Digital technologies are now embedded in engineering education, but little is known about the extent to which they save students time. This paper attempts to address this question. Using data from surveys of 112 engineering students at the University of Sharjah, the author attempts to understand the relationship between the integration of digital technologies into coursework, students’ perceptions of digital integration, and their engagement and satisfaction with digital learning, and the perceived amount of time required to complete academic tasks. A 5-point Likert-scale questionnaire was developed for engineering students at different academic levels and analysed with descriptive statistics, Pearson correlation, and three-stage multiple regression analysis. All variables predicted time reduction and engagement and satisfaction were the single largest predictors. The regression model explained 42% of the variance in time reduction and regardless of the variables, study duration decreased. The paper recommends the use of digital tools, along with engaged and satisfied learners, to effectively reduce study time. The paper concludes with recommendations for course design and teacher digital literacy, and institutional digital strategy in engineering education.

This study examines the determinants of Government Effectiveness in six Gulf Cooperation Council (GCC) countries over the period 2003–2024 using a panel dataset of 168 observations. An Integrated Socio-Digital Governance Framework is developed to assess the roles of Digital Government Development, Human Capital, and Organizational Ergonomics and Workplace Safety in shaping institutional performance. The analysis employs a dynamic System Generalized Method of Moments (System GMM) estimator to address persistence, endogeneity, and unobserved heterogeneity. The findings indicate that Digital Government Development, Human Capital, and Organizational Ergonomics and Workplace Safety Conditions significantly improve Government Effectiveness. Furthermore, the interaction between Digital Government Development and Human Capital is positive and significant, suggesting that digital transformation yields stronger governance outcomes when supported by adequate workforce capabilities. The results remain robust across alternative specifications and estimation methods.

This study examined the factors that motivate commuters in Zamboanga City to utilize Grab Trike, a recently introduced app-based micro-mobility service. The study utilized the use of the Perceived-Risk Theory with the integration of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2) to reach a deeper understanding of a user-commuter behavior. It examined how people's tendency to try the service is influenced by several factors, including its perceived benefits, individual motivation, social influence, and incorporated risk concerns. To identify the critical factors impacting adoption and to shed light on how commuter decisions are influenced by technology and trust, the study employed Structural Equation Modeling (SEM) to show these interactions. An online questionnaire was used to collect surveyed information from 350 qualified participants. The results showed that the Intention to Use (ITU) Grab Trike was significantly impacted by Subjective Norm (SN), Perceived Behavioral Control (PBC), and Attitude Toward Use (ATU). The results also showed that consumers' favorable opinions regarding utilizing the facility were strengthened by motivational factors such as Performance Expectancy, Effort Expectancy, Hedonic Motivation, Price Value, Habit, and Social Influence. The results also emphasized how these attitudes are shaped by perceived risks, including time, money, performance, social, and physical dangers. It is interesting to note that users' preexisting beliefs eased the effects of these threats rather than merely acting as obstacles. Put differently, those who already had a favorable opinion of Grab Trike were less likely to be worried about things like cost, safety, or imaginable inconvenience. Finally, the study sheds light on how social influences, perceived risk, and motivation all have an equal impact on whether new transportation options are accepted in a developing city. To assist the city's objective of creating a more sustainable transportation system, the findings provide Grab, local government entities, and urban transport planners with useful advice on how to improve safety etiquette, pricing systems, and community trust.

Large language models offer a scalable means of supporting expert judgment elicitation in analytic hierarchy process decision making, but their pairwise judgments may still violate consistency requirements in comparison-intensive hierarchical tasks. This study develops a multi-agent iterative elicitation framework that treats inconsistency as an elicitation-stage convergence problem rather than a post hoc matrix repair task. To operationalize this framework, a stage-adaptive focus-pair revision mechanism is proposed to select revisable comparisons from inconsistent matrices, provide rule-based soft hints, and adjust revision priority and scope according to the current inconsistency regime. A CubeSat design-and-development risk assessment task is used for validation. Across twenty independent runs, all inconsistent revision trajectories converged monotonically to acceptable consistency, and the treated outputs preserved a decision-plausible high-priority risk layer. Compared with a Xu–Wei direct correction baseline, SA-FPR achieved comparable top-priority stability with substantially fewer pairwise judgment modifications, while retaining traceable focus-pair revisions and expert-side rationales.