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2 Annals of Computer Science and Information Systems

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Innovative teaching, delivering materials and the student's satisfaction in online learning : evidence from a sharp shift due to Covid-19 pandemic in Vietnam

Binh Vu Thi Thanh, Nga Nguyen Thi Hong, Loan Nguyen Thi Thanh

Annals of Computer Science and Information Systems

2022

Vol. 34

87--92

Online learning is one of the trend in modern education today. In the context of the complicated Covid-19 epidemic, the role of online learning in teaching and research activities is even more critical. Innovative teaching methodologies and providing materials are two decisive factors in online education, so improving those two factors will help increase the quality of online learning. The research explores the influence of innovative teaching approach and the effectiveness of delivery materials on student satisfaction at higher education institutions in Vietnam. The research collected data through survey questionnaires with 527 responses. The study tested the measurement quality and examined hypotheses through multivariate regression analysis. The findings confirmed a positive effect of innovative teaching approaches and the effectiveness of delivering materials on student satisfaction in online courses. Based on the findings, the research proposed some recommendations to improve innovative teaching methodologies and provide materials in e-learning to enhance the quality of online learning.

Data Mining for Bankruptcy Prediction: An Experiment in Vietnam

Hung Dang Ngoc, Binh Vu Thi Thanh

Annals of Computer Science and Information Systems

2021

Vol. 28

175--184

In the history of the world economy, the bankruptcy of some large companies has caused global financial crises. The study aimed to postulate a model of bankruptcy prediction for listed companies on Vietnam's stock market. The research used six popular algorithms in data mining to predict bankruptcy risk with data collected from 4693 observations in the period 2009-2020. The research results showed that Logistic algorithms, Artificial Neural Network, Decision Tree have a high level of predicting bankruptcy with an accuracy of 98%. The study identified the three most important indicators: inventory turnover ratio, debt to equity ratio, and debt ratio that affect the corporate bankruptcy prediction. The study showed the threshold points of 10-indicators to avoid bankruptcy likelihood. These results recommended that the model could be applied in practice to reduce risks for businesses and investors in the Vietnamese market.