Factors Affecting High School Teachers’ Attitudes Towards Online Teaching

The transition to distance learning during COVID-19 has completely overturned the teaching-learning way of the world’s education system. Based on the technology acceptance model, this study was conducted to explore what factors might affect the teachers’ attitudes toward the online teaching regime. Structural equation modeling was employed to analyze data drawn from high school teachers in Vietnam. The findings presented that the perceived usefulness of digital teaching was the most fundamental determinant of teachers’ attitudes and played a mediating role in linking the perceived ease of use to attitude. As an external factor, school assistance was significantly associated with both perceived ease of use and perceived usefulness, which provides facilitating conditions to ensure successful adoption of online teaching. Age and teaching experience also had a significant influence on external assistance and teachers’ attitudes, respectively. This investigation sheds light on promoting digital transformation in the education sector in Vietnam and other countries.


INTRODUCTION
The unprecedented development of the Internet and modern technologies has pervaded every aspect of the education system, which leads to an increasing tendency for online education over the past few decades (Baber, 2021;Liu et al., 2010;Yuen & Ma, 2008).Online learning is a term that presents the form of learning conducted wholly over the Internet where the learners have an access of the virtual classroom instead of traditional face-to-face method (Oblinger et al., 2005).As it makes use of virtual platforms, the online delivery mode provides efficient and flexible ways of teaching, which opens opportunities and approaches to pedagogical innovation (Almahasees et al., 2021;Junco et al., 2013).Similar to other developing countries, Vietnam is undergoing a nationwide digital transformation in education, with the aim at improving capacity for technology application and communication in teaching and learning; in turn, narrowing the gap with developed countries.Having a wide range of advantages, teaching and learning online are of the targets of educational strategy in Vietnam, which has been emphasized on Circular No. 09/2021/TT-BGDDT issued in 2021 by the Ministry of Education and Training.However, there is a concern that teachers may be hesitant to adopt the new form of online teaching because of the fear of innovation, the lack of confidence, the workload issues, and other influential factors (Betts, 2009;McQuiggan, 2012;Wingo et al., 2017).The sudden outbreak of COVID-19 has triggered online teaching activities and to an extent accelerated progress towards a greater use of online platforms in education.In the wake of the schools' closure, the quick response of shifting into online learning is inevitable to ensure students' access to education.It is the first time the whole education system in Vietnam has switched to entirely virtual teaching methods instead of mostly face-to-face teaching; leading to a huge challenge for educational institutes and teachers to ensure the quality of education through online training (Maheshwari, 2021).
Given that instructors play a key role to gain colossal success in the education system, it is crucial for the institutions to explore what factors might impact the teachers' attitude toward the online teaching regime (Almahasees et al., 2021;Chandwani et al., 2021;Drueke et al., 2021;Hermanto, 2020;Wang et al., 2021).As shown in the literature, the technology acceptance model (TAM) has attracted considerable interest in studies related to e-learning and is expected a robust model for understanding the drivers of faculty members' attitudes toward virtual teaching methods (Drueke et al., 2021;Mailizar et al., 2021;Teo et al., 2008;Wingo et al., 2017;Yuen & Ma, 2008).However, while TAM has been so far widely applied in research related to technology users' intention, research on its application in examining users' attitude in the field of education, in particular, online teaching is limited.
From those earlier studies, it can be seen that the importance of research on instructors' attitude towards online teaching has recently been emphasized.However, most of them have focused on university faculty while little has been conducted on exploring the attitude of high school teachers to use the Internet-based form of course delivery.Likewise, in the context of Vietnam, none has been carried out to identify the attitude among high school teachers enrolled in teaching online, especially in the condition of emergency remote teaching during the pandemic.Hence, the aim of this survey is to scrutinize determinants of teachers' attitude toward online teaching in some selected high schools in Vietnam.A structural equation modelling (SEM) technique is adopted to analyze the interconnection among the four variables in a TAM model, which are: attitudes towards online teaching, perceived usefulness, perceived ease of use, and technical, administrative, and pedagogical assistance (herein external assistance).In addition, the effect of demographic variables on teacher's attitude is also investigated by using ANOVA and Independent T-test techniques.Having a comprehensive understanding of the relationships among variables that influences teachers' attitude is expected to provide a source of reference for planning suitable policies aimed to create favorable online teaching conditions applied in general education institutions in the future.In terms of methodology, with the use of the dependent variable being attitude instead of the actual use or behavioral intention used in most of previous studies and the addition of external assistance served as an additional variable, it is hoped to contribute the new insight on existing TAM model.

The Technology Acceptance Model (TAM)
The TAM, developed by Davis (1985), is among the most effective models that can be used to explain the connection between beliefs, attitude, and the intention to adopt technology (Teo, 2019;Yuen & Ma, 2008).Internal beliefs include perceived usefulness that implies 'the degree to which a person believes that using a particular system would enhance his or her job performance' and perceived ease of use that is 'the degree to which an individual believes that using a particular technology would be free of effort' (Davis, 1989;Davis et al., 1989).The original TAM model (shown in Figure 1) includes two main components, namely perceived ease of use and perceived usefulness of technology, which are considered main indicators of users' attitudes and behavioral intention toward using technology.The TAM also suggests that perceived ease of use has a direct effect on perceived usefulness.In addition to that, both perceived ease of use and perceived usefulness are hypothesized to be affected by the external variables (illustrated by X1, X2, and X3) (Davis, 1985;Marangunić & Granić, 2015).
To improve the effectiveness of the model, the addition of external variables categorized into four groups of organizational, system, personal characteristics, and other variables have also received attention in recent studies (Yousafzai et al., 2007).By applying the TAM, previous investigations have found various results involving the correlation between perceived usefulness, perceived ease of use, and external variables and attitude to use technology in teaching.

Factors Affecting Teachers' Attitude Towards Online Teaching
Several investigations have recently conducted to seek the determinants of teachers' attitude towards online teaching.Examples from those studies pointed out that both perceived usefulness and perceived ease of use served as the two significant predictors of teachers' attitude towards technology use (Teo et al., 2008) while others stated that one of them was not a significant influential factor (Drueke et al., 2021;Luik & Taimalu, 2021;Teo, 2012;Yuen & Ma, 2008).Of external variables, facilitating conditions such as technical support or institutional direction was proved the main factors directly affecting teachers' attitude towards digital teaching (Fathema et al., 2015;Jones, 2004;Lim & Khine, 2006;Prottas et al., 2016) or indirectly influencing their attitude through perceived ease of use (Teo et al., 2008).In contrast, this factor did not significantly explain the attitude of teachers in the research of Teo (2012).Besides, it is reported that there were mixed results on the relationship between teacher's attitude toward online teaching and demographic variables such as gender (Xhaferi et al., 2018), age, teaching experience (Prottas et al., 2016), and other factors (Almahasees et al., 2021).

THeOReTICAL FRAMewORK AND HyPOTHeSeS FORMULATION
In order to predict the drivers of teachers' attitude toward online teaching, the TAM model is utilized as a research framework in this study, in which the attitude of the teacher is predicted by two main factors, perceived ease of use and perceived usefulness, with perceived ease of use linking directly to the perceived usefulness.Besides, these factors are hypothesized to be predicted by the external assistance.Consequently, a research framework is developed and given in Figure 2.
The attitude towards online teaching in this framework means the degree to which teacher's positive or negative feelings about online teaching, which might shape the success of online education (Baber, 2021;Teo, 2019).A teacher with a positive attitude towards online teaching not only help Source: Davis (1985) to enhance the quality of education but also have a motivation to overcome the difficulty of the new teaching process (Taylor & Watson, 2003).The attitude is influenced by various variables.Among those, perceived usefulness has been proved to be a strong predictor of attitude (Drueke et al., 2021;Luik & Taimalu, 2021;Teo et al., 2008;Teo, 2012).Perceived usefulness could be explained to the extent to which an individual thinks that applying virtual teaching would help them to have better teaching performance.With regard to this concept, the following hypothesis is proposed: Hypothesis One (H1): Teachers' perceived usefulness has a positive effect on their attitude towards online teaching.
In addition, perceived ease of use which refers to the extent to which an individual thinks that applying online teaching would be without particular difficulty, has been found to be another critical antecedent of teachers' attitude to use the virtual teaching system (Keong et al., 2014;Teo et al., 2008;Yuen & Ma, 2008).On the other hand, the correlation between perceived usefulness and perceived ease of use is hypothesized, in which perceived usefulness plays a mediating role in linking perceived ease of use to attitude (Fathema et al., 2015;Teo et al., 2008).Therefore, the following hypotheses are proposed: Hypothesis Two (H2): Teachers' perceived ease of use has a positive effect on their perceived usefulness of online teaching adoption.Hypothesis Three (H3): Teachers' perceived ease of use has a positive effect on their attitude towards online teaching.
From the literature, external factors have been added to examine the chain of correlation between these variables and the attitude through two core factors, perceived usefulness and perceived ease of use (Keong et al., 2014;Marangunić & Granić, 2015).Several studies have concluded that the existence of external variables resulted considerable links between these variables and perceived usefulness and perceived ease of use.For instance, Groves and Zemel (2000) indicated that there were numerous kinds of support, namely training and refresher courses, educational resources available, quality assurance conditions, and other administrative supports were believed to be a crucial influence on the information and communications technology application in teaching.In agreement with that, Teo et al. (2008) and Keong et al. (2014) reported that facilitating conditions related to a managerial response to assist teachers on the technical issue during the process of teaching online had a considerable impact on perceived usefulness and perceived ease of use.From these views, external assistance which covers technical, administrative, and pedagogical assistance is chosen as an external factor in this study's framework; thus, the following hypotheses are proposed: Hypothesis Four (H4): External assistance has a positive effect on teachers' perceived usefulness of online teaching adoption.Hypothesis Five (H5): External assistance has a positive effect on teachers' perceived ease of use of online teaching adoption.
Furthermore, it is suggested that contextual factors such as demographic variables, cultural diversity, and technology characteristics which could have an effect on the TAM model (Gururaja, 2021;Marangunić & Granić, 2015).It is found that gender, age, teaching experience, employment status, and computer confidence have a relationship with factors in the TAM model (Prottas et al., 2016;Sadik, 2006).Focused on only demographic characteristics, this study propose the following hypothesis: Hypothesis Six (H6): Gender, age, educational level, and teaching experience have an impact on elements included in the TAM model.

MeTHODOLOGy Survey Instrument and Data Collection
The survey consisted of three parts was structured to examine factors affecting teachers' attitudes towards online teaching.Based on the foundation of TAM and measurements validated by the earlier studies (Baber, 2021;Davis, 1989;Fathema et al., 2015;Jogezai et al., 2021;Keong et al., 2014;Kisanga, 2016;Teo, 2019;Yuen & Ma, 2008), thirteen items were adapted and listed in the Appendix.The first part of the questionnaire comprised of 3 items designed to measure the attitude of teachers to adopt a method of teaching via the Internet (ATT) (ATT1-ATT3).Followed by the second part that was regarding external assistance (AS) (three items, AS1-AS3), perceived usefulness (PU) (four items, PU1-PU4), and perceived ease of use (PEU) (three items, PEU1-PEU3).All items were designed on a five-point Likert scale arranged in order from 1=strongly disagree to 5=strongly agree.The last part was the questions on teachers' demographics, namely gender, age, educational level, and teaching experience.The questionnaire was translated into Vietnamese with wordings revised to improve the clarity of the questions.After that, it was pretested and then modified to ensure the content's validity and reliability.Finally, the final version of the survey was established using Google Forms.
The survey targeted a group of full-time high school teachers who have experienced in online teaching.Upon the approval of school's principals, the survey's link was initially delivered to some of teachers in some high schools in Danang city, Vietnam and then further distributed to additional teachers via snowball sampling during one month from December 5, 2021 to January 5, 2022.A total of 222 responses was collected, twenty of them were deleted after data screening and cleaning.As a result, 202 samples left, which was higher than a sufficient sample size for SEM analysis of 100 to 150 cases (Kline, 2015).Similarly, a suggested minimum sample size of 166 was found by applying power analysis based on anticipated effect size (0.3), the number of latent variables (4) and observed variables (13) (Cohen, 2013;Westland, 2010).Therefore, it can be confirmed that the size of the sample in this survey is suitable for further analysis.

Data Analysis
This research preliminarily employed exploratory factor analysis (EFA) and reliability test by using Statistical Packages for Social Sciences (SPSS, version 22, IBM Corp., Armonk, NY).Factor analysis with varimax rotation was carried out to clarify the relationship survey instrument.Kaiser-Meyer Olkin measure of sampling adequacy (KMO > 0.70) and Bartlett's test of sphericity (significant at p < 0.001) were used to judge the appropriateness of the model.In addition, Eigenvalue (> 1) and factor loadings (> 0.50) were calculated to decide the number of retaining factors (Hair, 2010;Taherdoost et al., 2014).To examine the internal reliability of the remaining items, Cronbach's alpha measure was adopted and its suggested value was higher than 0.7 (0.6 is commonly accepted) (Hair, 2010).
Consequently, assisted by analysis of moment structures (AMOS, version 22, IBM Corp., Armonk, NY) software, the two-step approach of SEM was applied to examine path correlations between and within latent variables in the survey's proposed conceptual model.The first step, known as confirmatory factor analysis (CFA), involves measurement for reliability, convergent, and divergent validly, which indicates how well the relationship between the measured items and the latent constructs.The second one is called the structural model, which estimates the hypothesized relationship among constructs.
Lastly, the application of SPSS 22 was repeated to perform descriptive analysis, independentsamples T test, and one-way analysis of variance (ANOVA) for exploring the influence of demographics on all elements shown in the conceptual model of this study.

Participants' Characteristics
A total of 222 teachers participated in the survey, but only 202 responses could be used after the data cleaning process.The majority of the participants were female (83%) while only 17% were male, which is aligned with the fact that teaching profession has been women-dominated, especially in Vietnam's basic education system.Out of these, most of the teachers got a Bachelor degree (69%), doubling the proportion of those who were at a Master's level (31%).The number of teachers who aged at the range of (22-39) years old was almost equal to that of seniors who aged at (40-60), 51% and 49%, respectively.In terms of teaching experience, most teachers in this survey had taught for around 10 to 15 years (31%) and from 16 to 20 years (27%), followed by those who experienced in teaching less than 10 years or longer than 20 years, consisting of 21% for each.The descriptive statistic of participants' identities is summarized in Table 1.

exploratory Factor Analysis and Reliability Test
The performance of factor analysis with varimax rotation was done to explore the main variables to create the model from a set of initial items used in this study.The KMO correlation was 0.815, being higher than a suggested level of 0.70 (Hair, 2010), which is considered adequate for analyzing the EFA output.The result of Bartlett's test of Sphericity (Approx.Chi-Square = 996.15,sig.<0.0001) indicates that the matrix is not an identity matrix; hence, the dataset is acceptable to move forward with the factor analysis (Bartlett, 1950).After the extraction phase, main factors were extracted with the explained variance of 76.53% and the Eigenvalue was at 1.118 (greater than a critical value of 1).All of the initial items were retained because their factor loadings were larger than the recommended values of 0.5 (Hair, 2010).Consequently, as expected, there were four factors used for a further test of this study, namely, external assistance (AS) (3 items, AS1-AS3), perceived usefulness (PU) (4 items, PU1-PU4), perceived ease of use (PEU) (3 items, PEU1-PEU3), and one dependent latent variable of attitude (ATT) (3 items, ATT1-ATT3).
To check the reliability of items in each extracted factor, most of the values of Cronbach's alpha were higher than the standard level of 0.7.However, as suggested, AS1 was deleted to improve the Cronbach's alpha of AS factor.Table 2 presents the Cronbach's alpha of all revised factors.

Measurement Model
It is necessary to assess the measurement model before the structural model, which includes the test for the composite reliability, convergent and discriminant validity of each item in the factor.As shown in Table 3, standardized estimates of all measured items in the model were higher than 0.6 and significant at the p-value < 0.001 level, which met the threshold of 0.5 suggested by (Hair, 2010).The composite reliability (CR) and the average variance extracted (AVE) for all factors were above the cut-off value of 0.7 and 0.5, respectively, indicating that internal consistency and convergent validity were well-established.To check the discriminant validity, the application of the heterotrait-monotrait (HTMT) ratio criterion was performed.Following a limit value suggested by Henseler et al. (2015), all the HTMT values of factors were lower than 0.9, implying that the discriminant validity of this study's measurement model was confirmed.
To determine how the model fits well to the data, various indices were used in CFA, which includes absolute fit, incremental fit, and parsimonious fit.Absolute fit indices examine to an extent an a priori model fits well to the data, which consist of the goodness of fit index (GFI), the adjusted goodness of fit index (AGFI), the root mean square residual (RMR), the standardized root mean square residual (SRMR), and root mean square error of approximation (RMSEA).The second one, incremental fit indices that are the results of a comparison of the Chi-square between the hypothesized model and baseline model, embracing the normed fit index (NFI), the Tucker-Lewis index (TLI), the comparative fit index (CFI), the incremental fit index (IFI), and the relative fit index (RFI).The last one, parsimonious fit indices include the parsimonious goodness-of-fit index (PGFI), the parsimonious normed fit index (PNFI), and the parsimony comparative fit index (PCFI).In addition, due to the restrictiveness of the Chi-Square statistic in case that sample size is small, relative chisquare (CMIN/DF) is used to assess the fit of model instead (Byrne, 2016;Hair, 2010).As presented in Table 4, all goodness-of-fit results of this study met the suggested values; thus, the measurement model well fits to the data.

Structural Model
The relationship of the structural model was identified by the path coefficient among factors proposed in the framework of the research.Looking at Figure 3, 80% of the variance in attitude was explained by its predictors, which was pretty high in such investigations related to technology acceptance (Teo, 2019).On the other hand, being performed as mediators, the variations in perceived usefulness and perceived ease of use were interpreted by their antecedents by 42% and 26%, respectively.The high R square value extracted from this study presented the model is acceptable.
Table 5 shows the results of hypothesis testing; of five hypotheses, four were supported (H1, H2, H4, and H5), except for H3 that revealed the insignificant relationship between perceived ease of use and attitude.Meanwhile, perceived usefulness was the strongest predictor of attitude while a direct effect of perceived ease of use on attitude to teach online was not verified.However, perceived ease of use positively affected perceived usefulness, implying that perceived ease of use had an indirect effect on attitude.Regarding the influence of external assistance on perceived usefulness and perceived ease of use, it was detected that their path coefficients were both significant positive.
As can be obtained from Figure 3 and Table 5, perceived usefulness was proved significant and powerful in explaining teachers' attitude toward online teaching activities, with the path coefficient of 0.889 (p-value < 0.001).It thereby can assume that the perceived usefulness of the advanced teaching method is extremely important.In other words, if teachers believe that technology-based teaching activities are helpful for improving their performance, they were likely to form a strong attitude toward using online teaching.This result was in agreement with existing studies that demonstrated  that every unit increase in perceived usefulness would enhance the positive attitude of teachers (Luik & Taimalu, 2021;Prottas et al., 2016;Teo et al., 2008).It is reasonable because of the fact that the usefulness in this research is linked to the utilitarian aspect of online teaching adoption; as a result, its better productivity would induce higher willingness among teachers to teach via online platforms.Therefore, it should be emphasized in the first place in the effectiveness of virtual education, hence, increasing the positive attitude of teachers toward a more technologically advanced modality.
On the other hand, the perceived ease of use failed to reach significance in predicting teacher' attitude, which was not consistent with the outcomes in the research of Teo et al. (2008) and Yuen and Ma (2008) who concluded that perceived ease of use had been confirmed a predictor of attitude, intention and usage in most studies using TAM.On the contrary, Luik and Taimalu (2021) and Teo (2012) determined that only perceived usefulness had significant causal linkages with the attitude while perceived ease of use was not, which supported this research's findings.Interestingly, the perceived ease of use was detected to be highly correlated with perceived usefulness, showing its standardized path coefficients being 0.519 (p-value < 0.001).It turns to the fact that the perceived ease of use had an indirect effect on attitude toward using technology through the mediator variable of perceived usefulness for teachers.Similar results were confirmed by Luik and Taimalu (2021) who reported that perceiving easily when applying technology in teaching would increase teachers' positive belief in the usefulness of online teaching.The possible explanation for the insignificant direct relationship between perceived ease of use and attitude could be that the prevalence of the user-friendly information and communications technology application makes it easy for teachers to access the modern method of teaching.As a result, the online teaching method that is considered easy-to-use must simultaneously be perceived as applicable before it positively linked to the attitude.
Furthermore, external assistance was significantly associated with not only perceived usefulness but also perceived ease of use with the standardized path coefficients being of 0.208 (p-value = 0.007) and 0.511 (p-value < 0.001), respectively, implying its significant perception anchor of the core factors in TAM.This significant correlation emphasizes the assistance involved technical, administrative, and pedagogical issues is crucial and helpful for all teachers.Meanwhile, the presence of adequate support makes teachers feel more confident to successfully adopt the online teaching method in an easy and effective way.This concept was in line with the conclusion of previous studies, which expressed the important need for the availability of technical and instructional design support (Lee, 2001;Luik & Taimalu, 2021;Prottas et al., 2016;Wickersham & McElhany, 2010).In fact, the insufficiency of school's direction associated with course design and delivery was proved the big obstruction which hampered the teachers' engagement with online teaching (Lim & Khine, 2006;Teo, 2019).Therefore, it is necessary to ensure supports from the school, which in turn builds up teachers' confidence in switching from traditional face-to-face teaching method to the online one and fostering technology integration in teaching and learning.

The effect of Demographics on Factors in the Model
In this study, relationships between teachers' demographic variables and TAM factors including external assistance, perceived ease of use, perceived usefulness and attitude was also examined.Firstly, an independent-samples T test was performed to examine the effects of gender, age, and educational level on those main factors.It was detected that gender and educational level was not correlated to any factor while only age had a statistically significant effect on external assistance.Specifically, AS mean score for those aged at (22-39) years old (M = 3.804, SD = 0.983) was significant higher than that for those whose age of (40-60) years old (M = 3.480, SD = 0.992), p-value = 0.021.These results suggest that younger perceived higher technical, administrative, and pedagogical support from schools than their seniors did.A one-way ANOVA was then conducted to determine if there was a difference in the effect among four levels of the teaching experience on external assistance, perceived ease of use, perceived usefulness and attitude.The result revealed that teaching experience had a significant influence on only the attitude at p-value = 0.005.A Scheffe post hoc test showed that those who had taught for less than 10 years were more favorable attitude towards online instruction, compared to those who had more years of teaching, groups of (10-15) and (15-20) years.There was no statistically significant difference between the teachers who had more than 20 years of teaching and their juniors.The findings from the two tests were consistent, it indicated that young teachers might receive the school's assistance more effectively, which helps them find it easy and useful to apply online teaching method, in turn having positive attitudes.

CONCLUSION
By applying the modified TAM, the study scrutinized the factors affecting high school teachers' attitude toward online teaching.It was specified that the perceived usefulness of digital teaching was the most fundamental antecedent of teachers' attitude while the perceived ease of use indirect affected attitude toward using technology through the mediator variable of perceived usefulness.Rather than concern about how easy it is to perform lectures via online platforms, teachers more focus on the usefulness of the online teaching method.Therefore, to harness the positive effect of attitude on online teaching, a favorable perception of the usefulness of digital education should be considered a focal point.Once teachers perceive that online teaching is a worthwhile method, they will have a high tendency to adopt it.As an external factor, school's assistance is strongly linked to both perceived usefulness and perceived ease of use, which provides facilitating conditions to ensure successful adoption of online teaching amongst teachers.Hence, it is important to provide teachers with sufficient support in terms of technical, administrative, and pedagogical issues.Besides, age and teaching experience also had a significant influence on external assistance and teachers' attitude, respectively.Younger teachers might find it easier to adapt the transition to an online environment than their aged counterparts, which induces their higher willingness toward online teaching.
This study serves not only the theoretical contribution but also practical innovation.Methodologically, few studies, if any, have focused on understanding the attitude among high school teachers enrolled in web-based teaching by using modified TAM.In addition, the employment of SEM is considered a progressive which helps to better predict the relationship among proposed factors.In terms of practical implication, this study is expected to assist educators in identifying the drivers that motivate teachers' attitude toward online teaching.By understanding the demand of teachers, the appropriate supports will be provided to enhance the capacities of teachers in the basics of adopting online teaching, orientating towards a blended or hybrid teaching and learning approach in the future.Particularly, in the context of Vietnam, the Ministry of Education and Training has recently released a Circular, which focuses on the management and organization of online teaching in general education institutions.It thereby sheds light on promoting digital transformation in the Vietnamese education sector aimed at ensuring the teaching quality and completing the general education curricula.It also turns to provide insights for policy-makers to develop more useful and innovative teaching strategies, which ensure the success in the online education paradigm, which is applicable not only in Vietnam but other countries as well.

APPeNDIX
Hong Thi Thu Nguyen is a lecturer at The University of Danang, University of Science and Education, Vietnam.Her research interest is in information technology adoption and environmental education and management.She currently focuses on the user' behaviour, intention, willingness, and preference toward e-learning systems, which is considered crucial foundation for the achievement of effective digital transformation success in education.

AS1
Assistance is available when I face difficulties in using online teaching platforms (Fathema et al., 2015;Keong et al., 2014;Prottas et al., 2016;Timothy Teo, 2019) AS2 Guidance on the online teaching method and delivery is available AS3 Specialized instruction on how to teach online is available Perceived Ease of Use (PEU) PEU1 I find it easy to apply technology in online teaching (Baber, 2021;Davis, 1989;Fathema et al., 2015;Keong et al., 2014;Timothy Teo, 2012;Wang et al., 2021;Yuen & Ma, 2008) PEU2 I fínd it easỵ to use online teaching platform to perform my lectures PEU3 I find it easy to understand the structure and functions of the whole online teaching platform.

Figure
Figure 2. Conceptual framework

Figure 3 .
Figure 3.The estimated structural model Note: The bold and dash lines illustrate the significant and insignificant path coefficients, respectively.** p < 0.01, *** p < 0.001