences could help undergraduate hospitality students gain their professional competency in terms of cultural skills in the hospitality and tourism context is the main issue to be described by this study. Content analysis has been conducted on in-depth interview data given by hospitality oversea exchange students who are both current students and graduated ones. The most popular modes of international student exchanges such as team project, assignment, presentations, and travel exchanges are taken into consideration to highlight deeper insights into a mutual interest between the cross-cultural experiences and the professional competency related cultural skills. The study reveals that cultural understanding needs to be experienced in the real setting context. Furthermore, we also discovered that cultural exchange outcomes are normally obtained in the daily informal practices instead of formal studies. However, the current study is constrained within few selected countries where students have been experienced and the current partnership between the home and host Institutions. This paper provides actionable guidelines and approach for integrating the critical component of cultural exchange program in the traditional curriculum program of hospitality

Effect of Organic Loading Rates on Performance of Treating Dairy Wastewater in a Lab-Scale Sequencing Batch Reactor

This study aims to investigate, the effect of organic loading rates (OLRs), nutrient ratio addition, and sludge retention time (SRT) on treating dairy wastewater in a sequencing batch reactor (SBR) system. This investigation is verified by experiments conducted in 3 phases at 3 different OLRs (1.8, 1.2, and 0.9 kg/m3d, respectively).  Urea ((NH2)2CO) is added to make a suitable (COD:N:P) ratio of (100:5:1) in dairy wastewater. The SRT is adjusted from 50 days to an appropriate value of 18 days. The obtained results show that the COD, TN, and TP removal efficiencies are increased with decreasing OLRs. Sludge concentration in the SBR tank is stable at 1100 mg/L after adding (NH2)2CO. In addition, the SBR operated at a suitable SRT (i.e. 18 days) helps the biomass stably, resulting in enhancement of COD, TN, and TP removal. The results are helpful to the design of SBR for treating dairy wastewater

ViCLEVR: A Visual Reasoning Dataset and Hybrid Multimodal Fusion Model for Visual Question Answering in Vietnamese

In recent years, Visual Question Answering (VQA) has gained significant attention for its diverse applications, including intelligent car assistance, aiding visually impaired individuals, and document image information retrieval using natural language queries. VQA requires effective integration of information from questions and images to generate accurate answers. Neural models for VQA have made remarkable progress on large-scale datasets, with a primary focus on resource-rich languages like English. To address this, we introduce the ViCLEVR dataset, a pioneering collection for evaluating various visual reasoning capabilities in Vietnamese while mitigating biases. The dataset comprises over 26,000 images and 30,000 question-answer pairs (QAs), each question annotated to specify the type of reasoning involved. Leveraging this dataset, we conduct a comprehensive analysis of contemporary visual reasoning systems, offering valuable insights into their strengths and limitations. Furthermore, we present PhoVIT, a comprehensive multimodal fusion that identifies objects in images based on questions. The architecture effectively employs transformers to enable simultaneous reasoning over textual and visual data, merging both modalities at an early model stage. The experimental findings demonstrate that our proposed model achieves state-of-the-art performance across four evaluation metrics. The accompanying code and dataset have been made publicly accessible at \url{https://github.com/kvt0012/ViCLEVR}. This provision seeks to stimulate advancements within the research community, fostering the development of more multimodal fusion algorithms, specifically tailored to address the nuances of low-resource languages, exemplified by Vietnamese.Comment: A pre-print version and submitted to journa

ViHOS: Hate Speech Spans Detection for Vietnamese

The rise in hateful and offensive language directed at other users is one of the adverse side effects of the increased use of social networking platforms. This could make it difficult for human moderators to review tagged comments filtered by classification systems. To help address this issue, we present the ViHOS (Vietnamese Hate and Offensive Spans) dataset, the first human-annotated corpus containing 26k spans on 11k comments. We also provide definitions of hateful and offensive spans in Vietnamese comments as well as detailed annotation guidelines. Besides, we conduct experiments with various state-of-the-art models. Specifically, XLM-R$_{Large}$ achieved the best F1-scores in Single span detection and All spans detection, while PhoBERT$_{Large}$ obtained the highest in Multiple spans detection. Finally, our error analysis demonstrates the difficulties in detecting specific types of spans in our data for future research. Disclaimer: This paper contains real comments that could be considered profane, offensive, or abusive.Comment: EACL 202