The paper considers an important problem of the successful development of social qualities in an individual using machine learning methods. Social qualities play an important role in forming personal and professional lives, and their development is becoming relevant in modern society. The paper presents an overview of modern research in social psychology and machine learning; besides, it describes the data analysis method to identify factors influencing success in the development of social qualities. By analyzing large amounts of data collected from various sources, the authors of the paper use machine learning algorithms, such as Kohonen maps, decision tree and neural networks, to identify relationships between different variables, including education, environment, personal characteristics, and the development of social skills. Experiments were conducted to analyze the considered datasets, which included the introduction of methods to find dependencies between the input and output parameters. Machine learning introduction to find factors influencing the development of individual social qualities has varying dependence accuracy. The study results could be useful for both practical purposes and further scientific research in social psychology and machine learning. The paper represents an important contribution to understanding the factors that contribute to the successful development of individual social skills and could be useful in the development of programs and interventions in this area. The main objective of the research was to study the functionalities of the machine learning algorithms and various models to predict the students’s success in learning.

Even in the late stages of the COVID-19, the physical and psychological trauma caused by the epidemic continues to affect people, particularly university students, whose physical and psychological health is vulnerable to environmental influences. The purpose of this article is to investigate the relationship between learning adaptability and “state” anxiety among university students enrolled during the COVID-19(2020-2022), as well as the role of self-management in mediating this process. The findings reveal a negative association between college students' academic adjustment and their state anxiety, a process that also includes a mediation role for self-management, with subjects in this research being college students enrolled during COVID-19. This study offers a theoretical foundation for investigating the factors influencing anxiety from an operationalized viewpoint, as well as for further effective regulation of university students' mental health and anxiety reduction.

The present study focuses on improving Cognitive Radio Networks (CRNs) based on applying machine learning to spectrum sensing in remote learning scenarios. Remote education requires connection dependability and continuity that can be affected by the scarcity of the amount of usable spectrum and suboptimal spectrum usage. The solution for the proposed problem utilizes deep learning approaches, namely CNN and LSTM networks, to enhance the spectrum detection probability (92% detection accuracy) and consequently reduce the number of false alarms (5% false alarm rate) to maximize spectrum utilization efficiency. By developing the cooperative spectrum sensing where many users share their data, the system makes detection more reliable and energy-saving (achieving 92% energy efficiency) which is crucial for sustaining stable connections in educational scenarios. This approach addresses critical challenges in remote education by ensuring scalability across diverse network conditions and maintaining performance on resource-constrained devices like tablets and IoT sensors. Combining CRNs with new technologies like IoT and 5G improves their capabilities and allows these networks to meet the constantly changing loads of distant educational systems. This approach presents another prospect to spectrum management dilemmas in that education delivery needs are met optimally from any STI irrespective of the availability of resources in the locale. The results show that together with machine learning, CRNs can be considered a viable path to improving the networks' performance in the context of remote learning and advancing the future of education in the digital environment. This work also focuses on how machine learning has enabled the enhancement of CRNs for education and provides robust solutions that can meet the increasing needs of online learning.

In the process of teaching and learning at any stage, the important role of interest guidance cannot be ignored. Especially in college mathematics teaching, mathematical knowledge is very complex and abstract, and most students are unable to effectively understand and master it during the learning process. So it is even more important to fully stimulate students' interest in learning. This article analyzes the significance and current situation of stimulating students' learning interest in university mathematics teaching, and conducts effective strategy analysis. In order to effectively awaken students' desire for knowledge, guide students to change from passive learning to active learning, so that students can continue to grow and progress in this process.

The advent of the COVID-19 pandemic has precipitated a paradigm shift in education, marked by an increasing reliance on technology and virtual platforms. This study delves into the post-pandemic landscape of Islamic higher education at the State Islamic Institute of Palangka Raya, Central Kalimantan, Indonesia, focusing on students’ readiness, attitudes, and interests toward sustained engagement with e-learning. A cohort of 300 students across all semesters of Islamic Education partook in the investigation. Utilising Structural Equation Modelling, the study gauged students’ preparedness, perceptions, and inclinations toward online learning. Results indicate a general readiness among students for online learning, with a pivotal role attributed to technological devices and internet connectivity. Positive attitudes toward online learning were prevalent, with flexibility and accessibility emerging as significant advantages. Moreover, students showed keen interest in online learning, valuing its technological advancements, affordability, and intellectually challenging nature. These findings highlight the digital transformation of traditional teaching methods among Islamic higher education students, who are typically known for their emphasis on direct interaction in teaching and learning. Their receptivity to innovative learning modalities and adaptability to the digital era’s difficulties highlight the need for educational institutions to leverage this enthusiasm. Comprehensive online learning platforms, robust technological support, and a conducive learning environment are advocated to empower Islamic higher education students in navigating the digital landscape and perpetuating their pursuit of knowledge and enlightenment.

This study examines the influence of organizational learning and boundary spanner agility in the bank agent business of Indonesia’s financial inclusion. This study is based on quantitative studies of 325 bank agents in Indonesia. The results of this research strongly show that organizational learning has a significant impact on boundary spanners’ agility to achieve both financial and non-financial performance. This study presents a novel finding that organization learning with a commitment to apply and encourage learning activities and agility with improved responsiveness and resilience boundary spanners can achieve bank agent performance. Organizational learning of bank agents needs to improve commitment to apply and encourage learning activities, always be open to new ideas, and create shared vision and knowledge transfer mechanisms. Organizational agility in bank agents need also to improve the capability to be more responsive and adaptable to culture changes in a volatile environment. This research provides valuable insights to policymakers, banking supervisors, bank top management teams, and researchers on the factors that may improve the effectiveness of the agency banking business to promote financial inclusion. Participating banks in the agent banking business need to set a clear vision, scope, and priority of strategy to encourage organizational learning and agility.