In the dynamic landscape of modern education, it is essential to understand and recognize the psychological habits that underpin students’ learning processes. These habits play a crucial role in shaping students’ learning outcomes, motivation, and overall educational experiences. This paper shifts the focus towards a more nuanced exploration of these psychological habits in learning, particularly among secondary school students. We propose an innovative assessment model that integrates multimodal data analysis with the quality function deployment theory and the subjective-objective assignment method. This model employs the G-1-entropy value method for an objective evaluation of students’ psychological learning habits. The G-1-entropy method stands out for its comprehensive, objective, and practical approach, offering valuable insights into students’ learning behaviors. By applying this method to assess the psychological aspects of learning, this study contributes to educational research and informs educational reforms. It provides a robust framework for understanding students’ learning habits, thereby aiding in the development of targeted educational strategies. The findings of this study offer strategic directions for educational management, teacher training, and curriculum development. This research not only advances theoretical knowledge in the field of educational psychology but also has practical implications for enhancing the quality of education. It serves as a scientific foundation for educators, administrators, and policymakers in shaping effective educational practices.

The study aims to explore the extent to which Jordanian e-news sites rely on artificial intelligence applications in their news content. The researchers will use a media survey methodology, and the sample will consist of 45 editors-in-chief and editors from 10 Jordanian news sites, namely: Ammon, Khabrny, Joe24, Saraya, Amman Net, Jafra, Crown News, Petra, Kingdom, and Roya. The researcher will use an electronic questionnaire, which led to several findings, the most significant of which are: Many news and media sites have introduced artificial intelligence systems to enhance the services they provide to the public. A significant number of journalistic and electronic media websites have shown interest in data analysis tools for their media services. Electronic news sites are clearly striving to improve their capabilities in using artificial intelligence technologies to enhance the services they provide to the Jordanian audience. Additionally, most electronic media websites have expressed a willingness to develop a plan to improve cybersecurity systems to protect against hacking and intrusion attempts, safeguarding their data and the AI systems that operate continuously.AI systems in media organizations also aim to enhance the news experience for users by enriching media services with modern, communicative content.

This study uses the annual financial data of Chinese A-share listed firms from 2010 to 2020 to investigate the relationship between multiple large shareholders (MLS) and earnings management (EM). After analyzing the samples using the Ordinary Least Squares (OLS) model and endogenous switching regression (ESR) model, the empirical results show that the presence of MLS can increase corporate EM activities and the MLS have a significantly positive effect on EM in both the treatment and control groups. In addition, this conclusion still holds after conducting multiple robustness tests. The cross-section analysis shows that the external audit supervision quality, institutional shareholders, and the uncertainty of the external economic environment have significant impacts on the baseline model results. Lastly, mediation effect analysis shows that the presence of MLS increases the corporate operating risk through EM activities. The conclusions of this paper are critical for policymakers to supervise China’s capital market, improve the level of corporate governance of China’s listed firms, and further promote reform of ownership structure.

This study explores the feminization of poverty and the dynamics of the care economy in rural areas, focusing on the municipality of Génova, Quindío, Colombia. The novelty of this study lies in its analysis of the compounded effects of the COVID-19 pandemic on women’s economic participation and care responsibilities in a rural context, offering insights relevant to Latin America. This study addresses the critical problem of how increased caregiving responsibilities and labor informality during the pandemic have disproportionately impacted economically active women, exacerbating gender inequalities. The objective is to analyze the relationship between the care economy and feminization of poverty, providing policy recommendations for post-pandemic recovery in rural settings. The methodology consisted of a two-stage approach. In the first stage, a probabilistic stratified sampling design was applied using data from the Colombian National Population and Housing Census and the Génova, Quindío, and Colombia Municipal Panel. In the second stage, fieldwork was conducted with a sample of 347 women using the RedCap application for data collection. The results indicate a significant increase in unpaid domestic and caregiving work during the pandemic, particularly for the elderly, disabled, and children. Additionally, labor informality increased, further limiting economic opportunities for women. The key conclusion is that public policies aimed at reducing gender disparities in rural labor markets must prioritize caregiving support and formal employment opportunities for women. These findings suggest that addressing the care economy is crucial for closing gender gaps and fostering equitable economic recovery in rural Latin American areas.

The study investigates the role of foreign language enjoyment (FLE) and engagement in the context of English language learning among Chinese students, emphasizing the significance of positive emotions in enhancing academic success. Utilizing a sample of 249 students majoring in international trade, the research employs the foreign language enjoyment scale to count their enjoyment level and foreign language engagement scale to assess various dimensions of student engagement, including cognitive, emotional, behavioral, and social engagement. By conducting regression analysis, the findings reveal that FLE positively influencing learners’ learning outcome while engagement doesn’t pose significant impact on their learning outcome. The study highlights the importance of fostering positive emotions in educational settings to improve language learning outcomes and suggests that understanding the interplay between FLE and other affective factors can lead to more effective teaching strategies in foreign language education.