Search results

This exploratory research intends to comprehend the perspectives of high school teachers toward incorporating technology in instruction.

Drawing upon Davis’s technology acceptance model as a theoretical framework, this study examines several aspects, including teachers’ access to and ease of using technology, as well as the support provided by educational institutions for the integration of technology in teaching. The quantitative data analysis (reliability tests, descriptive statistics, Mann–Whitney test) was computed via Statistical Package for the Social Science software. Furthermore, the study uses structural equation modeling to validate and substantiate the relationships (path analytical model) between the examined variables.

The key finding points to the fact that female teachers have statistically significant positive beliefs toward technology usage/integration in instruction than their counterparts (i.e. male teachers) (p < 0.01). Even though there exists no significant difference in computer usage/integration of teachers across age, nationality, grade, educational level and years of teaching experience, findings demonstrated the impulse of assisting and acclimating high school teachers to use technology in their education. Conclusively, the study culminates with future scope, considering the derived findings.

The study illustrates a validated framework (through path analytical modeling) for teachers’ technology integration in instructions. It highlights that the extent to which teachers use technology in the classroom is impacted by factors such as their accessibility to technology, comfort with its usage and the level of institutional support they receive for integration.

This study explored the perceptions of Arab professionals toward pracademia and the ways they position themselves as professionals in this field.

Narrative data were elicited through semi-structured interviews with a total of eighteen pracademics identified for their work in teacher education. Participants included ten professional development (PD) specialists, three university supervisors and five specialists working at the Ministry of Education in Qatar.

Narrative analysis of the interviews revealed variations in their identity renegotiations, with one group experiencing an emerging pracademic identity and the other group “holding on” to their previous practitioner identities. The narratives further provided insight into Arab pracademics relating to three themes: (1) definitions and roles, (2) knowledge and skills and (3) relationships with others, all of which pertain to pracademic identity construction.

The study contributes to understanding the identity renegotiation of pracademics working in multiple contexts in an Arab setting. Several recommendations are offered to support pracademics' identity renegotiation as a social activity.

Purpose: In this study, monolith analysis methods, microservice identification, and decomposition methods proposed for the transition to microservice architectures that enable the development of appropriate solutions by adapting to the complex demands that will shape the technological infrastructure of the future are evaluated.

Need for the study: Decomposition from monolithic architectures to microservices has become a popular approach in organizations and companies with Industry 5.0. This transformation of Industry 5.0 enables businesses to gain a competitive advantage and can provide a quick solution to personalized problems such as personal service systems.

Methodology: The study, decomposition from monolith to microservice, initially includes monolith analysis, followed by microservice decomposition review. Various classification methods have been proposed for microservice identification and decomposition and are aligned with Industry 5.0 principles, focusing on artificial intelligence (AI)-based approaches, especially human-centered AI.

Findings: Four analysis methods (domain, static, dynamic, and version) are identified for monolith analysis, with static and dynamic being the most common. Version analysis is not typically used alone. In the decomposition phase, clustering-based methods are prevalent due to the uncertain dimensions of microservices. Rule-based and unsupervised methods are identified for decomposition, with AI algorithms like affinity propagation, Kmeans clustering, hierarchical clustering, Hungarian algorithm, genetic algorithm, latent Dirichlet allocation (LDA), and minimum spanning tree (MST) being employed.

Practical implications: Microservice architecture enables flexibility, scalability, and resilience compared to monolithic structures. Decomposing large-scale monolith projects into microservices is challenging, requiring selection of appropriate monolith analysis methods based on project details (e.g., domain analysis for detailed Unified Modelling Language (UML) diagrams) before proceeding with decomposition. This transformation improves deployment, maintenance, fault isolation, and scalability, while allowing for diverse service-specific databases and programming languages.

Science, Technology, Engineering, and Mathematics (STEM) education, its importance, and its difficulties have been defined. This chapter seeks to present the digital tools that have been used during the pandemic period and that have been focused on promoting STEM education at different levels. The efforts made by educational organizations worldwide are mentioned. Different regions are shown presenting the best experiences of digital tools that enhance the elements of STEM and can be extended to different levels of education from elementary school to university. On the other hand, successful experiences of the use of technological tools from the teachers' point of view are shown, depicting the tools that have worked the most during the process of adapting to online classes to devise a much better educational plan that continues to take advantage of digital tools for STEM education.