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As online education has become more widespread at the higher education level, effective quality assurance strategies are essential to ensure the quality of online instructional practices. The focus of the current study was to explore the quality assurance strategies for online instruction in higher education through a comprehensive review of previously conducted studies. The qualitative systematic review method was employed by following the PRISMA guidelines to extract and analyze the previously conducted studies related to the quality indicators for online instruction. In line with PRISMA guidelines, fifty-three (53) studies related to the focused area of the current study were identified via searching various databases, including Google Scholar, Litmaps, Web of Science, ERIC, Science Direct, and Academia. Additionally, themes were generated after systematically reviewing the selected studies. The findings highlighted the key themes such as well-designed instructional resources, fully prepared instructors, creating a sense of online learning community among learners, motivated interaction between learners and instructors, effective implementation of advanced technological tools, incorporation of innovative assessment techniques, and continuous improvement plans for online courses. However, these significant insights can assist online education programs by directing the development and implementation of robust quality assurance frameworks to address the multidimensional aspects of online instruction. Keywords: Online instructional practices, Quality assurance strategies, Higher education, PRISMA, Quality teaching.

Science education is a significant predictor of a country's technological advancement. Multiple factors like quality teaching, conducive learning environment, and students’ personal traits may contribute in the quality of science learning. Students’ personal traits, such as their attitude, study habits, and interests, may help them learn science effectively. In this study, we examine whether secondary school students’ study habits predict their motivation for learning science. This study was causal-comparative in nature. The study's target population comprised 1,47,538 students of 9th-grade enrolled in 1323 secondary schools in the Gujranwala Division. The study population comprised 35,858 students of 9th-grade enrolled in 268 secondary schools in Sialkot District. Two-stage sampling techniques were used in this study. In the first stage, 10% of schools were randomly selected as clusters from each stratum (male & female). Secondly, from each selected school, the researcher randomly selected one section when more than one section was available. If there is a single school, all students in that school would be included in the study sample. Sample of the study: Two questionnaires were used in this research to collect data. The first questionnaire consisted of 20 items was developed to assess secondary-level science students’ study habits and 2nd consisted of 20 items was developed to assess the science students’ motivation of secondary-level. Results indicated that reading habits, note-taking, study environment, test preparation, and time management were statistically correlated with motivation; however, note-taking did not account for any variance in science students’ study habits and motivation. Keywords: Study Habits, Motivation, Self-efficacy, Science Learning, Secondary School students.

Parental advocacy plays a pivotal role in ensuring educational rights of children with special needs, their inclusion as well as addressing the problems affecting their equitable learning opportunities. This study was conducted to identify the strategies parents can use to advocate for the educational rights of their children with special needs and the challenges they face along the way. The study was quantitative in approach, with a descriptive survey research design involving 300 parents of primary school children in four special education centres in District Bhakkar, Punjab, Pakistan. Data were collected using newly developed scales based on a 5-point rating scale. Data were analysed through independent-samples t-test to determine differences between male and female respondents, as well as between rural and urban respondents. The study revealed that most of the parents of children with special needs lacked awareness about the strategies and options available which they could use for advocacy. Male and urban parents were found to be more informed than female and rural parents respectively. Additionally, the study found that a significant number of parents faced multiple challenges in their struggle towards advocacy. Rural parents were more likely to face challenges than urban parents in advocating for the educational rights of their children with special needs. Keywords: Special education, Disability, Disabled child, Gifted child, Scales.

Artificial intelligence (AI) has gained rapid development in the field of education for improving classroom instruction, assessment and students’ learning outcomes. This meta-analysis specifically focused on the overall impact of AI on the academic performance of students. Using “Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)” guidelines, the study synthesized 18 studies retrieved from three databases (“Directory of Open Access Journals - DOAJ, PubMed, and Google Scholar”) published between 2015 to June 2025 and used the information extracted from the studies for the analysis. The studies comprised a sample of 3436 participants from various educational levels fulfilled the inclusion criteria. For the analysis, the data from the studies was coded and entered into “Jaffery’s Amazing Statistical Program (JASP) version 0.18.3”. The results showed that there was a moderate to large (0.62) pooled effect size under the random-effects model. Moderating effects of four variables, type of institution, sample size, area of the subject and AI types were examined. Results depicted that the sample size moderated the effectiveness of AI in predicting the academic performance of students significantly. However, other moderating variables, that is, type of institution, area of the subject and AI type did not show any significant effects. Based on the findings, the meta-analysis presented practical implications for both policy and practice. Keywords: Artificial Intelligence, Academic Performance, Moderators, Forest Plot, Funnel Plot.