Journals
2026 EN
Zakariya Yusuf Feyisara · Adeniran Babatunde Joseph · Umahaba Ramatu Ematum
+1 more
We examined how mathematics self-concept influences approaches to learning mathematics among prospective mathematics teachers (PMTs) in Nigeria. Using a cross-sectional survey design within the context of students’ approaches to learning theory, we generated datasets from 200 final-year PMTs across government-owned higher institutions in Nigeria. This theory provides a framework for explaining differences in approaches to learning and the factors that affect them. We measured the constructs using validated instruments and analysed the dataset through structural equation modelling. The measurement models demonstrated appropriate construct validity with omega reliability coefficients ranging from .788 to .879. Contrary to theoretical expectations, mathematics self-concept showed a significant negative effect on deep approaches to learning (β = −.685, p < .001) and a significant positive effect on surface approaches to learning (β = .307, p < .001), with the structural model exhibiting an appropriate fit (comparative fit index = .955, Tucker–Lewis index = .941, standardised root mean square residual = .055). These suggest that within the PMTs context, strong mathematics self-concept may be grounded in examination-oriented success, thereby reinforcing surface learning strategies rather than conceptual engagement. Conversely, lower self-concept appears to prompt compensatory deep learning efforts. These findings are theoretically provocative as they challenge the directions of effects between research constructs.
Journals
2026 EN
Diab Jasmin Lilian · Jouhari Ibrahim · Mellies Romain
This study presents the first comprehensive, data-driven analysis of irregular maritime migration from Lebanon to Europe between 2019 and 2022. Amid Lebanon’s economic, political, and social collapse, sea departures surged, becoming a critical survival strategy for refugees and Lebanese nationals alike. By triangulating 150 sources including the Lebanese Armed Forces, UNIFIL, media outlets, humanitarian NGOs, and cross-validating with UNHCR, International Organization for Migration, and Frontex, the study compiles a unified, publicly accessible dataset mapping departures, routes, interceptions, and casualties. Findings show a tenfold increase in attempts, from 208 individuals in 2019 to over 2,500 in 2022, alongside a sharp rise in Lebanese nationals among those departing. The analysis traces a geographic expansion of departure points, a shift toward longer and riskier routes to Italy, and escalating smuggling costs reflecting growing commercialization. Allegations of systemic corruption, state complicity, and weakened enforcement capacity further compound risks at sea. Beyond documenting trends, the study challenges narratives that frame Lebanon solely as a refugee-hosting state, repositioning it as an emerging origin point within Mediterranean migration systems. It provides essential empirical infrastructure for policy and scholarship while situating observed patterns within broader crisis dynamics without asserting causal claims.
Journals
2026 EN
Alasso Mohamud Mohamed · Omar Abukar Mukhtar · Mohamed Mohamud Ahmed
+1 more
This study examines the impact of Somali citizens’ perceptions of e-service efficiency and government transparency on their attitudes toward corruption in a post-conflict setting. Utilizing theories of transparency, digital governance, and institutional accountability, this study employed a quantitative approach, using a structured questionnaire administered to 488 respondents in Mogadishu. Structural equation modeling (PLS-SEM) was used to assess the relationships between variables. The findings indicate that both perceived government transparency ( β = 0.507, p < 0.001) and e-service efficiency ( β = 0.189, p < 0.01) significantly affect citizens’ attitudes toward corruption, with transparency exerting a more substantial influence. These results suggest that enhancing transparency and optimizing digital service delivery can promote public intolerance of corruption even in fragile state contexts. However, the 43% variance suggests that other institutional and sociopolitical factors also contribute. This study recommends prioritizing transparent governance, improving digital infrastructure, promoting digital literacy, and incorporating citizen feedback mechanisms to bolster public integrity and trust in Somalia.
Journals
2026 EN
Mkamilo Herman · Busungu Constantine · Juma Ibrahim
Rice ( Oryza sativa ) is an essential crop for both food security and household income in Tanzania; however, yields remain low at 2–3 tonnes per hectare, compared with the global average of 4.5 tonnes. Among thefactors limiting productivity is rice blast disease, caused by Magnaporthe oryzae ( M. oryzae ). This study assessed farmers’ knowledge, attitudes, and management practices related to the disease across major rice-growing regions. A mixed-methods approach was adopted, combining qualitative and quantitative techniques. Farmers were purposively selected from Morogoro, Tanga, Kilimanjaro, Mwanza, and Mbeya, and data were collected through semi-structured, face-to-face questionnaires, surveys, and transect-walk field observations. Most respondents had primary education (56%), followed by secondary education (27%), while only 10.5% had tertiary education. Chi-square analysis showed no significant differences in management practices implemented by farmers (χ² = 19.2, p > 0.2). Agrochemicals were the primary control method for 43.5% of respondents, whereas 19% practiced early weeding. Farmers in Kilimanjaro and Tanga combined field monitoring with fungicide use, while those in Mwanza and Mbeya often intervened only after symptoms appeared. A significant difference emerged in awareness of peak disease months (χ² = 85, p < 0.001), with April and May identified as high-risk periods.
Journals
2026 EN
Hassan Ali Yusuf · Mohamed Amir Mohamud · Abdullahi Abdulfatah Mohamed
+1 more
Agriculture serves as the cornerstone of Somalia’s economy, providing livelihoods for the majority of the population and contributing significantly to national economic development. Despite its critical role, the key factors influencing agricultural production in Somalia have not been thoroughly analyzed. Thus, this study explores the roles of foreign direct investment (FDI), foreign aid, and agricultural labor in influencing agricultural production in Somalia from 1990 to 2023, employing the Autoregressive Distributed Lag (ARDL) model, along with stationarity tests, bounds testing, and Granger causality analysis, to ensure the robustness of the results. The findings confirm a stable long-term relationship among variables. In the long term, FDI and agricultural labor positively affect agricultural production, while development food aid has an adverse effect. This implies sustained capital and labor boost productivity, but food aid may distort markets and create dependency. In the short term, food aid and labor positively influence production, with FDI’s effect being positive but insignificant. The Granger test results of this study indicate unidirectional causality from agricultural output to FDI, suggesting that agrarian growth attracts investment. A bidirectional relationship exists between labor and production. Agricultural labor also Granger-causes food aid, implying that increased employment may reduce future reliance on food aid. Based on the findings, the study suggests easing legal and administrative barriers to attract FDI, enhancing public-private partnerships, maintaining targeted emergency assistance while gradually shifting toward locally supportive and production-enhancing modalities to reduce long-term dependency and support sustainable agriculture, and improving labor productivity through training, mechanization, and institutional reforms.
Journals
2026 EN
Alsalman Abdullah · Alrifai Samar · Younas Sarah
+6 more
Gamma irradiation is a crucial step for enhancing genetic variability and improving crop traits when conducting mutation breeding. Thus, this study aimed to identify the optimum irradiation doses that enhance growth while avoiding damage during the early seedling growth phase of Hassawi rice ( Oryza sativa L.). Seeds were exposed to six gamma irradiation doses (0, 100, 200, 300, 400, and 500 Gy) using a Cobalt-60 source and grown under controlled laboratory conditions. Seedling growth traits, including shoot length, root length, and total seedling length, were measured at two intervals one week apart. Growth responses showed a clear dose-dependent pattern with significant differences among the treatments ( p < 0.05). Low-to-moderate doses (100–300 Gy) stimulated or maintained seedling growth, with notable increases in shoot and total seedling lengths at specific stages, indicating hormetic effects. In contrast, higher doses (≥400 Gy) consistently reduced shoot, root, and total seedling length, markedly impairing seedling vigor. This study highlights the value of gamma irradiation as a tool for crop improvement when applied at low doses (100–300 Gy) and recommends further research on yield-related traits to enhance practical agricultural applications.
Journals
2026 EN
Fallatah Mahmoud Ibrahim · Hoda Najmul
Entrepreneurship is widely acknowledged as a driver of economic development in emerging economies, yet the specific financial capabilities that underpin individuals’ entrepreneurial intentions (EI) remain insufficiently understood. Drawing on the Theory of Planned Behavior and complementary perspectives from self-regulation and consumer socialization, this study examines how four dimensions of financial capability—financial knowledge, financial attitude, financial behavior, and financial socialization—influence EI among university students in Saudi Arabia. Using survey data from 438 students and Partial Least Squares Structural Equation Modeling, the findings show that financial attitude, financial behavior, and financial socialization significantly predict EI, whereas the direct effect of financial knowledge on EI is non-significant. By demonstrating that financial knowledge exerts influence primarily through attitudinal and behavioral channels rather than as a direct driver of intention, the study advances a more nuanced understanding of how financial capability shapes entrepreneurial motivation. Theoretically, the study contributes by extending the Theory of Planned Behavior with finance-specific capability constructs and clarifying their distinct roles in intention formation. Practically, the findings offer actionable insights for educators and policymakers to design integrated, behavior-oriented financial capability interventions aimed at strengthening early-stage entrepreneurial intentions.
Journals
2026 EN
Wanyana Mercy · Musenze Ibrahim Abaasi · Abdul Mpaata Kaziba
Using the social exchange theory and Spritzer’s empowerment model, this research explains how servant leadership affects innovative work behavior. There is a lack of empirical evidence on servant leadership’s influence on innovative behavior within the African or higher education context, as well as mediating models of psychological empowerment in the relationship between servant and innovative work behavior. The present study particularly hypothesizes that psychological empowerment positively mediates the Servant Leadership-Innovative Work Behavior relationship. To examine the proposed links, using a cross-sectional survey, the study uses a sample of 308 academic staff members employed by Uganda’s public universities. The findings derived from the structural equation modeling validate each of the study’s hypotheses and suggest new research directions of inquiry for servant leadership and innovative work behavior research. Specifically, servant leadership predicted innovative work behavior, and psychological empowerment significantly mediated the relationship between servant leadership and innovative work behavior. The present study clarifies the hitherto understudied relationship between servant leadership and employees’ innovative work behaviors in Uganda’s public universities, as well as the crucial role psychological empowerment plays in this relationship. This is an important finding for both theory and practice.
Journals
2026 EN
Alzoubi Raed Hussam · Abo Murad Maisoon · Shnaikat Baker Gamel
+4 more
With an escalating level of disruption and complexity, the success of crisis management depends more on the symbolic support of the leaders to new technologies such as artificial intelligence (AI). The aim of the research is to investigate why AI symbolization by leaders that is conceptualized as the observable encouragement and endorsement of AI in depth actions and artifacts is important in crisis response within organizations. Drawing on the contingency theory, we investigate what mechanism connect AI-symbolizing connect leaders to improved crisis management. Specifically, we test a serial mediation model where AI knowledge sharing (AIKS) and AI self-efficacy (AISE) explain the pathway from leaders’ AI symbolization to crisis management effectiveness. Data were collected from 343 executives in Jordan’s private airline sector as well as analyzed using PLS-SEM. The findings reveal that leaders’ AI symbolization significantly enhances AIKS and AISE, which in turn strengthen crisis management capabilities. In practice, the findings indicate that leaders’ visible advocacy for AI fosters an organizational climate that strengthens technological confidence and communication, particularly in high-stakes contexts. Moreover, the study addresses gaps at the intersection of leadership, artificial intelligence, and crisis management, offering a timely lens for rethinking organizational preparedness in the digital era.
Journals
2026 EN
Alnor Nasareldeen Hamed Ahmed · Al-Matari Ebrahim Mohammed · Mohammed Omer Alsir Alhassan
+2 more
This paper will be reviewing how the adoption of AI in enterprises has affected financial analysis, with respect to financial reporting, forecast accuracy, and cost-effectiveness between the years 2020 and 2024. The study examines the adoption of AI and the moderating factors of the firm size, age, leverage, and financial loss using 180 observations of 10 banks and 26 insurance firms. The research methodology involves linear regression, OLS and correlation analysis to cover variance and heterogeneity. The findings demonstrate that there is a positive, strong and statistically significant correlation between AI use and performance in financial analysis. Smaller companies are less prone to the use of AI, and there is no strong impact of financial loss. The stability of the traditional and advanced regression models facilitates the validity of the results. The research gives both empirical evidence and practical information on how AI helps to increase the efficiency of financial analysis and serves as a good guide to be followed by decision-makers who want to be more efficient in their analytical performance.