E-learning has become an integral part of higher education, significantly influencing the teaching and learning landscape. This study investigates the impact of student characteristics such as gender, grade, and major on E-learning satisfaction. Utilizing Structural Equation Modeling (SEM) and collecting data through 527 valid questionnaires from Nanjing Normal University students, this research reveals the nuanced relationships between these variables and E-learning satisfaction. The findings indicate that gender, grade, and major significantly and positively impact student satisfaction with E-learning, highlighting the need for tailored E-learning resources to meet diverse student needs. The study underscores the importance of continuous improvement in E-learning resources and platforms to enhance student satisfaction. This research contributes to the understanding of effective E-learning strategies in higher education institutions.

As autonomous vehicles (AVs) revolutionize the global transportation landscape, their implications for emerging economies like Malaysia remain a subject of significant interest. This study delves into the multifaceted world of AV technology, focusing on Malaysia’s unique transportation challenges and opportunities. Through interviews with key stakeholders and experts, the research uncovers valuable insights into AV technology’s awareness, regulatory landscape, integration hurdles, potential benefits, and inclusivity impact in the Malaysian context. The study finds that while AVs hold the promise of improved road safety, reduced traffic congestion, and enhanced environmental sustainability, addressing challenges related to regulation, infrastructure, and public acceptance is imperative for successful integration. Additionally, AV technology has the potential to significantly enhance inclusivity in transportation, benefiting individuals with disabilities. The study underscores the need for holistic policy and infrastructure development to leverage the benefits of AV technology and pave the way for a sustainable and inclusive transportation future in Malaysia.

Using data from 31 provinces, municipalities, and autonomous regions in mainland China from 2006 to 2019, we employ a double difference (DID) model and a spatial double difference (SDID) model to estimate the impact of the High-speed Railway (HSR) on the income gap between urban and rural residents, as well as its spatial spillover effects. Our research reveals several key findings. Firstly, the introduction of high-speed railways helps to narrow the income gap between urban and rural residents within local areas, but its spatial effects can lead to an increase in the income gap in neighboring provinces. Secondly, from a spatial perspective, intermediate variables such as industrial structure, education, science and technology, and foreign trade can also contribute to balancing the income gap between urban and rural residents, although the impact of population mobility is not significant. Thirdly, further analysis of the spatial effects demonstrates that education plays a significant role in balancing the income gap both within the local province and neighboring provinces. Additionally, adjustments in industrial structure, advancements in science and technology, and foreign trade have stronger spillover effects in reducing the income gap among neighboring provinces compared to their impact at a local level.

This study explores the complex dynamics of handling augmented reality (AR) data in higher education in the United Arab Emirates (UAE). Although there is a growing interest in incorporating augmented reality (AR) to improve learning experiences, there are still issues in efficiently managing the data produced by these apps. This study attempts to understand the elements that affect AR data management by examining the relationship between the investigated variables: faculty readiness, technological limits, financial constraint, and student engagement on data management in higher education institutions in the UAE, building on earlier research that has identified these problems. The research analyzes financial constraints, technological infrastructure, and faculty preparation to understand their impact on AR data management. The study collected detailed empirical data on AR data management in UAE higher education environments using a quantitative research methods approach, surveys. The reasons for choosing this research method include cost-effectiveness, flexibility in questionnaire design, anonymity and confidentiality involved in the chosen methods. The results of this study are expected to enhance academic discourse by highlighting the obstacles and remedies to improving the efficiency of AR technology data management at higher education institutions. The findings are expected to enlighten decision-making in higher education institutions on maximizing AR technology’s benefits for improved learning outcomes.

This study uses a Time-Varying Parameter Stochastic Volatility Vector Autoregression (TVP-SV-VAR) model to conduct an empirical analysis of the dynamic effects of China’s stock market volatility on the agricultural loan market and its channels. The results show that the relationship between stock market and agricultural loan market volatility is time varying and is always positive. The investor sentiment is a major conduit through which the effect takes place. This time-varying effect and transmission mechanism are most apparent between 2011 and 2017 and have since waned and stabilized. These have significant implications for the stable and orderly development of the agricultural loan market, highlighting the importance of the sound financial market system and timely policy, better market monitoring and early warning system and the formation of a mature and sound agricultural credit mechanism.