Journal of Global Research in Education and Social Science

Institutional Gender Inequality and Fertility Timing Across Countries

Masaaki Yoshimori — Mon, 15 Jun 2026 00:00:00 +0000

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

Mercy Malopa, Edward Missanjo, Henry Kadzuwa, Winfore Ng’ambi — Fri, 10 Jul 2026 00:00:00 +0000

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.

Towards a Sustainable Art Ecosystem: How Immersion in XR Virtual Exhibitions Shapes Purchase Intentions

Xi Wang, Hai Tao Du — Wed, 22 Jul 2026 00:00:00 +0000

Aim: This study investigated the effect of immersive extended reality (XR) virtual art exhibitions on art purchase intentions among Chinese university students. Based on the Technology Acceptance Model (TAM), it examined the effects of perceived usefulness, perceived ease of use, and immersion (flow experience) on purchase intention in XR-based commercial art environments.

Method: A survey experiment was conducted in which 300 Chinese university students visited a VR art exhibition and completed a questionnaire measuring TAM constructs, immersion, and purchase intention.

Results: The analysis indicated that exposure to virtual exhibitions substantially increased perceived usefulness and, consequently, purchase intention. Perceived usefulness and perceived ease of use were positively associated with art purchase intention, and perceived usefulness partially mediated this relationship. The TAM framework was strongly supported in the XR art context, with perceived usefulness and perceived ease of use jointly accounting for 66% of the variance in purchase intention.

Implications: Greater immersion in virtual art exhibitions can increase consumer engagement and willingness to purchase. Retailers and platforms should create intuitive and immersive XR environments to support art sales. The findings inform e-commerce strategies in the art market and clarify the theoretical contribution of TAM research in immersive environments.

Originality: This study is among the first empirical investigations of Chinese university students in a commercial art XR environment and provides evidence of how immersion in virtual exhibitions shapes art purchase intention. It offers practical insights for the use of XR technology in art marketing and contributes to understanding technology acceptance on emerging digital art platforms.

Exploring Teachers’ Pedagogical Practices for Enhancing English Speaking Skills in Upper Primary Classrooms in Paidha Town Council, Zombo District, Uganda

Irene Afoyorwoth, Sekitto Ayoub, Josephine Bweyale — Wed, 19 Aug 2026 00:00:00 +0000

This study explored teachers’ pedagogical practices for enhancing English speaking skills among selected upper primary learners in Paidha Town Council, Zombo District. The study was motivated by a lack of research on how teachers actually use speaking methods in poor rural schools. The study was guided by Social Cognitive Theory and the Communicative Language Teaching approach. A qualitative research design was used to obtain an in-depth understanding of classroom practices and teachers’ instructional experiences. Data were collected from two selected primary schools through semi-structured interviews, classroom observations, and document analysis. The participants included eight upper primary English language teachers and two headteachers. Of these, three teachers were chosen for fourteen lesson observations to allow for a closer and more detailed examination of daily classroom interactions. The findings show that, while teachers knew about communicative practices such as group discussions, role-plays, storytelling, dialogues, and question-and-answer activities, they struggled to use them effectively in actual lessons. The main pattern in the findings revealed that teachers knew the theory but failed to use it in practice. Instead of conducting authentic speaking tasks, lessons became simple, repetitive routines in which group work was often poorly structured, role-plays were mainly conducted through textbook reading, storytelling activities were frequently reduced to copying notes, and choral responses dominated many lessons. The study also found a gap between planned learner-centred activities and actual classroom delivery. These findings suggest that teachers require more practical support in planning, managing, and assessing speaking-focused activities. By showing these classroom challenges in rural schools, this study adds to existing knowledge by indicating that knowledge of teaching methods alone is insufficient to help pupils speak well if teachers lack practical support for their specific school environments. The study concludes that improving pupils’ English-speaking skills requires the consistent use of participatory classroom practices, constructive feedback, and targeted professional development for teachers.

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

Jingwei Zhou, Wenhao Dai — Fri, 03 Jul 2026 00:00:00 +0000

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

Hanhao Liu, Zezhong Yang — Fri, 10 Jul 2026 00:00:00 +0000

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.

Artificial Intelligence and Digital Platforms in Language Education at Bangladeshi Higher Education Institutions: A Critical Narrative Review of Evidence, Mechanisms and Structural Constraints

Sharmin Rahman Bipasha — Thu, 13 Aug 2026 00:00:00 +0000

Generative artificial intelligence and institutional digital platforms have entered university language classrooms in Bangladesh faster than the research base needed to evaluate them. This article critically reviews the evidence produced within and about Bangladeshi higher education, reading it against the wider international literature on computer-assisted language learning, automated feedback and generative writing tools. Sources were identified through structured searching of openly accessible scholarly indexes and citation databases, supplemented by backward and forward citation tracing and by examination of authoritative institutional documents, with the final search conducted on 5 June 2026. The synthesis is organised around five analytical problems: the structural and sociolinguistic conditions that precede adoption; the epistemic limits of the perception and acceptance studies that dominate the national corpus; the contested evidence on writing and feedback; the near-absence of evidence on speaking, interaction and multilingual practice; and the governance vacuum surrounding academic integrity. Three conclusions are reasonably secure. Adoption among Bangladeshi students and teachers is already extensive and largely informal; teacher preparedness is constrained by institutional rather than individual factors; and no study conducted in Bangladesh has yet measured language learning outcomes under controlled conditions. Claims about improved writing, speaking or engagement in this setting therefore rest almost entirely on self-report. The international experimental literature on which such claims are implicitly modelled reports effects that are heterogeneous, sensitive to learner digital literacy, and accompanied by evidence of cognitive offloading and reduced authorial control. The review argues that the prevailing framing of artificial intelligence as an access-equalising technology is inadequately supported in a system already stratified by uneven connectivity, examination-oriented assessment and contested medium-of-instruction policy. Priorities for subsequent work include outcome-based designs anchored in Bangladeshi curricula, investigation of tool performance on Bangla-English bilingual production, and empirical study of institutional policy formation rather than its absence.

From Prototype to Classroom: A Scoping Review of the Effectiveness and Translational Readiness of AI-Enabled Educational Interventions for Autistic K–12 Learners

Fnu Najma Abdul Aleem — Mon, 17 Aug 2026 00:00:00 +0000

Artificial intelligence (AI) has been positioned as a means of individualising instruction and social-communication support for autistic pupils in kindergarten to grade twelve (K–12) settings. Prototype systems that combine social robotics, adaptive virtual environments, wearable sensing and, more recently, large language models have proliferated, yet the transition from laboratory demonstration to durable classroom practice remains poorly characterised. This critical narrative review examines what the accessible evidence supports about the effectiveness of AI-enabled educational interventions for autistic K–12 learners, and appraises the readiness of these interventions for translation into ordinary school settings. Literature was identified through structured searching of open scholarly indexes and registries, supplemented by citation tracking and targeted retrieval from institutional sources, covering January 2000 to 5 June 2026. Evidence was appraised for design adequacy, comparator quality, outcome selection, reporting completeness and implementation relevance, and was synthesised thematically around three interdependent readiness dimensions: technical, contextual and normative. Pooled estimates from robot-mediated and virtual-reality interventions are consistently positive but unstable, with wide confidence intervals, heavy dependence on small trials, and effect sizes that attenuate sharply when analyses are restricted to randomised designs and detection-bias-free outcomes. Very few studies examine generalisation to untrained settings, maintenance beyond short follow-up, or delivery by teachers under routine conditions. Machine-learning components that supply the adaptive behaviour of these systems are rarely validated externally, and evidence from speech and vocal-marker research indicates substantial performance loss across tasks, languages and speaker populations. Reporting of adverse events, conflicts of interest and pre-registered outcomes remains inadequate across the wider autism intervention literature, which constrains confidence in the subset relevant to AI. Contextual readiness is the least-studied dimension: implementation research in autism education concentrates on early implementation phases and rarely addresses sustainment, cost or scale-up. Normative questions concerning outcome selection, autistic participation in design and data governance are raised more often than they are resolved. The field is therefore better described as accumulating feasibility evidence than as approaching classroom readiness, and the principal constraint is no longer technical novelty but the absence of pragmatic, teacher-delivered, adequately powered evaluations conducted in ordinary schools.