This study aims to investigate and evaluate factors related to the knowledge management model at universities in Hanoi, Vietnam. Based on the system literature review (SLR) approach, the study follows descriptive and inductive approach results of the document review process. Eight factors were synthesized with the fuzzy analytic hierarchy process (FAHP) to evaluate the priority order. Ten experts from seven universities participated in the survey. The results rank as follows: (1) knowledge sharing factor (this also has the highest best nonfuzzy performance (BNP) and average multiplier weight (GM)); (2) knowledge management with big data systems; (3) knowledge creation; (4) knowledge use; (5) knowledge gathering; (6) leadership; (7) knowledge rating; and (8) knowledge storage. Discussions, conclusions, limitations of the study, and suggestions for future studies are also mentioned in this study.

And learning to online mode. This had huge impact on the students, especially for those who had not been used to being online for learning before. This mixed methods study utilized correlation, factor analysis and multiple regression techniques to identify significant predictors of students’ satisfaction with online learning in a higher education institution in Vietnam amid COVID-19 Pandemic. The study results show that learners’ interaction with content, peers and instructors correlated to and predicted student satisfaction. The study also indicated that although students valued the chance to be online for learning during the historic time, they viewed that interaction was limited and instructors should improve online teaching pedagogy. These findings provide learners, teachers and curriculum developers with new insights into learner interaction and its relation to course contents, teaching pedagogy and learning satisfaction in an Asian context.

This study aims to explore lecturer attitudes to, and intentions for, using a learning management system (LMS) in a Vietnamese university. Its two main purposes are to (a) identify the factors that influence lecturer attitudes and intentions to use an LMS, and (b) examine the causal relationships among the factors. To achieve this aim, the study used Davis’ (1985) technology acceptance model (TAM) as a baseline. The study expands the original model to include two constructs: perceived internet self-efficacy (PIS), and support to use (SU). The results of the study revealed that PIS was a significant direct predictor of lecturers’ perceived ease of use and behavioural intention to use an LMS. However, the support to use construct did not predict perceived ease of use. The study suggests that institutions should conduct an in-depth survey of teacher needs to assist with making well-informed decisions about developing an LMS for future emergencies.