Measuring e-learning systems success: Data from students of higher education institutions in Morocco

The COVID-19 pandemic has forced Higher Education Institutions (HEI's) to rethink the teaching approach taken. In response to this emergency state, Moroccan universities switched to the e-learning approach as an alternative to face-to-face education. At this level the assessment of e-learning systems success becomes a necessity. This data article aims to identify e-learning systems success determinants during the COVID-19 pandemic. The data was collected from students of the Moroccan Higher Education Institutions. The research data are collected via an on a self-administered online questionnaire, from a sample of 264 university students. The responses are collected from students of 12 Moroccan universities and 31 Moroccan educational institutions. The data were analyzed using a structural equation modeling method under the Partial Least Squares approach (PLS-SEM). Data analysis was performed using SmartPLS 3 software. Universities managers can use the dataset to identify key factor to enhance e-learning system success.


Value of the Data
• The dataset is useful because it helps to explore the factors that affect the E-Learning systems success in Higher Education Institutions (HEI's). • This dataset can be used to enlighten Moroccan educational institutions managers on the importance of system quality and instructor quality as a key factor to improve perceived usefulness, e-learning systems use and e-learners satisfaction. • The dataset will be useful for universities managers and policymakers to renovate practices in order to enhance e-learning system use, e-learners satisfaction, and e-learning system success. • This dataset provides insights into diverse aspects of system quality, instructor quality, social influence, learner computer anxiety, perceived usefulness, e-learning system use, e-learner satisfaction, and e-learning system success. • This dataset can be adapted for use in order to assess the e-learning system success in primary and secondary education.

Data Description
The constructs and measurement items used in this data article were drawn from previous research ( Table 1 ). A questionnaire survey was carried out among Moroccan Higher Education Institutions (HEI's). The questionnaire was self-administered via the Google Forms tool during the months of May and June. The research data and questionnaire are available in Mendeley data on: https://data.mendeley.com/datasets/h9vdjh8tk7/2 Due to the lack of a sample frame, we have resorted to a non-probabilistic sampling method. This kind of method is used for practical reasons of accessibility and reduced cost. Table 2 illustrates the profile and characteristics of students who participated in this survey. A total of 264 responses from students were received, including 187 women (70.80%) and 77 men (29.20%). Almost half of the respondents to our questionnaire are undergraduate students (46.2%). The responses are collected from students of 31 Moroccan educational institutions affiliated with 12 universities ( Tables 3 and 4 ). 25.67% of students indicate that they do not use any video conferencing systems and 17.05% among them do not use any online learning platforms. As an alternative, teachers refer to WhatsApp groups in order to interact with students, as they use YouTube videos for transferring knowledge. It is to highlight that Google meet and Zoom are the most video conferencing systems used in Moroccan HEI's. Additionally, Moroccan students use several online learning platforms such as; Coursera, Google Classroom, LinkedIn Learning, Moodle, and Udemy ( Table 5 ). I am pleased enough with e-learning system E-Learning System Success

ELSS1
The system has a positive impact on my learning Overall, the performance of the system is good ELSS3 Overall, the system is successful ELSS4 The system is an important and valuable aid to me in the performance of my class work.

ELSS5
The system helps me to Increase knowledge (increased knowledge) [12]

ELSS6
The system helps me to Increase Self-reliance (self-reliance) Strongly agree].  To test the research model, we used the Partial Least Squares approach). Because of the exploratory character and the small size of our sample, we have used the PLS-SEM as an appropriate method to analyze hypothesis and research model. Fig. 2 summarizes steps of the structural equation modeling method under the Partial Least Squares approach [13][14][15] .

Experimental Design, Materials and Methods
For data analysis, we used the SmartPLS 3 software. Table 6 summarizes the convergent validity, according to several criteria: individual item reliability ( > 0.7), composite reliability ( > 0.7), factor loadings ( > 0.7) and average variance extracted (AVE > 0.5). Likewise, the discriminant validity is ensured thanks to the Fornell-Larcker criterion ( Table 7 ), and the cross-loading criterion ( Table 8 ). In short, Fig. 3 shows the SEM-PLS estimation for the measurement and structural model.   As indicated in Fig. 4 , the values of the coefficient of determination of the couple endogenous constructs; perceived usefulness, and e-learning system use are moderated, which are 0.499 and 0.447 respectively. In addition, the values of R ² of the e-learner satisfaction, and e-learning system success are substantial, which are 0.690 and 0.789 respectively.  The size effect (f 2 ) values are all acceptable, except the effect of system quality and perceived usefulness on e-learning systems use ( Table 9 ). The system quality and perceived usefulness have no significant effect size on e-learning system use (f 2 < 0.02).
The predictive relevance (Q 2 ) values are all greater than zero, which makes it possible to conclude that the model has an acceptable predictive power [14] . Finally, the Goodness of Fit of the Model of this study is very strong (GoF = 0,674,868 > 0.36) [16] .
According to SmartPLS outputs, it turns out that instructor quality contributes to the explanation of perceived usefulness, e-learning systems use, and e-learner satisfaction. Likewise, the    system quality has a positive and significant effect on perceived usefulness, and e-learner satisfaction. On the other hand, social influence has a significant effect on e-learning systems use.
In the same, the perceived usefulness contributes to the explanation of e-learner satisfaction.
In contrary, learner computer anxiety has a significant and negative effect on e-learner satisfaction. Finally, the perceived usefulness, e-learning systems use, and e-learner satisfaction greatly contributes to the explanation of e-learning system success ( Fig. 5 ).

Ethics Statement
The consent of respondents was obtained. Participation in the study was voluntary, and participants could withdraw from the survey at any point. The online survey was completely anonymous and does not contain any information allowing identifying the participant.

Declaration of Competing Interest
The authors declare that they have not known competing financial interests or personal relationships, which have, or could be perceived to have, influenced the work reported in this article.

Funding Resources
This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.