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 study aimed to identify the role of school administration in achieving educational and learning goals from the point of view of educational supervisors in the stage of basic education. The descriptive method was adopted. As for the sample size, it has reached (59) educational supervisors. A questionnaire consisting of 29 paragraphs divided into four areas was used. The data were statistically analyzed on the Chi-square test, the percentage, and the mono-variance analysis. The result showed that the school administration contributes to achieving educational goals. It also works to solve problems in democratic ways, and in modern methods, there are differences in the criteria for choosing the headmaster. The study recommended that sch
... Show MoreOrganizational learning is one of the most important means of human resource development in organizations, but most of the organizations, especially public ones do not realize the importance of organizational learning enough, and estimated his role accurately in building intellectual capital, the resource competitive importantly for organizations of the third millennium and who suffers is other end of lack of understanding of its meaning and how to prove its presence and measured in public organizations, so there is the need for this research, which aims to investigate the effect of organizational learning its processes (knowledge acquisition, Information transfer, Interpreting the information, Organizational me
... Show MoreThis study aimed to identify the political factors influencing the performance of specialized journalists in Iraqi electronic newspapers. The significance of the study stems from the role of communication in newspapers that have established themselves in reality due to their wide dissemination, multiple uses, expanding freedom base, and the current diversity in perspectives. These newspapers highlight and publish societal issues of concern. The importance of these newspapers is associated with their creators who face various factors affecting their value and performance, whether positively or negatively. In light of this, the political factor was identified as the primary driver for other influencing factors. The
... Show MoreResearchers need to understand the differences between parametric and nonparametric regression models and how they work with available information about the relationship between response and explanatory variables and the distribution of random errors. This paper proposes a new nonparametric regression function for the kernel and employs it with the Nadaraya-Watson kernel estimator method and the Gaussian kernel function. The proposed kernel function (AMS) is then compared to the Gaussian kernel and the traditional parametric method, the ordinary least squares method (OLS). The objective of this study is to examine the effectiveness of nonparametric regression and identify the best-performing model when employing the Nadaraya-Watson
... Show MoreThis article focuses on the relationship of gender to the effectiveness of both women and men in public relations work. Its aim is to identify the extent to which public relations employees are aware of the concept of gender, and to reveal the role of the institution in determining certain roles for both women and men at work, as well as to find out which employees are most effective in public relations activities within the institution.
The researcher uses public relations employees and officials in Iraqi ministries as a research sample to capture the point of view of both parties on the effectiveness of workers in public relations based on the definition of gender. The sample consists of 396 individuals
... Show MoreThe problem of research is that there are differences between learners in processing in formation in general and there is variation at the learners level perform scrolling skill of the passes up and down by the volley ball .Therefore the researchers decided to conduct astudy through which identify the relationship between information processing and the skill of scrolling from the top and bottom by the volleyball. The researchers used the descriptive approach by themethod of interconnectivity .Asampleconsist of21 students from first staye in collage of physical education and sports science for Girls(university of Baghdad) and attest has been applied(process information and scroll up and down) on the research sample after the required
... Show MoreMost of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B
... Show MoreThe advancements in Information and Communication Technology (ICT), within the previous decades, has significantly changed people’s transmit or store their information over the Internet or networks. So, one of the main challenges is to keep these information safe against attacks. Many researchers and institutions realized the importance and benefits of cryptography in achieving the efficiency and effectiveness of various aspects of secure communication.This work adopts a novel technique for secure data cryptosystem based on chaos theory. The proposed algorithm generate 2-Dimensional key matrix having the same dimensions of the original image that includes random numbers obtained from the 1-Dimensional logistic chaotic map for given con
... Show MoreIn data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.