Students from different cultures possess varying levels of skills in learning, remembering, and understanding concepts. Some terms and their explanations may seem easy for one group of students but difficult for another. Therefore, delivering educational content that aligns with student’s learning capabilities is a challenging task based on cultural orientations. This study addresses the learning challenges by developing a Thesaurus Glossary E-learning (TGE) framework method. This study introduces the TGE method which is a multi-language tool with visual associations that adapts to students’ capabilities. It also examines cultural differences and native languages, particularly aiding Arab Native to visualize appropriate terms (thesaurus) and their explanations (glossary) based on students’ learning capabilities. TGE learns from students’ term selection behavior and displays terms at a simple or advanced level that matches their learning ability. Additionally, TGE demonstrated its effectiveness as an e-learning tool, accessible to all students anytime and anywhere. The study analyzed 314 records related to student performance, out of which 114 students were surveyed to evaluate the effectiveness of the TGE method. This work presents TGE as a novel e-learning tool designed to enhance conceptual thinking within the context of modern educational practices during the digital transformation. TGE is based on artificial intelligence algorithms and associative rules that simulate the human brain, establishing logical connections between related key terms and sketching associations among diverse facets of a situation. An experiment was conducted at a private university in the Sultanate of Oman to assess the effectiveness of the proposed TGE tool. TGE was integrated with selected subjects in information systems and used by the students as a resource for e-learning methods and materials. The results show that 85% of students who used TGE improved their performance by 19%. We believe this work could establish a new smart e-learning teaching method and attract modern and digital universities to enhance student learning outcomes linked with conceptual thinking.

This study investigates the impact of artificial intelligence (AI) integration on preventing employee burnout through a human-centered, multimodal approach. Given the increasing prevalence of AI in workplace settings, this research seeks to understand how various dimensions of AI integration—such as the intensity of integration, employee training, personalization of AI tools, and the frequency of AI feedback—affect employee burnout. A quantitative approach was employed, involving a survey of 320 participants from high-stress sectors such as healthcare and IT. The findings reveal that the benefits of AI in reducing burnout are substantial yet highly dependent on the implementation strategy. Effective AI integration that includes comprehensive training, high personalization, and regular, constructive feedback correlates with lower levels of burnout. These results suggest that the mere introduction of AI technologies is insufficient for reducing burnout; instead, a holistic strategy that includes thorough employee training, tailored personalization, and continuous feedback is crucial for leveraging AI’s potential to alleviate workplace stress. This study provides valuable insights for organizational leaders and policymakers aiming to develop informed AI deployment strategies that prioritize employee well-being.

The research aims to explore the role of Electronic Human Resources Management on employee performance through employee engagement. The present research’s population included all Jordanian Service and Public Administration Commission employees. The data was collection through a questionnaire that was administered for the study Population. 262 questionnaires collected from employees working in Service and Public Administration Commission in Jordan valid for statistics. The analysis of the data was undertaken through the use of SEM (structural equation modelling). The results showed that E-HRM has a direct impact on employee performance and employee engagement. Consequently, the indication from the results was that a significant role in mediation within the effect that E-HRM had upon employee performance been played by employee engagement. The conclusion reached was that transformation of the public sector through implementation of technological HRM methods fosters employee engagement, with that being a key driver for the alignment of employee behaviors for the achievement of high levels of employee performance.

This paper critically reviews the prevailing generalizations in current research on Generation Z (Gen-Z) travel behavior. While various studies have characterized Gen-Z’s transportation preferences as leaning towards sustainable and technology-integrated modes of transport, this paper argues that the findings are largely based on observations from developed countries and may not accurately reflect behavior in developing countries. This paper is written using a narrative literature study approach. Through a comprehensive literature review, the paper highlights the differences in Gen-Z travel patterns across different geographical regions, emphasizing the need for context-specific analysis. The paper addresses often overlooked factors such as economic limitations, infrastructure challenges, and cultural nuances that shape mobility choices. The aim is to dissect the cohort effect and look at its validity across different socio-economic landscapes through existing literature. As such, the paper provides nuanced insights into the heterogeneity of Gen-Z travel behavior and suggests cautioning against over-generalization, as well as advocating for a more localized approach in transportation policy and planning. The paper also encourages similar research in developing countries to gain a more comprehensive understanding of Gen-Z travel behavior globally.