DEVELOPING THE INFORMATION TECHNOLOGY APPLICATION COMPETENCE OF TEACHERS IN ONLINE TEACHING

Developing the competence to use information technology in teaching is one of the important occupational competencies for teachers in the digital age. Information technology application development has many implications in promoting the training process to train and develop students, in accordance with the actual conditions of education in Vietnam and the general trend of the world is essential.Research paper on needs assessment using information technology of teachers in online teaching, proposing the process of identifying the structure of information technology competencies and requirements for capacity development to use information technology in online teaching of training institutions. The parameters in this paper present an empirical research result to address the need to develop the information technology application competence in online teaching, necessary to successful organize online teaching with a variety of theoretical and practical pedagogies in technology in education

Assessment of Information Technology Use Competence for Teachers: Identifying and Applying the Information Technology Competence Framework in Online Teaching

This paper proposes a theoretical framework as a foundation for building information technology competence framework and the requirements for using information technology competence of teachers in online teaching at training institutions. The parameters in this paper survey was conducted on sample space (n = 342) and 42 expert opinions to identify information technology competence framework with criteria and skill sets necessaries to successfully organize online teaching. This paper discusses on teaching developing information technology competence to change minds and develop teachers' competency to meet the online teaching trend of the digitalization today. So, building information technology competence framework in online teaching has many meanings in training process contribute to improving the learning capacity of students

Assessment of High School Students’ Learning and Development of Qualities and Competencies: A Case Study

This study aims to assess high school students' learning outcomes, their achievement of goals and fulfilling academic requirements and how the entire teaching and learning process takes place. The study, consisting of an experimental group and a control group was conducted for pre-test and post-test comparisons of the academic performance of 88 10th grade students. 44 students were selected as the experimental group that underwent a specific teaching strategy to monitor their development of qualities and competencies in one semester, and the remaining 44 students acted as the control group. The data collected after the tests were analyzed using SPSS software (V20). The results showed that the students in the experimental group had better academic results than those in the control group. The findings of this study have implications for policy, further research as well as approaches for the assessment of students’ development of qualities and competencies in Vietnam

Transfer AdaBoost SVM for Link Prediction in Newly Signed Social Networks using Explicit and PNR Features

AbstractIn signed social network, the user-generated content and interactions have overtaken the web. Questions of whom and what to trust has become increasingly important. We must have methods which predict the signs of links in the social network to solve this problem. We study signed social networks with positive links (friendship, fan, like, etc) and negative links (opposition, anti-fan, dislike, etc). Specifically, we focus how to effectively predict positive and negative links in newly signed social networks. With SVM model, the small amount of edge sign information in newly signed network is not adequate to train a good classifier. In this paper, we introduce an effective solution to this problem. We present a novel transfer learning framework is called Transfer AdaBoost with SVM (TAS) which extends boosting-based learning algorithms and incorporates properly designed RBFSVM (SVM with the RBF kernel) component classifiers. With our framework, we use explicit topological features and Positive Negative Ratio (PNR) features which are based on decision-making theory. Experimental results on three networks (Epinions, Slashdot and Wiki) demonstrate our method that can improve the prediction accuracy by 40% over baseline methods. Additionally, our method has faster performance time

Factors Affecting Business Performance: Expanding Theoretical Measurements

Purpose: The article aims to expand a scale system of factors that impacts on business performance.   Theoretical framework: The paper based on the empirical data collected from various types of participants, including accountants (for information providing), managers (for decision-making), sales staff (for work), and lecturers (for research) in Vietnam.   Design/methodology/approach: By descriptive and comparative statistical analysis of SPSS 20 software with 124 valid observations, the survey has proposed the scale system of influencing factors (03 groups of external factors, 05 groups of internal factors) and business performance measures (10 financial and 11 non-financial indicators).   Findings: This study points out the different evaluations according to the demographic features of survey subjects on the group of financial indicators. Specifically, the group of accountants (representing information providers) obtains a lower score than the group of information users. Likewise, the post-graduated participants show stricter assessments of financial indicators in comparison to the rest of the group.   Research, Practical & Social implications: These results suggest the scale system for measuring influencing factors toward business performance in enterprises for further research.   Originality/value: The value of the study is providing an expansion of the factors affecting the efficiency of an enterprise and points out a commonly used set of financial performance measurement indicators. Research results provide useful references for research on related issues

Investment on environmental social and governance activities and its impact on achieving sustainable development goals: evidence from Chinese manufacturing firms

Achieving sustainable development goals (SDGs) is a global requirement that attracts new researchers and regulators. So, the current research investigates the impact of investment on the environment, social, and governance (ESG) activities on the achievement of SDGs of the Chinese manufacturing companies. The current article also examines the mediating impact of organizational effectiveness among the nexus of investment in ESG activities and the achievement of SDGs of the Chinese manufacturing companies. The current research has taken the questionnaires to gather the data and used the smart-PLS to analyze the data. The results exposed that investment in the environment and social activities have a positive impact on the achievement of SDGs. The findings also revealed that the organizational effectiveness significantly mediates among the nexus of investment in the environment and social activities and the achievement of SDGs of the Chinese manufacturing companies. This study provides help to the relevant authorities to achieve the SDGs using the investment in ESG activities

Attentive Deep Neural Networks for Legal Document Retrieval

Legal text retrieval serves as a key component in a wide range of legal text processing tasks such as legal question answering, legal case entailment, and statute law retrieval. The performance of legal text retrieval depends, to a large extent, on the representation of text, both query and legal documents. Based on good representations, a legal text retrieval model can effectively match the query to its relevant documents. Because legal documents often contain long articles and only some parts are relevant to queries, it is quite a challenge for existing models to represent such documents. In this paper, we study the use of attentive neural network-based text representation for statute law document retrieval. We propose a general approach using deep neural networks with attention mechanisms. Based on it, we develop two hierarchical architectures with sparse attention to represent long sentences and articles, and we name them Attentive CNN and Paraformer. The methods are evaluated on datasets of different sizes and characteristics in English, Japanese, and Vietnamese. Experimental results show that: i) Attentive neural methods substantially outperform non-neural methods in terms of retrieval performance across datasets and languages; ii) Pretrained transformer-based models achieve better accuracy on small datasets at the cost of high computational complexity while lighter weight Attentive CNN achieves better accuracy on large datasets; and iii) Our proposed Paraformer outperforms state-of-the-art methods on COLIEE dataset, achieving the highest recall and F2 scores in the top-N retrieval task.Comment: Preprint version. The official version will be published in Artificial Intelligence and Law journa

Synthesize and characterization of artificial human bone developed by using nanocomposite

The combination of biopolymers with bioceramics plays vital role in development of artificial bone. Hydroxyapatite is extensively used as a material in prosthetic bone repair and replacement. In this paper synthesis of Hydroxyapatite- Polymethyl methacrylate – Zirconia (Hap-PMMA-ZrO2) composite by using powder metallurgy technique. The mechanical, morphological, In-vitro biocompatibility and tribological properties were characterized by universal testing machine, micro-vickers hardness tester, high resolution transmission electron microscope (HR-TEM), MTT assay and pin-on-disc setup. In-vitro cytotoxicity test on HeLa cell lines shows cell viability constant when doses concentration increases so material found non-toxic. Results show that micro Vickers hardness i.e. 520 approximately matches with natural human bone i.e. 400. Compressive strength is less as compared to human bone because of powder metallurgy route used for fabrication and is 74 MPa. Density of proposed composite artificial human bone i.e. 1.52 g/cc is less as compared to natural bone i.e. 2.90 g/cc. The Hap-PMMA-ZrO2 composite will be good biomaterials for bone repair and replacement wor