With the gradual penetration of artificial intelligence technology into various fields of society, it has brought many deeper and broader impacts, gradually improving the status of artificial intelligence in talent cultivation and education to adapt to the current development of social intelligence technology. Therefore, as the core course of artificial intelligence education in universities, machine learning needs to deeply analyze and explore the main factors that affect its development, in order to better mobilize students' learning enthusiasm and teachers' educational innovation, enhance the teaching and learning effectiveness of the course, and maximize the exploration of the educational achievements of artificial intelligence.

As Bangladesh faces its current energy crisis, public-private partnerships (PPPs) emerge as a promising solution, bridging the strengths of both sectors toward a brighter, more electrified future. This research focuses on the challenges in Bangladesh’s power sector: increasing electricity demand and the imperative for a consistent supply of renewable energy sources. The research employs content analysis, exploring various aspects, including policy documents, regulatory frameworks, stakeholder engagements, and resource assessments, with a specific focus on three key variables: regulatory framework, stakeholder engagement, and informed policymaking. Drawing on the ‘resource-based view’ theory, the study emphasizes the significance of ‘mitigating resource risks’ through ‘resource assessment.’ Empirical support is derived from an extensive review of literature in reputable journals and research articles, enhancing the research’s credibility with real-world evidence. The study provides a practical roadmap for stakeholders navigating Bangladesh’s power sector, addressing energy challenges, and promoting sustainability.

The study aims to explore the extent to which Jordanian e-news sites rely on artificial intelligence applications in their news content. The researchers will use a media survey methodology, and the sample will consist of 45 editors-in-chief and editors from 10 Jordanian news sites, namely: Ammon, Khabrny, Joe24, Saraya, Amman Net, Jafra, Crown News, Petra, Kingdom, and Roya. The researcher will use an electronic questionnaire, which led to several findings, the most significant of which are: Many news and media sites have introduced artificial intelligence systems to enhance the services they provide to the public. A significant number of journalistic and electronic media websites have shown interest in data analysis tools for their media services. Electronic news sites are clearly striving to improve their capabilities in using artificial intelligence technologies to enhance the services they provide to the Jordanian audience. Additionally, most electronic media websites have expressed a willingness to develop a plan to improve cybersecurity systems to protect against hacking and intrusion attempts, safeguarding their data and the AI systems that operate continuously.AI systems in media organizations also aim to enhance the news experience for users by enriching media services with modern, communicative content.

This study explores the early travelers to Petra, Jordan, during the 20th century. To gain insights into the evolution of early travel experiences to Petra during this specific period, the researchers utilized narrative analysis and conducted in-depth interviews with 14 elderly inhabitants of Wadi Musa who resided in the area at that time. These interviews provided valuable information and served as a basis for visually representing the primary routes that emerged from the participants’ narratives. This study delves into the accessibility of early travelers to Petra in the 20th century by creating a comprehensive map that outlines the trails, byways, and roads used by these travelers to reach Petra. The study’s findings also revolve around the identified stages derived from the data gathered through these interviews.