Journal of Applied Data Sciences
Vol 6, No 4: December 2025

Moodle-based Blended Learning: Factors Influencing the Behavioral Intention of Undergraduate Students

Khazalah, Fayez (Unknown)
Alrababah, Saif Addeen (Unknown)
Mansour, Ayman (Unknown)
Alafif, Tarik (Unknown)



Article Info

Publish Date
13 Sep 2025

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.

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Journal Info

Abbrev

JADS

Publisher

Subject

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

Description

One of the current hot topics in science is data: how can datasets be used in scientific and scholarly research in a more reliable, citable and accountable way? Data is of paramount importance to scientific progress, yet most research data remains private. Enhancing the transparency of the processes ...