Virtualization and Cloud computing are two popular research directions in recent times. Today, Virtualization is being used by a growing number of organizations to reduce power consumption, Server Consolidation, Testing and Development, Dynamic Load Balancing and Disaster Recovery, Virtual Desktops and Improved System Reliability and Security. Virtualization also provides high availability for critical applications, and streamlines application deployment and migrations. Through cloud computing, Information Technology resources can be delivered as services over the Internet to the end user. Virtualization is one of such important core technologies of cloud computing. In this paper, we present a detailed review on virtualization. Furthermore, three technologies for x86 CPU virtualization and the architecture of Xen are introduced. Specifically, we propose an architecture of the cloud computing platform based on virtualization. Finally, we discuss the performance evaluation of server virtualization in saving cost, time and energy consumption.

Ghanaian universities have employed various marketing mix to stimulate demand for their services; particularly in recruitment and engagement of home and international students. This paper examines the relative influence of factors affecting the college choice decisions of students. It is based on a survey of 2,534 admitted students at a major university in Ghana, to which 39 percent of the sample responded. We used Factor analysis to rate 26 University borne attributes upon which student decisions are based. The outcome was used to build a five-scale preference measure, which were evaluated with a qualitative approach in analyzing gathered data using descriptive statistics, cross tabulation and chi square. The results revealed some marketing strategies that can be used in institutions of higher learning to boost students’ enrolment in their order of perceived effectiveness. The following were found to influence decisions: word of mouth (family and friends), proximity/nearness, accreditation/affiliation, affordability and lecturing Style.

The COVID-19 pandemic significantly disrupted traditional education systems globally, with African Higher Education Institutions particularly challenged due to pre-existing infrastructural and technological limitations. This study examines the response of the University of Education, Winneba, in Ghana, to the pandemic by transitioning to online learning using the MOODLE Learning Management System and other digital platforms. This study employs a mixed-methods approach, integrating qualitative observations, quantitative data analysis, and machine learning (ML) techniques to comprehensively explore the transition to online learning at the University of Education, Winneba. Key findings indicate that while the transition enabled the continuity of education for over 92,000 students, challenges such as limited Internet access, inadequate digital literacy among faculty and students, and technical infrastructure limitations were significant barriers. The study recommends targeted investment in digital infrastructure, comprehensive training for educators, and policy reforms to support sustainable online education. This research contributes to understanding the digital transformation of education in African HEIs and offers a framework for improving resilience in future disruptions.

The study aimed to explore the preparedness of preservice teacher trainees (PSTTs) in implementing the computing curriculum in Ghana’s basic schools. It focused on examining curriculum alignment, contextual conditions, preparedness, and the challenges faced during their training. The study employed a descriptive survey design complemented with interviews. The population of this study comprised PSTTs in the Basic Education Departments of teacher training institutions who took computing as part of their programme. A total number of 139 PSTTs were selected using the purposive sampling technique. Descriptive Statistics, Thematic analysis and Multiple Linear Regression were used to analyse the data. The results revealed that there is an alignment between the training institution computing curriculum and the basic school computing curriculum in content and implementation. Another finding showed that while PSTTs exhibit strong theoretical understanding, significant gaps exist in their practical training. The study recommended that Policymakers develop and implement policies that ensure continuous review and alignment of teacher training institution curriculum with the basic school computing curriculum. Furthermore, the study suggested providing PSTTs with more hands-on training and resources to help prepare them to implement the computing curriculum effectively. This study highlights the importance of addressing the preparedness of PSTTs in implementing the computing curriculum, which is crucial for equipping students with the necessary digital skills for the twenty-first century.

The integration of Artificial Intelligence (AI) in education offers unprecedented opportunities to personalize learning experiences, automate routine tasks, and derive data-driven insights. However, this technological evolution is inextricably linked with significant ethical considerations and data privacy challenges. This chapter provides a comprehensive exploration of the critical ethical dimensions and data protection imperatives that arise from the increasing adoption of AI within educational tools and systems. It examines the key ethical issues, including algorithmic bias and fairness, transparency and accountability, the impact on student autonomy, and the evolving role of human educators. Furthermore, it explores the data privacy risks associated with the extensive collection and processing of sensitive student information, highlighting the importance of robust data protection protocols and compliance with legal and regulatory frameworks. The chapter also explores strategies for fostering ethical AI development and implementation, emphasizing the importance of inclusive design methodologies, stakeholder engagement, and the integration of ethical considerations into AI education curricula. Ultimately, the chapter highlights the imperative for a balanced approach that harnesses the transformative potential of AI in education while upholding ethical principles and safeguarding data privacy. It calls for collaborative efforts among policymakers, educators, and technology developers to establish comprehensive ethical guidelines and ensure the responsible and equitable deployment of AI in educational contexts.