MANAGING CHANGE TO UPGRADE ENGLISH TEACHING IN VIETNAM

Managing change in English Language Teaching (ELT) has been implemented to meet the changing requirements and expectations of language learners in a globalized society. This paper investigates the application of change management models in the field of ELT, with particular emphasis on Vietnam. The research employed a document analysis approach by reviewing and analyzing relevant academic papers on change management and managing change in ELT. The study identified five change management models, including Lewin's Change Management Model, ADKAR Model, Kotter's 8 Step Change Model, McKinsey 7S Model, and Kübler-Ross Five Stage Model. Many of these models have been employed in the ELT sector. The best practice of applying change management models in EFL is recommended to Vietnam in order to improve English teaching in its institutions and centers. The paper is expected to provide an in-depth analysis of various change management models and their potential application in the Vietnamese context.  Article visualizations

Empirical Investigation of Omni-channel Customer Behavior: Multiple Mediation Effects of Website and Mobile Interactivity

While existing retail research has focused on retail channels in isolation from a single or multi-channel retailing perspective, there is a need to investigate shopping behavioral intention from an omni-channel and customer-centric retailing perspective. The main of this study is to analyze the customer omni-channel behavior under multiple mediating effects of website and mobile interactivity. Data collected from valid 287 respondents via both online and paper form. Partial least squares structural equation modeling (PLS-SEM) and Smart-PLS software have been used to test proposed hypotheses. The result underlined the significant positive effects of technology literacy, attitude towards website interactivity and attitude towards mobile device interactivity on customer’s behavioral intention. Moreover, website interactivity and augmented reality have highest impact attitude towards website interactivity and attitude towards mobile device interactivity respectively

IMPACT OF THE EVFTA AGREEMENT: A STUDY ON VIETNAM'S EXPORTED GOODS

Abstract The research aims to assess the quantitative impact of the Vietnam-European Union Free Trade Agreement (EVFTA) on Vietnam's export growth to the EU market. The study employs quantitative analysis using the SMART model with data on export turnover and scenarios of tariff reduction to 0% when EVFTA takes effect. Based on the export turnover data and necessary parameters, the analysis results show an increase in Vietnam's exports to the EU market when EVFTA becomes effective. As a result, the research proposes some implications to promote Vietnam's export activities to the EU in the future

The Impact of Education on Child Abuse Prevention

This research investigates the impact of education on child abuse prevention in Vietnam by using Vietnamese government's reports (2012 – 2019) on child abuse. In order to analyze the impact of education on child abuse prevention, this study focuses on reviewing the previous policies in preventing child abuse, surveying three main determinants of parents, teachers and children and testing the data collected from the survey. The result shows that education plays an important role in improving the ability to take actions against child abuse. Some recommendations to parents, teachers, children and the government are also proposed for encouraging improvements in child abuse prevention education. Keywords: Child Abuse Prevention, Education, Vietnam DOI: 10.7176/EJBM/12-20-09 Publication date:July 31st 202

The Factors Affecting the Level of Information Disclosure on Financial Statements in the Industrial Enterprises Listed on Ho Chi Minh Stock Exchange

This research analyzes the factors affecting the level of information disclosure on financial statements in the industrial enterprises listed on Ho Chi Minh stock exchange. Using financial statements of 87 industrial enterprises of the fiscal year 2017, the research shows that there are 6 factors affecting and having a positive relations with the level of information disclosure. These include: the scale of business, Duration of operation, Audit firm reputation, Solvency, Financial leverage and Return on Equity (ROE). The result points to signals that help the State Securities Commission to control better of information disclosure of firms. In addition, the study recommends measures for shareholders, especially those in large companies to strengthen the supervision, control managers in the disclosure of business information

RMDM: A Multilabel Fakenews Dataset for Vietnamese Evidence Verification

In this study, we present a novel and challenging multilabel Vietnamese dataset (RMDM) designed to assess the performance of large language models (LLMs), in verifying electronic information related to legal contexts, focusing on fake news as potential input for electronic evidence. The RMDM dataset comprises four labels: real, mis, dis, and mal, representing real information, misinformation, disinformation, and mal-information, respectively. By including these diverse labels, RMDM captures the complexities of differing fake news categories and offers insights into the abilities of different language models to handle various types of information that could be part of electronic evidence. The dataset consists of a total of 1,556 samples, with 389 samples for each label. Preliminary tests on the dataset using GPT-based and BERT-based models reveal variations in the models' performance across different labels, indicating that the dataset effectively challenges the ability of various language models to verify the authenticity of such information. Our findings suggest that verifying electronic information related to legal contexts, including fake news, remains a difficult problem for language models, warranting further attention from the research community to advance toward more reliable AI models for potential legal applications.Comment: ISAILD@KSE 202

Performance Investigation of High-Speed Train OFDM Systems under the Geometry-Based Channel Model

The high-speed of train (HST) in combination with the high carrier frequency of HST systems leads to the severe inter carrier interference (ICI) in the HST orthogonal frequency division multiplexing (HST-OFDM) systems. To avoid the complexity in OFDM receiver design for ICI eliminations, the OFDM system parameters such as symbol duration, signal bandwidth, and the number of subcarriers should be chosen appropriately. This paper aims to propose a process of HST-OFDM system performance investigation to determine these parameters in order to enhance spectral efficiency and meet a given quality-of-service (QoS) level. The signal-to-­interference-­plus-­noise ratio (SINR) has been used as a figure of merit to analyze the system performance instead of signal-to-noise ratio (SNR) as most of recent research studies. Firstly, using the non-stationary geometry-based stochastic HST channel model, the SINR of each subcarrier has been derived for different speeds of the train, signal bandwidths, and number of subcarriers. Consequently, the system capacity has been formulated as the sum of all the single channel capacity from each sub-carrier. The constraints on designing HST-OFDM system parameters have been thoughtfully analyzed using the obtained expressions of SINR and capacity. Finally, by analyzing the numerical results, the system parameters can be found for the design of HST-OFDM systems under different speeds of train. The proposed process can be used to provide hints to predict performance of HST communication systems before doing further high cost implementations as hardware designs

Bacteria associated with soft coral from Mot island - Nha Trang bay and their antimicrobial activities

Microbial communities associated with invertebrates had been considered as a new source of bioactive compounds. The soft coral associated bacteria in Mot island, Nha Trang bay were isolated, extracted and assessed for antagonistic activity against human and coral pathogens, the strongly active strains were identified by 16S rRNA analysis. The soft coral associated bacterium SCN10 had abcd antibacterial pattern which was named for inhibition towards Bacillus subtilis (pattern a), Escherichia coli (pattern b), Salmonella typhimurium (pattern c) and Serratia marcescens (pattern d). It was the nearest strain to the well-known antibiotic producer Bacillus amyloliquefaciens with 99% sequence similarity. Whereas strain SCL19 had abde pattern which means inhibition of the growth of B. subtilis, E. coli, S. marcescens and Vibrio parahaemolyticus (pattern e). This strain SCL19 affiliated with Bacillus sp. strain A-3-23B with 99.8% identity. In addition to antimicrobial activity to the aforementioned tested bacteria, the isolate SCX15 also inhibited Vibrio alginolyticus (pattern f) and Candida albicans (pattern g), so this isolate possessed abcdefg antimicrobial pattern. The coral associated isolate SCX15 was identified as Bacillus velezensis with 99% sequence similarity. Among the 78 screened strains, 25 isolates possessed antibacterial activity against at least one of seven tested microorganisms and exhibited 12 different types of antimicrobial activities, suggesting that they can produce many different natural substances with antibacterial activity