Keywords

1 Introduction

Education, notably higher education, faced a significant challenge during the COVID-19 pandemic, being severely affected, as well as many aspects of economic and social life. This period also represented a significant threat to the higher education sector worldwide, putting us in front of an unexpected but very complex context since physical presence lectures stopped during the pandemic’s peak [1]. Higher education institutions focused their technical, organizational, and pedagogical aspects to find quick responses for the transition from traditional to distance learning, to ensure the continuity of the educational process, and to provide high-quality education [2, 3], ensuring equity, transparency, and legal certainty in the distance learning process [4].

There is a common understanding that distance learning technologies are still applied and continuously evolving in the post-pandemic era since they offer several benefits, such as improving access to education opportunities for a more significant part of the population, counterbalancing the decreasing university-age population and providing graduates with the capability to respond to labour market requirements. The higher education sector has changed in terms of methods, technology, and content, and the labour market requirements have also changed. Education prepares people to succeed in the labour market. The creation, delivery, and use of information are changing rapidly. To face all the new realities, individuals need experience utilizing new forms of communication, work, or study [5, 6]. The endowment of students with the skills required by the knowledge society combined with pandemic lessons is one of the most significant ways to evaluate the efficiency of higher education.

Under these circumstances, our paper aims to evaluate the perception of satisfaction and comfort in using online tools and examine the impact of the critical aspects involved [7, 8].

2 Theoretical Background

Electronic educational technology for learning is considered the cornerstone of building an inclusive knowledge-based society [9], and the innovative pedagogies supported by the new technologies made the evolution of an alternative instructional method possible. The large-scale use of the Internet has also contributed to its increase during the last decades [10].

Investing in modern educational technologies is critical for institutions, and the most important indicators of assessing the cost-effectiveness of learning are the satisfaction and experience of students [11]. The information and technology infrastructures are the engine of the evolution of distance learning. It has also long been emphasized that the focus should be on creating learning-centred environments supported by technology [12]. The Information and Communication Technology (ICT) tools and digital skills are essential in adapting to distance learning during COVID-19 [13]. Using the interview method, Almaiah et al. [14] identified the main challenges facing distance learning, concluding that they extend beyond the infrastructure issue, including technical, managerial, and course content issues with potential effects on participants' comfort and satisfaction in the educational process. An increase in satisfaction with using distance learning tools could be supported/encouraged by its ability to foster a peer-to-peer learning approach, to support group cohesiveness, trust, and a sense of belonging and community, even if it will have to manage different learning styles and cultural attitudes toward learning [15].

Marek et al. [16] conducted a worldwide survey to explore the teaching staff's experience after moving to distance learning during the COVID-19 pandemic. They found, as expected, that those with experience with distance learning before the pandemic were more comfortable with the short-notice transition decided by the pandemic. Even under these circumstances, a higher workload and stress were experienced compared to traditional face-to-face learning. By contrast, another research [17] found that the transition to distance learning, regardless of existing or not previous experience, required new teaching methods and assignment changes, which may imply a lower expected volume of work for students.

Our paper aims to identify the critical factors affecting the students’ satisfaction during e-learning lectures. This is important for moving towards an efficient and inclusive educational system to create a resilient future of education.

3 Materials and Methods

We used a structured questionnaire to assess university students’ satisfaction with the e-learning experience. The survey was conducted via simple random sampling during September–October 2021. The final sample was 368 University of West Attica students in Athens, Greece. Students’ satisfaction criteria were created using relevant bibliographic sources [18,19,20,21]. The satisfaction criteria (variables) were the following:

Platform Reliability: This criterion included questions on platform security and interaction with users. Platform Usability: This criterion included questions on platform easiness of use and learning, user-friendliness and compatibility with various browsers. Platform Functionality: This criterion included chat options, whiteboard and media sharing capabilities. Platform Efficiency: It included options about the speed of various programs, connection speed and stability, frequency of errors. Trust-Empathy: Interaction with professor and fellow students, student motivation to participate in the teaching process.

Concerning the sample demographics, female students were 65% and male students 35%. The average student’s age was 23.6 years. Around 65% of the samples were students covering the expected study period (1st–8th semester), while the other 35% exceeded the standard study period of 8 semesters.

The analysis is performed by applying the multi-criteria model MUSA (Multi-criteria Satisfaction Analysis). This approach resembles the ordinal regression method and sets total satisfaction as the dependent variable and the criteria as the explanatory variables. This methodology is extensively analyzed in relevant literature [7, 22, 23]. The method assigns weights to the independent variables according to partial satisfaction in each sub-criterion. Furthermore, the total satisfaction is explained according to the explanatory variables. An action diagram for the criteria is produced, and actions are suggested according to each area [7].

4 Results

The results show a high overall satisfaction of the students from the university e-learning education. Looking at Fig. 1, we see that the total satisfaction amounted to 93.79%.

Fig. 1
A line and a bar graph of satisfaction function. The line graph plots value versus total satisfaction scale. The data is as follows. Dissatisfied, 81.44. Neutral, 86.47. Satisfied, 91.47. Very satisfied, 100. The bar graph plots satisfaction in percent versus methods with MUSA 1 at 93.79.

Satisfaction function

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Concerning the impact of the separate satisfaction criteria on the variable of total satisfaction, according to Fig. 2, the criterion of “Platform Reliability” had the most decisive impact (44.63%), followed by “Empathy-Trust” (19%), the “Platform Usability” (12.8%), the “Platform Efficiency” (11.9%) and finally the “Platform Functionality” (11.67%).

Fig. 2
A horizontal bar graph of satisfaction. It plots criteria versus weight. The data is as follows. Empathy trust, 19. Platform reliability, 44.63. Platform functionality, 11.67. Platform efficiency, 11.9. Platform usability, 12.8.

Satisfaction criteria weights

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Figure 3 shows that students’ satisfaction is high in all five criteria. Specifically, “Platform Reliability” was first with 94.09%, followed by “Platform Usability” with 92.85%, while students were also delighted with the criterion of “Stores Platform Functionality” with 92.39%. On the other hand, “Empathy-Trust” and “Platform Efficiency” had the lowest percentages, which amounted to 91.31% and 90.49%, respectively.

Fig. 3
A bar graph plots satisfaction in percent versus criteria. The data is as follows. Platform usability, 92.85. Platform efficiency, 90.49. Platform functionality, 92.39. Platform reliability, 94.09. Empathy-trust, 91.31.

Students’ satisfaction for each of the used criteria

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Looking at Fig. 4, we can see that none of the criteria fell in the bottom right area of high importance and low performance. This leads to the conclusion that no important criterion that explains student dissatisfaction exists. Furthermore, the criterion of Platform Reliability is in the leverage opportunity area, so this can be considered the competitive advantage of the e-learning system, which should be further improved and promoted.

Fig. 4
A 4 quadrant scatterplot of satisfaction versus weights. Platform reliability is in quadrant 1 with highest satisfaction and weights. Platform usability and platform functionality are in quadrant 2 with low satisfaction. Empathy-trust and platform efficiency are in quadrant 3 with platform efficiency the lowest.

Action diagram

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5 Discussion and Conclusions

This paper focused on students’ satisfaction with the educational process, which was challenged to switch to distance education during the COVID-19 pandemic. The results emphasized the competitive advantages of using e-learning technology in student satisfaction during the educational procedure. Students reported a high level of satisfaction under the five criteria. Moreover, the more critical satisfaction criterion (according to the MUSA method) was found to be that of platform reliability. This is a competitive advantage that the university should prioritize. A similar study [1] found that organization policy is a crucial variable in improving the e-learning experience for students and professors. An e-learning-centered organization policy could further support the platform reliability variable.

Furthermore, the criterion of empathy-trust is the second most important. As found in a similar study [6], it is essential that the students gain familiarization and trust in the platform, and this can be achieved by focusing on understanding theoretical concepts through respective exercises. On the other hand, in this case study, the criteria of platform usability and functionality are of low importance and high satisfaction, leading to the fact that the university could transfer sources from those aspects to strengthen the essential satisfaction criteria of platform reliability. In a similar study [24], the authors criticized the claims that educational technologies are a ready-made remedy for the COVID-19 education crisis, stressing that not only digital connectivity is essential but also the ability of people to access and their endowment with skills to use technology effectively and safely to achieve educational goals. These variables are essential for increasing the comfort of using distance learning tools and increasing participants’ perceived satisfaction in the process. The improvement of digital skills is also supported by Konig et al. [13].

However, the factors affecting the satisfaction of using distance learning procedures and processes extend beyond the infrastructure issue, including technical and managerial support and course content [14]. Social media platforms and the Internet of things (IoT) may contribute so that online communities with similar interests can be created and innovative communication technologies can be employed in higher education [25,26,27,28].

The importance of our study lies in the fact that assessing the potential effect of distance learning and its implications, as well as its benefits, will be the focus of researchers and policymakers in the post-pandemic period to design new coordinates of the educational process considering the experiential situation we have all faced.