Mathematics plays a leading part in day-to-day life and has enhanced a necessary component for human accomplishments. Students from many countries do not reach the expected level in mathematics. Therefore, it is essential to pay close consideration to the causes related to ability in mathematics. Mathematics attitude is considered as one of the critical variables in the process of mathematics learning. This study aimed to determine students’ attitudes and achievements through problem-based learning in mathematics. The selected study group contained 600 students and 35 teachers from rural public secondary schools in District Rawalpindi, Pakistan. The data collection was done using questionnaires from students and teachers and collected data analyzed by SPSS 23 and Amos 23. This study’s result was carried out using Partial Least square structural equation Model (PLS-SEM), descriptive analysis, and hypotheses testing. The outcomes in this study indicated that the mean fluctuated between 1 to 4.5, 3.71 to 4.20, and Std. Deviation fluctuated between 0.6 to 2.0 and 0.75 to 1.55 in the students and teacher models, respectively. The results of the PLS-SEM students’ model show a negative attitude towards mathematics. The teachers’ PLS-SEM model showed the Effects of using problem-based learning (PBL) on students’ achievements. According to the hypotheses testing, the acceptance of hypotheses by stating that the Confidence in Learning Mathematics Scale (C), Value of Mathematics Scale (V), and Student Mathematics Motivation Scale (M) are significant effects for the Students’ Attitude Toward Problem-Based Learning (ATPBL). But the Attitude Toward Enjoyment in Mathematics Scale (AE) was rejected, and it did not significantly affect the ATPBL. As well as, the Problem-solving learning and students’ achievement (PLA), Advantages of problem-solving learning (APL) and Difficulties in using problem-solving learning (DPL) have a significant positive effect on the ATPBL. Finally, this study suggested that teachers also adopt new teaching methods corresponding to mathematics, and there is a need to explore particular mathematics skills to enhance students’ learning abilities.

Leadership plays a significant role in the performance of individuals and organizations. This paper investigates the impact of leadership styles on the innovative performance of female leaders in Pakistani Universities using a survey approach. This paper aimed to (a) discover a leadership style practiced by females and (b) discover the relationship between leadership style and the innovative performance of female leaders. Several female leaders, including faculty members, heads of departments, deans, coordinators, and directors, from public and private universities of Punjab (a province of Pakistan), were involved in this study. A sample of one hundred female leaders was selected using a multistage sampling method. In the first stage, five public and five private sector universities were selected through a simple random method. In the second stage, ten female leaders (five from each of the social science and basic science departments) were selected from each university through a purposive sampling method. The researchers adopted a reliable instrument to collect the survey data. The collected data were analyzed using SPSS (Version 26). Mean scores and Pearson correlation coefficients were used to discover the relationship between various variables. The investigation revealed that most female leaders practice the transactional leadership style in their universities. This study also discovered a moderate positive relationship between both leadership styles, namely transactional and transformational, and innovative performance. The study recommends that various workshops and seminars may be conducted to increase the practices of both leadership styles to enhance innovation in Pakistani Universities.

The Technical Education and Vocational Training Authority (TEVTA) plays a crucial role in the socioeconomic development of a country. Still, it is often stigmatized as a secondary choice in the Global South. This study explored the interrelationships and impacts of factors such as family, school, and society on the perception and reputation of TEVTA. By employing quantitative methods, the analysis focused on how family, society, and school support influence these perceptions and reputations within TEVTA programs. Social Cognitive Theory is the theoretical underpinning of this study, in which 350 students from 13 TEVTA institutes participated by filling out questionnaires. The data was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) and IBM SPSS 28. This study indicates that family and societal influences significantly shape students' perceptions, confirming their pivotal role in enhancing the reputation of these programs. School support also emerged as a critical factor, significantly impacting students' perceptions but not directly influencing the programs' reputation. The analysis underscores the importance of understanding the sociocultural context to develop effective strategies for the TEVTA sector in Pakistan. This clear understanding is essential for developing effective strategies to improve the reputation of TEVTA programs in this setting. Moreover, this research offers policy suggestions to make vocational education more attractive and accessible to diverse students, ultimately contributing to the country's socioeconomic development. This study applied Social Cognitive Theory (SCT) to explore how individual thoughts, environmental influences (such as family, school, and society), and behaviors interact within the context of TEVTA programs. This approach fills gaps in current research and offers a clearer understanding of what affects TEVTA's perception and reputation.

This study aimed to compare the styles of leadership practices of female leaders in public and private Universities in Pakistan. In this study, both quantitative and qualitative data were collected using a mixed-method approach. An adapted and developed questionnaire was used for quantitative data collection, whereas qualitative data were collected through a semi-structured interview schedule. A sample of 200 female leaders was selected for quantitative data collection, while 10 females from the said sample were selected for qualitative data collection through a simple random method. Quantitative data were analyzed using SPSS, whereas qualitative data were analyzed using thematic analysis. Based on the statistical results, this study discovered statistically significant differences in female transformational and transactional leadership styles and significant differences in job performance based on the university sector. This study discovered statistically insignificant differences based on the different positions of female leaders regarding transformational and transactional leadership, and job performance. Moreover, qualitative data revealed that female leaders clearly understood both leadership styles and how to improve job performance by practicing them. The originality of this study concerns the identification of the differences between leadership styles (transformational and transactional) practiced by female leaders of public and private Universities in Pakistan and explains female leaders' perceptions of the role of leadership styles in their job performance.

Self-Serving leadership is a global phenomenon and requires both literary and practical attention to understand how it unfolds and impacts organizations. More specifically the investigation of this underexplored dark side of leadership in Pakistani service sector organizations has its unique significance. So, in this regard, the current study took the initiative to investigate the relationship between a Leader's self-serving behaviour and a follower's self-serving counterproductive work behaviour. Moreover, the underlying mechanism of self-serving cognitive distortions was proposed, with followers' Machivellianism strengthening the indirect relationship between leaders' self-serving behaviour with self-serving counterproductive work behaviour through the self-serving cognitive distortions. The proposed theoretical framework was explained by the Social Learning theory. This study adopted a survey method with the collection of data by utilizing the convenience sampling method, in three-time waves with peer-reported self-serving counterproductive work behaviours. The data was analyzed by utilizing confirmatory factor analysis to establish discriminant and convergent validity. Moreover, the hypotheses testing was done utilizing Hayes Process Macro 4 (Mediation) and 7(Moderated Mediation). The results proved that the self-serving cognitive distortions mediated the relationship between the leader's self-serving behaviour and the follower's self-serving counterproductive work behaviours. Moreover, it was established that the High Mach tendencies strengthed the indirect positive relationship between a leader's self-serving behaviour with self-serving counterproductive work behaviour through the self-serving cognitive distortions. It is important to note that the current study provides a view to the practitioners that formulation of effective policies and systems for identifying and discouraging the tendencies of Leaders' self-serving behaviour and employing people with low Mach Tendencies can avoid the self-serving counterproductive work behaviours harming the overall welfare of the organization.

Artificial Intelligence (AI) is central to China's strategic vision for technological advancement and global competitiveness. Guided by ambitious national policies, notably the “New Generation Artificial Intelligence Development Plan,” China seeks to transform key sectors such as healthcare, education, finance, transportation, and manufacturing through extensive AI applications. Universities across China actively integrate AI into curricula, fostering research-driven learning environments, and engage in collaborative projects with industry leaders such as Baidu, Alibaba, Tencent, and Huawei. These collaborations ensure graduates acquire practical, industry-relevant competencies. While challenges such as talent shortages, data privacy concerns, and resource disparities remain, China is actively working to address these issues. This overview provides a foundation for further exploration of China's approach to leveraging AI as a cornerstone of its global technological leadership.