Social Media Technologies Used for Education: An Empirical Study on TAM Model During the COVID-19 Pandemic
Omar A. Alismaiel
Javier Cifuentes-Faura
Waleed Mugahed Al-Rahmi- 1College of Education, King Faisal University, Al-Ahsa, Saudi Arabia
- 2Faculty of Economics and Business, University of Murcia, Murcia, Spain
- 3Faculty of Social Sciences and Humanities, School of Education, Universiti Teknologi Malaysia, Skudai, Malaysia
The study’s major goal was to figure out what factors impact university students’ behavior and intentions to use social media to boost their academic performance during the COVID-19 Pandemic. Given the context-dependent nature of online learning, the Technology Acceptance Model (TAM) was adopted and supplemented with components largely relevant to harnessing social media for collaborative learning and engagement. Collaborative learning, student participation, and a social media mindset are just a few of the new features. The enlarged model was validated using empirical data from an online survey questionnaire filled by a sample of 409 Saudi Arabia higher education students, which assesses students’ social media usage intentions and academic performance during the COVID-19 Pandemic. AMOS-SEM was used to analyze the model’s various assumptions (Analysis of Moment Structures- Structural Equation Modeling). The findings revealed that: (1) utilizing social media for collaborative learning and student engagement has a direct positive impact on perceived usefulness, ease of use, and enjoyment; (2) perceived usefulness, ease of use, and enjoyment has a direct positive impact on attitude to use social media; and (3) the link between TAM characteristics “usefulness, ease of use, and pleasure” and behavior intention to use social media is mediated by attitude to use social media. (4) Students’ attitudes and behavior intentions on social media have a direct positive influence on their academic performance during the COVID-19 Pandemic. Academics, higher education institutions, and educational technology application providers will benefit greatly from the conclusions of this study, both theoretically and practically.
Introduction
Previous research on the use of social media in higher education (Awidi et al., 2019; Manca, 2020) has shown that it may be utilized to increase student collaboration and engagement, as well as augment conventional learning and enhance academic success (Awidi et al., 2019; Manca, 2020). This study, on the other hand, aims to look at the use of social media for maintaining formal academic performance during the COVID-19 Pandemic in public institutions that do not have a strong social media presence and were relied on in-class communication before to COVID-19, particularly after the global pandemic. COVID-19 has had a major negative impact on many facets of education, and has been especially detrimental to those students with the least resources. Institutions with little technological adaptability have also suffered from the changes caused by the pandemic (Faura-Martínez et al., 2021; Talib et al., 2021; Tang et al., 2021). Following their academic success as measured by the TAM model, students’ academic performance during the COVID-19 Pandemic entails using social media as the exclusive and official platform for academic-related purposes such as teaching and learning, student support, community building, and participation. The social media phenomenon has had an impact on Saudi Arabia, as it has on many other countries. According to data, education is one of the top five countries in terms of the number of social media profiles created (Alamri et al., 2020; Ali Qalati et al., 2021). Among research students, social media is frequently seen as enhancing active collaborative learning. In higher education, however, there is a scarcity of study on this subject. As a result, the current study attempted to fill a vacuum in the literature by analyzing how the usage of social media for active collaborative learning and engagement affects research students’ academic performance during the COVID-19 Pandemic. The technology acceptance model and constructivism theory were used to create the research model (TAM). This study examined the interactive and perceptual aspects of social media use using constructivism theory and the technology acceptance paradigm (TAM). Active collaborative learning, according to Shen et al. (2021), is a continuous process in which students communicate and exchange ideas and opinions via social media (Phuthong, 2021). These modes of communication also include social media technologies such as e-mail, intranets, blogs, video conferencing, photograph sharing, wikis, and virtual mobile phone enterprises (Anser et al., 2020). Communication, in its broadest sense, is a system that enables people to connect, cooperate, and communicate with one another in a group setting via active collaborative learning and engagement with material, opinions, encounters, experiences, and technologies (Rahman et al., 2020). Due to the ease of use and utility of social media, students may become more active, increase understanding and conversation among classmates, supervisors, professors, and experts, seek professional support, and solve problems (Ghani et al., 2019). The reported ease of use and usefulness were statistically significant satisfaction indicators. People who have more friends and engage with more pupils are happier, according to research, than those who have fewer friends and contact with fewer students (Mostafa, 2020). Despite this, educators who use social media have expressed concerns about its difficulties, as well as insufficient evaluation and assessment (Moran et al., 2019). Students on campus require more support in accessing extra social media active collaborative learning choices than they do in face-to-face sessions, according to an empirical research. When it comes to using social media for active collaborative learning and engagement, lecturers may play a vital role in supporting students with speedy questions, solutions, and coordination (Hamadi et al., 2021). Evaluative times were created to allow teachers and students to provide feedback (Khan et al., 2021). Use of social media has an impact on study habits and can be a study distraction (Van Den Beemt et al., 2020). Individual learning capacity and accountability for vast amounts of communal information should also be fostered and monitored, despite the fact that the present educational focus has shifted substantially from individual learning to active collaborative learning (Liang et al., 2021). Students must also become more self-directed in their usage of technology as it becomes increasingly integrated into school (Sakurai et al., 2021). Students who were unfamiliar with the technology, as well as those who had had negative experiences with it, expressed interest in using social media for active collaborative learning and engagement, but stated that they would prefer to use media for interaction (Dzogbenuku et al., 2021). In the United States sample, multitasking and time wasting were also shown to attenuate the unfavorable connection between social media use and GPA. It’s conceivable that this is related to European pupils’ lower proclivity for multitasking (Rasheed et al., 2020). Active collaborative learning, on the other hand, will be successfully managed (Bouton et al., 2021). University students who use Facebook spend less time studying and get poorer marks than those who do not, according to Ohio State College data (Abbasi et al., 2021). As a result, students’ overall academic performance during the COVID-19 Pandemic suffers as a result (Masood et al., 2020). Cañabate et al. (2021) discovered that students’ comprehension of networking technology is passive rather than active (Cañabate et al., 2021). While there have been many social media studies aimed at elucidating influential factors on the use of social media networks, there have been few comprehensive studies on social media networks that have combined all essential factors of social media network use for active collaborative learning and engagement in a single study (Pitafi et al., 2020). As a result, social media research in higher education will be able to include all factors related to social media, which is seen as a critical step in understanding students’ use of social media for active collaborative learning and engagement, as well as the impact it has on their academic performance during the COVID-19 Pandemic. As a result, the primary goal of this research is to overcome the flaws that will be developed in a model that demonstrates perceptual, social media use to active collaborative learning, engagement, and satisfaction of research students in higher education using the Technology Acceptance Model TAM model (Davis, 1989) to evaluate academic performance during the COVID-19 Pandemic. Furthermore, while many social media models exist for measuring research students’ academic performance during the COVID-19 Pandemic and satisfaction via social media for active collaborative learning and participation in higher education, none exist for measuring research students’ academic performance during the COVID-19 Pandemic and satisfaction via social media for active collaborative learning and participation in higher education, indicating a gap in the field. As a result, using the TAM model, the study’s research subject will be to analyze and examine the aspects that define the relationships between active collaborative learning and engagement in order to affect research students’ academic success. According to the researcher’s major study question, what are the perceptual features that influence active collaborative learning and engagement, and hence academic success? Thus, the goal of this study is to create a model of social media use for active collaborative learning and engagement based on perceptual factors that influence academic performance during the COVID-19 Pandemic in higher education institutions, as well as to validate the Technology Acceptance Model (TAM) for interactivity and social media use for active collaborative learning and engagement on research students’ academic performance during the COVID-19 Pandemic in higher education institutions.
Social Media Use in Higher Education
In terms of skills, higher education has recently moved its emphasis from knowledge to lifelong learning (Greenhow et al., 2020). Cooperation skills are highly valued by employers, hence they are included in this list (Raza et al., 2020). The most broad definition of active collaborative learning was offered by Bui et al. (2021), who defined it as a scenario in which two or more individuals study or seek to learn something new together. Given the broad definition of the term “social media,” the bulk of research looked at specific social media platforms like MySpace, Facebook, and Twitter as educational successes, which seems sensible. The objective and functions of social media sites are to make it easier for users to exchange emails, add friends, construct personal profiles, join groups, develop apps, and locate other users (Stockdale and Coyne, 2020). Web 2.0, as opposed to its predecessor, web 1.0, which was more static and less dynamic, allows for increased user engagement, collaboration, and customization (Tajvidi and Karami, 2021). They include active collaborative learning via Facebook, blogs, and YouTube, among other things, as noted in Shahbaznezhad et al. (2021).
Perceptual Variables Used With Theories
Davis et al. (1989) introduced the Technology Acceptance Model (TAM), which will be used in this investigation. This model looks at the elements that determine how people utilize social media when they try out a new product or service (Davis et al., 1989). According to several research, perceived simplicity of use and utility have a substantial influence on satisfaction and willingness to utilize new technology (Rahmi and Birgören, 2020). The Technology Acceptance Model (TAM) is also used in this study, which says that perceived usefulness and ease of use are the most important criteria in determining whether or not a new technology is adopted. The most widely used theoretical model in this subject is TAM, which was established by Davis et al. (1989) to explain why people embrace or reject computer innovations like social media. Prior research provides the foundation for building and creating a research model to examine the influence of social media use in collaborative learning on research students’ learning outcomes. Constructivism theory and the technology acceptance model were used to design the research model (TAM). Based on the findings, eight operational themes of key factors on social media use for active collaborative learning and engagement that impact academic performance during the COVID-19 Pandemic were identified and classified (see Figure 1).
Figure 1. Research model.
Using Social Media for Collaborative Learning
Individuals work together to attain their shared learning goals through cooperative learning, which takes occur in groups (Khan and Mansoor, 2020). Positive interdependence, individual accountability, promotive interaction, interpersonal and small group abilities, and group processing are the five core aspects of collaborative learning (Lee and Yang, 2020). Positive interdependence, which “exists when group members think that they are linked in such a way that no one can achieve unless everyone succeeds,” is the most important aspect. “Everyone fails if one person fails” (Khan and Mansoor, 2020). Group processing is the last component, which entails group members analyzing their work in accordance to their objectives and maintaining positive working relationships (Khan and Mansoor, 2020). To guarantee that all five key aspects are in place, teachers must dedicate substantial planning time to cooperative learning (Junco et al., 2013; Al-Rahmi and Zeki, 2017; Al-Rahmi et al., 2019a). Cooperative learning groups, according to Khan and Mansoor (2020), are generally 2–4 students in size, with smaller groups being recommended. There is no ideal group size for cooperative learning. The number of students in a group is decided by a variety of factors, including the length of time the group will be working together, the ages and previous group work experience of the students, as well as the resources and equipment available (Chatterjee and Correia, 2020).
Student Engagement
The theory of student engagement arose from a proportionate educational approach to increase student involvement. Today, engagement is defined as the amount of energy a student devotes to educational activities that are scientifically linked to better college outcomes (Bond et al., 2020). Academic interactions with professors, participation in class activities, and interaction with classmates in the quest are all forms of engagement (Meintjes and van Wyk, 2020). Because this type of online tool has been proved to boost student academic success and experience by fostering cognitive engagement and social connection, the social media network was chosen (Aljuboori et al., 2020).
Perceived Usefulness
Perceived usefulness is the most crucial measure of IT use among users, according to the TAM model (Davis, 1989). On the other hand (Acharya and Ganesan, 2019), discovered that the utility of information systems (IS) had a negative influence on attitudes about their utilization. According to previous study, PU has the largest influence on attitude (Martinho et al., 2018). Furthermore, PU had a significant impact on future intentions to utilize social media (Abdullah et al., 2016; Scherer et al., 2019). According to Al-Rahmi et al. (2018a) perceived utility (PU) in the context of social media is defined as the degree to which users believe that social media may assist them achieve teaching and learning objectives.
Perceived Ease of Use
In the context of social media, Al-Rahmi et al. (2018a) defined perceived ease of use (PEU) as the degree to which consumers believe that utilizing social media is straightforward. According to past research, PEU has a significant influence on perceived usefulness (Abdullah et al., 2016; Binyamin et al., 2019). In addition, past research has found that PEU is a significant predictor of attitudes toward social media use (Fokides, 2017; Al-Rahmi et al., 2021a). PEU influences perceived usefulness, behavioral attitude, intention, and actual usage, according to TAM (Davis, 1989). The regression results, according to Davis (1989), indicate that, from a causative standpoint, PEU may come before perceived usefulness, rather than being a parallel and direct driver of utilization (Venkatesh and Davis, 2000).
Perceived Enjoyment
Perceived joy has an impact on the rising popularity of social media as a motivator (Rauniar et al., 2014; Al-Rahmi and Zeki, 2017). “The degree to which the act of utilizing technology is designed to be pleasurable in and of itself, independent of any potential performance concerns,” according to the definition (Davis et al., 1992). Users on social media are more interested in a service if they can experience it in a more immersive environment (Rauniar et al., 2014). People who love using a web system have a positive perspective of their interactions with it, according to Moon and Kim (2001), and are thus more inclined to utilize it to increase their collaborative learning (Sa’nch et al., 2014). However, when compared to other external factors, perceived enjoyment as an external factor in the context of student learning has not been frequently detected in previous TAM investigations.
Attitude to Use Social Media
Triandis (1971) defines attitude as a representation of sentiments and understanding about a topic or situation, as well as an individual’s positive or negative behavior. Attitude includes three components, according to Mantle-Bromley (1995), which are concerned with people’s preferences, knowledge of the attitudinal object, and reactions and intents toward the object, respectively. Previous study on the acceptability of social media has discovered that attitude is a key factor in determining whether or not to utilize it (e.g., Al-Rahmi et al., 2018b, 2021b). Attitude is discovered to be a significant influencer on behavioral intention (Al-Rahmi et al., 2018b; Rasheed et al., 2020). As a result, the researchers observed that students’ opinions had an impact on their desire to use online learning technologies. Furthermore, according to a study done by Sujeet and Jyoti (2013), attitude and PEU may influence enhanced behavioral intention among Omani students. Rupak et al. (2014) discovered that TAM has a substantial positive association between perceived usefulness and PEU, and that both categories had a favorable influence on behavioral intention in their research of social media usage behavior.
Behavior Intention to Use Social Media
Many earlier research on technology adoption have highlighted attitude as an important determinant of online earning and social media learning (Tosuntaş et al., 2015). Users that have a good mindset are more likely to use social media, according to Cheung and Vogel (2013). Given the rapid rise of online learning, Wang and Wang (2009) claim that the desire to utilize it differs greatly from actual use. To have a better knowledge of how different social media platforms are used. Al-Rahmi et al. (2020a) argue that there is a chance that the intention and behavior are conflicting, since the intention to embrace social media might be impacted by unanticipated occurrences. As a result, Dlalisa and van Niekerk (2015) performed an assessment of users’ intentions and discovered that there is no substantial link between their intention and their actual usage of learning management systems and social media platforms. TAM is an extension of the TRA established by Davis (1986), and it gives a theoretical foundation for analyzing how external variables affect interior beliefs, attitudes, and actual usage, which determines their pleasure and use of technology. It also serves as a framework for explaining user behavior when it comes to adopting new technology and investigating the factors that impact attitudes toward such technology use (Davis, 1989). The purpose of this study is to analyze students’ and instructors’ satisfaction with the use of social media for active collaborative learning and participation, as well as its impact on academic advancement in higher education institutions, using a TAM-based questionnaire.
Academic Performance During the COVID-19 Pandemic
Active participation in collaborative learning is encouraged by social media. To say that social scientists’ attention is drawn to social media by the increased interest in active collaborative learning is an understatement (Abdillah et al., 2020). Clapp et al. (2021) used a social bookmarking application to increase active collaborative learning by using the method and virtual framework built for the benefit of student motivation and collaborative group learning among peers, teachers, and owners in another study (SSCL). Knowledge and experience transfer are seen as complements to precise knowledge development that is relevant to real-world circumstances (Sohaei et al., 2020). The primary advantages of using social media to aid learning and teaching will not be fully appreciated until more research is conducted into how social media’s social characteristics can be used to attract low- and disengaged students to interact in educationally purposeful ways with their high-engaged peers and teachers, ensuring that it contributes to the prosperity of many students (Al-Rahmi et al., 2015). However, data reveal a beneficial association between social media platforms and how they may be utilized to increase learning in a few rare circumstances (Bond et al., 2020).
Research Methodology
We sent out 430 questionnaires for the study, and 419 were returned by respondents; after human processing, 7 of the 419 questionnaires were incomplete (“students did not complete the survey”) and had to be deleted, leaving 412. Outliers, defined as “data that differs abnormally from other values in a random sample,” were found in three of the remaining 412 questionnaire copies put into SPSS, bringing the total number of viable surveys to 409 students (Hair et al., 2012) argued for such exclusions, claiming that outliers might lead to erroneous statistical conclusions and should be removed. For the purpose of the study, we built a conceptual model based on the TAM model to measure student satisfaction and academic performance during the COVID-19 Pandemic.
Instrument Development
Despite the fact that Likert scales are widely used in IS research and have been fully evaluated in marketing and social science, they were utilized to gauge responses in this study (Krejcie and Morgan, 1970; Garland, 1991; Shih, 2004). All of the factors in this study are rated on a five-point Likert scale from 1 to 5: The five alternatives are (1) Strongly disagree, (2) Disagree, (3) Undecided, (4) Agree, and (5) Strongly Agree. When choosing and creating a measuring scale, several elements that affect the scale’s reliability, validity, and usability must be taken into account. With the support of a pilot study with students, the questionnaire was fine-tuned and tested ahead of time to examine how students and researchers in higher education felt about using social media for active collaborative learning and engagement, as well as how it influenced their academic performance during the COVID-19 Pandemic. A 30-item questionnaire was prepared after minor layout adjustments, and the online survey was given near the end of the semester in September 2021. In the questionnaire adapted from previous studies, four items extracted from Lee and Yang (2020) were utilized to investigate the usage of social media for collaborative learning. Three questions obtained from the study were used to assess students’ use of social media (Shahbaznezhad et al., 2021). To measure PEU, perceived enjoyment, and perceived usefulness, a subset of four questions from Davis et al. (1992) were employed. Students’ attitudes toward using social media were assessed using three questions adapted from Davis (1986), four items from Davis et al. (1992), and four items from Davis et al. (1992). Students’ academic success was assessed using four items from Davis et al. (1992) and Al-Rahmi et al. (2020b).
Sample Size and Data Collection
In higher education, sampling is a statistical strategy for selecting a subset of individual observations from a population with the goal of influencing student and researcher academic performance during the COVID-19 Pandemic through the use of social media for active involvement and collaborative learning. Random and non-random sampling are the two types of sampling methods. Because a random sample strategy assures that the research target group has an equal chance of being picked, it was adopted in this study.
Data Analysis and Results
The empirical analysis of the current study attempts to see how the interrelationships of numerous independent and dependent factors related to using social media for active collaborative learning affect students’ and researchers’ academic performance during the COVID-19 Pandemic. Structural Equation Modeling was the primary statistical tool employed in the data analysis for a variety of reasons (SEM). When using the SEM, researchers have long contested whether the two-step or one-step procedure is better. The responses that have been authorized are entered into the SPSS software for analysis. This requires coding and data processing. The SPSS application is used to code the data in this investigation. The application of character symbols (mainly numerical symbols) to data is what data coding is all about. The data is modified for acceptability before being entered into SPSS and AMOS-SEM.
Validity and Reliability
A range of statistical approaches, such as the split-half methodology, internal consistency, intra-observer, and test–retest, can be used to investigate reliability (see Tables 1, 2). Individual item and scale reliability were investigated in this work, with scale reliability comprised of three types of measures: internal reliability (IR), composite reliability (CR), and average variance extracted (AVE). IR, are examples of scale reliability. Because internal consistency dependability is a widely used approach, it was adopted in this investigation. IR is critical in this study because it involves many item scales (Bryman and Cramer, 2004; Hair et al., 2012). The item is deemed dependable if the squared multiple correlations in (R2) of each item in the measurement model exceed 0.5. Individual item dependability is established when the standardized loading is equal to or greater than 0.50. Furthermore, the AVE displays the overall amount of variation explained by the hidden construct in the indicators (Hair et al., 2012).
Table 1. Relationship between factors and items (Validity and Reliability).
Table 2. Sample covariances (Group number 1).
Measurement Model
According to Hair et al. (2012), a range of goodness of fit metrics may be used to evaluate the overall model measure, which are split into three categories: absolute fit measures, incremental fit measures, and parsimonious fit measures. The measurement model is first examined for its validity (unidimensionality, reliability, and validity) using the two-step technique. Second, the structural model will perform further estimations between variables to see whether it matches the observed data (Hair et al., 2012). The adjusted goodness-of-fit index (AGFI), Tucker- Lewis index (TLI), incremental fit index (IFI), and comparative fit index are examples of incremental fit measures (CFI) shown in Figure 2 and Table 3.
Figure 2. Measurement model.
Table 3. Contrast media-induced nephropathy (CMIN) and the adjusted goodness-of-fit index (AGFI).
Hypothesis Testing
According to Hair et al. (2012), a direct impact is a relationship between two constructions that follows a single path. In other words, it is the direct relationship between variables and their impact on one another. The Critical Ratio (CR) and p-value recommendation values for the present research, which contains sixteen direct impacts, must be estimated to guarantee that all routes in the model are supported. To arrive at a suggested value, the CR parameter estimate divided by an estimate of its standard error should be more than 1.96 (see Figures 3, 4, and Table 4).
Figure 3. Structural model.
Figure 4. Hypothesis testing.
Table 4. Regression weights: (Group number 1–Default model).
Discussion and Implications
This study contributes to the existing body of knowledge by using the TAM model to better understand how students utilize social media for collaborative learning and management. Students’ communication, participation, and collaboration have all changed as a result of social media. Students are encouraged to learn through social media collaboration and participation, where students and professors interact as well as students and students communicate (Stevens, 2009; Al-Rahmi et al., 2021b). Perceived usefulness, PEU, and perceived enjoyment all exhibited a strong positive relationship with social media use for collaborative learning and engagement, according to our findings. According to these figures, social media has gained in popularity among students due to its simplicity and broad use. Forming groups, transferring resources, communicating with others, and coordinating through social media are all activities that students like. Perceived usefulness and student engagement and collaborative learning; PEU of social media with student engagement and collaborative learning; attitude toward social media; and behavior intention to use social media to influence students’ academic performance during the COVID-19 Pandemic all showed a significant positive relationship. Perceived usefulness, ease of use, and enjoyment are all crucial factors in determining whether or not to use a virtual learning environment, according to a previous study (King and He, 2006; Al-Rahmi et al., 2021a). According to the findings of this study, social media or social networking sites may be a beneficial tool for boosting student engagement and cooperation in the construction of learning environments. According to Al-Rahmi et al. (2019a) the technology acceptance model incorporates indicators of collaborative learning such as “reported ease of use” and “perceived usefulness,” as well as “engagement,” “peer interaction,” and “teacher’s participation.” Finally, research has been conducted on the influence of social media on collaborative learning and participation. However, in this study, the TAM’s major elements of PEU, perceived enjoyment, and perceived usefulness were employed as predictors of student social media usage. It has been proposed that a student’s use of social media predicts their attitude toward it, their behavior while using it, and their academic accomplishment. The following are the key conclusions of the study: PEU influences students’ attitudes toward using social media, as well as their behavior intending to use social media and academic accomplishment. This study’s findings are comparable, but not identical, to those of earlier investigations. The direct and indirect impacts of PEU on social media enjoyment and utility are investigated in this study. Active technology usage for educational purposes is on the rise, according to the research, and has a substantial influence on collaborative learning and student engagement (Al-Rahmi et al., 2019b). Collaborative learning and student engagement influenced reported ease of use, perceived enjoyment, and perceived usefulness in this study. Furthermore, the attraction, practicality, and ease of use of social media have an indirect influence on collaborative learning and student participation. All of these linkages were examined using a single model. According to our findings, perceived usefulness, ease of use, and enjoyment have a substantial impact on students’ attitudes about social media, as well as their behavior intention to use social media to improve academic performance during the COVID-19 Pandemic. Due to its simplicity and widespread usage, social media has grown in popularity among students, according to these statistics. Social media is also popular among students, who utilize it for engagement, resource sharing, and collaborative learning. There was also a substantial positive association between the perceived usefulness and enjoyment of using social media for collaborative learning and engagement.
Conclusion and Future Work
This study updates the TAM Model to better understand students’ views regarding social media and their plans to use it to improve their academic performance during the COVID-19 Pandemic. The findings suggest that utilitarian orientations to a social media site’s perceived utility, enjoyment, and ease of use are important determinants of collaborative learning and student engagement, which is a driver of students’ academic performance during the COVID-19 Pandemic. Using the TAM model, we found a link between students’ attitudes about social media and their behavior intention to use in the context of social media usage for education during the COVID-19 Pandemic. We studied and included additional crucial elements, such as using social media for collaborative learning and students’ participation, to make the TAM model more meaningful in the context of understanding the acceptance and usage of social media to affect students’ academic performance during the COVID-19 Pandemic. A structural equation modeling (SEM) approach and a 30-question online questionnaire were used to analyze these characteristics. Students’ perceptions of social media’s usefulness, enjoyment, and ease of use are positively influenced by collaborative learning and engagement, according to the findings; three variables influenced students’ attitudes toward social media and intentions to use it to improve their academic performance during the COVID-19 pandemic. In addition, the following four categories of strategic recommendations were discussed: using social media as a platform for education learning during the COVID-19 pandemic; using social media as a platform for collaboration and student engagement; social media as a useful, enjoyable, and easy-to-use platform; students’ attitudes toward social media and intentions to use it to improve their academic performance during the COVID-19 Pandemic. When these approaches are paired with a set of standards for using social media in higher education, students may be able to perform better in class. According to the current study, future research could incorporate other and additional variables to analyze the impact of various aspects on students’ academic performance during the COVID-19 Pandemic through the use of social media for collaborative learning and student engagement. Future research should look into additional studies and variables that influence the usage of social media for collaborative learning and participation in order to improve students’ academic performance during the COVID-19 Pandemic (e.g., environmental and cultural).
Data Availability Statement
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.
Author Contributions
All authors have contributions, read and agreed to the published version of the manuscript.
Funding
This work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia (Project No. GRANT140).
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s Note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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Keywords: social media technologies, AMOS-SEM, TAM model, COVID-19 pandemic, academic performance
Citation: Alismaiel OA, Cifuentes-Faura J and Al-Rahmi WM (2022) Social Media Technologies Used for Education: An Empirical Study on TAM Model During the COVID-19 Pandemic. Front. Educ. 7:882831. doi: 10.3389/feduc.2022.882831
Received: 24 February 2022; Accepted: 11 April 2022;
Published: 28 April 2022.
Edited by:
Ana Luísa Rodrigues, University of Lisbon, PortugalReviewed by:
Ying Xie, Northern Illinois University, United StatesNorhisham Mohamad Nordin, Sultan Idris University of Education, Malaysia
Copyright © 2022 Alismaiel, Cifuentes-Faura and Al-Rahmi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Omar A. Alismaiel, oalismaeel@kfu.edu.sa