˜The œcritical review of social sciences studies

This research investigates the effect of AI-based personalized learning systems on students' performance, engagement, and participation, as well as challenges and ethical issues related to AI implementation in education. Adopting a quantitative research approach, data were gathered from 268 university instructors from all provinces of Pakistan using a self-administered questionnaire. Correlation analysis indicated a high positive correlation between AI-based learning and student performance (r = 0.74, p < 0.001), whereas regression analysis indicated significant influence on participation and engagement (β = 0.72, p < 0.001). Moreover, chi-square findings validated that accessibility problems (χ² = 12.76, p < 0.001) and data privacy issues (χ² = 15.89, p < 0.001) are significant challenges. The results indicate that AI improves learning outcomes but needs meticulous implementation to overcome barriers of access, ethics, and the working of teachers. This research adds to the increasing body of research on AI-based education and highlights the importance of inclusive, ethical, and regulated adoption of AI in higher education.

This study examined how students' problem-solving abilities and metacognitive awareness—more especially, their capacity to organize, track, and assess their own learning—were affected by AI-based scaffolding. The main goal was to ascertain how learners' knowledge of their own thought and learning processes was improved by structured support utilizing artificial intelligence. A quasi-experimental design was employed involving 300 students, aged 15–22, from secondary schools and undergraduate institutions in Lahore, Pakistan. Participants were divided into two equal groups: one received instruction using AI-assisted scaffolding tools, while the other was taught using traditional methods. Data were collected using standardized pre-tests, post-tests, and structured questionnaires. The results showed a strong favourable relationship between metacognitive awareness and AI-based scaffolding. Students who used AI-assisted learning showed improved ability to efficiently solve issues, organize their thoughts, and self-regulate their learning processes. Additionally, the study discovered that female students outperformed male students in terms of metacognitive awareness, pointing to a potential gender-based difference in the way students used metacognitive techniques and interacted with AI tools. Additionally, learning regulation improved more for pupils who had previously used AI tools. These findings corroborated other studies that shown how well intelligent tutoring programs enhance self-regulated learning. The study came to the conclusion that there was a great deal of promise for improving students' cognitive and metacognitive abilities through the use of AI technologies in the classroom. In both traditional and digital learning contexts, these technologies provide a more efficient, personalized, and interactive learning experience.

This research investigates the impact of AI-driven technologies on reducing educational inequality, particularly focusing on personalized learning and accessibility for underserved communities. A quantitative research design was adopted, with data gathered using structured questionnaires from 300 university teachers across the Punjab and Sindh divisions of Pakistan. The study tested three hypotheses: (H1) AI-driven personalized learning significantly reduces educational inequality and enhances student engagement, (H2) AI-powered accessibility tools improve outcomes for students with disabilities, language barriers, and those from underserved communities, and (H3) ethical challenges, such as data privacy, algorithmic bias, and the digital divide, hinder AI implementation in education. Data analysis was performed using correlation, regression, and post-hoc statistical techniques. The results indicated that AI-driven personalized learning correlates positively with both educational inequality reduction and student engagement. Additionally, AI-powered accessibility tools were found to significantly benefit students facing various challenges, while ethical concerns, particularly related to data privacy and algorithmic bias, emerged as significant barriers to AI adoption. These findings suggest that while AI holds immense potential for improving educational practices, addressing ethical challenges is crucial for its effective implementation. The study highlights the need for strategic policy and technological solutions to integrate AI into Pakistan’s education system, particularly in higher education.

This study examines the impact of Artificial Intelligence (AI) on critical thinking and writing skills in higher education. AI technologies have become increasingly integrated into academic environments, but their effect on students' cognitive abilities, particularly in writing and critical thinking, remains underexplored. A quantitative approach was adopted, with a sample size of 200 students from four universities: two public and two private institutions. Fifty students were selected from each university, ensuring diversity in both academic settings. The study explored students' perceptions of critical thinking and writing proficiency using AI intervention through surveys. The findings indicate that while AI tools improve writing efficiency, their impact on enhancing critical thinking skills is more limited, with variations observed between public and private universities. The results suggest that AI when integrated thoughtfully, can support the development of writing skills but requires additional frameworks to foster deeper critical thinking. This study provides valuable insights into how AI can be leveraged in educational contexts to balance skill development.

The integration of artificial intelligence (AI) into education raises significant concerns about algorithmic bias and its impact on equity. This study examines the linkage between teachers' perceptions of AI bias and their concerns for fairness in the classroom while also assessing the influence of teaching level and AI familiarity. Through a cross-sectional survey of 270 educators in Punjab, Pakistan, we utilized quantitative methods, including correlation and regression analysis, to test our hypotheses. Our findings reveal a strong positive association between perceived algorithmic bias and threats to educational equity. We found that school teachers were significantly more aware of AI bias than university faculty. Furthermore, greater teacher familiarity with AI tools correlated with a more nuanced understanding of their potential biases. These results underscore the urgent need to address the "black box" nature of educational AI. The study provides empirical evidence that, without careful regulation and comprehensive teacher training, AI-driven tools risk perpetuating and even exacerbating existing educational inequalities, aligning with global concerns about the ethical deployment of AI in sensitive sectors.

The integration of Artificial Intelligence (AI) into academic advising is rapidly transforming how higher education institutions support student success. This study explores the effectiveness of AI-driven academic advising systems in enhancing student support, improving retention rates, and optimizing career pathways. Using a survey-based methodology, data was collected from 1,200 university students across three institutions that have implemented AI-powered advising platforms. The survey assessed students’ experiences with the AI system, focusing on usability, personalization, academic confidence, retention likelihood, and alignment of academic choices with career goals. Results indicate a significant positive impact of AI on students’ perception of guidance quality, timely decision-making, and clarity in career planning. Furthermore, students reported increased satisfaction and a stronger sense of being supported academically, with many noting that AI-generated insights helped them make informed choices about courses and careers. These findings suggest that when implemented ethically and with proper institutional support, AI-driven academic advising can serve as a powerful tool for personalized education and long-term academic success.

The research evaluates how artificial intelligence impacts personalized marketing through its three major effects on customer encounter and predictive market segmentation alongside brand audience interaction. Managers use AI to monitor consumer information while automating communication and adding tailored suggestions for consumers which leads to higher marketing results. This research employed a quantitative strategy which obtained data from secondary records involving AI marketing strategy case studies in addition to academic literature and industry reports. The evaluation of how AI helps personalization, engages customers better and optimizes targeting effectiveness occurred through statistical analysis. The analytic power of AI in marketing allows organizations to improve personalization because it examines consumer activities which results in specialized advertisement delivery. The use of AI-powered chatbots with virtual assistants delivers better customer support efficiency thereby producing happier clients who remain active with the system. The major obstacles in AI application involve privacy issues with customer data together with biased algorithms running against human interaction standards. The implementation of AI technologies in marketing operations brought about two key benefits consisting of automated choices along with maximized consumer connections. The presence of ethical problems involving data security as well as transparency remains unresolved. Organizations who apply AI-driven strategies successfully will achieve competitive superiority in their fields. Upcoming studies need to focus on how generative AI produces content as well as ethical standards for AI systems and its organizational usages throughout different sectors. Sustainable AI-designed marketing initiatives require organizations to maintain equal proportions between machine automation and human employee involvement.

This research examines the contribution of AI-based personalized learning and social media-based educational resources to bridging educational inequalities in disadvantaged communities in Pakistan. Guided by a quantitative study design, the research administered a survey to 339 teachers of private universities in different provinces of Pakistan using snowball sampling methods for data collection. Self-administered questionnaires were employed for data collection, and multiple regression and correlation tests were applied to test the correlation between AI-based personalized learning, academic performance, and the contribution of social media-based educational resources. The findings established a high positive correlation between AI-based personalized learning and academic performance (r = 0.612, p < 0.01) and social media-based educational resources playing a significant role in enhancing the academic performance of students in rural areas. An ANOVA test also revealed that the digital divide moderates the potential of AI and social media in education (F = 9.13, p < 0.01). The findings recognize the promising contribution of AI and social media to facilitating educational access and performance but also underscore digital disparities challenges. The research recommends targeted investment in digital infrastructure, digital literacy, and the ethical integration of AI technologies as key to promoting equitable educational opportunity.

This study allowed for the investigation of the probable effects of integrating emotion detection technologies into AI-based classroom instruction on academic learning results, faculty motivation, and student engagement at East Pakistani higher education institutions. The quantitative, correlational, and predictive study design was used and simple random sampling was utilized to enable the collection of data amongst a sample of 250 undergraduate and postgraduate students. Analysis of the data used descriptive stats, Pearson correlation, simple linear regression and independent samples t-test. The results indicated that there is moderately strong, positive, and significant relationship between emotion recognition technologies and student engagement. Regression analysis ensured that emotion-sensitive AI systems were significant in predicting the academic learning of students, which helped in explaining considerable proportion variances. Also, a strong correlation between emotional responsiveness of AI-based classrooms and the level of student motivation was witnessed. These findings altogether demonstrate the significance of incorporating emotion recognition features into AI-augmented learning spaces so as to achieve humanization of learning by involving it in the development of an emotionally responsive learning process that is student-oriented. Alongside this, the paper has also pointed towards the necessity of employing ethically set principles regarding the use of emotional data, culturally aware AI algorithms, as well as educator training on the interpretation of emotional analytics.

The proliferation of e-commerce has rendered the psychology of online shopping an intriguing area of investigation. Online shopping is significantly influenced by several psychological triggers, involving cognitive and emotive processes in purchasing decision-making in the digital marketplace. This study examines three aspects—scarcity, urgency, and personalization—to determine the impact of these variables on consumers' online buying behavior as these triggers substantially impact e-commerce, necessitating an understanding of the customer psyche. The study used a quantitative design to collect data from 400 adult online buyers aged 18 to 50. The data are analyzed through ANOVA and regression analysis. The findings indicate that consumers react differently to psychological triggers, and urgency and scarcity produce more powerful purchase intent effects than personalization strategies. Moreover, findings suggest that customers retired of personalized techniques due to ethical issues. This study has implications for marketers, brand strategists, user experience (UX) designers, and consumer psychologists. Marketers may customize their strategies and win customer trust; brand strategists may connect with consumers ethically and increase brand loyalty, and UX designers may improve user engagement and satisfaction by integrating these triggers into digital interfaces. Likewise, consumer psychologists may better understand how emotional and cognitive reactions affect online shopping behavior, enabling future research and therapy.

The empowerment of women is empowered by their financial ability, but in Pakistan, this is influenced by norms and values of families and communities. This study examined how social and cultural factors affect women's financial independence based on their daily experiences of employment opportunities, household expectations, cultural restrictions, education access and financial decision-making. A qualitative phenomenological design was used. The subjects were recruited by purposive sampling of 25 women aged 22-50 years and having different marital status, educational level and employment status (employed, self-employed and homemaker) from both urban and semi-urban areas. In-depth semistructured interviews were conducted in Urda and English, and audio-recorded with consent, to collect data. Interpretative thematic analysis was used, guided by the six phases of Braun and Clarke, and reflexive notes were kept throughout to ensure anonymity was achieved, using coded identifiers. Five themes emerged from the illustrative findings: patriarchal expectations, family support, mobility restrictions, access to employment, and control over personal earnings. Financial independence was a negotiated rather than an achieved process; family was a key enabler but patriarchal norms, limited mobility and gendered labor markets were important constraints. Even amongst those who had income, women were often giving it up. The results indicated that there is a need to not only educate women, but to also tackle household and community norms to achieve financial independence for women.

Although artificial intelligence (AI) is becoming increasingly common in the workplace and in public discourse, the perception of it, and their perception of it in relation to their feelings about job security, is under-researched in developing economies. The research design used in this study was quantitative survey-based research design based on the Technology Acceptance Model (TAM) and perceived employment insecurity perspectives. In Pakistan, 300 working class, university graduates, and potential labor-market entrants were sampled across various education, banking, information technology, administration, and other services sectors. AI awareness, perceived usefulness, technological adaptability, perceived job displacement, reskilling intention and employment insecurity were measured using an online questionnaire. The data analysis was conducted using SmartPLS with partial least squares structural equation modeling (PLS-SEM). The measurement model had good loadings, reliabilities, convergent and discriminant validities. The awareness of AI was an important predictor of perceived job displacement and reskilling intentions; while it also had a strong association with perceived usefulness. Perceived job displacement was the largest predictor of employment insecurity, reskilling intentions was the smallest. The total effect of AI awareness was not significant as the displacement and reskilling pathways counterbalanced each other, yet reskilling intentions mediated the relationship between AI awareness and employment insecurity. The results indicate that neither being aware nor being unaware creates an alarm or a reassuring effect for the workers and policies should focus on reskilling in addition to dealing with the fear of displacement.

Digital learning is integral to higher education, and still many of the students feel apprehended while learning through technology, which might affect the acceptance of digital learning. The current study aimed to investigate the anxiety in digital learning and technology acceptance among university students, and to test the relationship between anxiety in digital learning and technology acceptance. The number of 248 students was selected by convenience sampling and a quantitative cross sectional survey was conducted. Technical, performance and social-interaction anxiety were measured using a structured questionnaire evaluated on a 5-point Likert scale along with perceived usefulness, perceived ease of use and behavioral intention. Data were analyzed using descriptive statistics, Pearson correlation and multiple regression at .05 level of significance in SPSS. The students' digital learning stress was found to be moderate (M = 2.84, SD = 0.76) and technology acceptance was high (M = 3.69, SD = 0.68). There was a negative correlation between digital learning anxiety and overall technology acceptance (r = −.45, p < .01) and the three dimensions of anxiety together accounted for 22% of the variance in technology acceptance, with the technical anxiety and performance anxiety dimensions being significant predictors. The results indicate that confidence-promoting tasks, task design, and technical support can help reduce anxiety and enhance the acceptance of digital learning environments.

Representations of international conflicts are rarely neutral; ideological, political, and institutional frameworks shape them. Critical Discourse Analysis (CDA) offers a robust tool for scrutinizing how media representations construct social and political realities. The U.S.-Iran Conflict, a persistently featured geopolitical issue in Western media, has been interpreted through divergent ideological lenses; however, existing CDA findings remain fragmented across different countries, media outlets, and methodologies. This systematic review synthesizes prior research using van Dijk's socio-cognitive model to examine the ideological construction of the U.S.-Iran Conflict in American and Iranian newspapers. Following the PRISMA 2020 guidelines, a comprehensive search of major databases (Google Scholar, Web of Science, Scopus, ERIC, ScienceDirect, Taylor & Francis, and Sage) was conducted for studies published between January 2000 and May 2021. From 780 initial records and 45 eligible full-text assessments, 6 studies met the strict inclusion criteria for in-depth thematic synthesis. The analysis reveals consistent use of van Dijk's "ideological square," with discursive strategies such as lexicalization, evidentiality, and appeals to authority shaping opposing viewpoints. Western media frames Iran as a security threat, while Iranian media portrays the US as a hegemon and emphasizes national autonomy. The review identifies critical research gaps (e.g., cyber conflicts, longitudinal studies) and provides methodological directions, contributing significantly to applied linguistics and political media discourse analysis.

This article analyses the protection and practical enforcement of women’s rights in Pakistan as a challenge to public security. Its main argument is that the difficulties cannot be reduced to a mere lack of formal law. Pakistan’s constitutional framework recognises equality before the law, prohibits discrimination on the grounds of sex, and ensures women’s full participation in national life. The state has also adopted sector-specific legislation on sexual violence, workplace harassment, honour-related crimes and institutional supervision. Nevertheless, official and publicly available evidence points to a persistent gap between legal guarantees and the protection of life. This gap is visible in gender-based violence, under-reporting, uneven access to justice, limited institutional capacity, provincial disparities, weak implementation of protective procedures and insufficiently integrated data systems. Methodologically, the article combines legal-dogmatic analysis, institutional analysis and a public-management perspective. It draws on constitutional provisions, CEDAW documentation, federal and provincial legal instruments, the National Commission on the Status of Women Act 2012, UNFPA data, Human Rights Commission of Pakistan reporting and recent comparative evidence on the global divide between women’s legal rights and enforcement. The article proposes an institutional capacity model in which women’s rights are treated not merely as declarations of constitutional equality, but as enforceable public-security obligations requiring coordination, resources, trained personnel, evidence-sensitive procedures, reliable data and accountability. The conclusion is that durable protection depends on the state’s ability to convert rights into administrative performance and safe institutional pathways for women.

This study aimed to examine the expectations of newly enrolled students at public and private universities. A survey research design was used in this study. The study population comprised newly enrolled students at public and private universities. A random sampling technique was used to draw the sample. Saeed Ghiasi Nodooshan (2022) _ student expectations have questions used for data collection. The questionnaire contains 60 items) with 3 sections (A) containing Demographic information, (B) Statements (C) questions, which are divided into two main factors: social expectations (items 30) and academic expectations (items 30). The researcher used a questionnaire to collect data from 400 students of four universities in the district of Lahore. The scale was based on a 5-point Likert scale. Descriptive statistics (standard deviation, frequency, mean) and inferential statistics (independent t-test) were used to analyze the data. It was found that students have high expectations for their university life. Data collected from surveys reveal their desires to excel academically, meet new people, and gain practical experience. Furthermore, the study indicates that students often feel anxious about meeting the expectations of their professors and their families, leading to stress and lower academic performance. As such, this research suggests that universities need to address the social and academic expectations of newly enrolled students by offering mentorship programs and support services, creating a supportive environment that would enhance their overall success.

In recent years, strategic educational leadership has been identified as a key factor for sustaining institutional performance in the context of the current educational environment, where change in technology, in social processes, and in organizations is a key concern. In a recent conceptual review, the association between strategic educational leadership and sustainable institutional performance is reviewed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) format. Studies were conducted by searching peer-reviewed articles from major academic databases for trends, theories, and leadership/managerial practices between 2016 and 2025. In recent literature, strategic leadership is highlighted as a means of improving institutional sustainability in terms of designing vision-driven plans, creating collaborative government, innovation, engaging stakeholders, and decision-making in an adaptive way (Habeeb & Eyupoglu, 2024; Al-khamaiseh et al., 2025). In addition to that, sustainable leadership practices play a vital role in organizational resilience, academic excellence, and the adaptation of the institution in a higher education landscape (Ashraf & Hashmi, 2025). In addition, the review emphasizes transformational and digital leadership approaches as critical in enhancing the performance of institutions and sustainability results, which are growing in importance (Ali & Amin, 2025). Results suggest that strategic educational leadership contributes to the sustainability of an institution by establishing shared visions and clear plans, developing the capacity of staff members, and building the capacity for evidence-based management practices. The paper suggests a conceptual approach combining strategic leadership aspects with institutional sustainability indicators to find empirical studies and policy recommendations in the future. This review further enriches the educational leadership body of knowledge by providing a holistic conceptual vision on the potential strategic leadership practices to enhance institutional sustainability and future educational outcomes.

Education serves as the essential basis for national development which needs both intellectual development and emotional plus social health to be developed. Guidance and counselling (G&C) establish themselves as international necessities which help to provide complete education while decreasing student dropouts and increasing student coping abilities and protecting their mental wellbeing (UNESCO 2002 Gysbers Henderson 2012). The American School Counselor Association (ASCA, 2019; 2022) International standards require a student-to-counselor ratio of 250 students per counselor while maintaining confidentiality and equity standards and defining professional roles. Pakistan currently lacks effective and consistent G&C services which function at all educational levels but especially affect elementary education. The university introduced counselling services for its students in 1983 according to Ibrahim and Almas yet the service never developed to support primary school students. National policies, including the NEP 2009 and the Single National Curriculum 2020, mention life skills but fail to provide operational frameworks, defined roles, or accountability mechanisms (Zahid et al., 2019). The National Education Policy (NEP) 2017–2025 gap analysis study examines chapter 21 which focuses on Guidance and Counselling and Character Development. The researchers used qualitative document analysis according to Bowen 2009 and Creswell and Poth 2018 to assess eight dimensions through the Policy Analysis Framework which included definition level specificity role clarity student to-counsellor ratio implementation mechanisms and accountability. The comparative analysis between UNESCO (2019) and WHO (2020) and ASCA models shows that Pakistan's policy lacks crucial elements. The research findings show that counsellor roles remain unspecified while teachers perform counselling duties without proper training and there is no oversight system or financial support for these activities. The study concludes that Pakistan needs an operational framework for G&C at elementary schools which should include staffing standards and training programs and methods for accountability and assessment of results. The educational system in Pakistan needs these gaps to be addressed because their resolution will help decrease student dropouts and enhance student psychosocial growth and bring Pakistani education standards up to global benchmarks.

The green turn in global politics emerged as a transformative phenomenon that reshaped international power relations, ideological orientations, and environmental governance structures. This study examined how environmental sustainability influenced geopolitical power, political ideologies, and the development of planetary environmental governance. A qualitative research design based on a systematic literature review and thematic analysis was employed to investigate contemporary developments in global environmental politics. The study utilized a purposive sample of 50 peer-reviewed scholarly publications obtained from reputable academic databases, including Google Scholar, Scopus, Web of Science, and ResearchGate. Data were analyzed through thematic categorization to identify dominant trends and patterns within the literature. The findings revealed that renewable energy leadership accounted for 28%, green technological innovation represented 22%, and climate governance influence constituted 18% of the major power transformation dimensions identified in the reviewed studies. Regarding ideological shifts, sustainable development emerged as the dominant paradigm with 26%, followed by ecological modernization at 20% and climate justice at 18%. The results further indicated that multilevel governance accounted for 24% and multistakeholder collaboration represented 22% of the key components associated with planetary environmental governance. The analysis demonstrated that environmental sustainability increasingly functioned as a source of political influence, economic competitiveness, and international legitimacy. The study concluded that the green transition significantly transformed global politics by integrating sustainability principles into power structures, governance mechanisms, and policy frameworks. Planetary environmental governance emerged as a critical approach for addressing interconnected environmental challenges through collaborative, science-based, and multilevel governance arrangements.

Interdisciplinary education is an educational approach in which various theories, methods, and subjects are integrated to examine complex topics, enhance understanding, and develop innovative approaches. This chapter offers a comprehensive understanding of interdisciplinary and online interdisciplinary practices for enhancing advanced learning opportunities around the globe. These educational models seek to soften the existing restrictions among numerous subjects to enhance problem-solving and analysis. It enables collaboration, access to diverse disciplinary perspectives, and flexibility across the globe. The online delivery is meant to facilitate interaction without physical presence. Online interdisciplinary education signifies a transformative approach by incorporating various disciplinary perceptions within digitally facilitated settings. It is an educational method that describes how to utilize various digital platforms to integrate knowledge, skills, and techniques from different academic disciplines to help learners understand the real-world complex challenges.