Journal of Global Research in Education and Social Science

Emigration Intentions and Drivers among Residents of Colombo Municipal Council, Sri Lanka

2026-09-03T12:22:41+00:00

Emigration has been a persistent feature of Sri Lanka's socio-economic landscape since the 1970s, but the 2022 economic crisis triggered an unprecedented surge, with foreign employment departures rising from 122,264 in 2021 to a record 311,161 in 2023. While existing research has examined national-level migration trends and the economic drivers of emigration, limited attention has been given to emigration intentions among highly urbanised populations and their relationship with observed national migration patterns. This study examines the drivers of emigration intentions among residents of the Colombo Municipal Council (CMC), Sri Lanka’s most urbanised and highly educated area, and compares them with national migration trends. A quantitative cross-sectional survey was conducted using a structured questionnaire among 69 residents of the Colombo Municipal Council (CMC), selected through non-probability convenience sampling. Data were analysed using descriptive statistics, including frequencies and percentages, and the findings were compared with national migration statistics obtained from secondary sources. Emigration intention among respondents was pervasive: 86.4% intended to migrate within the next five years, with economic factors being the dominant motivation, followed by educational and family reasons. Income dissatisfaction was near universal (95.5%), 90.9% believed that better opportunities existed abroad, and only 22.7% rated their quality of life as good. The comparative analysis shows convergence in economic motivation but sharp divergence in gender and skill profiles: the sample was 63.6% female and 77.3% degree-holding, whereas only 44.7% of actual national departures are female and roughly 21% are classified as skilled. This gap points to constrained migration aspirations among urban women, who face regulatory barriers such as the Family Background Report requirement, and to a distinct brain-drain segment whose departure carries the greatest long-term developmental cost. The study concludes with six evidence-linked policy recommendations: improve income and economic stability, reduce the cost of living, improve urban quality of life, retain skilled human capital, create more quality employment opportunities, and strengthen political stability and good governance.

Benchmarking Documented Student Entrepreneurship Support: A Comparative Study of Highly Ranked Universities Using Clark’s Entrepreneurial University Model

2026-09-03T12:27:09+00:00

Student entrepreneurship has become an increasingly significant function within universities, encompassing entrepreneurship education, mentoring, venture development, funding, incubation, networking, and additional institutional support mechanisms. However, universities differ substantially in the organisation and integration of these forms of support. This study addresses this gap by employing a qualitative comparative documentary research design to examine student entrepreneurship support across ten highly ranked universities and to benchmark documented practices against a focal university. Drawing on Clark's Entrepreneurial University model, the analysis applies five pathways: strengthened steering core, expanded developmental periphery, diversified funding base, stimulated academic heartland, and integrated entrepreneurial culture. The study examines publicly accessible institutional documents, including entrepreneurship centre webpages, programme descriptions, institutional reports, official news releases, and related materials. The findings indicate that leading universities do not adhere to a single model of student entrepreneurship support. Instead, they combine entrepreneurship education, experiential learning, mentoring, venture development, funding, infrastructure, networking, and external engagement in varied institutional configurations. The comparison further reveals that the focal university has documented elements corresponding to all five Clark pathways, although the breadth and consistency of publicly available evidence differ across pathways. These findings suggest that benchmarking should prioritise transferable institutional functions rather than direct replication of specific university structures. As the analysis relies exclusively on publicly accessible institutional documentation, the findings reflect the breadth and visibility of documented support and may not capture practices that are implemented but not publicly reported. This study contributes to research on entrepreneurial universities and student entrepreneurship by demonstrating how comparative documentary analysis can identify institutional patterns and provide a context-sensitive foundation for strengthening university entrepreneurship ecosystems.

Impact of Trade on Economic Growth in India: An Empirical Analysis

2026-09-17T14:07:51+00:00

Aims: The study aims to empirically analyse the impact of trade on economic growth in India during the period 1997–2025. Specifically, the study aims to (i) examine the trend and growth pattern of India’s trade and GDP, and (ii) assess the statistical relationship between trade and economic growth.

Study Design: Quantitative analysis

Methodology: The study relies on annual time-series data sourced from secondary databases such as the World Bank and the Ministry of Commerce and Industry of India. Descriptive statistical techniques are employed to analyse trends and growth rates of GDP and trade. Pearson correlation analysis is used to examine the strength of the association between trade and economic growth. To empirically estimate the impact of trade on growth, a log-linear regression model is applied, with real GDP as the dependent variable and total trade (exports plus imports) as the key explanatory variable.

Results: The empirical findings reveal a strong and positive relationship between trade and economic growth in India. Total trade significantly enhances GDP, with a trade elasticity of 0.667. Exports are found to have a significant positive impact on growth, while imports do not exhibit a statistically significant effect. The extended model confirms the robustness of trade’s contribution even after controlling for gross capital formation. Overall, the results strongly support the trade-led growth hypothesis in the Indian context.

Conclusion: Overall, the results suggest that policies aimed at strengthening export capacity, improving trade infrastructure, and enhancing global competitiveness can further stimulate economic growth in India. Future research may explore sector-specific trade effects and long-run cointegration dynamics to deepen understanding of the trade–growth nexus.

Measuring Student Engagement through LMS Analytics: A Comparative Content Analysis of Moodle, Canvas, Blackboard Learn, and D2L Brightspace

2026-09-18T11:55:48+00:00

Student engagement is an increasingly significant concern in higher education as learning management systems (LMSs) generate and organise extensive data on students' learning activities and interactions. However, LMS analytics do not represent all dimensions of student engagement equally, and limited comparative evidence exists regarding how major LMS platforms publicly document engagement-related indicators. This study addresses this gap through a comparative documentary content analysis of learning analytics in Moodle, Canvas, Blackboard Learn, and D2L Brightspace. Utilising the Student Engagement in Digital Learning (SEDL) Framework, the analysis classifies documented analytics indicators across four engagement dimensions: behavioural, cognitive, emotional, and social. The study examines publicly accessible official LMS documentation, including analytics documentation, reporting and dashboard materials, administrator and instructor documentation, and official developer or API documentation that explicitly identifies learner- or learning-related measures. A standardised search protocol, inclusion and exclusion criteria, unit of analysis, and coding procedure yielded a corpus of 101 distinct student engagement indicators. The findings demonstrate that these indicators are unevenly distributed across platforms and engagement dimensions. Behavioural indicators account for 44 indicators (43.6%), social indicators for 35 (34.7%), and cognitive indicators for 22 (21.8%), while no explicit native emotional engagement indicators were identified. Moodle presents the broadest documented measurement profile, with indicators spanning behavioural, cognitive, and social engagement, whereas Canvas, Blackboard Learn, and D2L Brightspace are more strongly concentrated on behavioural and social indicators. In total, 78.2% of the documented indicators represent behavioural or social engagement, suggesting a hierarchy of measurement visibility in which engagement that produces observable digital traces is more readily represented within native LMS analytics than cognitive or emotional engagement. These findings indicate that LMS analytics do not merely measure a pre-existing construct of student engagement; rather, they shape which aspects of engagement become visible and measurable through digital data. As the analysis relies exclusively on publicly accessible official documentation, the findings reflect documented measurement visibility and may not capture proprietary, configured, or otherwise undocumented capabilities. This study contributes to research on learning analytics and student engagement by demonstrating that comparative analysis of LMS documentation can reveal differences in how contemporary learning management systems operationalise and render student engagement measurable.

Teacher-Perceived Determinants of Learning Retention among Junior High School Students: Basis for an Enhancement Program

2026-09-22T13:20:21+00:00

Learning retention is essential for sustained academic achievement, particularly at the junior high school level, where students build foundational knowledge and skills for subsequent learning. Retention may be influenced by pedagogical practices, including active learning, instructional multimedia, formative assessment, and differentiated instruction, as well as student-related factors such as prior knowledge, intrinsic motivation, study habits, and attention span. Understanding these determinants from teachers’ perspectives can help identify classroom-based factors that support or hinder students’ ability to retain and apply learning over time. This study examined teacher-perceived pedagogical and student-related determinants of learning retention among junior high school students and used the findings as the basis for a Learning Retention Enhancement Program. A mixed-methods design was employed using a researcher-developed questionnaire completed by 84 of 95 teachers, representing an 88.42% response rate, together with open-ended responses on implementation challenges. Teachers reported frequent use of active learning strategies (M = 4.12), instructional multimedia (M = 3.79), formative assessment (M = 4.17), and differentiated instruction (M = 4.09). Among student-related determinants, prior knowledge (M = 3.70) and intrinsic motivation (M = 3.95) were rated positively, whereas study habits (M = 3.35) and attention span (M = 3.21) received neutral ratings. Perceived learning retention was neutral for knowledge recall (M = 3.23) and conceptual understanding (M = 3.35), while application of skills in new contexts was rated positively (M = 3.41). Spearman correlations indicated significant positive associations between the pedagogical determinants and the three retention dimensions. Attention span and study habits showed particularly strong associations with knowledge recall and skill application. Kruskal-Wallis tests showed no significant differences in perceived determinants across teacher age, gender, teaching experience, educational attainment, or subject specialisation (p > .05). The findings support a school-wide enhancement programme centred on retrieval practice, differentiated instruction, formative feedback, attention-supportive pacing, and structured study habits.

Spatial Patterns of Housing and Socio-Economic Deprivation in Rural Communities of Rivers State, Nigeria: Implications for Rural Development Planning

2026-09-23T13:50:46+00:00

Housing deprivation is an important spatial expression of wider socio-economic inequality because the quality, occupancy, service connections and accessibility of a dwelling reflect both household resources and the distribution of public investment. This paper examines spatial patterns of housing and socio-economic deprivation in rural communities of Rivers State, Nigeria, and discusses their implications for rural development planning. This study was conducted in 21 rural communities selected from six Local Government Areas (LGAs)—Abua/Odual, Degema, Opobo/Nkoro, Oyigbo, Ikwerre and Ogu/Bolo in Rivers State, Nigeria. The study adopted a transformative research philosophy and concurrent triangulation mixed-methods design. A household sample of 399 was determined using the Taro Yamane formula, with 372 valid household observations used in the deprivation-index and inferential analyses, complemented by key informant results. Housing deprivation was measured through a composite Housing Deprivation Index (HDI) comprising housing quality, overcrowding, infrastructure access and neighbourhood-condition indicators. A Relative Importance Index (RII) ranked the severity of individual housing problems, while chi-square analysis tested the relationship between socio-economic deprivation and housing condition. Results reveal marked spatial inequality. Ogu-Bolo recorded the highest HDI (2.61, very high), followed by Abua-Odual (2.47, very high), Opobo-Nkoro (2.32, high) and Degema (2.18, high); Oyigbo (1.96) and Ikwerre (1.83) recorded moderate deprivation. Overcrowding was the most severe indicator (RII=.88), followed by shared household facilities (.84), inadequate potable water (.83) and electricity deprivation (.80). The cross-tabulation further showed that 51.4% of highly deprived households occupied poor housing, compared with 18.1% of low-deprivation households. Socio-economic deprivation was significantly related to housing condition, χ² (4) =48.672, p<.001, Cramer’s V=.256. The paper concludes that rural housing deprivation in Rivers State is multidimensional and geographically uneven, with riverine and peripheral communities carrying a disproportionate burden. It recommends institutionalising deprivation-index-based planning, prioritising high-deprivation LGAs, integrating housing with water, electricity, sanitation and accessibility improvements, and strengthening participatory and spatially targeted rural development.

The Relationship Between Artificial Intelligence Literacy, Self-Regulated Learning, and Academic Engagement among University Students Who Use Generative AI at Indonesian Universities

2026-09-25T04:17:27+00:00

Generative artificial intelligence (GenAI) is increasingly used by university students to support information retrieval, idea development, writing, feedback, and learning management, but its educational value may depend on students’ AI literacy and capacity for self-regulated learning. This study examined the associations of AI literacy and self-regulated learning with academic engagement among Indonesian university students who use GenAI. A quantitative associational design was applied to 312 students recruited through purposive online sampling. Data were collected using five-point Likert-scale measures and analysed through validity and reliability tests, classical assumption tests, multiple linear regression, t-tests, an F-test, and the coefficient of determination. AI literacy was positively associated with academic engagement (B = 0.463, t = 12.232, p < 0.001), while self-regulated learning also showed a positive association (B = 0.523, t = 13.263, p < 0.001). The standardised beta coefficient was higher for self-regulated learning (β = 0.496) than for AI literacy (β = 0.457). Together, the two predictors accounted for 64.5% of the variation in academic engagement (R² = 0.645; F = 281.011, p < 0.001). These findings indicate that AI literacy and self-regulated learning are complementary capabilities associated with stronger academic engagement among GenAI-using students. The results support the importance of promoting critical AI use alongside students’ capacity to plan, monitor, and regulate their learning.

From Platform Proficiency to Digital Pedagogy: Digital Competences at Uganda Christian University

2026-09-25T12:28:01+00:00

The study examined the digital competences that enhance the capacity of technology-adapting educators to deliver online learning effectively in private universities in Uganda, with specific emphasis on the TPACK framework. Guided by a constructivist paradigm, the study adopted an exploratory qualitative case study design. Participants comprised 15 technology-adapting educators, three technical staff members, and two focus group discussions. Purposive sampling was used. Data were generated through in-depth interviews, focus group discussions, and document analysis and were analysed thematically. Findings revealed that educators possessed developing digital competences characterised primarily by functional use of the learning management system Moodle, videoconferencing, and basic digital communication platforms. However, their competences varied in depth, with stronger evidence of technological knowledge than of pedagogical application. Through the TPACK lens, educators were able to select and use digital tools to support lesson design, learner engagement, classroom management, assessment, and feedback, while also enabling them to organise and communicate subject-specific concepts. The findings further indicated that online learning depends not merely on educators’ ability to use digital technologies but on their capacity to integrate technology with appropriate pedagogical approaches and subject content. The study concludes that digital competence among educators is multidimensional and is strengthened through meaningful interaction among technology, pedagogy, and subject content. It recommends professional development programmes that move beyond basic technological skills towards sustainable development of TPACK, leading to pedagogically and contextually appropriate technology choices for online learning in higher education contexts.

Knowledge, Attitude and Practices (KAP) of Teachers toward Inclusive Education in Pinamungajan District II

2026-10-01T12:54:57+00:00

Inclusive education seeks to ensure equitable access to quality learning opportunities for all students, including learners with special educational needs. Its effective implementation depends substantially on teachers’ knowledge, attitudes, and classroom practices, as these influence their readiness to accommodate diverse learning needs. However, limited district-level evidence is available on teachers’ preparedness for inclusive education in Pinamungajan District II, particularly regarding the influence of professional and demographic factors on inclusive teaching practices. This study investigated the knowledge, attitudes, and practices (KAP) of teachers regarding inclusive education in Pinamungajan District II. Utilising a descriptive-correlational research design, the study profiled a predominantly female, millennial, and academically ambitious teaching workforce. The results revealed that teachers possessed a neutral level of knowledge (mean = 3.01), a neutral attitude (mean = 3.02), and inconsistent implementation of inclusive practices (mean = 3.07). Significant gaps were identified in technical competencies, specifically regarding legal frameworks (RA 7277), assistive technologies, and differentiated instruction. Correlation analysis using Spearman’s rho revealed very strong, significant positive relationships among knowledge, attitude, and practice, confirming that cognitive understanding and emotional disposition are critical determinants of classroom execution. While most demographic factors showed no significant differences in KAP, grade level handled and training attended emerged as significant predictors of teacher readiness. The primary challenges included resource constraints, large class sizes, and diverse learner needs. To address these gaps, the study proposes the Enhancement Plan for Inclusive Education (EPIE), a strategic framework focusing on technical training, resource localisation, and a tiered certification roadmap to transition inclusive education from passive compliance to a standardised, school-wide culture.