## 5 Discussion  
In the literature, there is some research on the topic that we presented in this paper. In the following, we discuss these findings and compare them to ours. Some of them differ in methodology and approach, and others in results. [PERSON] and [PERSON] [43] in their research revealed that the quality of e-learning consisted of three elements: course content and design, administrative and technical support, and instructor and learner characteristics. Comparing their research with ours, it turns out that they approached the quality of e-learning in a different way. Namely, in our research, we identified 14 characteristics that affect the quality of e-learning, while these authors addressed three main segments. According to the results of their research, the content and design of the course were the most important dimensions of overall e-learning quality. Furthermore, further analysis indicated that student satisfaction partially mediated the relationship between the quality of e-learning and intentions of continued use. In turn, in our research, we examined the correlation between the resources to participate in e-learning and the evaluation of the quality of e-learning. It turned out that students who rate their resources for participating in e-learning as very low rate the quality of this type of class as low. A similar situation occurred with regard to the good assessment of resources--students rated the quality of learning highly. Therefore, the assessment of the quality of e-learning is also influenced by the resources possessed by students (the student's technical infrastructure), which the authors of the publication that was mentioned did not take into account. In another study [85], [PERSON] et al. determined a different group of the key determinants of the quality of e-learning. These factors included administrative support, course content, course design, social support, technical support, instructor characteristics, and learner characteristics. Referring to the research method, in our paper we developed a survey, using a Google questionnaire, while [PERSON] [44] used structured interviews. Several (fifteen) participated in the examination. In conclusion, this method allowed the author to gather more detailed data on the quality of e-learning by focusing on individual experiences. However, a limitation of this approach was the significantly smaller research sample size compared to our study, which included 621 students. In the paper, both positive and negative perceptions of online learning were identified, along with the factors influencing these perceptions. Positive aspects included flexibility, cost-effectiveness, access to electronic research databases, and well-designed online classroom interfaces. On the contrary, negative perceptions were attributed to delayed feedback from lecturers, lack of technical support, low self-esteem and motivation, feelings of isolation, one-way teaching methods, and poorly designed course materials. Our research found that three variables were assessed positively: logging into the e-learning platform (score of 4.38), ease of use (score of 4.20), and adherence to the scheduled class times by academic teachers (score of 4.15). [PERSON] et al. [86] focus their research on an e-learning success model in the context of the COVID-19 pandemic. They assess the effectiveness of e-learning and investigate the key antecedents of e-learning effectiveness. A structured survey (a sample of 1202 students) was used among students from Imam Mohammad Ibn Saud Islamic University to examine the linkages among the proposed models. The research findings of the authors indicate that effective e-learning is supported by the interactions between the following four factors: the e-learning system, readiness for e-learning, interactivity, and resistance to change. To some extent, the authors' research is similar to ours because the issue of e-learning quality is related to e-learning effectiveness.