Massive open online courses (MOOCs) are intentionally designed to be easily accessible to many learners, regardless of their academic level or age. MOOCs leverage internet-based technology, allowing anybody with an internet connection to have unrestricted access, regardless of their location or time limitations. MOOCs provide a versatile and easy opportunity for acquiring top-notch education, enabling anyone to learn at their preferred speed, free from limitations of time, cost, or geographical location. Given the advantages they offer, MOOCs are a valuable method for improving the quality and availability of education in Indonesia. Following the outbreak of the COVID-19 pandemic, colleges and institutions have implemented the establishment of digital campuses. One important characteristic of these digital campuses is that they prioritize processes but overlook data and lack standardized standards. The problems and fundamental causes include challenges related to the comprehensive information architecture. The main factor contributing to this challenge is the absence of uniform and well-defined information standards. The existing connectivity and data exchange mechanisms in several schools are poor, leading to substantial data discrepancy among various departments due to the limited content of the fundamental data utilized. Moreover, the absence of clear information about the reliable source of data exacerbates the problem. The main objectives of data governance are to improve data quality, eliminate data inconsistencies, promote extensive data sharing, utilize data aggregation for competitive benefits, supervise data modifications based on data usage patterns, and comply with internal and external regulations and agreed-upon data usage standards. The aim of this project is to create a data governance framework that is customized to the specific conditions in Indonesia, with a specific emphasis on MOOC providers. The researcher chose design science research (DSR) as the research paradigm as it can successfully tackle relevant issues linked to the topic by creating innovative artefacts about the data governance framework for MOOC providers in Indonesia. This research highlights the necessity and significance of implementing a data governance framework for MOOC providers in Indonesia, hence increasing their awareness of this requirement. The researchers incorporated components from the data management body of knowledge (DMBOK) into their data governance framework. This framework includes ten components related to data governance, which are further divided into sub-components within the MOOC providers’ framework.

This article presents an analysis of Russia’s outward foreign direct investment based on the balance of payments. The country has been affected by the “Dutch disease,” characterized by a heavy reliance on the mining industry and revenues from oil and gas exports. The financial account reveals a consistent outflow of capital from Russia, surpassing inflows. A significant portion of domestic investment goes abroad, often to offshore destinations. This capital outflow has not been fully offset by foreign capital inflows. These findings underscore the challenges faced by Russia in managing its financial position, including the need to address capital outflows, diversify the economy, and reduce dependence on raw material exports. Furthermore, this article aims to identify the presence of Russian capital in OECD countries by comparing data from the Central Bank of Russia and the OECD. The analysis reveals significant discrepancies between the two datasets, primarily due to unavailable or confidential information in the OECD dataset. These variations can also be attributed to differences in methodology and the specific nature of Russian outward direct investments, particularly those involving offshore jurisdictions. As a result, accurately determining the extent of Russian capital in OECD countries based on the available data becomes a challenging task (including for the tourism industry as well).

Targeted Poverty Alleviation refers to the targeted funding work completed in the process of higher education development. However, at present, in the process of implementing the requirements of Targeted Poverty Alleviation in China's universities, some students' families are difficult to complete identification, and there are also some problems in the information management of the funders, which has seriously affected the funding for students with financial difficulties in their families during the period of higher education in China. With the rapid development and progress of Big data technology, through the establishment of a sound information technology system, we must help students actively change the funding model in the future and greatly improve the funding, which is of great significance to the development of university funding supervision and management.

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.

Central Sulawesi has been grappling with significant challenges in human development, as indicated by its Human Development Index (HDI). Despite recent improvements, the region still lags behind the national average. Key issues such as high poverty rates and malnutrition among children, particularly underweight prevalence, pose substantial barriers to enhancing the HDI. This study aims to analyze the impact of poverty, malnutrition, and household per capita income on the HDI in Central Sulawesi. By employing panel data regression analysis over the period from 2018 to 2022, the research seeks to identify significant determinants that influence HDI and provide evidence-based recommendations for policy interventions. Utilizing panel data regression analysis with a Fixed Effect Model (FEM), the study reveals that while poverty negatively influences with HDI, underweight prevalence is not statistically significant. In contrast, household per capita income significantly impacts HDI, with lower income levels leading to declines in HDI. The findings emphasize the need for comprehensive policy interventions in nutrition, healthcare, and economic support to enhance human development in the region. These interventions are crucial for addressing the root causes of underweight prevalence and poverty, ultimately leading to improved HDI and overall well-being. The originality of this research lies in its focus on a specific region of Indonesia, providing localized insights and recommendations that are critical for targeted policy making.