The approach to delivering education in Libya has undergone a significant transformation in recent years. Various tools now support the educational process, shifting it from rote learning to creativity, interaction, and skill development. This study aims to examine the feasibility of implementing e-learning in Libyan universities. A statistical analysis was conducted on approximately 400 samples to identify patterns. The findings highlight the importance of e-learning in enhancing the quality of education by outlining its benefits and limitations. Moreover, it was found that employees consider e-learning an effective alternative to traditional education. Despite this consensus, concerns remain regarding the availability of sufficient infrastructure. 

Background and aims

In recent years, the education sector in Libya have been affected by wars and political fluctuations, impacting the quality and availability of education. There have been challenges in providing the necessary educational resources, as well as in training and qualifying teachers. E-learning, it can be an effective tool in improving education under difficult circumstances. Online education can provide opportunities for students to access educational resources easily, and can contribute to enhancing communication between teachers and students. E-learning can also play a role in developing students’ technology skills, which is important in our modern era. In 2019, the Faculty of Science at the University of Gharyan partially implemented online learning as a response to COVID-19 pandemic, and this program continued for two academic terms. Therefore, the paper aims to highlights both the advantages and limitations of E-learning within the environment of university education in Libya

Background and aims. Online learning has become increasingly popular in recent years due to its convenience and flexibility. However, it can be challenging for learners to stay engaged and motivated when studying online. One solution to this problem is the use of chatbots, which are computer programs that use Artificial Intelligence (AI) and Natural Language Processing (NLP) to simulate conversation with humans. ChatGPT, a language model that can generate human-like conversation in real time developed by OpenAI, has the potential to revolutionize online learning. This is by providing personalized and interactive learning experiences. This paper provides an overview of the potential impact of ChatGPT on online learning, exploring the benefits of using ChatGPT in enhancing the online learning process as well as identifying the limitations and challenges of this technology. Methods. Two experiments were conducted to evaluate ChatGPT's effectiveness in the domain of learning. Experiment 1: presents the authors’ experience with ChatGPT as Arabic speakers. Experiment 2: reviews ChatGPT’s performance in writing academic papers and retrieving references. Results. Overall, both experiments demonstrated the limitations of ChatGPT in generating reliable academic text that is sufficient for a scientific paper both in Arabic and English. Conclusion. ChatGPT is a tool that can guide learners throughout their learning process. But this tool exhibits limitations that learners need to dedicate more efforts to succeed

Face recognition is a biometric technique that can be used for a variety of purposes, such as national security, access control, identity fraud, banking, and finding missing children. Faces are highly dynamic and facial features are not always easily extracted, which can lead to discarding textural information like the smoothness of faces, a hairstyle that, might contain strong identity information. In addition, brightness, scale, and facial expressions play a significant role in the face-recognizing process. Therefore, face recognition is considered as a difficult problem. To figure out this problem effective methods using databases techniques are needed. This paper describes face recognition methods and their structure. Based on Wen Yi Zhao and Rama Chellappa work the face recognition methods are divided into three groups: a holistic approach, feature-based approach, and hybrid approach, where Principal Component Analysis PCA, a holistic approach method, is presented as a mathematical technique that can assist the process of face recognition. Also, the paper shows how the PCA is used to extract facial features by removing the principal components of the available multidimensional data.