This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big Data External and Internal, Innovative Usage, Indexing, and Sources Accuracy. In addition, Artificial intelligence positively affects business performance, including Data Accuracy, Data Transparency, Data Speed, and Creative Thinking and Learning. Moreover, business intelligence has a direct and positive impact on business performance, including Data Warehouse, Data Mining, Business Process Management, and Competitive Intelligence. In addition, the findings indicate that e-learning which represents system quality, information quality, and self-efficacy has a positive relationship on enhancing business performance. Interestingly, the present findings are inconsistent with those of previous studies showing the variables of interest which have no effect on e-learning and business performance. Taken together, the findings of this study suggest that firms should begin to apply processes related with applying e-learning and developing business performance. The novelty of the present study lies in highlighting the key dimensions of big data, artificial intelligence, and business intelligence when it comes to enhancing e-learning and business performance at Jordanian telecommunications industry.

This research was conducted to determine knowledge acquisition by employing digital technology for public sector employees. This study adopts system quality, information quality, user satisfaction, service quality, and net benefit as the empirical considerations. The data analysis technique in this study used SEM (Structural Equation Modeling). Respondents in this study were 198 people consisting of public sector employees who used a learning management system. The results showed that service quality has a significant effect on user satisfaction. User satisfaction has a significant effect on net benefits. Meanwhile, system quality had no significant effect on user satisfaction, information quality had a significant effect on user satisfaction. The findings would imply the strategies to strengthen the implementation of e- learning is to increase user satisfaction. The finding managerially points out the necessity to evaluate the transformation of classical training programs in terms of face-to-face learning to blended learning by integrating online learning and face-to-face in the public sector knowledge acquisition model of training. The findings present an evaluation using empirical examination and highlights the importance of continuity to arrange action plans in public sector to synchronize knowledge acquisition model through training to obtain behavioral change and wider organizational impact of the training on public sector institutions.

E-learning results from the integration of technology and education and has become an effective learning medium today. E-learning courses and systems with various services are on the rise owing to its importance. E-learning systems should be evaluated to assure successful delivery, effective usage, and positive impacts on learners. A holistic model that identifies various levels of success on a vast range of success determinants was proposed. The model was empirically validated using data obtained from 724 e-learning student users in Jordan. Structural Equation Modelling (SEM) was used in data analyses. Results showed that perceived usefulness of information systems, user training, system quality, and management support have positive effects on user’s behavioral intention; whereas perceived ease of use has not. Also, SEM displayed that user behavioral intention has a positive effect on information systems use, use on student satisfaction, and the latter on student loyalty. Machine Learning (ML) methods produce high correlation values reaching up to 80% in predicting Behavior Intention (BI) from the input factors, and student loyalty from student satisfaction factors. This indicates that the ML are promising techniques to forecast the future targets based on the input independent features.

E-learning in knowledge management was examined in this study, specifically on how it assists organizations in improving knowledge transfer and e-learning management, to increase performance and employee knowledge management. In this study, e-learning and knowledge management systems and technology were jointly implemented, and its impact on organizational performance was examined. Organizational management was also explored. The present study investigated the relationship between knowledge management (KM) and innovation performance (IP). The mediating effect of knowledge Management was deeply explored. Randomly selected managers from 57 Jordanian manufacturing companies were the study samples, and there were 470 managers involved in this study, from strategic, tactical, and operational levels. Questionnaires were used to gather data, and the questionnaire items covered the constructs of knowledge management, organizational learning (OL), knowledge-oriented leadership (KOL) and IP. A research model was proposed and was tested using structural equation modeling (SEM). The findings were as follows: KOL positively affected KM; KOL positively affected IP; OL negatively affected IP; KOL positively affected KM; OL positively affected KM; KM positively affected IP and KM mediated the relationship between KOL, OL and IP.

The goal of this study is to develop and verify a model for successful e-Learning based on the experiences of students in the "new normal". From Jordanian universities, 550 students who have taken any e-Learning course were randomly selected. Data were collected via a survey questionnaire, and Structural Equation Modeling (SEM) was employed to test the proposed study model. The findings indicate that contactless learning and high-quality e-learning systems have a beneficial impact on student satisfaction. In addition, e-Learning cognitive involvement was found to solidify e-Learning satisfaction. Furthermore, the results show a positive and significant impact of e-Learning cognitive involvement and e-Learning satisfaction on e-Learning achievement. Also, e-Learning system quality positively affects e-Learning cognitive involvement, besides a direct impact of contactless learning quality on e-Learning cognitive involvement.

The aim of this research is to study the acceptance of university students to use Microsoft Teams e-Learning system and their intention to use it as a Learning Management System (LMS) for education during the COVID-19 pandemic in Jordan. An ex-tended Technology Acceptance Model (TAM) with a blend of external factors that are used together for the first time was developed and used for the purpose of this study. TAM was used because of its wide use and success during the past few years for evaluating the influence of different factors affecting the acceptance and intention to use e-Learning platforms within educational institutes. However, all the studies were examining the variables and factors affecting the behavioral intention and acceptance to use LMSs when normal and conventional classroom study is available. In this research, seven external variables, in addition to the four TAM variables, were introduced in a model including one external variable, Internet Connectivity (IC), used for the first time in the field of education. A model is constructed by extending TAM with the introduced external variables, hypotheses are constructed and a questionnaire for 396 students at two universities in Jordan is conducted. Reliability, confirmatory factor, model fit, and hypothesized structural model analyses are presented. Results show that all the variables tested affect, either directly or indirectly, the acceptance and intention to use MS Teams during the pandemic. 21 hypotheses were tested between the constructs and found significant except the relations between (Social Norm - Perceived Usefulness) and (Technical Support - Perceived Usefulness).

Educational activities have changed due to the pandemic and it was necessary to respond by giving continuity to the formative processes with virtual platforms as it happened at the Universidad Nacional del Centro del Perú - School of Social Work. The objective was to know the level of satisfaction of students in the use of the virtual platform chosen, using the Questionnaire for the evaluation of learning environments in distance education (Sp-DELES) of 42 questions with dimensions: teacher support, student interaction and collaboration, personal relevance, real learning, active learning, autonomy and satisfaction. A total of 213 students were consulted, the instrument was distributed digitally and anonymously. For the descriptive analysis, the results were ranked in three response categories: agree, indifferent and disagree; the Autonomy dimension was valued with 69.01% agreement and 9.39% disagreement. The dimension with the lowest appreciation was Satisfaction with 25.35% agreement and 28.64% disagreement. Structural equation modeling was performed with SmartPLS, obtaining that Faculty support (FS) and Active learning (AL) have a direct relationship with Satisfaction (S) in the use of the virtual platform with beta values (β) of 0.279 and 0.872 respectively. Contrarily, Real learning (RL) and Autonomy (A) have an inverse relationship with Satisfaction (S) with beta values (β) of -0.025 and -0.122 respectively. The study reflects that there is no relationship between Interaction and Communication among Students (ICS), Personal Relevance (PR) and Satisfaction (S) as the p-values were greater than 0.05. The value of the coefficient of determination (R2) was 0.778 being the representative model. The study is non-experimental, descriptive, explicative and cross-sectional.

Broadening the approval and usage of technology to study online education is not a novel study subject, and several researchers have addressed it. However, the production of a systematic Technology acceptance model capable of examining online education adoption in the current Covid-19 is seen as a vital research path. Literature research was conducted to evaluate the most used external influences of innovation adoption regarding online learning acceptance. The search revealed that computer self-efficacy, corona apprehension, perceived ease of use, and perceived usefulness are the external factors for technology acceptance. The purpose of this paper is to investigate the variables that online education programs' approval among students can influence. 185 students from Jordan's Al-Zaytoonah University and Applied Science Private University participated in the online research. The online questionnaire system in this report was analyzed using SmartPLS tools. According to the findings, perceived usefulness, behavioral intent of use, self-efficacy, and Corona fear all positively affect the adoption of online education programs. The findings of this study were used as a required input in the latest online education interactive analytical production that was used extensively during the pandemic.

This study aims to determine the effect of e-readiness, e-learning, e-book on the achievement of graduate students; and the influence of e-readiness, e-learning, and e-books on the achievement of graduate students. The research population is graduate students with a sample of 210 doctoral students in Jakarta. The sample selection method is simple random sampling. The research method is a survey method with an associative approach. The data analysis technique is structural equation modeling (SEM) using SmartPLS 3.3.3 software and the data was obtained through the distribution of online questionnaires. The results show that there was an effect of e-readiness on graduate achievement; there was an effect of e-learning on graduate achievement; and finally, there was an effect of e-books on graduate achievement. This research can indicate that the curriculum developed by the students is in accordance with the learning outcomes, especially in the implementation of the learning process.

The purpose of the article is to determine the factors affecting the satisfaction of Duy Tan University students for online learning during the acute respiratory infection caused by the new strain of Coronavirus (Covid-19). Based on survey, analysis, processing and evaluation of the obtained results, the article aims to focus the analysis within specific limits with the goal of honestly reflecting and thereby offering solutions for the effective use of online learning in the learning process of students. The results show that there are five factors affecting student satisfaction, in order of influence, as follows: (1) Tuition fees; (2) Teaching staff; (3) Interoperability; (4) Facilities and (5) Training programs. Based on these results, the Board of Directors of Duy Tan University will change several factors in order to improve student satisfaction in online learning in the near future.