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University teaching innovation through digital game-based learning: Pre-service teacher readiness for digital transformation in higher education
Full text linkThe use of game-based digital tools has become a highly relevant and dynamic element in the training of future educators, playing a pivotal role in shaping diverse teaching and learning processes. These tools offer a more engaging, effective, and interactive learning experience, designed to boost student motivation and provide immediate feedback. This study examines the impact of a didactic intervention using gamified digital tools (Genially, Quizizz, & WebQuest) on students' learning and motivation in online university classrooms. The intervention was implemented over five months with future teachers (n = 262) enrolled in Early Childhood and Primary Education programs, as well as Music and Physical Education specializations at a private Spanish university. A design involving measurements before and after the intervention was employed to assess its impact, including an exploratory and a confirmatory factor analysis to validate the instrument’s three-dimensional structure. The findings confirm that the use of digital games enhances students’ perceptions of their own learning. Moreover, correlation analyses supported the robustness of the results, showing consistent relationships between the dimensions, while differences across age, gender, and degree type remained minimal or disappeared after the intervention. These results have practical implications for higher education, supporting the integration of such tools not only in music and physical education but across a range of curricular subjects
Effects of macroeconomic variables on unemployment in Kenya
Full text linkUnemployment remains a major global challenge, with uneven progress across regions towards the 3% target. In Kenya, despite various interventions since independence, the issue remains unresolved and persistent. The aim of the study was to examine the effects of macroeconomic variables (economic growth, lending rate, development expenditure, and VAT) on unemployment in Kenya and provide empirical insights for designing policies to create employment. The study employed a time series research design to assess how changes in the macroeconomic variables under review influenced unemployment. The study adopted a two-regime Markov switching model with all parameters switching on secondary data for the period 1991-2024. Regime 1 represents a period of stagnating unemployment, while regime 2 represents a period of trend unemployment. The findings established that in both regimes, while economic growth significantly reduced unemployment, development expenditure was found to significantly increase unemployment. Conversely, the lending rate reduced unemployment, but the effect was only significant in regime 2. Similarly, VAT significantly increased unemployment only in regime 2. The findings imply that policymakers should promote sustainable and inclusive growth, while strategically allocating development funds to sectors that are labor-intensive and have high employment potential to create more employment opportunities and reduce unemployment. Additionally, they should enhance access to credit and consider targeted VAT reforms, such as exemptions or reductions of VAT rates, especially during periods of trend unemployment
Agro-climatic shocks and multidimensional poverty in rural Nigeria: The nexus
Full text linkThe increasing frequency and intensity of agro-climatic shocks pose serious threats to rural livelihoods in Nigeria, where agriculture remains the primary source of sustenance. This study examines the relationship between agro-climatic shocks and multidimensional poverty among rural households, utilizing data from the 2018/2019 General Household Survey. Using the Multidimensional Poverty Index, logit regression, and ordinary least squares regression models, the study assesses the extent and determinants of multidimensional poverty in the face of climate-induced shocks. The findings reveal that many rural households experience multidimensional poverty, with 60.8 percent facing key deprivations in access to education, healthcare services, and basic infrastructure. Poor rainfall, property loss, and declining output prices are major contributors to worsening poverty. Households affected by poor rainfall are more likely to fall into multidimensional poverty, reflecting the vulnerability of rain-fed agriculture to climatic variability. Limited access to credit, non-participation in cooperative societies, and lack of extension services further increase poverty risks by weakening adaptive capacity. The study calls for climate-resilient agricultural policies, improved rural financial inclusion, and stronger social safety nets as essential measures to reduce the adverse effects of agro-climatic shocks and support the resilience of rural communities in Nigeria
Analysis and control of the permanent magnet synchronous motor model
Full text linkThe permanent magnet synchronous motor (PMSM) is rapidly becoming a cornerstone of diesel–electric ship propulsion. The dynamics of the PMSM are highly nonlinear and require thorough understanding to enable efficient operation. In this work, bifurcation analysis and multi-objective nonlinear model predictive control (NMPC) are performed on a PMSM model. The PMSM is frequently used for diesel–electric ship propulsion. Bifurcation analysis is a powerful mathematical tool used to address the nonlinear dynamics of such processes. Several factors must be considered, and multiple objectives must be met simultaneously. MATLAB program MATCONT was employed to perform the bifurcation analysis. The MNLMPC calculations were carried out using the optimization language PYOMO, in conjunction with advanced global optimization solvers IPOPT and BARON. The bifurcation analysis revealed the existence of Hopf bifurcation points and a limit point. The MNLMC converged on the Utopian solution. The Hopf bifurcation point, which causes an undesirable limit cycle, is eliminated using an activation factor involving the tanh function. The limit point, which can lead to multiple steady-state solutions, is advantageous because it allows the Multiobjective nonlinear model predictive control calculations to converge to the Utopia point, representing the optimal solution in the model
Building A Portfolio Under Economic Uncertainty
Full text linkThis study explores how the returns and volatility of stocks, gold, bonds, and Bitcoin (BTC) respond to movements in inflation, interest rates (SBI), and exchange rates. To capture inter-asset relationships, the Granger Causality Test was applied, while GARCH modeling was used to evaluate hedging behavior under normal market conditions. An investment portfolio was then formulated using the Arbitrage Pricing Model (APT), comprising 28% stocks, 16.28% gold, 26.76% bonds, and the remaining proportion in BTC, delivering an estimated return of 0.0178 with optimized risk. The dataset covers monthly trading activity from 2018 to 2023 as in-sample observations, with an additional seven months used for out-of-sample validation. The results reveal that BTC returns correlate with those of gold and bonds, while stock volatility shows a link to BTC volatility. Gold consistently serves as a hedge against macroeconomic variables, whereas bonds primarily act as a portfolio diversifier. These findings underscore the relative stability of gold and bonds as instruments for risk mitigation against BTC’s inherent volatility. Viewed through a sustainability lens, incorporating gold and bonds into the portfolio enhances resilience, lowers systemic risk, and supports long-term financial sustainability, aligning investment strategies with responsible and stable wealth management
Exploring Information Asymmetry and Fair-Trade Mechanisms for Sustainability in Taiwan’s Used Car Market
Full text linkThis study examined information asymmetry comprising adverse selection and moral hazard and the role of fair-trade mechanisms in promoting sustainability in Taiwan’s used car market. Using a qualitative document analysis of literature, reports, and statistical data, the research found that adverse selection prevented buyers from distinguishing between high- and low-quality vehicles, driving higher-quality cars out of the market. Consequently, moral hazard intensified as sellers concealed defects for profit. However, enhanced information technology and greater market transparency helped mitigate asymmetry by enabling buyers to better assess product quality and strengthening regulatory oversight. The findings underscored key policy implications for market governance, fair-trade regulation, and sustainability accounting. Improved information disclosure and accountability enhanced consumer protection, reduced unethical behavior, and supported market efficiency and stability. As adverse selection and moral hazard diminished, the market evolved toward fairness and sustainability. Overall, the study connected information asymmetry with fair-trade policy, offering insights for regulators to strengthen disclosure standards and market transparency. It also emphasized the importance of sustainability accounting in reinforcing consumer trust, accountability, and long-term market resilience, providing valuable guidance for policymakers in designing balanced and transparent governance frameworks
Year-wise analysis of school responsiveness of school teachers towards NISHTHA 2.0 online in-service teacher education program
Full text linkThe present study aims to assess the responsiveness of school teachers to the 13-course module of the NISHTHA 2.0 online in-service teacher education program. This research employs a descriptive survey method. The study involved teachers from the Muzaffarpur district in Bihar, India, who participated from 2021 to 2024. Eight blocks (four from the eastern subdivision and four from the western) were randomly selected from a total of sixteen using the lottery method, and teachers from these blocks were chosen through cluster sampling. Data collection tools included a self-made inventory and semi-structured interviews. Percentage analysis and the t-test were used as primary statistical tools for analyzing quantitative data, while qualitative data from interviews were analyzed using thematic analysis. Notable differences were observed in enrollment and completion rates among the 13 courses in the NISHTHA 2.0 program, with overall participation declining over time. Each course recorded some level of responsiveness from school teachers, indicating that all modules engaged at least a portion of the target population, despite variations across years, blocks, and subjects. No course exceeded 50% enrollment in any year, suggesting staggered teacher participation over multiple years. This study contributes to the global understanding of professional development by offering valuable insights into the design and implementation of large-scale online in-service programs
Revisiting the forecasting power of public health expenditure and climate change impact on life expectancy in Nigeria: A scenario analysis.
Full text linkIn this study, we investigate the forecasting power of public health expenditure and the impact of climate change on life expectancy in Nigeria. This study relies on time-series data covering a period of 35 years (1988 to 2022) and uses a bias-adjusted ordinary least squares (OLS) method to predict the relationship and ARMSE to forecast with 8 policy options (scenarios) for 5 years. The analysis is based on data sourced from FAO, 2025, and WDI, 2025 databases. The results reveal a positive impact of both climate change (CC) and public health expenditure (PHE) on life expectancy (LE). In a single predictor model, for every one-degree Celsius rise (or fall) in CC and a percentage rise (or fall) in PHE, LE will rise (or fall) by 52.3 and 2.82, respectively. However, in a multiple predictor equation, the responses of LE to a change in CC and PHE are 15.14 and 2.12, respectively. We also reveal the 3rd scenario as the best option for policymaking. Given these positive impact results, the study concludes that climate change has led to an improvement in healthcare investment in Nigeria to mitigate the effects of climate-induced health challenges. We thus advise the government to sustain its improvement in the health sector through budgetary allocation and implementation
Acceptance and use of technology in online learning in higher education: A student perspective
Full text linkThis study examines a level and model for technology acceptability and use in online learning inside universities. The unified theory of UTAUT is used as an analysis tool. An associative quantitative method is used with a sample of 392 students. Data were collected by distributing questionnaires through a specially designed Google Form. The data obtained were then analyzed using variance-based SEM-PLS. The study findings show the adoption and utilization of technology in online education for university students are excellent. In addition, the structural analysis shows that all hypotheses developed in the model have a solid and significant direct and indirect correlation. Four predictors tested as a model, namely performance expectancy, effort expectancy, social influence, and facilitating conditions can predict behavioral intentions. Furthermore, behavioral intentions influence usage behavior positively and significantly. The conclusion of this study makes it clear that the UTAUT model can predict the acceptance and use of technology in online learning for university students. This study provides practical implications for university managers and policymakers to build students' trust in the technology offered by providing easy access and facilities according to their needs and expectations. Facilitating conditions including performance, adequate internet network access and compatible technology need to be considered by all parties so that the use of technology can be carried out smoothly
Evaluating the effectiveness of a computerized achievement test using learn smart for psychometric assessment under item response theory
Full text linkThis study aimed to reveal the differences in individuals’ abilities, their standard errors, and the psychometric properties of the test according to the two methods of applying the test (electronic and paper). The descriptive approach was used to achieve the study’s objectives. The study sample consisted of 74 male and female students at the University of Technology and Applied Sciences in Rustaq. An electronic test was built on the Learn Smart platform supported by artificial intelligence in psychological measurement. The results showed no statistically significant differences in the individuals' average ability estimates and their standard errors between the electronic and paper-based tests. Besides, the vocabulary difficulty estimates in the electronic test ranged between -2.562 and 2.007 and the vocabulary difficulty estimates in the paper-based test ranged between -3.483 and 2.194. All of them are within the acceptable range. The chi-square values for the electronic test items are not statistically significant except for items (8 and 10). On the other hand, all chi-square values for the items on the paper test are not statistically significant except the item numbers (3, 6, 8, 10 and 12) which are statistically significant at the 0.05 and 0.01 levels