ABSTRACT
BACKGROUND: Online learning has become a new thing that is adapted and supports the learning process, including in nursing education during the COVID-19 pandemic. However, various studies report that there are limitations to conduct the online learning. AIM: The objective of the study was to identify the effectiveness of the real-case online-based learning in understanding the nursing care plan process and, self-efficacy from the students’ perspective. METHODS: Mix methods;explanatory sequential designs. One-hundred and fifty-seven respondents participated in the quantitative approach (64 students in the intervention group and, 93 students in the control group). Six students among the quantitative approach were participated in the qualitative approach. Mann-Whitney’s statistical approach was used for the quantitative approach, while Colaizzi’s method of data analysis was used for the qualitative approach. RESULTS: There was no significant difference between the control and treatment groups in the nursing care plan (p = 0.13) and student self-efficacy (p = 0.45). In addition, there were five themes identified by the students’ perspectives regarding the real case online learning, including;1) opinions on learning, 2) the feelings experienced during the learning, 3) learning benefits, 4) learning barriers, and 5) expectations of learning. CONCLUSION: The real case online learning provides a different atmosphere including more interesting class, interactive interaction with the patients directly and providing positive experience for the students in the form of seeing the real cases online. The infrastructure/facilities (internet availability and stability) are important factors in the online learning process. The real case online learning is recommended as an alternative of learning that is more interesting and interactive involving the patients, students, and direct supervisors. Further research on the learning process of nursing care with a mixed system;limited offline and online cases with real, comprehensive, and interdisciplinary approaches are recommended.
ABSTRACT
Potentialized by Natural Language Processing (NLP) technology, we can build a chatbot or an AI Agent to automatically address the need to automatically get credible and timely information, especially in the fight against epidemics. However, Vietnamese understanding is still a big challenge for NLP. This paper introduces an AI Agent using the Attention algorithm and Albert model to implement the question/answering task in the Covid-19 field for the Vietnamese language. In the end, we also built two other modules, one for Vietnamese diacritic auto-correction and another for updating Covid-19 statistics (using RASA framework), to deploy a Covid-19 chatbot application on mobile devices. © 2021 ACM.
ABSTRACT
This article discussed Vietnam’s ongoing efforts to decentralize the health system and its fitness to respond to global health crises as presented through the Covid-19 pandemic. We used a general review and expert’s perspective to explore the topic. We found that the healthcare system in Vietnam continued to decentralize from a pyramid to a wheel model. This system shifts away from a stratified technical hierarchy of higher- and lower-level health units (pyramid model) to a system in which quality healthcare is equally expected among all health units (wheel model). This decentralization has delivered more quality healthcare facilities, greater freedom for patients to choose services at any level, a more competitive environment among hospitals to improve quality, and reductions in excess capacity burden at higher levels. It has also enabled the transformation from a patient-based traditional healthcare model into a patient-centered care system. However, this decentralization takes time and requires long-term political, financial commitment, and a working partnership among key stakeholders. This perspective provides Vietnam’s experience of the decentralization of the healthcare system that may be consider as a useful example for other countries to strategically think of and to shape their future system within their own socio-political context. Copyright © 2020 Via Medica