Design the model
model <- bayesvl()
model <- bvl_addNode(model, "DL", "norm")
model <- bvl_addNode(model, "sex", "cat")
model <- bvl_addNode(model, "ecostt", "norm")
model <- bvl_addNode(model, "edumot", "norm")
model <- bvl_addNode(model, "edufat", "norm")
model <- bvl_addNode(model, "Location", "binom")
model <- bvl_addArc(model, "sex", "DL", "slope")
model <- bvl_addArc(model, "ecostt", "DL", "slope")
model <- bvl_addArc(model, "edumot", "DL", "slope")
model <- bvl_addArc(model, "edufat", "DL", "slope")
model <- bvl_addArc(model, "Location", "DL", "varint")
```
Figure 1 presents the network and design of the Digital Literacy model for the probabilistic dependency among the variables. Code for the plot function to test the design of the Digital Literacy model and the generated Stan code are available in Appendix B.

**Figure 1.** Map of the Digital Literacy model.

The results of the Digital Literacy model are shown in Table 2. The model is verified using the MCMC method, and the chains are shown in Figure 2. Overall, all the chains are resembled, suggesting the autocorrelation phenomenon. Rhat is around 1 (more than 1.1 means problem), and *n*\_eff is above 2000 (more than 1000 means good sign). From Figure 2, we can see that the convergence of our model is good.


**Table 2.** The results from the hierarchical Digital Literacy model.

**Figure 2.** The MCMC chains for the Bayesian model of Digital Literacy.

Figure 3 displays the density and value of SES status, gender, mothers' education level, and fathers' education level to students' digital literacy. The SES status has a positive association with the level of students' digital literacy (mean = 0.48). The distribution of *b\_edumot\_DL* (mean = 0.2) and *b\_edufat\_DL* (mean = 0.08) are narrow with a high density, which indicates a firm association between the parents' education and students' digital literacy (the mother's education has more impact than the father's). The 'sex' coefficient lies in the negative zone of Figure 3 value's bar (mean = −0.15), which represents a weak association between students' gender and the students' digital literacy (girls' digital literacy is slightly higher than boys').

**Figure 3.** Posterior coefficients of the Digital Literacy model.

The students from an urban area (αa\_Location[2] = 40.50) have a higher level of digital literacy than their counterparts from rural (αa\_Location[1] = 39.8). However, the difference is relatively small. Hence, the results indicate that students have a fairly similar level of digital literacy regardless of where their school is located.

#### *4.2. E*ff*ects of Digital Literacy Level, Gender and School Location on the Students' Digital Resilience*

Three direct factors that could have an impact on the students' digital resilience are their digital literacy, gender, and school location. Here we investigate their relationship by using the following hierarchical Digital Resilience model (2):

$$\text{ldr} \sim \text{dl} + \text{sex} + \text{(location)}.\tag{2}$$

Examples of code that are used to command the bayesvl package to construct the Digital Resilience model are as follows:


Figure 4 presents the network model for the probabilistic dependency among the variables in the Digital Resilience model. Code for the plot function to test the design of the Digital Literacy model and the generated Stan code are available in Appendix C.

**Figure 4.** Map of the Digital Resilience model.

The Digital Resilience model is verified using the MCMC method, and the chains are shown in Figure 5. Foremost, we can see that the convergence of our model is suitable as Rhat is around 1, and *n*\_eff is above 1000. The results of the Digital Resilience model are shown in Table 3.

**Figure 5.** The MCMC chains for the Bayesian model of Digital Resilience.


**Table 3.** The results from the hierarchical Digital Resilience model.

Figure 6 displays the correlation between students' digital literacy, gender, and digital resilience. The distribution of *b\_DL\_DR* is narrow (mean = 0.59), with an excellent credibility range, suggesting a positive association between the students' digital literacy and resilience.

**Figure 6.** Posterior coefficients of the Digital Resilience model.

On the other hand, even though the standard deviation of *b\_sex\_DR* is relatively high, the distribution completely falls in the negative zone (mean = −1.17), which indicates that girls are more likely to obtain digital resilience than boys.

Both coefficients of variables representing rural area (αa\_Location[1] = 32.08) and urban area (αa\_Location[2] = 32.15) are not very different from each other. Thus, they suggest that those students are digitally resilient, regardless of their location.

#### **5. Discussion**

Our study shows that students' digital literacy and resilience have a correlation with their family background and gender but little correlation with their location. Another significant finding is the

positive relationship between students' digital literacy and digital resilience, which will be discussed in the following sections.

#### *5.1. Family Background and Students' Digital Literacy*

What are the relationships between students' socio-economic status, parents' education, and their digital literacy and resilience?

The results of this study show that there is a positive correlation between family socioeconomic factors and students' digital literacy. In Vietnam [16], more students nowadays have the chance to access to the Internet. In congruence with past findings, students who have more access to the Internet might have better chances to improve their digital literacy than the others. This ties in with the findings in the previous studies stating the importance of family cultural capital for secondary school students' digital competence [56].

In addition to SES status, parents' education also shows a positive association with students' digital literacy. The explanation for this is that digitally skilled parents can guide their kids to use computers in comparison with those parents with lower digital literacy. Schunk and Pajares [57] state that children more likely to achieve success in school have more time spent with their parents in school-related activities. In previous studies by Trung T., et al. [58] and Le, et al. [59], family and a scholarly culture at home have been proved to be essential for fostering children's reading habits; the parents are the role models, motivators, and facilitators for their children. Similar to previous studies, digitally skilled parents are believed to encourage their kids more frequently to explore the Internet or software such as PowerPoint to create their learning products [23]. Data also shows that mothers' education seems to have a higher association with the child than fathers' education. This result is relevant to the previous finding that the education level of the mother (having a university diploma or higher) strongly enhances the academic performance of students [59]. Given the circumstances of Vietnamese culture [50,52], it can be the reason that the mother more often stays at home and spends more time with a child than the father. In this digitalization era for an emerging economy, it is critical for the youth to develop their creativity and innovation, partly by utilizing online tools, rather than relying on capital or physical resources [8]. Therefore, based on these findings, it might be the case that campaigns to enhance students' digital literacy should also include instructions to parents regarding how they should carry out the experience of digital tools usage.

#### *5.2. Gender and Students' Digital Literacy*

What is the relationship between students' gender and their digital literacy and resilience?

Results from the Bayesian analysis show that girls obtain higher digital literacy and, especially, digital resilience than boys. This result is contrary to that of previous studies that found no significant relationship between gender and IT skills [23] or no gender differences [45]. However, it is consistent with other findings that there was a variation in digital literacy related to gender, which has been illustrated in many previous studies, several of which highlight the advantage of males [31–35]. while others underline that of females [36–38]. In a recent study, researchers reveal that gender is not associated with differences in digital attainment [60]. It is likely that there has been a vivid change within the gender gap in the new digital generation. Moreover, perceptions from modern parents, teachers, and society might have influenced the students' readiness to enhance digital literacy, regardless of any self-perceptions from boys or girls.

Both boys and girls at the secondary school level need help to develop better digital skills and protect themselves from online risks. Digital technologies will continue to develop strongly in the future, with a fast pace predicted. Therefore, gender inequity in digital literacy is likely to happen in such less developed countries if there is no support from the authorities. Digital fluency and gender equity will need to be carefully and continuously evaluated in order to create a balanced, digitalized society.

It will also be crucial in order to formulate further measures aimed at studying how to shorten the gender gap in students' digital literacy for other less developed countries.

#### *5.3. School Location and Students' Digital Literacy*

What is the relationship between students' school location and their digital literacy and resilience? A feature worth noting is that school location does not have an association with Vietnamese students' digital literacy. The evidence shows that even though the students from urban areas do have higher digital literacy than students in a rural area, the difference is insignificant. The widespread availability of the Internet might have been a contributor to this new feature as students from almost everywhere in Vietnam can have accessibility to knowledge via online platforms. The number of Internet users in Vietnam ranks 25 th in top countries of the world in 2019 [61], which represents the significant widespread of the Internet across the country. Our result has then proved to be different from the previous studies, which suggested that geographical location is evaluated as a factor affecting the digital skill gap of the students [62]. Our evidence also shows that there might be more equality in the distribution of IT education in both rural and urban areas. The Vietnam Ministry of Education and Training has issued a new general education program with Circular No. 32/2018/TT-BGDĐT [63], which addresses IT subject as a compulsory subject, starting to be taught officially in schools from grades 3 to 12. According to the new general educational program, IT skills will play a key role in preparing students with the ability to receive, expand knowledge, and cautious in the era of digital information, connectivity, and globalization. The expected outcome of this plan is to provide students with knowledge of personal information in digital environments, such as the concept of identity information and personal accounts. It also equips learners with an understanding of the risks of abuse and invading personal information such as how to prevent theft of personal information, prevent fraud, and being bullied in an online environment. Accordingly, the students will know the concepts of commercial software, open sources, and digital intellectual licenses, starting from the 2019–2020 school year. With this new policy, more students will be educated towards digital literacy, regardless of their location.

#### *5.4. Digital Literacy and Digital Resilience*

Results from the Digital Resilience model show a positive correlation between the students' digital literacy and their digital resilience. In the previous section, the findings from the digital literacy model indicate a positive correlation between the students' digital literacy and their family background, which includes socioeconomic status and the parents' level of education. From both models' results, we notice an indirect connection between the students' family background and their digital resilience; also, the socio-economic status and the level of education from parents might positively relate to the digital resilience of the students. Our study suggests that parents with sufficient digital literacy can help to manage students' online activities and behaviors, observing whenever they encounter online risks. The suggestion ties in with a previous study [27], which highlights the need to promote Internet access and use among the parents, as they might feel more confident in guiding their children on the Internet, promoting a positive attitude towards online safety and proactive coping strategies if they are frequent Internet users themselves. A previous study of 700 U.S. students indicated that these learners need to navigate online risks by communicating with their parents; communication is a requirement of good parenting in a digital generation [64]. Regarding the role of parents in students' Internet usage, Livingstone et al. [65] find a positive association between a parent-children conversation on Internet-related issues and high-school students' concerns about online privacy. Parents play an essential role in their children's learning as those children spend substantial time with them; in doing so, they absorb lessons from their parents in dealing with various social demands and expectations [66].

Our study suggests that students can protect themselves from online risks by being aware of these dangers in advance. Therefore, it is essential to invest in IT education in order to prevent children from encountering online risks. As digital technologies become further integrated into the everyday life of Vietnamese, young children are potentially exposed to higher risks. A previous study shows that children with low self-efficacy and more psychological difficulties are more vulnerable online as they experience stronger negative feelings and are more likely to only go offline for a while or simply hope that a problem would go away [67]. The authorities need to teach the students how to get away from those negative feelings and from being exposed to sexual risks online such as seeing explicit sexual images or sexual messages. However, there is a problem that students spend much time on the Internet, and their digital literacy sometimes is higher than that of their parents' [68]. Therefore, the parent's ability to manage their children's online activities and protect them from online risks might need additional help from the experts. In this case, they are the teachers, tutors who are experts in digital literacy and having sufficiently pedagogical skills. The findings from Shin and Lwin [2] suggest that teachers' Internet-related discussions at school can reduce students' potential exposure to online risks. Teachers are believed to play a role in stimulating their students to employ proactive problem-solving strategies, as well as teaching them how online tools and applications work [27]. Accordingly, sufficient digital literacy among the teachers themselves is, therefore, essential. As 84% of Vietnamese own a smartphone which has online functions [69], accessing the Internet has become easier nowadays. One must take into consideration that more considerable efforts are needed to teach and control the children's accessibility to information technologies (IT), especially from an early age. It is crucial to develop digital resilience in young generations [70].

#### **6. Conclusions and Limitations**

This study aims to advance the knowledge about the relationship between digital literacy and digital resilience and the students' socio-economic status, family background, gender, and school location. The research employs Bayesian statistics to analyze a dataset of 1061 Vietnamese students taken from the UNESCO's "Digital Kids Asia Pacific (DKAP)" project to explore the relationship between the students' background and their digital abilities. The empirical findings not only show the positive correlation between the socio-economic status, parents' level of education, and the students' digital literacy and resilience but also reveal little connection between digital knowledge and skills and the gender factor. Attention should be paid to the positive relationship between students' digital literacy and digital resilience. These empirical results are mostly consistent with previous studies from other contexts, which shows an alignment of Vietnam's situation with the global landscape of students' digital literacy and digital resilience.

At the moment, as digital technologies are considered state-of-the-art and students have more opportunities to use them, providing a safe environment to enhance their digital literacy might need serious investment from multiple stakeholders. This study, therefore, is of considerable significance to provide implications for policymakers, educators as well as parents. Given the proper implementation of a new educational program making the IT subject a compulsory one, the Vietnam Ministry of Education and Training should also work closely with experts from both the education and digital fields to continuously update the content of this subject to catch up with the current trends. This also makes sure that students are equipped with knowledge and skills to exploit information technology as a tool that supports their learning together with protecting themselves from increasing online risks. Educators, especially education management, should encourage the integration of technology in most, if not all, subjects so that students can have more opportunities to practice their digital literacy skills. This cannot be completed without proper training on how students may expose to different types of risks within different contexts of online activities. Additionally, Vietnamese students have shown strong performance in mathematics, science, and innovative domains, which is represented by their high scores in the Program for International Student Assessment (PISA). Although Vietnam's 2018 PISA test data are not included in the reports that compare performance with other countries due to questions about its validity, the country is still regarded as "a positive outlier in absolute scores conditional on its low level of GDP" [71]. This strong foundation of math, science, and innovation knowledge can also help to leverage the digital literacy and resilience abilities of the students, preparing

them for the development of scientific domains in Vietnam [72]. Last but not least, parents, in particular those from disadvantaged backgrounds, should be supported by education institutions, by improving their own digital literacy, and improving their digital resilience, so that they can better guide their children in these situations. Vietnam aims to achieve Sustainable Development Goals by 2030, and one of its top priorities is to provide quality educational systems [73]. In particular, to achieve this Sustainable Development Goal 4 in this digital age, it is essential to enhance the educational quality of digital subjects for secondary students.

Although significant insights could be obtained from analyzing this dataset, the study is not without limitations. Firstly, the particular location and research objects are chosen randomly and on a small-scale, which are not able to reflect a whole society and its development of digital literacy. Secondly, this paper focuses on Vietnam, specifically, without any comparison to other countries, which may lead to a subjective opinion. These preliminary results, however, do hint at several directions for future research. Our result shows that the family background of the student is positively associated with their digital literacy and resilience. However, the reason why students are being affected by their family background in digital literacy has not been answered yet. Therefore, future studies could focus on the psychological aspect of the students upon the development of their digital literacy.

Moreover, a way to enhance students' digital resilience might come from online learning, which gives the students a chance to practice with digital tools and handling online risks. According to Vu [74], online learning is relatively new in the teaching context of Vietnam, but this mode of learning is catching up quickly; far from being reserved or going against a new way of learning, most of the students who were born in the digital age welcome the changes and are willing to adapt their traditional learning styles. In fact, since the COVID−19 outbreak in Vietnam, most schools have been closed as a measure to prevent the spread of infection [75]. Therefore, these educational institutions have been attempting to move most or all of their curriculum to online platforms.

However, the suddenness of the pandemic might lead to an imbalance in the adaptability of both teachers and learners in different environments. This has created various difficulties for them, especially in posing even more disadvantages and risks for students with low levels of digital literacy and resilience. Depression and stress, therefore, might be the results for those students amid the requirement of digital literacy for online learning. Previous studies indicate a high prevalence of depression and its association with acculturation stress and social connectedness among the students in an international university in Japan [76,77]. The findings highlight the importance of support programs that consider the role of acculturation and social connectedness for the students. E-learning might become an inevitable part of modern society. However, the connectedness and mental health of learners should be taken into consideration for the sustainable development of a country's education system.

There have been many efforts from the scientific community on developing online learning schemes. A study indicates that the improvements of e-learning include: more collaboration between students since some students engage differently, more coordination and organization, better workload management in the group activities, and some technical problems being overcome, such as through updating modifications [11]. In previous studies [78,79], Biasutii also contributes a reliable analysis coding scheme to examine transcripts of online asynchronous discussion groups in university students, which is based on the following indicators: (1) inferencing, (2) producing, (3) developing, (4) evaluating, (5) summarizing, (6) organizing, and (7) supporting. The coding scheme later serves the aim of comparing the processes activated by different online tools. Hence, future research studies can apply this coding scheme to examine the online learning experiences in Vietnamese secondary school students amid the development of e-learning systems.

Overall, this research could be a contribution to the development of a higher education system and called for further studies from Vietnamese researchers. In the chaotic situation of a rapid shift from traditional teaching and learning to online forms amid the COVID−19 pandemic, this could shed light on significant issues to make sure that students benefit from inclusive and equitable quality education as one particular objective of SDG4 [80,81].

**Author Contributions:** Conceptualization, T.T., V.-P.L. and Q-H.V.; Data curation, M.-T.H., M.-H.N., T.-D.N. and T.L.N.; Formal analysis, M.-H.N. and T.-H.T.; Investigation, T.T., T.-H.P., T.-T.V. and Q.K.; Methodology, M.-T.H., M.-H.N., K.-L.P.N. and V.-P.L.; Project administration, M.-T.H.; Resources, Q.K., V.-P.L and Q.-H.V.; Software, V.-P.L.; Supervision, T.T. and Q.-H.V.; Validation, T.-H.P., T.-T.V., Q.K. and Q.-H.V.; Visualization, M.-H.N. and K.-L.P.N.; Writing—original draft, K.-L.P.N., T.-H.T.N., T.-D.N. and T.-L.N.; Writing—review & editing, M.-T.H., T.-H.P. and T.-T.V. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Acknowledgments:** The authors would like to send appreciation to UNESCO Hanoi and the Vietnam National Institute of Educational Sciences, Hanoi, for their tremendous efforts in implementing the Digital Kids Asia Pacific project in Vietnam. This paper is dedicated to the late professor Van Nhu Cuong (a.k.a, Van Ny Kyong; 1937–2017) by his former mathematics student Vuong Quan Hoang. This paper is dedicated to the late professor Van Nhu Cuong (a.k.a, Van Ny Kyong; 1937-2017) by his former mathematics student Vuong Quan Hoang.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **Appendix A. Questions' Description**



#### **Appendix B.**

Appendix B presents the plot function code and the Stan code for testing the network and design of the Digital Literacy model for the probabilistic dependency among the variables.

To test the design, the plot function can be used. The code can be seen below:


The Stan code that were generated by the bayesvl package for the Digital Literacy model:

*Sustainability* **2020**, *12*, 3819

for (i in 1:Nobs) {

```
> cat(model_string)
functions{
int numLevels(int[] m) {
int sorted[num_elements(m)];
int count = 1;
sorted = sort_asc(m);
for (i in 2:num_elements(sorted)) {
if (sorted[i] != sorted[i−1])
count = count + 1;
}
return(count);
}
}
data{
//Define variables in data
int<lower=1> Nobs; //Number of observations (an integer)
real DL[Nobs]; //outcome variable
int Nsex;
int<lower=1,upper=Nsex> sex[Nobs];
real ecostt[Nobs];
real edumot[Nobs];
real edufat[Nobs];
int<lower=0,upper=1> Location[Nobs];
int NLocation;
}
transformed data{
//Define transformed data
}
parameters{
//Define parameters to estimate
real<lower=0> sigma_DL;
real b_sex_DL;
real b_ecostt_DL;
real b_edumot_DL;
real b_edufat_DL;
real a0_Location;
real<lower=0> sigma_Location;
vector[NLocation] u_Location;
}
transformed parameters{
//Transform parameters
real mu_DL[Nobs];
vector[NLocation] a_Location;
//Varying intercepts definition
for(k in 1:NLocation) {
a_Location[k] = a0_Location + u_Location[k];
}
```


#### **Appendix C.**

Appendix C presents the plot function code and the Stan code for testing the network and design of the Digital Resilience model for the probabilistic dependency among the variables.

To test whether the design is correct, the plot function can be used. The code can be seen below:

```