A structural equation model for cyber academic dishonesty in higher education: Evidence from Taiwan.

With the continued spread of the rise of online teaching, and the massive use of 3C products (computer, communication, and consumer electronics), the cases of academic plagiarism or using others' works as own works caused by inappropriate use of the Internet are occurring all the time. However, very little research has been conducted on the cyber ethical climate in relation to cyber academic dishonesty. This study investigates the structural relationship between cyber ethical climate, cyber self-efficacy, cyber ethical attitude and cyber academic dishonesty, among university and graduate students, and develops a multiple mediation model. A total of 812 university and graduate students from 32 universities in Taiwan completed the online questionnaire. The results of the study show that the multiple mediation model is valid and find that the cyber ethical climate creates a favorable context for organizing members to demonstrate cyber ethical behavior, demonstrating the importance of mutual influence on cyber academic dishonesty between the cyber ethical climate created by teachers and the cyber ethical climate of class peers. Based on these results, we deeply examine the practical implications and make specific recommendations to improve the cyber ethical behavior of university and graduate students.

A sequential mediation model of perceived social support, mindfulness, perceived hope, and mental health literacy: An empirical study on Taiwanese university students.

This study explored the mediation of mindfulness and perceived hope between perceived social support and mental health literacy in university students. Of 568 students (205 males, 363 females, average age 20.97) from 70 Taiwanese universities, tools like the Perceived Social Support Scale, General Health Questionnaire, Mindful Attention Awareness Scale, and State Hope Scale were used, adapted to Traditional Chinese through back-translation. Confirmatory factor analysis affirmed model validity. Hayes' PROCESS Model 6 analyzed the data. The results showed an indirect effect of social support on mental health literacy via mindfulness and hope (B = 0.091, 95 % CI: 0.0613 to 0.1258). Three mediation paths were: (1) mindfulness (B = 0.035); (2) hope (B = 0.052); and (3) a combined effect (B = 0.003). A direct effect of social support on mental health literacy was significant (B = 0.120). The model explained 33.9 % of the variance in mental health literacy. The research underscores the link between social support, mindfulness, hope, and mental health literacy, identifying mindfulness and hope as mediators. It stresses the mediation impact and suggests strategies to boost mental health literacy in university students. Future research should expand to cross-cultural studies, further examine the evolving dynamics of social support, and incorporate both qualitative and experimental methodologies. The inclusion of factors such as alienation, well-being, and resilience can enrich the theoretical framework.

Influence of Imagery Training on Adjusting the Pressure of Fin Swimmers, Improving Sports Performance and Stabilizing Psychological Quality.

This study analyzed the effects of imagery training on athletes' imagery ability, physical anxiety and athletic performance. This study employed a mixed research approach. Snowball sampling was used to select 55 fin swimmers with imagery training experience and formal competition participation. Basic statistics were obtained, and Pearson product-moment correlation coefficient (PPMCC) analysis was performed using IBM SPSS Statistics for Windows, Version 26.0, and the results were compared with the opinions of three experts and were tested using multivariate validation methods. The results revealed that although imagery training can help athletes improve their performance and significantly reduce their anxiety during the competition, athletes can still make mistakes due to internal and environmental factors and even have negative thoughts that lead to their reduced likelihood of competition participation. By strengthening strategic and technical imagery training, we can help our fin swimmers perform at a higher level, achieve their goals, and improve overall satisfaction with their competition process and performance.

Influences of Flipped Teaching in Electronics Courses on Students' Learning Effectiveness and Strategies.

The potential influence of the COVID-19 pandemic has changed the status of school education and further accelerated the revolution of regular teaching method. This study compared the learning effectiveness and learning strategies of vocational high school students in flipped teaching and traditional teaching modes. By adopting flipped teaching on an electronics course throughout the entire academic year, this study aimed to explore the effect of learning strategies of the students under flipped teaching. The subjects of this study were 85 sophomore students majoring in Electrical Engineering. This study randomly selected one class as the control group (n = 43), and adopted the regular teaching method while another class was selected as the experimental group (n = 42), and employed the flipped teaching method. This study used the "Learning strategy scale of students in vocational high schools" as the instrument. The students' scores of the Testing Center for Technological and Vocational Education Test were used to evaluate their learning effectiveness. The results of this study indicate that students under the flipped teaching model made remarkable progress in the electronics course and the learning outcomes remained significant after a long period of time. Moreover, they made notable changes in their learning strategies, including "learning motivation", "reading and exams", "self-testing", and "problem solving strategies".

A transmission power optimization with a minimum node degree for energy-efficient wireless sensor networks with full-reachability.

Transmission power optimization is the most significant factor in prolonging the lifetime and maintaining the connection quality of wireless sensor networks. Un-optimized transmission power of nodes either interferes with or fails to link neighboring nodes. The optimization of transmission power depends on the expected node degree and node distribution. In this study, an optimization approach to an energy-efficient and full reachability wireless sensor network is proposed. In the proposed approach, an adjustment model of the transmission range with a minimum node degree is proposed that focuses on topology control and optimization of the transmission range according to node degree and node density. The model adjusts the tradeoff between energy efficiency and full reachability to obtain an ideal transmission range. In addition, connectivity and reachability are used as performance indices to evaluate the connection quality of a network. The two indices are compared to demonstrate the practicability of framework through simulation results. Furthermore, the relationship between the indices under the conditions of various node degrees is analyzed to generalize the characteristics of node densities. The research results on the reliability and feasibility of the proposed approach will benefit the future real deployments.