The study examined the effect of instructional leadership on school performance. Instructional leadership is a process that how quality practices: building and sustaining the school vision, monitoring of curriculum and instruction, leading a learning community, data gathering and assessing, and shared leadership were implemented by head teachers effectively. School performance is defined as the attainment of targets by teachers, students and schools. In district Sahiwal, head teachers were evaluated for instructional leadership by their SSTs (N=1026) on HTEQ. For school performance, a score of student achievement were obtained from their schools, while data on factors: cleanliness of schools, student presence, the functionality of facilities, and teacher presence were obtained through monthly visit reports of MEAs. The study revealed that head teachers were used practices of instructional leadership effectively and excellent level of schools' performance were found. The study explored a moderate relationship between variables (r=.54), and a 39 % variance in school performance could be explained through instructional leadership. The recommendations were also added in the study.

Math problem-solving is difficult for students and instructors. Metacognition abilities may help tackle these problems. Math problem-solving success depends on metacognitive abilities and methods. These abilities and tactics benefit students and instructors. Metacognitive abilities and methods are examined in mathematics problem-solving for instructors and students. A qualitative case-study design was utilised. to describe things deeply and broadly. Metacognitive abilities and methods such as task analysis, planning, monitoring, checking, and reflection, as well as self- and group-monitoring, reading and writing, self-regulation (SR), and self-assessment (SA), helped students solve arithmetic problems. Group talks and self-reflection help pupils tackle challenges, too. Meta-cognition for problem-solving is recommended for students and instructors.

The study examined the effect of professional learning communities (PLC) on the achievement of students. PLC is about developing collaborative learning among colleagues to enhance the performance of an organization within a specific environment. Student achievement has defined the performance of students which can be evaluated with the help of tests. Data were gathered from SSTs (N=890) involving three districts (Sheikhupura, Kasur, and Lahore) through a multistage sampling technique. The study adopted the Professional Learning Communities Assessment (PLCA) scale to examine the PLC which was developed by Olivier et al. (2010). Student achievement scores were obtained from their respective schools based on BISE results of 10th grade. The study found that teachers strongly agreed that they were part of PLC in their institutions. The study also found a moderate and significant relationship between both PLC and student achievement (r=.71), and a 41% variance in student achievement could be explained with the help of PLC. Overall, female teachers were found better than male teachers, while urban teachers were better than urban teachers for being part of PLC. The recommendations were also added to the given study.

The study aimed to identify the need of guidance and counselling framework for achieving improved learning outcomes in public sector secondary schools in Larkana. The teachers use corporal punishment to students for achieving academic results. This study determines how learners in public secondary schools in Larkana conceptualized the function of GC in academic achievement. We recruited 167 learners in this paper. The qualitative as well as quantitative method was adopted. The findings showed that most of the students were unaware of the counselling services' availability, they hardly ever used them. The study concluded that secondary schools in Larkana division faced a dearth of proper guidance and counselling framework. According to conclusions, the School Education and Literacy Department Sindh should implement a proper framework of Guidance and Counselling framework.

Deep fakes stand out to be the most dangerous side effects of Artificial Intelligence. AI assists to produce voice cloning of any entity which is very arduous to categorize whether it’s fake or real. The aim of the research is to impart a spoofing detection system to an automatic speaker verification (ASV) system that can perceive false voices efficiently. The goal is to perceive the unapparent audio elements with maximum precision and to develop a model that is proficient in automatically extracting audio features by utilizing the ASVspoof 2019 dataset. Hence, the proposed ML-DL SafetyNet model is designed that delicately differentiate ASVspoof 2019 dataset voice speeches into fake or bonafide. ASVspoof 2019 dataset is characterized into two segments LA and PA. The ML-DL SafetyNet model is centred on two unique processes; deep learning and machine learning classifiers. Both techniques executed strong performance by achieving an accuracy of 90%.

Blackboard is an Internet teaching management platform that allows a virtual learning environment via the Internet. It is the most popular system used by universities and educational institutions worldwide. However, this study is more concerned with foreign language (EFL) students' perceptions of the use of Blackboard in their courses. For this reason, we focused on 100 EFL students as respondents to the online questionnaire who attended the Language Department-College of Science and Humanities at Rumaah-Majmmah University in this research. Whereas, findings from both the survey data were analyzed by using (the SPSS Program) with the Lickert scale method showed participants had positive perceptions of the use of Blackboard technology for educational purposes. The results of students' perceptions proved the usefulness of Blackboard technology in the field of education. Hence, the suggestions of this study could be shared with other educational institutions in the kingdom.

The objective of the study was to explore Student Readiness in Online Learning Environment:  Student readiness in the online learning environment is a crucial factor in determining academic success. The research was descriptive and to attain the objectives a sample of a total of 300 students 92 male and 208 female students from the Bahauddin Zikariya University, Emerson University Multan, and The Women University Multan. The findings revealed students' overall moderate level of readiness for the online learning environment and positive attitude towards various aspects of online education.  The study findings may help institutions and teachers by providing further training to improve students' digital skills, ensuring the improvement of learning practices in new online environments, and implementing guidelines and policies.

The purpose of this research was to investigate the practices and challenges regarding mathematics laboratory in Punjab at school level. Descriptive survey design was used to collect data through questionnaire. The population was all secondary schools mathematics teachers of district Chakwal. The sample size was 60 through systematic random sampling technique. Only 5 percent of schools had mathematics laboratories but most of the schools had science and computer laboratories even did not have geometrical shapes and activity kits related to mathematics lessons. The big challenge regarding integration of mathematics laboratories was the lack of effective policy from the Government. There was no support from school management to purchase lab-related equipment and not a single period was included in the timetable for the laboratory. It was recommended that govt. may launch an effective policy regarding mathematics laboratory and school management may include three periods per week for mathematics lab work.

Time series analysis and decomposition are crucial in examining economic data as they uncover elements such as trends, and seasonal influences, within the data. However, some approaches have difficulty in accommodating complex, high-dimensional data. In this research, we investigate the possibilities of utilizing artificial intelligence (AI) tools, specifically, machine learning (ML) and deep learning (DL) for better timeliness and accuracy of economic forecasting. In some instances, it was shown how recent AI models can improve the data analysis of economic indicators (GDP, inflation, stock indices) through the accurate depiction of non-linear trends and changing seasonals. Model enhancements using AI also result in significant improvement in the accuracy of economic forecasts and provide more detailed and useful time series decomposition for economists and policymakers. This paper is a step towards more extensive use of artificial intelligence in econometric analysis and provides evidence on the feasibility of such in practical econometric studies.