eLearning Platforms Adoption and Use in Universities: a SEM Approach

eLearning platforms adoption and use by university students has become prevalent worldwide, developing nations still lag behind. This study aims to establish critical paths amongst determinants of “behavioural Intention” and “use behaviour” in eLearning platforms adoption and use by university students. The PLS-SEM method was used to evaluate the modified unified theory of acceptance and use of technology path model. A sample of 520 university students from Zimbabwe was used to collect data using an online survey created on Google Forms. The findings show that “Habit” had the most influence (0.804) on “Behavioural Intention,” followed by “Performance Expectancy” (0.319) and “Effort Expectancy” (0.270). Behavioural Intention had a significant influence (0.831) on “Use Behaviour.” The path model explains 88.8% of “Behavioural Intention,” and 76.1% of “Use Behaviour” variances. This study, though limited, is significant to students in higher education, policy makers and researchers given the importance of technology in the education sector. Keywords: ELearning technologies; ELearning Platforms; eLearning; Online Learning; ODeL; UTAUT; UTAUT2; Higher Education; Zimbabwe

Authors

Publication Details

Journal
Studia Universitatis Babeș-Bolyai Psychologia-Paedagogia
Published
2025-12-24
DOI
https://doi.org/10.24193/subbpsyped.2025.2.06
Primary Topic
Technology Adoption and User Behaviour
Type
article
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article

eLearning Platforms Adoption and Use in Universities: a SEM Approach

Alexander Maune
Studia Universitatis Babeș-Bolyai Psychologia-Paedagogia
Technology Adoption and User Behaviour
article

eLearning Platforms Adoption and Use in Universities: a SEM Approach

Alexander Maune
article en

Abstract

eLearning platforms adoption and use by university students has become prevalent worldwide, developing nations still lag behind. This study aims to establish critical paths amongst determinants of “behavioural Intention” and “use behaviour” in eLearning platforms adoption and use by university students. The PLS-SEM method was used to evaluate the modified unified theory of acceptance and use of technology path model. A sample of 520 university students from Zimbabwe was used to collect data using an online survey created on Google Forms. The findings show that “Habit” had the most influence (0.804) on “Behavioural Intention,” followed by “Performance Expectancy” (0.319) and “Effort Expectancy” (0.270). Behavioural Intention had a significant influence (0.831) on “Use Behaviour.” The path model explains 88.8% of “Behavioural Intention,” and 76.1% of “Use Behaviour” variances. This study, though limited, is significant to students in higher education, policy makers and researchers given the importance of technology in the education sector. Keywords: ELearning technologies; ELearning Platforms; eLearning; Online Learning; ODeL; UTAUT; UTAUT2; Higher Education; Zimbabwe

Studia Universitatis Babeș-Bolyai Psychologia-PaedagogiaVol. 70(2)
Partnerships for the goals
Openalex Percentile: Top 13%
Technology Adoption and User Behaviour
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