Dataset of Vietnamese teachers’ perspectives and perceived support during the COVID-19 pandemic

The COVID-19 pandemic has caused unprecedented damage to the educational system worldwide. Besides the measurable economic impacts in the short-term and long-term, there is intangible destruction within educational institutions. In particular, teachers – the most critical intellectual resources of any schools – have to face various types of financial, physical, and mental struggles due to COVID-19. To capture the current context of more than one million Vietnamese teachers during COVID-19, we distributed an e-survey to more than 2,500 randomly selected teachers from two major teacher communities on Facebook from 6th to 11th April 2020. From over 373 responses, we excluded the observations which violated our cross-check questions and retained 294 observations for further analysis. This dataset includes: (i) Demographics of participants; (ii) Teachers' perspectives regarding the operation of teaching activities during the pandemic; (iii) Teachers' received support from their schools, government bodies, other stakeholders such as teacher unions, and parents' associations; and (iv) teachers' evaluation of school readiness toward digital transformation. Further, the dataset was supplemented with an additional question on the teachers' primary source of professional development activities during the pandemic.


a b s t r a c t
The COVID-19 pandemic has caused unprecedented damage to the educational system worldwide. Besides the measurable economic impacts in the short-term and long-term, there is intangible destruction within educational institutions. In particular, teachers -the most critical intellectual resources of any schools -have to face various types of financial, physical, and mental struggles due to . To capture the current context of more than one million Vietnamese teachers during COVID-19, we distributed an e-survey to more than 2,500 randomly selected teachers from two major teacher communities on Facebook from 6th to 11th April 2020. From over 373 responses, we excluded the observations which violated our cross-check questions and retained 294 observations for further analysis. This dataset includes: (i) Demographics of participants; (ii) Teachers' perspectives regarding the operation of teaching activities during the pandemic; (iii) Teachers' received support from their schools, government bodies, other stakeholders such as teacher unions, and parents' associations; and (iv) teachers' evaluation of school readiness toward digital transformation. Further, the dataset was supplemented with an additional question on the teachers' primary source of professional development activities during the pandemic.
© 2020 The Author(s Value of the data • The dataset can be used for further analysis of teacher satisfaction and online teaching effectiveness with the focus on the chaotic context of a pandemic. • The dataset can be used to construct models to evaluate educational leadership and school effectiveness in abnormal situations. • The significant differences in Vietnamese teachers' income before and during COVID-19 in this dataset can contribute to overall economic models on COVID-19's damage. • The dataset will be useful for school managers and policymakers to renovate policies, regulations, and practices to enhance teacher satisfaction, engagement, and effectiveness. • The dataset presents a natural flow to measure teacher perceptions and satisfaction during COVID-19, which can be replicated in other countries.

Data Description
School effectiveness measurements include various factors related to students, teachers, and school managers that affect students' academic achievement [1] . Although the Vietnamese gov-ernment applied different systematic solutions to minimize the negative impacts of the COVID-19 pandemic [2] , there is a lack of empirical evidence to support the decision-making process of school leaders. Under the chaotic circumstances caused by the pandemic, the significant shifts in learning and teaching habits require school leaders to face critical unknown-unknown issues. The formation of this dataset is an extension of our recent study on students' learning habits during the pandemic [ 3 , 4 ], which contributes to the call of Elsevier on conducting research to tackle the current and potential impairments of the pandemic [5] . Regarding the sudden shift to online teaching and learning due to school closures, this dataset [6] portrayed Vietnamese teachers' perspectives and teaching effectiveness during the pandemic and schools' readiness toward the digital transformation.
Besides the information about the demographics of the participants, this dataset includes two primary groups of research items: (i) Teachers' perceptions of factors associated with online teaching and learning; and (ii) Teachers' opinions on school readiness and teaching effectiveness during the pandemic. The full questionnaires, variable code, and measurement parameters for all research items have been reposited in Harvard Dataverse [6] . Integrations among those variables can examine teacher satisfaction, self-reported teaching effectiveness, and school readiness during the pandemic. Tables 1 , 2 , 3

Experimental Design, Materials, and Methods
The data was collected from 6th to 11th April 2020, the ninth week of national school suspension in Vietnam, due to the COVID-19 pandemic. Considering that there are more than one million teachers in Vietnam, it is impossible to reach all types of teachers across the country. Thus, the researchers focused on the two biggest teacher communities on Facebook: Microsoft Innovative Education Expert Vietnam -MIE (38,600 members) and Vietnam Innovative Education Forum -VIEF (14,0 0 0 members). Firstly, the survey was announced by the admins of those groups and attracted around 500 interactions from members. Additionally, we randomly selected 1,0 0 0 members from each group and sent them the survey URL, separately. Overall, a total of 373 responses was collected. Couples of cross-checking questions with reversed Linkert scales were embedded in the survey and helped us to eliminate 79 bias observations. Finally, we analyzed the dataset of 294 respondents.
The differences between teachers' satisfaction among various demographic indicators and examined research items can be presented through ANOVA analysis. In particular, Table 4 shows the test of homogeneity of variances. Table 5 and Table 6 display the differences in teachers' satisfaction among demographic indicators and teachers' perception, respectively. The results of robust tests of equality of means are included in Table 7 .
Using questions with the five-points Linkert scale, this dataset demonstrated the factors associated with online teaching effectiveness, teacher satisfaction, and school effectiveness during the pandemic.
Regarding the control over online teaching effectiveness (ONL_EFF), we considered four factors. First, teachers' overall perceptions of the impact of the pandemic (FEEL) are the aggregated result of the influence of the pandemic on their health; their living habits; and their financial status [ 7 , 8 ]. Second, we indicated the teachers' received support (SUP) as a function of the support they receive from: School Board of Management; Parents Association; Teacher union; and Government bodies [ 9 , 10 ]. The question "I do not receive any support" was included to crosscheck the validity of respondents. Third, teachers' capability toward online teaching technologies (ICT_CAP) was the mean of their self-reported ICT (Information and Communication Technology) competency [10] before the pandemic emerged; the smooth of their online lesson during the pandemic; and the diversity of the tools which they mastered. Also, we added additional questions to examine the teacher's proactiveness in learning new ICT tools (ICT_ACT). We consider the influence of the above factors over online teaching effectiveness by the following regres-    .001 * Asymptotically F distributed. * * Robust tests of equality of means cannot be performed for Tearcher satisfaction because at least one group has the sum of case weights less than or equal to 1.

sion:
ONL _ EFF ∼ β0 + β1 * FEEL + β2 * ( SUP ) + β3 * ( ICT _ CAP ) + β4 * ( ICT _ ACT ) + u Regarding the influence over teacher satisfaction, we included teachers' self-reports among the three following constructs [11] . First, teachers' perceptions of online teaching activities (ONL_PER) were combined from the effectiveness of online class (in comparison with regular lessons -Onl_effective) [12] , students' activeness (Onl_active) [13] , workload increment (Onl_workload), and level of stress during the pandemic (Onl_stress) [14] . During further analytical processes, the measurement scale of increased workload and degree of stress should be reversed to ensure the consistency of the overall construct. Second, the school's readiness toward digital transformations during the pandemic (READY) was indicated by the eagerness of ICT infrastructure, teacher capabilities, policies, and regulation [15] . Third, regarding professional development, we included types and sources of new know-how that teachers absorbed during the pandemic (PD). A cross-checking question was added to exclude invalid answers "I do not have time to learn new things." If the response of this question is not consistent with the previous three, we will eliminate that observation. Considering teacher satisfaction as the primary outcome, the influence of those other factors listed above can be examined by the following regression: SAT ∼ β0 + β1 * ( ONL _ PER ) + β2 * ( READY ) + β3 * ( PD ) + u

Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships which have, or could be perceived to have, influenced the work reported in this article.