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All Journal Indonesian Journal of Electrical Engineering and Computer Science Journal of Applied Data Sciences
Mansour, Ayman
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Moodle-based Blended Learning: Factors Influencing the Behavioral Intention of Undergraduate Students Khazalah, Fayez; Alrababah, Saif Addeen; Mansour, Ayman; Alafif, Tarik
Journal of Applied Data Sciences Vol 6, No 4: December 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i4.888

Abstract

The demand for blended learning by higher education has increased since COVID-19. Blended learning combines the advantages of both face-to-face and online learning. Many HEIs in developing countries have started to depend on Moodle to offer blended courses to their students, as it is freely available and open source. The current study aims to explore the factors that influence the intentions to use Moodle-based Blended Learning (MBBL) by higher education students in a public university in Jordan, a developing country. For this purpose, we used a modified version of the UTAUT2 model. Data were gathered through a survey that targeted undergraduate students. The study used 319 valid response samples and analyzed the data using SmartPLS 4 software that implements PLS-SEM analysis. The data analysis results show that the factors that influence the students’ behavioral intention to use MBBL are performance expectancy (β = .18), effort expectancy (β = .21), social influence (β = .16), and habit (β = .25). However, the results indicate that facilitating conditions and hedonic motivation factors do not have a significant influence. In addition, the results reveal that result demonstrability has significant effect on both performance expectancy (β = .58) and effort expectancy (β = .52). Also, effort expectancy is found to influence performance expectancy (β = .17). Among the influential factors, habit is identified as the strongest predictor of intentions followed by effort expectancy, whereas social influence is the weakest predictor. The proposed model was able to explain 50% of variance in students’ intentions to use MBBL. The current study provides HEIs with valuable insights needed to improve the MBBL process and enhance the performance of students. It also suggests future research directions that build on this study to reach more generalized and stable results.
An improved hybrid AC to DC converter suitable for electric vehicles applications Mahafzah, Khaled A.; A. Obeidat, Mohamad; Alsalem, Hesham; Mansour, Ayman; Riva Sanseverino, Eleonora
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 3: September 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i3.pp1499-1513

Abstract

This paper introduces a novel hybrid AC-DC converter designed for various applications like DC micro-grids, Electric Vehicle setups, and the integration of renewable energy resources into electric grids. The suggested hybrid converter involves a diode bridge rectifier, two interconnected single ended primary inductor converter (SEPIC) and Flyback converters, and two additional auxiliary controlled switches. These extra switches facilitate switching between SEPIC, Flyback, or a combination of both. The paper ex-tensively discusses the operational modes using mathematical equations, deriving specific duty cycles for each switch based on the circuit parameters. This hybrid converter aims to decrease total harmonic distortion (THD) in the line current. The findings exhibit a THD of approximately 14.51%, showcasing a 3% reduction compared to prior hybrid converters, thereby enhancing the power factor of the line current. Furthermore, at rated load conditions, the proposed converter achieves 90% efficiency. To validate the proposed hybrid converter’s functionality, a 4.5 kW converter is simulated and performed using MATLAB/Simulink after configuring the appropriate passive parameters.
Co-Authors A. Obeidat, Mohamad Alafif, Tarik Alrababah, Saif Addeen Alsalem, Hesham Khazalah, Fayez Mahafzah, Khaled A. Riva Sanseverino, Eleonora