The Influence of the Information System Success Model and Theory of Planned Behavior on the Zoom Application Used by Elementary Education Teachers

Abstract

The study uses the Theory of Planned Behavior and the Influence of Information System Success to understand how users respond to the technology used for teaching and learning. The study intends to look at the relationship between the Information System Success model and Theory of Planned Behavior variables on utilizing the Zoom application by elementary education teachers, as well as how teachers’ satisfaction and intention to use technology affect the usage of technology. The primary approach for gathering data involved distributing the Influence of Information System Success model and Theory of Planned Behavior theories questionnaire survey to teachers in elementary education. A total of 219 elementary school teachers in Saudi Arabia who prepared for their online classes participated in the survey for this research. According to the study’s findings, behavioral intentions for using Zoom for educational purposes and user satisfaction have a strong positive association. Additionally, there is a strong association between other variables and users’ intention to use and satisfaction with the product (i.e., perceived technology fit, educational system quality, information quality, attitude towards using Zoom in elementary education, perceived behavioral control, and subjective norm). The findings also show that data points are favorably connected with the teachers’ satisfaction and intention for using the Zoom factors of the Information System Success model and Theory of Planned Behavior theories, despite the fact that there is no connection between both the attitudes towards utilizing Zoom and the behavioral intention to use Zoom for teaching elementary education students.

1. Introduction

The global coronavirus (COVID-19) outbreak is wreaking havoc across all industries, but especially in the fields of health and education. The virus has been a worldwide epidemic since March 2020, according to the World Health Organization [1]. The daily reports show how the COVID-19 burden is increasing, depressing millions of lives, and having an impact on the global economy [2,3]. The use of online learning as a tool could make teaching and learning more sophisticated, student-centered, and adaptable [4,5]. It is also regarded as a highly valued tool for learning because of its adaptability, cost effectiveness, and capacity to provide excellent education [6]. Moreover, important advantages of online learning are self-learning, affordability, simplicity, and adaptability. Nevertheless, it prevents them from participating in actual class activities, and they do not benefit from peer learning [7]. These interactions also affect the characteristics of the kids and hinder them from taking turns. Additionally, because it makes use of internet platforms, online learning has assimilated into the modern world [1,7].

Surprisingly, the COVID-19 epidemic resulted in the closure of elementary education teachers’ (EETs). These EETs are under a heavy responsibility to manage the extraordinary shift from conventional to online learning as a result of this closure [6]. Currently, the rapid development of online learning has prompted numerous EETs to actively target international students and encourage them to pursue online education through Zoom in order to save money [2,7]. The expansion of online education is also accelerating in Saudi EETs [1,8]. Saudi Arabia is extending its educational aims and aggressively influencing global educational developments in order to address the difficulties facing upcoming generations [9,10]. It has recognized numerous online EETs, including those studying at elementary education schools. Due to this closure, these EETs are under enormous pressure to manage the radical move from traditional to online learning [6,9].

The COVID-19 pandemic has impacted many sectors of human life in this state, including education. The only factor that can guarantee the continuation of education on a worldwide scale is the use of technology [11,12]. As a result, there has been a noticeable trend towards online courses in numerous nations around the world. To combat the spread of COVID-19, the Saudi government has begun establishing stringent laws. It ordered the elementary education schools facilities to shut in March 2020 after the first COVID-19 confirmed case was found in the nation [13]. The Saudi Arabian Ministry of Education (MOE) ordered to conduct online classes using social media technology to guarantee a safe and secure learning environment (Zoom, Google Meet, Google Classroom, etc.) [8,14]. As a consequence, all EETs that provide STEM courses now only provide their courses online [15]. In order to engage their students via online education, EETs have begun using online technologies such as Zoom and Microsoft’s Teams program, in line with the MOE’s mandate [16]. Yet, the quick switch from conventional to online learning made it necessary to share the students’ opinions on the latter in order to enhance and sustain the level of education [1]. Due to this, only a small number of studies [11,17,18,19,20] have looked at how Saudi Arabian students view web-based learning encounters. Significantly, Reference [17] highlighted the perceptions, attitudes, and readiness of Saudi dental school students for online dental education. It made use of the survey to evaluate the availability of technology, computer proficiency, perceived ease of use, usefulness, social standards, technical and institutional support, and general level of preparedness. Reference [1] evaluated how the COVID-19 lockout affected the perspective of distance learning instruction by health sciences students at two Saudi EETs.

According to [11], a test case was conducted at elementary education schools during the COVID-19 pandemic to evaluate how female students felt about online learning. A survey gauging the students’ opinions on online learning and their difficulties, benefits, and drawbacks during online learning was given to those bachelor’s degree English language students. Similarly, Reference [18] oversaw a case study that investigated how students at elementary education schools participating in COVID-19 perceived their education using Blackboard. The female students in a program in undergraduate English were given the Blackboard readiness survey. In order to understand the learning experiences of the students and offer relevant solutions, it demonstrated the opportunities and benefits of online learning.

Finally, Reference [20] conducted a qualitative investigation with fifteen undergraduate students from a Saudi public institution using a structured interview. It revealed the opinions of the students on online learning during COVID-19 [21]. The interview covered both the benefits and drawbacks of online learning, such as its accessibility to electronic databases, adaptability, and quality of the online classroom interface [22]. It also discussed the lecturer’s postponed feedback, the lack of technical support, the feeling of isolation, as well as the poor quality of its course content. Since then, Saudi Arabia’s elementary education schools system has faced numerous challenges [23]. The teachers were forced to use a different way to instruct kids at home as a result. The Zoom app represented their best viable choice. The government also made a lot of efforts to integrate e-learning and effectively inspire teachers and students. Online academic activities can now be continued thanks to Research Network tools [7,24]. To conduct online lessons, nearly all Saudi Arabian EETs prefer Zoom over other well-liked virtual conference systems such as Cisco Webex, Google Meet, and Microsoft Teams. Hence, among Saudi Arabia’s elementary education teachers and governmental EETs, Zoom has become a popular teaching tool for offering online lessons [6,25,26]. While reviewing the literature, it became clear from those studies how STEM students, including those in the health sciences and English language programmers, felt about online learning. Yet, their technology was unable to determine the students’ engagement and participation. A number of these studies claim that online learners experience challenges such as missing out on in-person interactions with teachers and peers [11,18]. According to Sun and Chen [27], in order to create interaction and collaboration and a vibrant online learning community, both educators and students need to be actively involved. Students’ engagement and participation in online programs such as Zoom, Collaborate, and Microsoft Teams can promote active learning [1].

Furthermore, Reference [28] advocated disclosing how technology use affects students’ academic achievements. Yet, no research has identified how students believe that social media platforms have helped them fulfill their course objectives. It was also discovered how other elementary education teachers’ teaching approaches and strategies influenced student-learning outcomes, including those studying at elementary education schools. As a result, it is necessary to create a survey and demonstrate the suitability of its variables for evaluating social media tools (Zoom), particularly among students at elementary education schools. To create a conducive environment for teaching and learning, it is crucial to ascertain the reasons why students are hesitant to participate in Zoom sessions on EETs. Hence, it is crucial to understand users’ satisfaction, behavioral intents to use Zoom at elementary education schools, and acceptance of using Zoom for online classrooms. Additionally, studies on the factors influencing users’ satisfaction, behavioral intentions to use Zoom in Saudi Arabia, and adoption of using Zoom at elementary education schools are difficult to discover in the literature, particularly in the Saudi Arabian setting. In order to better understand the elements that influence user happiness, the behavioral intents of using Zoom at elementary education schools, and the uptake of Zoom at elementary education schools, this study will look into such issues.

The objective of the current study’s empirical research is to ascertain how a broad variety of dependent and independent variables interact to affect user satisfaction, behavior intention for using Zoom in elementary education schools, and adoption of Zoom at elementary education schools. Structural equation modelling (SEM) was indeed the statistical method used in the data analysis for a number of reasons. Therefore, this study investigates the factors that influence the adoption of Zoom for online classes among HEIs of Saudi Arabia.

The Zoom Application Use at Elementary Education Schools

Using virtual conferencing tools such as Google Classroom, Zoom, Class Dojo, and others, many educators deliver classes online [29]. Zoom has integrated itself into the daily lives of kids and educators during the pandemic. For instance, they spend a lot of time looking at screens on electronic devices. Zoom facilitates real-time communication between teachers and pupils, transmits visual content via screencast and webcam, and supports many concurrent conversations. References [30,31] explain how great a collaboration tool Zoom is for making it possible for teachers to engage with pupils. Zoom makes it easier for teachers to present their subject to pupils using a shared screen, enhancing classroom interaction. To assist teachers in virtually duplicating much of what occurs in the classroom, Zoom provides a variety of digital tools [15,32]. Online classes can be recorded by both teachers and students for later viewing. In order to separate the students into groups of any size, teachers can create a variety of virtual rooms.

Getting students to participate in group discussions, projects, and other academic activities while enabling them to work independently is a successful strategy. Reference [33] claims that Zoom has several restrictions and difficulties. Zoom may be challenging to use at first, just like other programs. Students using Zoom might also encounter a shaky Internet connection, a subpar microphone or speaker, and a noisy setting. Due to network issues that hinder learning, Zoom lectures are less successful for schools’ students in Jakarta and Depok, according to [12]. Moreover, Zoom is criticized for privacy and security; security professionals caution that the default settings are not adequately secure [34]. If it is unsafe to teach classes in person or if doing so is impracticable, Reference [35] suggests using Zoom.

The COVID-19 pandemic has caused unprecedented disruptions to the education sector globally, including in Saudi Arabia. With the closure of schools and the need for remote learning solutions, Zoom has emerged as a popular platform for virtual communication and instruction [23,31]. In response to the pandemic, the Ministry of Education in Saudi Arabia took swift action to enable remote learning in elementary schools. Zoom, with its user-friendly interface and versatile features, was quickly adopted as a virtual platform for communication and instruction [36]. Elementary school teachers started using Zoom to deliver live lessons, interact with students, conduct virtual classrooms, and facilitate educational activities [37].

The adoption of Zoom in Saudi elementary education brought several benefits. Firstly, it provided a means for teachers to maintain regular communication with students and deliver live instruction, ensuring educational continuity during the pandemic [11,15]. Zoom’s interactive features, such as screen sharing, chat, and breakout rooms, facilitated engaging and interactive lessons. Teachers could share educational resources, conduct discussions, and provide immediate feedback to students [19]. The use of Zoom allowed for real-time interaction between teachers and students, fostering a sense of connection and engagement in the virtual classroom [18,20]. Considerations for the future include addressing the digital divide by ensuring universal access to technology and reliable internet connectivity for all students. Ongoing professional development and support for teachers will be essential in maximizing the potential of Zoom and other virtual platforms. Continual evaluation and research are needed to assess the effectiveness of Zoom in promoting student engagement, learning outcomes, and overall educational quality in Saudi elementary schools.

2. Theoretical Model and Hypotheses Development

An individual’s behavior intentions are a feature of three determinants, including “an individual’s attitude towards behavior, subjective norms, and perceived behavioral control”, according to the TPB, which was proposed by Icek Ajzen in 1985 as a theory for the interpretation of general human behavior [38]. An individual’s negative or positive feelings when engaging in behavior are defined by their attitude [39]. Any person’s preferences determine whether they have a negative or positive intention, often known as an attitude [38]. The intention of students towards e-learning systems is defined by attitude, which was previously explored as a prominent construct of TPB [40,41,42]. For instance, Reference [43] examined the impact of a good attitude on students’ intentions regarding e-learning. Thus, technologically based e-learning has a significant impact on students’ intentions to engage in their coursework directly [44]; however, there is not much research that looks at students’ attitudes regarding e-learning through augmented reality apps.

Moreover, Reference [45] developed an ISSM for gauging the effectiveness of IS in enterprises in order to generate net benefits. They maintained that the success of IS is underpinned by a multidimensional, symbiotic paradigm. Thus, it is crucial to comprehend and control the relationships between those dimensions. Then, many academics suggested modifications to this strategy [46,47]. Hence, Reference [48] upgraded their outdated model with ISSM, as depicted in Figure 1, by adopting some of the adjustments suggested by academics. They decided to raise the standards for client satisfaction and service excellence. The new model ascribed three crucial success factors—information quality, system use, and user satisfaction—to Zoom’s popularity at elementary education schools. Additionally, our study will make use of TPB [49] and the ISSM developed by [45] (see Figure 1).

2.1. Perceived Technology Fit

Perceived technology fit is a measurement of how people behave when using information systems to perform particular tasks. Perceived technical fit, behavioral intention for using, and actual social network utilized are all positively associated, according to scientific research [50]. Experimentally, it is anticipated that the connection between perceived fitting and behavioral intention to use will influence the intention for ongoing real social media use. With respect to adopting a behavioral intention for using Zoom and real Zoom use to meet the needs of obtaining, producing, or sharing knowledge, the idea was incorporated in our study to assess overall perceived value of academic accomplishment and satisfaction [51,52]. The behavioral urge to either directly or indirectly utilize a system [51,52] is referred to as user adoption [45]. The Zoom tool is used by students to conduct experiments that forecast a connection between perceived technology fit, user delight, and behavioral intentions to use Zoom. Users’ happiness and adoption of Zoom at elementary education schools are the factors employed in this study to assess users’ intentions to use Zoom for obtaining, creating, or sharing knowledge.

H1. 

PTF has a significant impact on US.

H2. 

PTF has a significant impact on BIUZ.

2.2. Educational System Quality

According to research [53] on creating a model for assessing the efficiency of e-learning at education schools, the high standard of the educational system both positively and negatively effects user satisfaction and directly the use of the system. This result implies that educational aspects in the e-learning system, such as chat rooms, discussion forums, and collaborative educational tools, might boost users’ usage and satisfaction with the system. Computer-supported collaborative learning (CSCL) has identified social interaction as a critical component of success and found that it significantly impacts student learning [54]. The study conducted by [55] for internet e-learning systems and by [56] for mobile educational environments indicated a substantial association between educational quality and perceived utility. A correlation between student satisfaction and the quality of the educational system has been observed by [57,58]. Moreover, Reference [59] discovered significance in the associations between assessment materials’ diversity and learner interaction in the e-learning system in terms of felt satisfaction. Furthermore, for an internet e-learning system, Reference [55] showed a substantial association between educational features and usefulness. The same outcomes were reported by [60], who discovered a substantial link between the construct of an interactive learning environment and both perceived usefulness and satisfaction.

H3. 

ESQ has a significant impact on US.

H4. 

ESQ has a significant impact on BIUZ.

2.3. Information Quality

Information quality is an essential and important aspect in assessing the performance of data and e-learning systems due to the key role that data play in achieving learning goals and the serious issues that arise from poor information integrity [61]. The association between INQ and utilization in addition to user satisfaction was examined using the [48] model. The information systems literature was used to demonstrate the close connection between quality of information and usage [62]. Studies by Reference [63] for knowledge management systems and [64] for information systems for health care arrived at the same conclusion. According to [65,66], in the same context, they discovered a substantial association between perceived utility, user satisfaction, and information quality. E-learning scholars have empirically examined the connections between quality of information and each of the three notions of usage, satisfaction, and usefulness. By way of illustration, Reference [67] discovered a significant correlation between the utility and satisfaction of online courses and the caliber of the content. In a study on online education in an organizational setting [14], it was shown that there is a substantial correlation between material quality and its perceived utility. A similar conclusion was reached with web-based LMSs [68,69].

H5. 

IQ has a significant impact on US.

H6. 

IQ has a significant impact on BIUZ.

2.4. Attitude to towards Using Zoom at Elementary Education Schools

According to Davis [70], “attitude” is a subjective sensation that an individual has when engaging in a particular conduct and is influenced by their opinions and beliefs. A significant association between attitude and personal behavior has been found in numerous studies in the past [33,71]. Several studies that looked at the relationship between attitudes and individual intentions to use websites in the context of SNS sites found a favorable relationship. When a user’s mood is positive, they are more likely to use Facebook, according to Chen’s [72] analysis of the variables that affected Facebook usage. Moreover, Chiang [73] showed that users’ continued intention to use SNS is significantly influenced by their mindset. In a similar vein, References [74,75] showed that attitude is among the most powerful determinants of continued intention to utilize social media platforms. According to Tariq et al. [76], Facebook usage among students rises when they have a favorable attitude towards it. According to Salahshour Rad et al. [77], the researcher’s attitude towards academic social networking sites (ASNSs) determines whether or not those sites are used. According to Terzi et al. [78], students majoring in midwifery and childcare have positive attitudes on using social media.

H7. 

ATUZ has a significant impact on US.

H8 

ATUZ has a significant impact on BIUZ.

2.5. Perceived Behavioral Control (PBC)

“Perceived behavioral control” [49] refers to a person’s perception of a task, which is categorized as easy or difficult depending on the resources available. Perceived behavioral control, which is often used across a range of domains, is one of the crucial aspects that can determine the decision to keep going [20]. It is currently used by researchers to forecast SNS usage [79]. Perceived behavioral control reportedly has a substantial role in influencing users’ inclination to use SNS frequently, according to [80]. PBC may have a direct impact on the intention to use technology, according to a number of studies conducted in various circumstances, including [81,82,83]. According to the research of [84], PBC has a beneficial impact on students’ intentions to utilize SNAs for academic-related activities. Using their smartphones as an example, students think that adopting SNAs in the classroom is simple, which favorably affects both their intention to use and their actual use [85]. Perceived behavioral control is positively correlated with a person’s propensity to utilize SNS sites, according to Gironda and Korgaonkar [86]. In the case of Pakistan, Tariq et al. [76] similarly supported the same finding, namely that perceived behavioral control significantly predicts users’ propensity to utilize social networking sites (SNS).

H9. 

PBC has a significant impact on BIUZ.

2.6. Subjective Norm (SN)

According to Ajzen [49], the perceived social pressure to engage in a particular activity is referred to as a “subjective norm”. It illustrates how opinions from loved ones and friends influence how people behave. According to [87], a person is more likely to engage in a particular behavior to gain acceptance from those in his or her influential group. The subjective norm in the context of SNS states that if a prominent person endorses SNS usage, a person will accept that person’s viewpoint and follow it [88]. Few researchers have looked at how subjective norms affect continued SNS use intentions [22,89]. For instance, Reference [87] examined the adoption of social media in Saudi Arabia and found that a subjective norm significantly influences a person’s propensity to use it. Similar findings have been observed by Choi and Chung [81], who claim that a subjective norm influences an individual’s inclination to use social networking sites. The continued use of social media in Malaysia using data from 133 online social network users was examined by Reference [90]. They claimed that social influence had an impact on how long people used social media. According to Mouakket’s [91] investigation into UAE students’ continued use of Facebook, subjective expectations are a significant factor influencing the students’ intention to do so. In their study on Zoom use among Omani students, Sharma et al. [92] found that social influence is a predictor of students’ Facebook usage. In their analysis of the variables influencing students’ intentions to use social networking sites, Doleck et al. [83] identified the subjective norm as a key contributor. Subjective norm, according to Kim et al. [93], has a favorable impact on social networking site addiction and usage.

H10. 

SN has a significant impact on BIUZ.

2.7. Users’ Satisfaction (US)

User attitude about the intention of employing technology is highly correlated with user pleasure. Users’ satisfaction, according to Dunbar et al. [94], is the effect that a technology application has on users’ attitudes while they are using the technology. Moreover, Dalvi-Esfahani et al. [66] described user satisfaction as the kind of emotion or enjoyment that arises from utilizing technology as a result of its advantages. References [95,96] offer a definition that is similar, defining user satisfaction as a subjective assessment that can be pleasant or unpleasant and arguing that the evaluation is brought about by the use of certain technology. The relationships between satisfaction, organizational goals, and social repercussions are close. The level of user happiness can be used to gauge how well internet platforms are working [24,36]. As a result, a number of factors may have an influence on how satisfied students are. Studies on student satisfaction with e-learning results [21] and prior reviews of the theory behind what drives student interaction, effective support, learning materials, and the learning environment [97] corroborate this viewpoint. According to [98], there are six factors that affect how enjoyable e-learning is regarded. Similar to this, it was asserted [60] that reported enjoyment may be influenced by feeling of self, felt concern, and active learning environments. Customer satisfaction with just an e-learning platform has been found to significantly influence users’ intentions to use the platform, which in turn significantly influences the system’s quality, the data it contains, as well as the service it offers [60].

H11. 

US has a significant impact on BIUZ.

H12. 

US has a significant impact on AZHE.

2.8. Behavioral Intention to Use Zoom at Elementary Education Schools

The behavioral intention to use is understood as a person’s intention, regardless of any confounding factors, to begin using or to continue using technology [99]. As a result, in this study, both students’ actual usage of social media to better their education and their behavioral desire to use it are factors that affect their learning success. Moreover, studies based just on TAM hypothesis showed that increased behavioral intention led to an increase in real social media usage [100,101]. Many of these concepts grew out of the Theory of Reasoned Action (TRA), which maintains that how one uses social media depends on how they feel about particular standards. The Theory of Planned Behavior (TPB) was later created as a result of this expansion to include seeming control [101]. Regular users’ perceptions suggest that PU and PEOU could additionally be ignored, which would enhance user satisfaction and continue their intended purpose [102]. According to research, people who love using social media will carefully analyze their connection with it and adopt better social media usage behaviors [103]. Research by [102] found a correlation between behavioral intention and students’ plans to use social media platforms frequently as well as in the future. According to the authors of [104], the way social networking sites are utilized for learning directly depends on behavioral purpose. The aim of users to use social networks and other system applications serves as the primary justification for models and theories on how people use technology [104,105].

H13. 

BIUZ has a significant impact on AZHE.

2.9. Adoption ZOOM at Elementary Education Schools

Elementary education schools were the first institutions in Saudi Arabia to use the internet in the 1990s. All of the nation’s campuses eventually adopted the technology [7,23]. In wealthy nations such as the United States, elementary education schools that provide degree programs frequently use information and communication technology (ICT). Both students and academics gain from the usage of ICT to promote learning [106]. Using online meetings, such as the Google Meetings tool, allows for simultaneous and asynchronous interaction between students and teachers, which aids with time management. Yet, when working with students who are unused to using online meeting technology, instructors’ views towards their charges can be a barrier to Zoom Meet adoption [107]. Instead of relying on innovative approaches that have been shown to be more effective than traditional ones, educators do not think that online meetings are useful teaching tools. An instructor may dismiss a student or decline to help them rather than encouraging them to use Zoom to advance their knowledge [108]. Most pupils, according to the author, struggle with this issue. Additionally, some professors lack the necessary technical skills, which is annoying to the students [107]. On the other hand, individuals from other cities and regions can join with ease in a virtual setting, allowing the creation of distinctive and incredibly diversified classrooms inside a single country, or even in terms of multiple countries. Since all educational departments in Saudi Arabia have been shut down, there has been a dramatic shift away from the old, or “traditional,” learning technique to a new, government-endorsed method of online learning [108].

3. Research Methodology

The primary goal of the study was to create a clear and understandable theoretical framework for analyzing aspects that influence users’ satisfaction with and intention to use Zoom at elementary education schools. The suggested model and survey were built, validated, and tested using a multistage testing technique. All the obtained data were assessed applying a 5-point Likert scale, including elements of Information System Success model and Theory of Planned Behavior variables and demographic. The questionnaire was divided into two main components. Demographic data were requested from the respondents in the first part. The second segment, which contained 46 items, was devoted to measuring the research model’s components. According to Hair et al. [109], two experts who were selected based on their competence in the adoption of educational technology and their research interests analyzed the survey. They were requested to evaluate the survey’s readability, clarity, relevance, and validity. Minor changes that were suggested by the evaluation results were fully taken into account. The questionnaire was made available to the responders anonymously, and they were guaranteed that their answers would be kept private. Participants tested 46 previously employed questions to gauge Zoom adoption at elementary education schools in Saudi Arabia, and nine components were taken into consideration while evaluating Zoom acceptance at elementary education schools in Saudi Arabia. All respondents were asked to complete the questionnaire in writing after it had been physically distributed in order to receive input on how well Zoom was being used for teaching and learning as well as their perceptions of how it affected students’ academic achievement.

In this study, 233 students from elementary education schools in Saudi Arabia participated in a physical survey. This created the circumstances for a generalizable study across numerous ethnicities and cultures. By way of participation, 219 were returned (93.9% return rate). Fourteen of these questions were obviously inadequate and had to be ignored after a human review of them. After entering the other 219 questionnaires into SPSS, it was found that 14 of them contained some unfinished responses. Participants in this study received 219 questionnaire responses from elementary education schools in Saudi Arabia during the first semester of 2022–2023, which lasted from November 2022 to February 2023. The SPSS application was used to analyze the permitted responses. Data processing and coding were required. The SPSS application was used to encode the information for this investigation. Adding character symbols to data—most often numerical symbols—is known as data coding. The data were altered to assure their acceptability before being entered into SPSS and Amos-SEM. Amos version 23 and SPSS Statistics version 26 were used to collect the data, and the results were evaluated using structural equation modelling (SEM).

Measurement Instruments and Data Colloection

A survey questionnaire was created utilizing metrics from past literary works to evaluate the proposed paradigm. Each evaluation item was scored using a Likert-type rating method with five potential results ranging from one (strongly disagree) to five (strongly agree). Five questions from [110] were modified and used to assess the perceived technological fit. In a similar vein, the scales for educational system quality and information quality were derived from studies in [111], while the items pertaining to the Theory of Planned Behavior (attitude towards using Zoom at elementary education schools, perceived behavioral control, and subjective norm) were adapted from [112,113,114,115]. Moreover, five items that were used to gauge user satisfaction were modified from [111]. The Behavioral Intention to Use Zoom at elementary education schools (BIUZ) Scale consists of six questions that were modified from [13,115]. Last but not least, five questions from [101,116] were modified and utilized to assess the acceptance of Zoom at elementary education schools (See

Table 1. CR, FL, reliability analysis.

Cod	Item	FL	CR	AVE	Cod	Item	FL	CR	AVE
Perceived technology fit	PTF_1	0.850	0.927	0.718	Subjective norm (SN)	SN_1	0.846	0.917	0.689
	PTF_2	0.802				SN_2	0.880
	PTF_3	0.866				SN_3	0.870
	PTF_4	0.887				SN_4	0.790
	PTF_5	0.828				SN_5	0.756
Educational system quality	ESQ_1	0.772	0.909	0.668	Users’ satisfaction	US_1	0.811	0.898	0.639
	ESQ_2	0.847				US_2	0.831
	ESQ_3	0.851				US_3	0.816
	ESQ_4	0.818				US_4	0.812
	ESQ_5	0.796				US_5	0.722
Information quality	IQ_1	0.804	0.892	0.624	Behavioral intention to use Zoom at elementary education schools	BIUZ_1	0.752	0.927	0.680
	IQ_2	0.844				BIUZ_2	0.778
	IQ_3	0.836				BIUZ_3	0.863
	IQ_4	0.716				BIUZ_4	0.843
	IQ_5	0.741				BIUZ_5	0.864
						BIUZ_6	0.840
Attitude to towards using Zoom at elementary education schools	ATUZ_1	0.846	0.934	0.739	Adoption Zoom at elementary education schools	AZHE_1	0.764	0.916	0.686
	ATUZ_2	0.829				AZHE_2	0.840
	ATUZ_3	0.870				AZHE_3	0.829
	ATUZ_4	0.882				AZHE_4	0.868
	ATUZ_5	0.871				AZHE_5	0.838
Perceived behavioral control (PBC)	PBC_1	0.742	0.890	0.618
	PBC_2	0.829
	PBC_3	0.794
	PBC_4	0.818
	PBC_5	0.745

). As a result, 59 (26.9%) of the respondents were female and 160 (73.1%) were male. In this study, there were 23 people (10.5%) between the ages of 18 and 20; 38 (17.4%) between the ages of 21 and 24; 88 (40.2%) between the ages of 25 and 29; 47 (21.5%) between the ages of 30 and 34; and 23 (10.5%) between the ages of 35 and above, and 77.2 percent of participants utilize Zoom five to eight times per day (

Table 2. Demographic profile.

Demographic	Discerption	N	%
Gender	Male	160	73.1
	Female	59	26.9
Age	18–20	23	10.5
	21–24	38	17.4
	25–29	88	40.2
	30–34	47	21.5
	35 and above	23	10.5
Frequency of Zoom usage	Once a day	5	2.3
	2–4 times a day	27	12.3
	5–8 times a day	169	77.2
	More than 8 times a day	18	8.2

).

4. Result and Data Analysis

4.1. Measurement Model Analysis

SEM and AMOS 23 were both essential statistical techniques employed in this study to analyze the results using (CFA). With regard to unidimensionality, validity, and consistency, this model evaluated convergence [117]. Moreover, the Cronbach’s alpha values ranged from 0.877 to 0.930, all of which were close to 0.70, and the CR values ranged from 0.890 to 0.934. All of the AVE values, which varied from 0.618 to 0.739, exceeded the predicted value of 0.50. (See Table 1). Figure 2 displays the ISSM model and the TPB Theory’s framework. Additionally, as shown in Table 1, concepts, items, and probability analysis provide latent constructs of 0.5 or greater, which are suitable for the dependent variables and evaluation of the mediator shown in Figure 3 [109,118].

The model’s conformity to all standards is attested to by recognized appropriateness indexes including CR, CA, and AVE. According to [109,119], “goodness-of-fit” methods including Tucker–Lewis coefficient should also be used to evaluate the score model (TLI), chi-square, incremental-fit index (IFI), normal chi-square, and relative-fit index (RFI). When the normed fit value (CFI) is at least 0.90, the model fits the data well. As indicated in Table 1, the root mean square prediction errors (RMSEA) that support the required suit are less than or equal to 0.08 to meet the specified criteria as stated by [109]. RMR, or root mean quarter residue, is recognized. The evaluation of independent, mediator, and dependent variables is shown in Figure 3, and

Table 3. Goodness of fit indices.

Type of Measure	Acceptable Level of Fit	Values
(RMR)	Near to 0 (perfect fit)	0.056
(IFI)	>0.90	0.909
(TLI)	>0.90	0.907
(CFI)	>0.90	0.908
(RMSEA)	<0.05 indicates a good fit	0.058

lists the goodness-of-fit indices that were used to rank the models.

In the current sample, just 1 of the 13 assumptions between the 12 major notions was rejected, indicating that students have not yet demonstrated their understanding. Students’ behavioral intention to utilize Zoom at elementary education schools is influenced by their attitude towards adopting Zoom at elementary education schools (0.01-H8). Students believe that using Zoom at elementary education schools is a good fit for technology and that it will increase user satisfaction (0.267-H1) and 0.01-H2). Students have intrinsic desire and perceived competency in MOOCs (0. 424-H2), educational system quality that meets users’ needs (0.261-H3), and behavioral intention to utilize Zoom at elementary education schools (0.224-H4). Additionally, learners have high-quality information, are satisfied with the service (0.82-H5), and plan to utilize Zoom at elementary education schools (0.139-H6). Zoom is used more frequently by students at elementary education schools, which increases user happiness (0.211-H7). Students’ Reported Behavioral Control Leads to Behavioral Intent to Use Zoom in elementary education schools (0.141-H9), Students’ Subjective Norm to Behavioral Intent to Utilize Zoom at elementary education schools (0.189-H10). The majority of the respondents concur that their behavioral purpose to adopt Zoom at elementary education schools boosted that utilization. In a similar vein, student (male and female) users’ facilitation increased their behavioral intention to use Zoom at elementary education schools (0.157-H11) and adaptation to using Zoom in elementary education schools (0.340-H12) (0.379-H13). Figure 3 and

Table 4. Hypothesis testing results.

Label	Factors	Relationship	Factors	Estimates	S.E.	C.R	p-Value
H1	PTF		US	0.267	0.071	3.788	0.000
H2	PTF		BIUZ	0.424	0.062	6.795	0.000
H3	ESQ		US	0.261	0.061	4.306	0.000
H4	ESQ		BIUZ	0.224	0.054	4.151	0.000
H5	IQ		US	0.182	0.069	2.638	0.008
H6	IQ		BIUZ	0.139	0.060	2.315	0.021
H7	ATUZ		US	0.211	0.056	3.758	0.000
H8	ATUZ		BIUZ	0.015	0.050	0.305	0.760
H9	PBC		BIUZ	0.141	0.051	2.739	0.006
H10	SN		BIUZ	0.189	0.053	3.531	0.000
H11	US		BIUZ	0.157	0.060	2.624	0.009
H12	US		AZHE	0.340	0.067	5.071	0.000
H13	BIUZ		AZHE	0.379	0.067	5.646	0.000

present the results of the measurement model.

4.2. Reliability and Validity Analysis

The linked factors had an effect on users’ enjoyment of Zoom as well as their behavioral intention to use Zoom at elementary education schools, even when Zoom itself was taken into consideration. Every variable passed the Cronbach alpha coefficient standards, resulting in a range of 0.888 to 0.934. In the reliability analysis section, the Cronbach’s reliability index, which for this study is 0.975, is discussed (

Table 5. Overall validity and reliability.

	ATUZ	PBC	SN	PTF	ESQ	IQ	US	BIUZ	AZHE	Cronbach Alpha
ATUZ	0.780									0.934
PBC	0.500	0.783								0.888
SN	0.576	0.402	0.691							0.915
PTF	0.514	0.444	0.497	0.704						0.926
ESQ	0.488	0.368	0.552	0.502	0.627					0.909
IQ	0.531	0.395	0.502	0.436	0.442	0.685				0.891
US	0.568	0.506	0.559	0.507	0.533	0.469	0.716			0.897
BIUZ	0.514	0.363	0.595	0.575	0.589	0.484	0.554	0.615		0.927
AZHE	0.522	0.437	0.547	0.501	0.507	0.484	0.488	0.498	0.687	0.915

). The variables’ index needs to be less than 0.80 [109], the AVE rate should be more than 0.5 [118], and the AVE square should be greater than the inter-construct correlation (IC) factor [118]. Additionally, the study evaluated the degree of construct validity across the board using these three standards. Confirmatory loadings met or were above the 0.7 threshold as well. Acceptance was based on Cronbach’s alpha as well as a combined reliability score of 0.70 or higher [109]. All of the study was measured to exhibit Cronbach’s alpha values that were notably higher than the permitted level of 0.70 after realigning the item-to-total connection for all 46 items. The 46 items’ factor loading improved as well, and the component alpha values demonstrated increased reliability. Table 5 makes the item-to-total relationships and the coefficient alpha very evident (Cronbach alpha). These findings show that the study scale and instruments used in this study have high validity and acceptability, allowing for additional data analysis using inferential analysis to evaluate the research hypotheses.

4.3. Hypothesis Testing Results

Table 4 displays the findings of the testing of the hypotheses. Figure 3 displays the structural equation model and the numbers for each path. (theorized connection). With the aid of an analysis conducted using SPSS-AMOS 23, the proposed associations were assessed. H8 was ignored since there was no evidence that attitudes towards the use of Zoom in elementary education schools were positively connected with behavioral intentions to do so (β = 0.015, t = 0.305). As a result, each construction’s hypothesis was stronger than that of the other constructions. H8 was ignored because there was a negative correlation between attitude towards adopting Zoom at elementary education schools and behavior intention for using Zoom in elementary education schools (β = 0.015, t = 0.305). As a result, each construction’s hypothesis was stronger than that of the other constructions. For instance, when compared to its other theory value (e.g., perceived technology fit to users’ satisfaction (US) (β = 0.267, t = 3.788), the theory of perceived technology accommodation on behavioral intention to use Zoom in elementary education schools was found to be significantly and positively related to behavioral intention to use Zoom in elementary education schools (β = 0.424, t = 6.795). Another illustration is the hypothesis users’ satisfaction was demonstrated to be significantly and positively connected to the adoption of Zoom in elementary education schools (β = 0.340, t = 5.071), whereas the relationship between information quality (IQ) and students’ behavioral control to use Zoom elementary education schools (β = 0.139, t = 2.315) shows the lowest hypothesis value.

4.4. Coefficient of Determination (R²)

In Amos path analysis, the significance of R² is determined based on squared correlations. According to reference [109], squared correlations of 0.75, 0.50, and 0.25 are considered as large, moderate, and weak, respectively. R² statistics provide insights into how the independent variable influences the dependent variable(s). In

Table 6. The value of R².

Factors	R Square	Results
Users’ satisfaction (US)	0.572	moderate
Behavioral intention to use Zoom at elementary education schools (BIUZ)	0.613	Large
Adoption of Zoom at elementary education schools (AZHE)	0.682	Large

, the R² value of the latent dependent construct is 0.682, which is higher than 0.50 and close to 0.75, indicating a high level of impact.

5. Discussion and Implications

This study investigated the attitudes of elementary education schools’ students towards the use, acceptance, and adoption of online emergency learning. This study examines the influences on the adoption of the ISSM model and TBI theory in online courses at elementary education schools in Saudi Arabia. Based on the ISSM model and TBI theory, nine constructs were discovered, and thirteen hypotheses were formulated. SEM was used to quantify the effects of all the variables and hypotheses. All thirteen of the model’s postulated hypotheses are confirmed by the empirical investigation. In order to investigate factors influencing the use of Zoom for academic purposes, a useful and integrated ISSM model and TBI theory were used in this study to define the framework students encountered when they used Zoom for education. One study found that using social media tools such as Zoom can help students learn more deeply and understand the significance of a subject by encouraging their understanding of the critical exploration process [120].

In order to evaluate 13 hypotheses and illustrate nine criteria for using Zoom for learning, a novel model was developed for this study. The outcomes are as follows: the new fit is the first consideration. There were two hypotheses in this study (H1 and H2) that had favorable effects on consumers’ happiness with their decision to utilize Zoom in elementary education schools. This is in line with earlier studies, which found a link between consumers’ happiness with their intention to use Zoom at elementary education schools and perceived technological fit [5,121,122].

The quality of the educational system, which is the second variable, had two hypotheses (H3 and H4) that had favorable effects on users’ satisfaction with their behavior and intention to use Zoom at elementary education schools. This is consistent with an earlier study [123,124,125] that showed a favorable correlation between users’ satisfaction with educational quality and behavioral intentions to use Zoom. These results, however, were at odds with those of an earlier study [111]. The next variable is content validity, which had two hypotheses (H5 and H6) that were supported by evidence, both of which had favorable effects on users’ happiness with their decision to utilize Zoom at elementary education schools. This is consistent with earlier studies [24,111,124,126], which found a positive correlation between users’ satisfaction with their behavior and intention to use Zoom and perceived information quality. Additionally, the users’ pleasure was significantly impacted by their attitude towards using Zoom at elementary education schools, which was associated with one assumption (H7).

This is consistent with earlier studies, which showed a positive correlation between task technology fit and perceived usefulness and usability [127,128]. According to Table 5’s findings, there is a bad link between students’ attitudes towards the use of Zoom in elementary education schools (H8) and their actual intent to utilize Zoom. This suggests that a person’s attitude towards adopting Zoom at elementary education schools has no bearing on that person’s underlying behavioral intention to utilize Zoom. The results of this study do not agree with those of studies performed by [33,37], who discovered that students who had a positive attitude regarding utilizing Zoom at elementary education schools were more likely to use it effectively. The TPB asserts that only intention may be the cause of conduct and that subjective norms and perceived behavioral control can be the cause of intention. The study’s findings confirmed the two research hypotheses on the influence of subjective norms and perceived behavioral control on behavior regarding intentions to use Zoom for teaching and learning at elementary education schools (supporting H9 and H10, respectively). These results are consistent with the TPB paradigm as well as earlier studies on the causes of adopting Zoom as a learning tool in education [129].

The findings also verified Hypothesis 2’s claims about how students’ adoption of Zoom in educational settings is influenced by their behavioral desire to use it for learning. These results, however, were at odds with those of an earlier study [89]. Users’ happiness is the mediating variable, and two hypotheses (H11, H12) that it examined had a significant positive influence on users’ behavioral intentions to use Zoom and their acceptance of using Zoom for educational purposes. Similar to other research, which showed a positive correlation between users’ satisfaction with their behavioral intention to use Zoom and uptake of Zoom at education schools [46,87], this study supports that conclusion. The behavioral desire to use Zoom for learning reasons is the final mediating factor, and according to one hypothesis (H13), it had a favorable influence on the adoption of Zoom for academic purposes. This is consistent with an earlier study that found a link between behavioral desire to use Zoom for learning and actual use of Zoom for educational purposes [33,105]. The findings of this study demonstrate that the sudden shift to online learning went off without a hitch and that the existing instructional resources were ready for the transition.

They had no trouble talking with one another or with their coworkers and academic peers. This was made possible by the diversity and accessibility of social media tools such as Google Meet and Zoom, which helped people overcome any obstacles they may have encountered, particularly during COVID-19 in Saudi Arabia [8,33]. According to this study, students who have a favorable opinion of Zoom are more likely to use it for online classes and have strong behavioral intentions to do so. Students’ happiness and behavioral desire to utilize Zoom are dependent on the favorable independent variables related to Zoom.

In addition, the perceived technology fit, educational quality, information quality, attitudes towards the use of Zoom in elementary education schools, perceived behavior control, and subjective norm all play a significant role in the adoption of Zoom through students’ happiness with and desire to use Zoom at elementary education schools. It implies that low attendance in Zoom classrooms is a result of students’ unfavorable attitudes towards Zoom. This unfavorable attitude results from ignorance, unfamiliarity, and incoherency about Zoom, as well as from a lack of intention to use Zoom when using computer or digital devices and applications.

The results suggest that policymakers should implement the necessary changes to improve the following: application of the new fit, educational system reliability, information quality, and attitude towards the use of Zoom at elementary education schools, perceived behavioral control, social norm, students’ satisfaction, and the original intent to use Zoom. Additionally, EETs should train students on Zoom before allowing them to take online courses. This will increase their happiness and behavioral control to utilize Zoom for instructional purposes at elementary education schools. In order to increase consumers’ happiness and intention to utilize Zoom when using computer/digital devices and applications, the curriculum of elementary education schools must also be updated.

6. Conclusions and Future Work

This study looks into the variables affecting elementary education schools in Saudi students’ use of Zoom for online classes. This study develops nine constructs, suggests thirteen hypotheses, and rests its theoretical framework on the ISSM and TPB. Using Amos-23, the measurements and SEM were put to the test. All thirteen of the theoretical framework’s presented hypotheses are found to be validated by the study’s data on students’ usage of Zoom for instructional purposes, with the exception of one. The adoption of Zoom at elementary education schools is thus influenced by independent variables that affect the users’ pleasure and behavioral desire to use Zoom. Every study has a unique set of restrictions.

This study assessed six model constructs that barely account for variations. Future studies may take into account a few additional factors, such as online teaching strategies, the quality of the Internet connection, and reported delight, that influence students’ embrace of technology. Additionally, this essay only focuses on the context of EETs. As a result, the results of this study could not be applied to other domains, such as primary and secondary education. In addition, future studies would take into account a wider range of demographic features. Additionally, the use of Zoom for teaching and learning may vary by gender, academic level, and institution type. Thus, it advises using multi-group analysis (MGA) based on gender, academic levels, and HEI type for future research. By including and confirming the impact of independent variables on users’ happiness and behavioral intention to use Zoom, as well as adoption of Zoom for teaching and learning, this study helps to validate the integrated ISSM and TPB model.