The purpose of the current study is to examine the mediating role of intercultural communicative competence on the relationship between teaching of English language and learning at Chinese higher vocational colleges. The convenience sampling technique was used to collect data from 668 teachers, teaching English language subjects in different public and private Chinese higher vocational colleges. Smart partial least squares-structural equation modeling on SmartPLS software version 4 was used to test the hypotheses. The result revealed the direct effect of English language teaching (ELT) is not significant on English language learning (ELL). However, the intercultural communicative competences (ICC) have been tested and proved to be a potential mediator between English language teaching and learning. Because the indirect effect of ELT on ELL is positive and significant through mediator ICC. Therefore, based on the findings of this study, it can be concluded that the inclusion of intercultural communication ability is a crucial component in the vocational education of college students. Policymakers should be cautious about promoting and expanding the availability of cultural teaching and learning across demographic conditions (e.g., linguistic and ethnic diversity, age, and gender) and various levels of language proficiency. In accordance with the effects of teacher education and professional development programs, the implementation of ICC content necessitates a harmonization of pedagogical approaches and assessment practices across designated levels in order to effectively achieve educational objectives. To promote ICC in English language education, there must be clear guidelines and communication to school leaders, educators, and administrators regarding the necessity and goals of cultural integration.

This paper presents a practical approach to empowering software entrepreneurship in Saudi Arabia through a unique course offered by the Software Engineering department at Prince Sultan University. The course, SE495 Emergent Topics in Software Engineering: Software Entrepreneurship, combines software engineering and entrepreneurship to equip students with the necessary skills to develop innovative software solutions that solve real-world problems. The course covers a range of topics, including platform development, market research, and pitching to investors, and features guest speakers from the industry. By the end of the course, students will have gained a deep understanding of the software development process and its intersection with entrepreneurship and will be able to develop a working prototype of a software solution that solves a real-world problem. The course’s practical approach ensures that students are well-prepared to navigate the complexities of the digital and software sectors and succeed in an ever-changing business landscape.

Relational database models offer a pathway for the storage, standardization, and analysis of factors influencing national sports development. While existing research delves into the factors linked with sporting success, there remains an unexplored avenue for the design of databases that seamlessly integrate quantitative analyses of these factors. This study aims to design a relational database to store and analyse quantitative sport development data by employing information technology tools. The database design was carried out in three phases: (i) exploratory study for context analysis, identification, and delimitation of the data scope; (ii) data extraction from primary sources and cataloguing; (iii) database design to allow an integrated analysis of different dimensions and production of quantitative indicators. An entity-relationship diagram and an entity-relationship model were built to organize and store information relating to sports, organizations, people, investments, venues, facilities, materials, events, and sports results, enabling the sharing of data across tables and avoiding redundancies. This strategy demonstrated potential for future knowledge advancement by including the establishment of perpetual data updates through coding and web scraping. This, in turn, empowers the continuous evaluation and vigilance of organizational performance metrics and sports development policies, aligning seamlessly with the journal’s focus on cutting-edge methodologies in the realm of digital technology.

This paper explores the integration of Large Language Models (LLMs) and Software-Defined Resources (SDR) as innovative tools for enhancing cloud computing education in university curricula. The study emphasizes the importance of practical knowledge in cloud technologies such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), DevOps, and cloud-native environments. It introduces Lean principles to optimize the teaching framework, promoting efficiency and effectiveness in learning. By examining a comprehensive educational reform project, the research demonstrates that incorporating SDR and LLMs can significantly enhance student engagement and learning outcomes, while also providing essential hands-on skills required in today’s dynamic cloud computing landscape. A key innovation of this study is the development and application of the Entropy-Based Diversity Efficiency Analysis (EDEA) framework, a novel method to measure and optimize the diversity and efficiency of educational content. The EDEA analysis yielded surprising results, showing that applying SDR (i.e., using cloud technologies) and LLMs can each improve a course’s Diversity Efficiency Index (DEI) by approximately one-fifth. The integrated approach presented in this paper provides a structured tool for continuous improvement in education and demonstrates the potential for modernizing educational strategies to better align with the evolving needs of the cloud computing industry.

As the complexity and scale of software applications increase, the challenges associated with testing these systems grow correspondingly, necessitating innovative and sustainable testing strategies. This paper explores a multifaceted approach aimed at addressing the intricate challenges inherent in testing large-scale software applications. Through a comprehensive examination of current industry practices and emerging trends, this study introduces a novel framework that integrates advanced testing techniques with state-of-the-art tools. This framework not only mitigates the challenges posed by the complexity and size of modern applications but also enhances the efficiency and effectiveness of the testing process. Key aspects of this research include a detailed exploration of test methodologies suited for large-scale applications, an evaluation of advanced tools designed for complex test scenarios, and an analysis of the impact of the test environment on sustainability. The findings offer valuable insights and actionable strategies for software development and testing professionals aiming to optimize testing processes and improve the quality and sustainability of their software in a rapidly evolving technological landscape.