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.

The objective is to determine the impact of economic growth on the externalities of infrastructure investments for the Peruvian case for the periods from 2000 to 2022. The methodologies used are descriptive, explanatory and correlational, analyzing qualitative and mainly quantitative methods. Econometric software was used, and correlations of variables were created for each proposed hypothesis. The estimated model shows that all the independent variables have a significant t-statistic greater than 2 and a probability of less than 5%, which indicates that they are significant and explains the model. The R² is 98.02% which indicates that there is a high level of explanation by the independent variables to the LOG(RGDP). The results of the estimated models demonstrate the existence of a positive and significant relationship of investments in infrastructure and externalities on the growth of the non-deterministic component of real GDP, therefore, in a practical way, private and public investment has a positive effect on the non-deterministic growth of real GDP.

The study, taking China as an example, employs a mixed-method approach of questionnaire surveys and in-depth interviews to explore the differing perspectives of disabled and non-disabled individuals on how to improve the social integration and quality of life of disabled people in developing countries. The study finds that the vicious cycle created by severe accessibility issues in developing countries is the root cause of the disabled’s difficulty in integrating into society. The impersonal barrier-free facilities suppress the desire of the disabled to travel, resulting in fewer disabled people on the streets and less visibility and attention, which leads to poorer accessibility facilities. Secondly, the study also finds that non-disabled people unconsciously show excessive sympathy and compassion when helping the disabled, which affects their self-esteem due to being patronized and helped. This creates two separate “social circles” between the disabled and the healthy. To address these issues, we have designed an application called “AbleMind” where the disabled can share experiences, make friends, seek help, and better integrate into society.