The COVID-19 pandemic has led to the end of in-person classes at universities and schools and the beginning of digital advancements in higher education. Flipped learning is very different from traditional teaching methods and necessitates some shifts in the roles of the teacher and the student. The purpose of this study is to investigate the effect of using flipped learning on students' achievement and measure their attitudes towards learning through it during the Corona pandemic period. A quasi-experimental study design was adopted through the pretest and posttest measurements. Two groups were randomly assigned one to be experimental, and the other a control. The present study showed that there was no statistically significant difference between the mean of the pre-measurement and post-measurement tests of the experimental group’s motivation towards learning using the flipped learning strategy. The findings from the quantitative data revealed that flipped learning contributed to the academic success of students and their attitudes toward learning during the corona pandemic period. Hence, further studies with more extended periods are recommended to examine the effect of Flipped learning on self-directed learning and other related variables.

Mobile e-learning within the education domain is now an integral part in education technology. However, there has been little discussion about the benefits and the challenges of the use of M-learning in the higher education system in KSA. Interviews were the primary instruments used for data collection in identifying the enabling and deterring the quality attributes of mobile e-learning use in the context in Saudi Arabia higher education. The research results revealed that learning content/information quality, system quality, service quality and instructional quality were the primary antecedents of Blackboard as a Learning Management System (LMS) in general and within the mobile devices, and this situation can enhance user’s attitude towards the use of E-learning. Data were analyzed and results were discussed. Recommendations were made based on the findings.

The present study aims to examine the implementation of Blockchain Technology within the financial sector, with a specific emphasis on its acceptance by Islamic banks operating in the United Arab Emirates (UAE). In the context of a technologically advanced period that necessitates expeditious and safe transactions, blockchain emerges as a viable remedy by obviating the need for intermediary entities and augmenting the velocity and security of transactions. This study uses Partial Least Squares Structural Equation Modeling (PLS-SEM) to investigate the important success aspects of technology and its influence on the performance of Islamic banks. The findings of this study are of particular importance, as they demonstrate the considerable impact of Investment Willingness on Financial Resources. Additionally, the study highlights the crucial role played by Organizational Culture and Leadership Support in fostering readiness for adoption. This study serves as an initial step towards the wider use of blockchain technology in the financial industry, with a particular focus on its application within Islamic banking institutions.

The aim of this study was to examine how the implications of the Covid-19 pandemic moderate the impact of Artificial Intelligence (AI) on the effective application of Cyber Governance (CG) in Islamic banks. A total of 93 questionnaires from branch heads of Islamic banks were used in this study, and the data were analyzed using the Statistical Package for Social Sciences (SPSS) through descriptive-analytical methods. The findings indicated that AI has a significant influence on the effective application of CG in Islamic banks. The study also revealed that the Covid-19 Pandemic positively moderates the influence of AI on the effective application of CG in Islamic banks. The results of this study have implications for regulators and decision-makers in proposing new legislation to effectively apply CG in the Islamic banking sector, which can help protect public funds and limit cyber-attacks. This study is the first to investigate the moderating effect of the Covid-19 pandemic on the influence of AI on the effective application of CG in Islamic banks.

With the digitization of historical databases and endowments, care must be taken when designing the framework for an information system on the web. Because conflicts arise frequently in reality, different data management requirements are necessary for the preservation of waqf property. For the purpose of creating and putting into place historical information systems and endowments for this inheritance, it is necessary to develop an acceptable management plan. An inheritance that is thought to be distinct from customary ones since it is governed by its own law is referred to as waqf, as an example. They typically comprise histories and endowments that need to be protected to ensure sustenance among the population and to ensure they live up to the standards of the community and country. This research was compiled and analyzed to support stakeholders in producing a more practical, focused, and value-delivery framework. The datasets were mapped based on relationships, graph databases, and semantic networks. Moreover, the framework was developed using several data representation models to ensure easier, faster, and more accurate methods of displaying the data. Relationships, graph databases, and semantic networks were used to map the datasets. The design was made available to users, administrators, and managers, with the latter group being in charge of maintaining data control over each entity. The case study was conducted using historical information and waqf from the Nadzir Pangeran Sumedang Indonesia Waqf Foundation (YNWPS) in the Kingdom of Sumedang Larang Indonesia (KSL).` The creation of a web-based information system to keep track of the data in each entity and ensure better preservation of historical genealogical databases and endowments was made simpler by the structured framework design.

The aim of this study is to examine the impact of Big Data on strategic foresight in the presence of open innovation as a (mediating variable) in the companies of the therapeutic industry and the medical supplies sector in Amman the capital city of Jordan. Out of the (121) companies making up the total of such companies, the study focused on (18) industrial companies that had more than (100) employees in total, however only (11) of those have consented to take part in the study. The study population consisted of (271) employees occupying different jobs (general manager, deputy general manager, unit manager, department manager). Due to the limited size of the population, the entire number of employees were included as participants using the comprehensive survey technique, and the number of returned and validated questionnaires for analysis were (259), representing (95.5%) of the total. In order to determine the study problem, pilot structured interviews were used in a sample of the mentioned companies. The questionnaire was employed as the key tool to measure the study variables through data collection, and the descriptive and inferential statistics methods were used to analyze the collected data, through calculations of the arithmetic mean, standard deviation, t-test and half-segmentation, exploratory and confirmatory factor analysis and the structured equation model using SMART PLS3 for hypothesis testing. The study culminated in several results, the most important of which was evidence that open innovation played a partial mediating role in the relationship between big data and strategic foresight in the companies of the therapeutic industries and medical supplies sector. Accordingly, a set of recommendations were put forward, the most important of which is to increase investment in big data in the companies due to its importance in foreseeing the future. As well as applying open innovation practices and strengthening strategic foresight practices due to its important role in avoiding extensive losses and seizing new opportunities. Highlighting the need to pay attention to open innovation practices that generate ideas and help to have strategic foresight.

Research on digital literacy, knowledge management and process innovation variables has not been widely carried out in Indonesia, therefore more studies need to be carried out immediately since small and medium enterprises (SMEs) play an important role in economic activities. The purpose of this research is to investigate the effect of digital literacy on knowledge management, digital literacy on process innovation and financial management on process innovation. The research method is quantitative using partial least square structural equation modeling (SEM) analysis with data analysis tools using SmartPLS 3.0 software. The study involved 489 respondents who owned SMEs and it was determined using simple random sampling. The type of variable scale used is the ordinal scale. The rating scale for each statement uses a rating scale technique with a Likert scale type. Online questionnaires are distributed through online media, the data analysis stage is the outer model test, namely the validity and reliability test and the inner model test, namely the hypothesis test or significance test. The independent variable of this research is digital literacy, the mediating variable is knowledge management, and the dependent variable is process innovation variable. Based on the results of research data analysis it was found that digital literacy had a positive and significant relationship on knowledge management, digital literacy had a positive and significant relationship on process innovation, knowledge management had a positive and significant relationship on process innovation. Knowledge management played as full mediators in the relationship between digital leisure variables and process innovation.

This research investigates the interplay between public administration, educational socialization on social media, population literacy awareness, and public satisfaction in the context of population services. The primary objective is understanding how these variables are interconnected and their collective impact on public satisfaction. The study employs a quantitative approach, collecting data through structured questionnaires from a randomly selected sample. Data analysis involves various statistical techniques using Smart PLS, including regression and mediation analysis. The findings reveal that public administration significantly influences population literacy awareness, underscoring the role of government agencies in shaping citizen understanding of demographic policies. While it was anticipated that population literacy awareness would mediate the relationship between public administration and educational socialization on social media for public satisfaction, this mediating effect needed to be supported. However, social media use was found to influence population literacy awareness, indirectly affecting public satisfaction directly. It highlights the potential of digital platforms to enhance citizen understanding and engagement. The implications are substantial. Governments should recognize the importance of effective communication and digital engagement in fostering an informed and satisfied citizenry. Additionally, tailored communication and education initiatives are crucial for promoting public understanding and engagement, ultimately contributing to higher levels of public satisfaction. The research's novelty lies in its exploration of the complex dynamics among these variables and its focus on the role of digital platforms in enhancing population literacy awareness. However, some limitations include the potential for context-specific findings and the need for further research in diverse settings.

Social media has proven to be quite effective in raising awareness and anti-corruption movements in society. This research aimed to analyze the use of social media Twitter as a means of the Corruption Eradication Commission (KPK) in conducting anti-corruption campaigns in Indonesia. The research employed a qualitative content analysis on the KPK's official Twitter account. The data were processed using the NVIVO 12 Plus software to answer research questions. This research revealed that the KPK's Twitter account is quite active in carrying out anti-corruption campaign activities, although in general it is not optimal. It can be seen from the low intensity of communication and limited communication network so that it is considered as less collaborative. Improving the problems is needed by KPK as it must also show good performance so that public trust continues in high condition. However, this research has limitations in looking at all anti-corruption campaigns carried out by the KPK because it only used Twitter as the reference. Therefore, further research is suggested to analyze all KPK social media such as Youtube and Instagram.

Educational systems worldwide have witnessed a significant shift towards technological applications, especially after COVID-19, which impacted how the learning contents are delivered in classrooms. Given the increased attention given to the numerous advantages of computer Simulations (CSs) programs, particularly in science education, this study compared the efficacy of employing a lab simulation of Newton's Second Law of Motion to teach physics in the UAE secondary school environment versus the more conventional approach (Face-to-face instruction). The study employed a quasi-experimental design that included 90 UAE 11th-grade students from two public schools in the City of Al Ain. The intervention included student engagement in the PhET interactive simulation of Newton’s second law of motion. The study employed the Test of Science-Related Attitudes (TOSRA) questionnaire to collect data before and after the intervention for the experimental and control groups. The findings demonstrated statistically significant differences between experimental and control groups in students' attitudes toward scientific inquiry, enjoyment of science lessons, and career interest in physics/science. Furthermore, results showed a significant difference in attitudes perceived in these scales, with males having a more significant effect size than female students in all three scales. The study concludes with implications and suggests recommendations for future research and practice.