The adoption of video conferencing platforms in higher education has surged, primarily driven by the need for flexible learning environments that can adapt to varying student needs and the rapid evolution of digital technologies[1]. The effectiveness of these platforms critically influences educational quality, impacting key outcomes such as student satisfaction and academic achievement[2][3]. Crucially, the transition to online learning platforms has highlighted the necessity of robust, user-friendly technology that can facilitate an interactive and engaging learning experience[4][5]. Studies have shown that the strategic implementation of such technologies can significantly enhance both the delivery of education and the educational outcomes[6]-[8]. Therefore, a deeper understanding of the determinants of video conferencing success is vital for optimizing these educational outcomes and ensuring the technology's effective integration into teaching strategies.

System quality, information quality, and service quality are critical components acknowledged as determinants of information system success, influencing various user-centered outcomes[9]. System quality enhances operational efficiency and user satisfaction, crucial for the seamless adoption of technology[10]. Information quality, through its relevance and accuracy, ensures that educational content meets learning standards and objectives, directly impacting educational effectiveness. Service quality provides essential support, helping users navigate and effectively utilize the technology. While these factors have been extensively studied across diverse sectors[11]-[15], their specific roles and impacts within the context of video conferencing for educational purposes remain underexplored and warrant a more focused investigation. The present study investigates how these dimensions of system quality, information quality, and service quality influence student satisfaction and academic achievement within the context of video conferencing used in higher education. This inquiry is crucial, particularly in light of the shift towards more digital and remote learning environments spurred by global challenges such as the COVID-19 pandemic[16].

The research employs a quantitative methodology, using a survey distributed among university students to assess their perceptions of system quality, information quality, and service quality, and how these perceptions influence their satisfaction and academic achievements. The use of Partial Least Squares Structural Equation Modeling (PLS-SEM) provides a robust method for analyzing complex model structures and multiple constructs that influence each other[17].

The findings of this study are expected to contribute to the theoretical literature by enhancing the understanding of how specific qualities of video conferencing platforms impact educational outcomes. Furthermore, these insights will have practical implications for educational technologists, university administrators, and policymakers aiming to improve the effectiveness of digital learning environments. Through a comprehensive analysis of the constructs derived from validated studies, this research addresses a significant gap in the existing literature on educational technology by detailing the nuanced relationships between the quality of service delivery systems and their direct effects on user satisfaction and academic performance in higher education settings.

This study strategically utilized Partial Least Squares Structural Equation Modeling(PLS-SEM) to analyze the data. Unlike traditional covariance-based SEM methods commonly employed in previous studies, PLS-SEM offers enhanced flexibility and robustness in handling complex models and non-normal data distributions[29]. This attribute is particularly advantageous in exploratory research or multidimensional studies like ours, where the model includes multiple constructs and intricate pathways. PLS-SEM not only handles large sets of predictor variables efficiently but also provides reliable results even with smaller sample sizes, making it superior in terms of applicability to diverse educational settings[30]. Moreover, PLS-SEM's ability to estimate latent variable scores directly contributes to a more nuanced understanding of the data, thus offering a methodological improvement over traditional techniques which might fail to capture such complexity effectively.

4.2 Hypothesis test

SEM analysis was conducted to test and confirm the hypothesized relationships among the constructs of this study.

A bootstrap resampling method with 5000 resamples was conducted to check the significance of the hypotheses within the research model. The analysis results are described in Figure 1 and Table 5.

Fig. 1. 
SEM results

Table 5. 
Significance testing results of the structural path coefficients

H	β	T	P	Result
H1a	0.443	6.931	0.000	Supported
H1b	0.309	3.596	0.000	Supported
H2a	0.376	6.671	0.000	Supported
H2b	0.221	3.014	0.001	Supported
H3a	-0.069	1.261	0.104	Not supported
H3b	-0.011	0.129	0.449	Not supported
H4	0.327	4.489	0.000	Supported

The discussion section delves into the significant and non-significant relationships revealed in the analysis of the structural path coefficients related to the quality and effectiveness of video conferencing platforms in higher education settings.

Starting with system quality, the analysis underscores a robust positive influence on satisfaction and academic achievement, as evidenced by the supported hypotheses H1a and H1b. This finding aligns with previous studies[35][36], which emphasized the critical role of system quality in enhancing user satisfaction and educational outcomes in tech-supported learning environments. The substantial beta values suggest that a high-quality system that is efficient, reliable, and user-friendly enhances student satisfaction and directly contributes to their academic success. These results reinforce the necessity for educational institutions to invest in superior technology to foster a conducive learning atmosphere.

In contrast, the results concerning service quality (H3a and H3b) indicate no significant effect on either satisfaction or academic achievement. This contradicts prior findings[37][38], where service quality was deemed essential for enhancing user satisfaction and learning outcomes. A possible interpretation of this discrepancy could be that students prioritize the functional aspects of the technology over the support services provided. This suggests that while service quality is generally important, its direct impact may be overshadowed by the more immediate effects of system functionality and information quality in virtual learning contexts.

Information quality's impact on satisfaction and academic achievement (H2a and H2b) was also significant, supporting the contention that high-quality, relevant, and accurate content is critical in educational settings. This is consistent with the findings of previous works[9][39], which argued that the quality of information significantly affects learning satisfaction and outcomes. The relationship between high-quality information and academic achievement underscores the idea that educational content must be both accurate and timely to effectively support student learning, suggesting that educators and platform developers should focus on curating and delivering top-notch content.

Finally, the relationship between satisfaction and academic achievement (H4) was significantly positive, highlighting satisfaction as a crucial mediator in the educational process. This aligns with formers studies[40][41], which found that satisfaction with learning platforms significantly enhances academic outcomes. This finding suggests that satisfaction might operate as a key driver of student engagement and motivation, which are vital for academic success in virtual learning environments.

In summary, the analysis results offer deep insights into how different aspects of video conferencing platforms influence learning experiences in higher education. While system and information quality directly enhance satisfaction and academic achievement, service quality does not show a significant impact, suggesting that the core functionalities of the platform are more critical to student outcomes than the ancillary support services. These insights are crucial for educational technology developers and providers aiming to enhance the effectiveness of virtual learning environments.

This research extends the understanding of the role that various qualities of video conferencing platforms play in higher education. Prior studies have emphasized the importance of system quality and information quality in educational contexts, noting their positive impacts on student satisfaction and academic achievement[35][39]. However, this study uniquely identifies that, contrary to expectations and previous findings[37][38], service quality does not significantly influence satisfaction or academic achievement in the realm of video conferencing used for higher education. This suggests that the technical aspects of a system, such as functionality and information accuracy, are more crucial than the support services provided. Scholars should consider this differentiation in future studies, potentially examining how and why the importance of service quality may differ based on educational settings or technological advancements. This insight encourages a reevaluation of the weight assigned to different system qualities in educational technology research. Further, this research significantly enhances the existing literature on video conferencing platforms in higher education by exploring the nuanced roles of system, information, and service quality in student outcomes. Unlike many existing studies that generally affirm the importance of all three dimensions[35][39], this study provides a differentiated view, especially highlighting that service quality does not impact student satisfaction or academic achievement as significantly as previously thought. By pinpointing this discrepancy, the study contributes a critical perspective that challenges prevailing assumptions in educational technology research. It underlines the need for educational institutions to prioritize technical performance and content quality over supplementary service features. This divergence from established research invites a broader discussion on the specific attributes that truly enhance learning efficiency and student engagement in digital environments, offering a valuable direction for future research to refine the design and focus of educational technologies.

The findings of this study provide actionable insights for practitioners involved in the implementation and management of educational technologies. For educational IT personnel and service providers, the emphasis on system and information quality over service quality highlights the importance of investing in robust and reliable technological infrastructures. This could involve enhancing the user interface to ensure it is intuitive and streamlining access to information resources to support real-time learning needs. For educators, understanding that the technological efficiency of video conferencing tools can directly impact student outcomes might encourage the adoption of platforms known for their superior system quality. Similarly, students should be guided to select and utilize platforms that are recognized not just for their functionality but also for the quality of information they can access, which this study has shown to be linked to higher academic achievement.

One notable limitation of this study is its focus on higher education without exploring varied educational levels such as K-12, which may exhibit different dynamics in technology use and needs. Future research could explore whether the findings here apply across different educational stages or if younger students' satisfaction and achievement are influenced differently by these platform qualities. Additionally, exploring the role of cultural differences in the acceptance and effectiveness of video conferencing tools could provide deeper insights, as cultural contexts might alter the importance or perception of system, information, and service quality in educational settings. This approach could help delineate more specific strategies tailored to diverse learning environments and technological landscapes.

Finally, the sample size of 236 in this study does not fully represent all specialized groups and platform types, particularly those with very small sub-sample sizes such as education majors and Google Classroom users. Future research should aim to either focus on specific user groups or expand the sample size and diversity to include a broader range of disciplines and platform types to enhance the generalizability of the findings.