Journal of Global Research in Education and Social Science

Institutional Gender Inequality and Fertility Timing Across Countries

2026-06-15T10:46:30+00:00

Background: Fertility behavior is a key area of economic and demographic research because of its strong connections to human capital formation, labor market outcomes, and long-term economic development. Early childbearing is particularly important as it can adversely affect women's educational attainment, employment opportunities, and lifetime earnings, while also generating lasting intergenerational consequences.

Aims: This study asks whether institutional gendered constraints shift the distribution of first births rather than affecting overall fertility levels.

Study Design: A longitudinal cross-country panel study combining a continuous-time life-cycle model with fixed-effects econometric analysis.

Place and Duration of Study: The study was conducted using annual country-level data from 100 countries worldwide obtained from the World Bank, UNESCO, and the United Nations Development Programme (UNDP), covering the period between 1990 and 2023.

Methodology: The paper combines a continuous-time life-cycle model with a strongly balanced panel of 100 countries observed annually from 1990 to 2023. Fertility timing is proxied by adolescent first births, capturing mass in the lower tail of the first-birth distribution. Gender inequality is measured using the UNDP Gender Inequality Index. Two-way fixed-effects models exploit within-country variation over time and allow for nonlinear and dynamic specifications.

Results: The study analyzed a balanced panel of 100 countries from 1990 to 2023 comprising 3,400 country–year observations. Higher Gender Inequality Index (GII) values were significantly associated with earlier fertility timing in fixed-effects models (β = 0.0126, SE = 0.0057, p < 0.05), and the relationship remained robust after controlling for gender development and schooling. Lagged models showed similar positive effects of prior gender inequality on early fertility timing (β = 0.0108, SE = 18.90, p < 0.10). Nonlinear specifications revealed significant regime dependence ( F = 18.90 , p < 0.001), with stronger effects in highly unequal environments. Dynamic models further showed strong persistence in fertility timing over time (β = 0.981 , SE = 0.004, p < 0.001).

Conclusions: Institutional gender inequality reduces incentives to delay childbearing by lowering the opportunity cost of early fertility. The findings indicate that fertility timing responds primarily to structural constraints rather than short-term fluctuations.

Nexus Between Rural Electrification, Climate Change Mitigation and Socioeconomic Outcomes in Malawi

2026-07-10T13:28:42+00:00

Access to clean and affordable energy is important for improving livelihoods and promoting climate change adaptation, mitigation and resilience. This study examined how electricity provision through the Malawi Rural Electrification Programme (MAREP) influenced livelihoods and helped reduce activities that contribute to climate change in Mwaye Village, Balaka District, Malawi. Snowball sampling, saturation principles and structured questionnaires were used to collect data from 72 respondents. The data were analysed using the chi-square test. The results indicate that socioeconomic benefits associated with rural electrification differed significantly (X2=46.32; P<0.05). The main benefits were improved health service delivery (80.1%), income generation (76.5%), job opportunities (72.3%) and rural enterprise creation (71.4%). Other benefits included enhanced education services (56.1%), community development (52.6%) and youth empowerment (50.3%). The results further show that socioeconomic improvements had significantly different effects on climate change adaptation outcomes (X2=54.85; P<0.001). Reported outcomes included reduced dependence on fossil fuel-powered maize mills and generators (90.4%), reduced climate-related health risks (75.2%), reduced reliance on firewood and charcoal for energy (50.6%), strengthened community adaptive capacity (82.3%) and improved drought resilience (74.8%). Overall, the study demonstrates that rural electrification improves livelihoods while reducing emissions-related activities and strengthening community adaptation and resilience. The findings support the continued expansion of electricity distribution to rural areas of Malawi to advance socioeconomic and environmental gains.

AI-VR Synergistic Technology in Virtual Simulation Training for Job-seeking Skills: Personalized Learning, Multimodal Interaction, and Adaptive Assessment

2026-07-03T07:56:31+00:00

This systematic review examines the integration of artificial intelligence and virtual reality in virtual simulation training for job-seeking skills, with attention to personalised learning, multimodal interaction, and adaptive assessment. The review synthesises 31 peer-reviewed sources drawn from five academic databases (Google Scholar, Scopus, ACM Digital Library, IEEE Xplore, Web of Science), covering literature on virtual reality training, artificial intelligence-supported personalised learning, multimodal learning analytics, immersive learning theory, and educational assessment. The review is framed around the need to improve conventional virtual training systems, which often rely on fixed scenarios, limited interaction patterns, and insufficiently individualized feedback. The findings suggest that artificial intelligence may extend the educational value of virtual reality by supporting learner modelling, adaptive content delivery, real-time feedback, and process-oriented assessment. In job-seeking skills training, these functions may help learners practise interview communication, professional behaviour, and workplace-related interaction in simulated environments that can be adjusted to individual performance and learning needs. The reviewed literature also indicates that immersive learning is not automatically effective; learning outcomes appear to depend on instructional design, cognitive load management, scaffolding, and the meaningful use of feedback. Multimodal data, including behavioural, speech, gaze, and interaction indicators, may provide richer evidence for diagnosing learner progress, although privacy, fairness, transparency, and accessibility remain important concerns. Overall, the review indicates that AI-VR integration has potential value for vocational education and job-seeking skills training, but current evidence remains limited by the scarcity of direct empirical studies on fully integrated AI-VR systems; many conclusions are therefore based on theoretical synthesis from related domains rather than direct empirical confirmation. Further research should use rigorous designs, authentic educational settings, and long-term outcome measures to examine whether such systems improve transferable employment-related skills.

Assessing Intelligent Technology Integration and Its Impacts on Mathematics Education in China

2026-07-10T06:40:57+00:00

Intelligent technologies are becoming an important component of mathematics education as schools seek to improve instructional precision, learning support, assessment, and teacher professional development. This review examines how intelligent technology has been integrated into mathematics education in China and identifies the main research themes, reported outcomes, challenges, development pathways, and methodological features in the existing literature. A narrative literature review and content analysis were conducted using 30 highly relevant CNKI-indexed publications on intelligent technology empowering mathematics education published between 2020 and 2025. The review indicates that current studies mainly focus on five dimensions: application scenarios, empowerment outcomes, challenges, development pathways, and research methods. Intelligent technologies are commonly discussed in relation to personalised learning, teaching resource generation, classroom interaction, integrated teaching-learning-assessment systems, and teacher role transformation. Reported benefits include improved teaching precision, richer learning experiences, more timely feedback, and support for data-informed teaching. However, the evidence base remains uneven. Many studies rely on case studies, classroom-practice summaries, or short-term empirical designs, while large-scale and long-term evidence remains limited. The review also identifies concerns regarding teacher digital literacy, student dependence on technological tools, data privacy, algorithmic bias, and unequal access to intelligent resources. Overall, effective integration requires closer alignment between technology, pedagogy, mathematics-specific learning needs, teacher capacity, and ethical governance.