Omer Gibreel

This study investigated the impact of prompt engineering competence, knowledge management, and task-individual-technology fit on the continued intention to use artificial intelligence (AI), as well as their implications for educational sustainability. Data from 437 undergraduate students who use AI tools for academic purposes were analyzed using PLS-SEM. The results indicated that prompt engineering competence significantly predicts knowledge acquisition and knowledge application, which, in turn, significantly predict both task-technology fit (TTF) and individual-technology fit (ITF). Furthermore, TTF and ITF were found to have significant impacts on the continuous intention, which, in turn, positively predicts educational sustainability through generative AI. The results of the multi-group analysis revealed that the hypotheses were supported in both the female and male samples and that the model maintained a consistent and robust structure across genders. Overall, the findings provide substantial evidence on how generative AI supports sustainable learning in education by developing prompt engineering skills, promoting effective knowledge management practices, and ensuring technology alignment.

Generative Artificial Intelligence (Gen-AI) systems offer significant opportunities for personalized learning in higher education. Studying the effects of personality traits on the use of Gen-AI is crucial for understanding the role of individual differences in integrating this innovative technology into education. Therefore, this study investigated how the Big Five personality traits, age, and gender predict the educational use of Gen-AI in higher education. In this study, data were obtained from 1016 university students through an online survey. The data obtained using the Five Factor Personality and educational use scales were analyzed using linear regression. Artificial neural networks (ANNs) were employed to investigate more complex and non-linear relationships. Additionally, multiple linear regression and multigroup analysis were employed to investigate age and gender differences. Significant and positive relationships were found between openness to experience, conscientiousness, extraversion, and the educational use of Gen-AI. However, neuroticism showed a negative association, while agreeableness did not demonstrate a significant association. The ANN model showed that openness was the strongest predictor. The results indicated that the effect of certain personality traits on Gen-AI use differed significantly between men and women. These findings significantly advance our understanding of the relationship between personality traits and the use of Gen-AI in higher education.

Background: Digital health interventions, especially mobile apps, have become instrumental in helping women at risk of polycystic ovary syndrome (PCOS), increasing their understanding of the condition, improving self-care, and fostering empowerment. However, their rapid proliferation has brought about significant challenges regarding quality assessment and evidence-based determination. Therefore, establishing reliable quality assessment methods is essential to assist patients with PCOS in identifying effective and trustworthy mobile health tools. Objective: This study was designed to assess the content and quality of mobile apps developed for patients with PCOS using the Mobile App Rating Scale (MARS) to provide insights into their strengths, limitations, and areas needing improvement. Methods: In this descriptive-analytical study conducted in June 2024, a comprehensive search was performed to identify English and Persian mobile apps related to PCOS through the Café Bazaar and Google Play Store platforms, using both direct search methods and auxiliary tools such as AppAgg and AppBrain. Two trained reviewers (AR and NN) independently reviewed the apps using the MARS tool. The interrater reliability was measured using the intraclass correlation coefficient test. The quality of each app was scored across 4 dimensions: engagement, functionality, aesthetics, and information quality. Results: Of the initial 199 apps identified, 15 met the inclusion criteria after screening and updates. The interrater agreement rate was 85%, which is considered acceptable. The apps’ overall quality was sufficient, as assessed using the MARS, with a mean score of 3.6 (SD 0.52) of 5. Functionality and aesthetics emerged as the highest-scoring dimensions, highlighting user-friendliness and visual appeal (n=10). In contrast, engagement following information quality received the lowest average score, indicating limited interactivity and gaps in providing evidence-based information. The Ask PCOS app achieved the highest overall score, performing exceptionally well in subjective quality (4.75) and app-specific quality (4.33), reflecting its strong capacity to positively impact users’ knowledge, attitudes, and behaviors related to PCOS. Uvi Health and Ask PCOS scored highest in engagement (4.2), while PCOS & PCOD Diet & Remedies led in functionality (5), and Uvi Health topped aesthetics (5). Conclusions: The findings revealed that even though many available PCOS-related apps demonstrate strengths in technical performance and design, critical limitations persist regarding user engagement and the credibility of the information provided. The predominance of commercially affiliated apps without academic or clinical oversight was identified as a key contributing factor to these shortcomings. These results underscore the need for future app development to incorporate more user-engaging features, reliable evidence-based content, and personalization strategies to enhance user engagement and support effective PCOS self-management. Addressing these limitations and leveraging the capabilities of existing mobile devices are essential steps toward improving the overall quality and impact of mobile health interventions for individuals with PCOS.

In a digitized world where artificial intelligence (AI) is rapidly infiltrating every aspect of our lives, it is crucial to utilize generative AI tools effectively. While the demand for AI technologies is increasing rapidly, challenges arise in their practical use. Accordingly, this study aims to develop a novel scale to measure users’ level of competence in prompt engineering. The psychometric properties of the Prompt Engineering Competence Scale (PECS) were evaluated using data obtained from 437 users. An exploratory factor analysis was performed to investigate the factor structure of the PECS. The results revealed a one-factor structure with a Cronbach's alpha value of 0.92. Confirmatory factor analysis results indicated that the one-factor model provided a good fit to the data. In the final stage, the item discrimination index was calculated to improve further the reliability and validity of the newly developed scale. The results suggest that the scale items were able to reliably discriminate users. These findings collectively indicate that the PECS is a valid and reliable instrument for measuring users’ level of competence in prompt engineering.

Purpose: With the advent of the information age and the growth of the Internet, many countries worldwide have looked into ways to incorporate novice innovation from information technology into their educational system. In tandem with the growth of this new form of innovation in learning, the national innovation system in the Middle East and North Africa (MENA) faced two main obstacles: policies that support the acceptance of novice innovation, and bridging the digital divide. Our study looks into the adoption of e-learning systems in Sudan and provides policies that would help increase the adoption of e-learning systems in Sudan. Design/Methodology/Approach: The paper is based on reliable and valid constructs that have been validated in several settings. It employs PLS to explore the significance of performance expectancy, effort expectancy, social influence and price value, which shows an intention to use e-learning systems. Findings: At the macro level, the study points out a strong need for a public-private partnership to support innovation in e-learning, especially with the advent of pandemics such as COVID-19 and civil unrest. The partnership should work on lowering Internet costs (Internet mobile service provider side) and Internet taxation costs (government side) for students who use the Internet to access e-learning and universities that implement e-learning systems. At the micro-level (student level), performance expectancy, effort expectancy, social influence and price value all showed a positive relationship with intention to use. Originality/Value: The study explores the validity and reliability of the UTAUT model in the context of Sudan as a North African country, paving the way for more quantitative and empirical research in Sudan. This study would pave the way for further extended research that looks into other factors affecting the development of e-learning systems in the developing world. On the practical side and at the micro-level, universities in Sudan and the MENA region must incorporate digital literacy courses from the student’s first year as soon as possible. These courses would empower them to be on the same level as their peers in other parts of the world and help them access the world of knowledge that the Internet has to offer. On the macro-level, public-private partnerships are essential in setting policies that reduce the cost incurred by the student in accessing the Internet across the MENA region. This partnership would help empower students to use these systems at an affordable price, bridging the gap that hinders them from accessing the Internet. Keywords: Sustainable Development; E-learning; Education; Civil Unrest; Digital Divide. Citation: Gibreel, O. and Abdalla, A. (2025): Bridging the Digital Divide: Sustainable E-learning During Pandemics and Civil Unrest. World Journal of Science, Technology and Sustainable Development (WJSTSD), Vol. 20, Nos 1/2, pp. WASD: London, United Kingdom.

Background: Snakebite statistics in Sudan are lacking despite the high estimated burden of the problem. One study in Sudan reported the presence of 17 medically significant snakes belonging to three major families: Burrowing asps, Elapidae, and Viperidae. These snakes usually become abundant during and after the rainy season, and most snakebite victims are farm workers. This study was set out based on the observed snakebite management, poor outcomes and lack of information on the healthcare provider’s knowledge of this serious, deadly medical and health condition in snakebite-endemic regions of Sudan. Materials and methods: In August 2022, a descriptive cross-sectional survey was conducted involving 394 medical and healthcare providers in snakebite-endemic regions of Sudan (Gaddarif, Sinnar, Khartoum, and Kassala). A validated questionnaire was used. It consisted of seven sections addressing the study population demographic characteristics, knowledge of snakes, snakebites, and their management. Data analysis used various statistical tests using Microsoft Excel and the Statistical Package for Social Sciences (SPSS) version 20 (IBM SPSS Inc., Chicago, IL) was done. Results: Among the 394 participants (44.7% males, 53.3% females), 58.1% demonstrated adequate knowledge of snakes, and 45.3% exhibited adequate knowledge of snakebites. A mere 25.9% received training in snakebite management, with 60.4% possessing adequate knowledge in this domain. Only 14% expressed high confidence in managing snakebites, and 40.9% reported having protocols for snakebite management at their health facilities. Conclusion: The study highlighted the inadequacy of healthcare providers’ knowledge in snakebite-endemic areas in Sudan regarding snakes, snakebites and snakebites management. Urgent interventions, such as intensive continuing professional education and training, are essential to address this neglected medical and health problem.