Low integrity is a challenge for any organization. However, most organizations emphasize integrity without explaining what is required of an individual with high integrity. Exhibiting high integrity is necessary for academics; yet, the level of academic integrity remains unclear. Therefore, the purpose of this study is to examine the integrity level of academicians in a Malaysian public university. This paper shares the findings on the level of integrity of academics based on a questionnaire completed by 213 academicians. Data were collected by survey questionnaire and was analyzed using descriptive and inferential statistics. An overall mean score of 9.45 from a possible 10.0 indicated a high level of integrity among academics. The self-evaluation results by academics also demonstrated that they have attained integrity at a high level for their generic task, teaching and learning, research and publications and service for community with a mean score between 9.36 and 9.49. The value with the highest mean score was for “service to community”, whereas the lowest was for “research and publication”. These findings show that the university has successfully instilled values of integrity among academicians. Nevertheless, the university must continue to enhance academic integrity by exploring religiosity. Using Google Scholar, a literature search identified an Islam-based academic integrity model to explain the quantitative findings. Finally, a mixed method approach and involving all universities in Malaysia are recommended to further the findings of this study.

Food safety in supply chains remains a critical concern due to the complexity of global distribution networks. This study develops a conceptual framework to evaluate how food safety risks influence supply chain performance through predictive analytics. The framework identifies and minimizes food safety risks before they cause serious problems. The study examines the impact of food safety practices, supply chain transparency, and technological integration on adopting predictive analytics. To illustrate the complex dynamics of food safety and supply chain performance, the study presents supply chain transparency, technological integration, and food safety practices and procedures as independent variables and predictive analytics as a mediator. The results show that supply chain managers' capacity to anticipate and control risks related to food safety can be improved by predictive analytics, leading to safer food production and distribution methods. The research recommends that businesses create scalable cloud-based predictive model solutions, combine data sources, and employ cutting-edge AI and machine learning tools. Companies should also note that strong, data-driven approaches to food safety require cooperative data sharing, regulatory compliance, training initiatives and ongoing improvement.

In China, ideological and political education is currently the hot direction of teaching reform in various colleges and universities, yet the development of appropriate teaching evaluation methods needs to catch up. This study addresses the pressing need for a preliminary investigation into the complex relationships among ideological and political education, the students’ learning satisfaction and teaching quality. This research examines the influence of teaching and ideological and political education quality on students’ satisfactions by designing a set of scales, collecting about 3800 questionnaires. Utilizing Structural Equation Modeling (SEM) and qualitative interviews, this study reveals that the teaching quality directly affects students’ learning satisfaction and ideological and political education. Notably, ideological and political education can also affect students’ learning satisfaction. The findings underscore the importance of including ideological and political education assessments in evaluating courses. This research contributes to the ongoing dialogue on effective teaching evaluation methods in the context of evolving educational practices.

While the rapid development of artificial intelligence has affected people's daily lives, it has also brought huge challenges to high school mathematics teaching, such as restructuring the classroom teaching structure, transforming the role of teachers, and selecting classroom teaching methods. Based on this, the article explores the application strategies of AI technology in improving knowledge introduction, improving mathematics classroom efficiency and stimulating students' learning interest, with a view to optimizing classroom teaching links, improving students' core discipline quality, and promoting the development of high school mathematics teaching informatization.

The present research focuses on researching the impact of the diverse communication media that facilitate or develop Student Motivation and Engagement in the educational systems of the states in the Gulf, especially Oman. The main goal of this work is to determine which type of method is most effective in encouraging students in view of cultural and technological factors present in the region. Comparisons using hypothesis testing and structural models which provided higher T value for Technology-Based Communication Methods (TBCM) and Human Face-to-Face Communication Methods (HFtFCM). Next, the research hypothesis H2 that TBCM has a direct positive relationship with SMaE was supported by the following regression coefficients: β = 0.177, t = 4.493; p = 0.000. On the other hand, there was no effect of HFtFCM on SMaE as indicated by a regression coefficient of 0.056 (p < 0.124) for this hypothesis and therefore, this hypothesis was rejected. The analysis using the mediator of Student Perception of Communication Effectiveness (SPoCE) only partly mediates TBCM and SMaE (β = 0.047, t = 3.737, p = 0.000). However, SPoCE was found not to moderate the relationship between HFtFCM and SMaE (β = −0.01, t = 1.125, p = 0.005). The present study underlines the efficiency of TBCM in the area of student engagement, while face-to-face conversation does not play significant part in this process. The obtain results conclude that, the traditional and technological evolution in the Gulf region supports the adoption of TBCM in educational systems. Such approaches support with the technological learning and likings of students, offering greater flexibility and engagement. Educational systems must highlight TBCM to better meet the growing needs of their student, while identifying that face-to-face remains important, though secondary, in energetic motivation.