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.

This longitudinal study is dedicated to the evaluation of the comprehensive impact of educational reforms through a mixed research methodology which is a combination of the quantitative- and qualitative-oriented research methods to check the students’ outcomes. Data was collected in the span of [mention the time frame] from various data sources for instance standardized test scores, school performance statistics, and through open-ended qualitative evaluation from both students and teachers. Data analysis carried on after the reforms had been put in place revealed that there was a considerable rise in mean test scores and success graduation rates. Therefore, formative evaluation demonstrates the need for implementing reforms that will eventually help the students in boosting academic performance. Besides, there is no difference among investor opinions on teachers, administrators, and students who are involved with the implementation of the reforms. Stakeholders manifest this new assistance as an outcome of lasting improvements in curriculum quality, methods of teaching, and student participation. The study approaches two main challenges that are confronted with education reform that is resourcelessness and to society the change of the educational system can be more suitable for the students to excel academically and it can have an impact on the whole community. Even though this study makes important advancements toward the realization of the complex education implementation process and its effect on student academics, there are elements in which it can be criticized. Both quantitative and qualitative performance improvement is important as well as all the important stakeholder participation. This way the transformation process becomes layered. In other words, these results point to the necessity of planning interventions for longer periods that target the challenges and the forces that maintain the low levels of education performance by the counties.

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. 

In recent years, e-sports, as an emerging form of competition, has been rapidly integrated into the daily life of college students, and with its rich interactivity, instant feedback and teamwork, e-sports provides them with an effective channel for emotional catharsis and psychological regulation. This study takes students from four universities as the survey object and adopts quantitative research method to analyze the relationship between different types of e-sports activities and psychological stress resistance through questionnaire survey method combined with spss. The samples were randomly sampled, and a total of 500 valid questionnaires were collected. The results of the study show that: 1. In terms of participation, the ability of students to withstand academic stress and life stress is significantly improved, and e-sports is an effective way to regulate emotions and relieve stress; 2. the three types of games (First-person Shooter, Multiplayer Online Battle Arena, Real-Time Strategy Game) have different impacts on stress tolerance, of which FPS has the greatest impact on stress tolerance; 3. the frequency of playing e-sports affects your stress tolerance; 4. teamwork and strategy play an important role in e-sports resilience.

The advent of Artificial Intelligence (AI) has transformed Learning Management Systems (LMSs), enabled personalized adaptation and facilitated distance education. This study employs a bibliometric analysis based on PRISMA-2020 to examine the integration of AI in LMSs from an educational perspective. Despite the rapid progress observed in this field, the literature reveals gaps in the effectiveness and acceptance of virtual assistants in educational contexts. Therefore, the objective of this study is to examine research trends on the use of AI in LMSs. The results indicate a quadratic polynomial growth of 99.42%, with the years 2021 and 2015 representing the most significant growth. Thematic references include authors such as Li J and Cavus N, the journal Lecture Notes in Computer Science, and countries such as China and India. The thematic evolution can be observed from topics such as regression analysis to LMS and e-learning. The terms e-learning, ontology, and ant colony optimization are highlighted in the thematic clusters. A temporal analysis reveals that suggestions such as a Cartesian plane and a league table offer a detailed view of the evolution of key terms. This analysis reveals that emerging and growing words such as Learning Style and Learning Management Systems are worthy of further investigation. The development of a future research agenda emerges as a key need to address gaps.

Higher education (HE) consists of both conventional and non-conventional methods of learning. Open and Distance Learning (ODL) is a non-conventional system where teachers (often referred to as facilitators) are physically not present. The conduct of practical in engineering and science education using ODL remains a challenge due to inadequate technology and the dispersion of the students, which results in a graduate skills gap in ODL programs. There is a possibility of using a cloud computing set-up, as well as platforms for the creation of simulated virtual practical settings (virtual laboratories-VLs), which could be accessible by ODL engineering and science and education-based students notwithstanding their locations. This paper adds to existing knowledge on VLs and discusses these inadequacies in engineering and science education with emphasis on the enhancement of online and collaborative learning, as well as the possible laboratory (lab) requirements. In addition, the paper highlights contemporary trends and some issues in VLs and remote labs.