Education around the world has been negatively affected by the new coronavirus disease (COVID-19) pandemic. Many institutions had to transition to distance learning in compliance with the enforced safety measures. Distance learning might work well for settings with stable internet connections, professional technical teams, and basic implementation of technology in education. In contrast, distance learning faces serious challenges in less fortunate settings with inferior infrastructure. This report aims to shed light on the immediate action steps taken at a leading pharmacy school in Iraq to accommodate for the enforced changes in pharmacy education. The University of Baghdad College of Pharmacy went from less than minimal technology impl

The study aims to identify the impact of electronic games on increasing the dropout rate among students in the basic stage in Jordan from their teachers’ point of view. The study adopted a descriptive survey method. Its community consisted of all fe(male) teachers of the basic stage in public and private schools, (First Amman, Irbid, and special education in Zarqa and Amman). The electronic questionnaire was used as a tool for the study. The results have shown that the effect of electronic games on increasing the dropout rate among students in the basic stage in Jordan was high. Besides, there are statistically significant differences due to the gender variable for males. There are statistically significant differences due to the varia

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

This research aimed to identify the structural model of the relationship between emotional creativity and self-efficacy among male and female students of the preparatory year at Tabuk University. The current study adopted the descriptive correlational approach, as it is appropriate to the nature of the study. The study tools contained (60) items that measure the relationship between emotional creativity and self-efficacy among the male and female students of the preparatory year at Tabuk University. The study sample was chosen by the stratified random method of the study community, where the study sample reached (183) male and female students of the preparatory year at the University of Tabuk. The results of the study showed that there a

For over a decade, educational technology has been used sparingly in our schools and universities. Online training courses have been used since 2003 to fill the gaps in our learning system and to add extra program besides classroom learning. This paper aims to investigate the Iraqi EFL instructors’ participating in online training courses and its influence on the process of teaching and learning.

       The sample of present study consists of 30 instructors from University of Baghdad. The questionnaire of sixteen items was constructed. After ensuring validity and reliability of questionnaire, it was applied on March 2013 and the result shows that most of instructors improve their teaching methods b

Given the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University

The study aimed to explore the relationship between future anxiety and life orientation of male and female nurses, working in government hospitals of Gaza Strip governorates. The study sample consisted of 228 nurses (131 male nurses and97 female nurses. To achieve the study objectives , the researcher used the future anxiety scale, prepared by the researcher, and life orientation scale prepared by Scheier and Craver (1985 ) and translated into Arabic by Bader Al-Ansari . The results indicated that the level of future anxiety among nurses working at government hospitals was (64.85%), a high percentage, whereas life orientation was (65.96%), a low percentage. Additionally , the results showed that the Pearson correlation coefficient betwee

The study seeks to analyze the perceptions of audience in UAE towards the performance of Emirates Satellite TV Channels. It analyzed the exposure motivations of audience to satellite TV channels, its positive and negative aspects and to what extent they abide by media ethics. A survey is conducted with a sample of four hundred. The study shows significant differences between male and female towards the characteristics of TV channels, its positive and negative aspects and its commitments to media ethics.

            The study also shows that the expectancy value model and third person effect model are applicable in studying the perceptions of audience and media people in UAE t

The increasing demand for continual learning in sequential data processing has led to progressively complex training methodologies and larger recurrent network architectures. Consequently, this has widened the knowledge gap between continual learning with recurrent neural networks (RNNs) and their ability to operate on devices with limited memory and compute. To address this challenge, we investigate the effectiveness of simplifying RNN architectures, particularly gated recurrent unit (GRU), and its impact on both single-task and multitask sequential learning. We propose a new variant of GRU, namely the minion recurrent unit (MiRU). MiRU replaces conventional gating mechanisms with scaling coefficients to regulate dynamic updates of hidden

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed