key: cord-0998159-3ugudmx7 authors: Al-Okaily, Manaf; Alqudah, Hamza; Matar, Ali; Lutfi, Abdalwali; Taamneh, Abdallah title: Dataset on the Acceptance of e-learning System among Universities Students' under the COVID-19 Pandemic Conditions date: 2020-08-18 journal: Data Brief DOI: 10.1016/j.dib.2020.106176 sha: d3b42957c3c1e7096b3c08eae41cf1ccb87de813 doc_id: 998159 cord_uid: 3ugudmx7 The COVID-19 pandemic has produced an unprecedented change in the educational system worldwide. Besides the economic and social impacts, there is a dilemma of accepting the new educational system "e-learning" by students within educational institutions. In particular, universities students have to handle several kinds of environmental, electronic and mental struggles due to COVID-19. To catch the current circumstances of more than two hundred thousand Jordanian university student during COVID-19. 2,500 students have been randomly selected to respond on an online survey using universities' portals and websites between March and April 2020. At the end of the data gathering process, we have received 587 records. The dataset includes 1) Demographics of students; 2) students’ perspectives concerning the factors influencing their intention to use e-learning system within the Jordanian universities context. Data were analyzed using Partial Least Squares - Structural Equation Modelling (PLS-SEM). Next, the result has confirmed the positive of direct effect variables (subjective norm, perceived ease of use, and perceived usefulness) on the students’ intention to use e-learning system. Next, the result has also confirmed the mediating effect of perceived usefulness and perceived ease of use between subjective norm and the behavioral intention to use the e-learning system with partially supported. Manaf The COVID-19 pandemic has produced an unprecedented change in the educational system worldwide. Besides the economic and social impacts, there is a dilemma of accepting the new educational system "e-learning" by students within educational institutions. In particular, universities students have to handle several kinds of environmental, electronic and mental struggles due to . To catch the current circumstances of more than two hundred thousand Jordanian university student during COVID-19. 2,500 students have been randomly selected to respond on an online survey using universities' portals and websites between March and April 2020. At the end of the data gathering process, we have received 587 records. The dataset includes 1) Demographics of students; 2) students' perspectives concerning the factors influencing their intention to use e-learning system within the Jordanian universities context. Data were analyzed using Partial Least Squares -Structural Equation Modelling (PLS-SEM). Next, the result has confirmed the positive of direct effect variables (subjective norm, perceived ease of use, and perceived usefulness) on the students' intention to use e-learning system. Next, the result has also confirmed the mediating effect of perceived usefulness and perceived ease of use between subjective norm and the behavioral intention to use the e-learning system with partially supported. Keywords: Distance learning, e-learning system, COVID-19, corona virus, acceptance, Jordan universities, TAM model. Education, Education Management The Jordanian universities students' intention to use e-learning system during the COVID-19 pandemic, subjective norm (SN), perceived ease of use (PEU), and perceived usefulness (PU), technology acceptance model (TAM). The raw data is available in Excel Workbook format. The analysed data in this article are provided in tables and figures. How data were acquired Online Survey The target population of this work was Jordanian universities students who are affected by COVID-19 pandemic. In light of the universities closure, all Jordanian universities have converted to the e-learning system. as a result, more than 200 thousand students from various universities were required to handle with a new educational system unprecedentedly. We collect data using an online survey through universities' portals and websites between March and April 2020. The participants of this dataset were the Jordanian universities students. In this regard, the questionnaire is provided as a supplementary file Repository name: Mendeley Data Data identification number: 1 Direct URL to data: https://bit.ly/3i8KkI5.  The dataset is valuable because it can be utilized as a reference for understanding the effect of factors, namely: subjective norms, perceived ease of use and perceived usefulness on the student's intention to accept the e-learning system.  This data presents the natural flow to measure students' intention to acceptance/use the elearning system during COVID-19 pandemic, which can be replicated in other countries.  This data can help to understand the factors that affect the E-learning system acceptance through integrating subjective norms with the extended Technology Acceptance Model (TAM). Besides, using both variables: perceived ease of use and perceived usefulness as mediation between subjective norms and the e-learning system acceptance.  Finally, the data is useful for all parties involved, especially for universities management, ministry of higher education, decision-makers in a country, researchers and practitioners in the e-learning system. The data presented in this paper is focused on the students in the Jordanian universities who using the e-learning system. The research was conducted according to and complies with all regulations established in the ethical guidelines by the Jordanian Ministry of Higher Education and Scientific Research. The data file spreadsheet accompanying this article consists of 587 rows and 24 columns of dataset. Every row represents an individual's response to a survey. A five-point range scale was applied to allow the respondents to indicate how much they disagree or agree with a certain statement, so a numerical value in the dataset file means the respondent level of agreement, with 1 being "strongly disagree" and 5 being "strongly agree". Demographic dataset regarding Jordanian universities students' profile indicated that 394 were male and 393 were female. Regarding the age 148 (25%) of the respondents were between 18 and 20 years old, 311 (53%) of the respondents were between 21 and 23 years old, and 128 (22%) of the respondents were more than 23 years. The majority of respondents were bachelor students 572 (97%) followed by master degree 15 (3% [2, 3] . Hence, internal consistency was confirmed. For the factors' loading, all items were higher than .70. Besides, the validity of the instrument was proved by calculating the average variance extracted [1] . Wherein, the results of the average variance extracted (convergent validity) are at acceptable level, which all variables have average variance extracted value larger than .50 (see Table 1 ). In addition, as shown in Table 2 the test of discriminant validity was also a part of measurement model (inner model) assessments. The discriminant validity was conducted to evaluate the range to which a provided study latent variable is distinct from others. Hence, when the average variance extracted of an individual latent construct is higher than the multiple squared correlations of that construct with other constructs, the discriminant validity will be at an acceptable level [6] . Thus, the results revealed that all studied variables had good discriminant validity values (see Table 2 ). Data were gathered using online survey through Jordanian universities students' portals and websites (between March and April 2020). The students were asked to fill in the online questionnaire through the provided link. From those 2,500 students, there were 587 responses. The questionnaire and the answers to the questions are provided as a supplementary file. The data were analysed using statistical test including Partial Least Squares Structural Equation Modelling (PLS-SEM) approach. We used Smart PLS 3.0 software [1] The study's model was contained two level of constructs (upper and lower), thus to conduct the measurement model assessment, each of composite reliability, indicators reliability, average variance extracted, and discriminate validity were tested. In regard to the composite reliability, the criterion of composite reliability was assessed to verify the internal consistency reliability. The values in Table 1 showed the constructs scores exceed the acceptable level of reliability 0.7 [2, 3] (see Table 1 ). Hence, internal consistency was confirmed. Besides, all factors' loading is higher than .70. The validity of the instrument was proved by calculating the average variance extracted [1] . Wherein, the average variance extracted is the indicator used for measuring convergent validity, by measuring the variance value of that the items share with their respective variable [1] . The results of the average variance extracted (convergent validity) are also presented in Table 1 , which all variables have average variance extracted value larger than .50. Cronbach Table 2 was also conducted to evaluate the range to which a provided study latent variable is distinct from others. Whereby, when the average variance extracted of an individual latent construct is higher than the multiple squared correlations of that construct with other constructs, the discriminant validity will be at an acceptable level [6] . As illustrated in Table 2 , all studied variables had good discriminant validity values. This work neither involves chemicals, procedures or equipment that have any unusual hazards inherent in their use nor involves the use of animal or human subjects. A primer on partial least squares structural equation modeling (PLS-SEM) SmartPLS 3., retrieved from Advances in International Marketing The use of partial least squares path modeling in international marketing Evaluation of structural equation models using the partial least squares (PLS) approach, Handbook of Partial Least Squares Evaluating structural equation models with unobservable variables and measurement error The authors would like to acknowledge the valuable contributions of the reviewers and editor who have provided critical suggestions to improve the quality of the article. The suggested comments have helped in improving the quality of the article considerably. The authors declare that they have no known competing financial interests or personal relationships which have, or could be perceived to have, influenced the work reported in this article. Supplementary material associated with this article can be found, in the online version, at https://bit.ly/3i8KkI5 (Mendeley Data).