Exploring the Factors Affecting Students’ Internet Habits, Self-Efficacy in E-Learning, and Academic Achievement: Structural Equation Modeling Approach

This research seeks to investigate the variables that might affect university-level students’ internet habits, their e-learning self-efficacy and academic achievement in a technology-enhanced teaching and learning environment. To attain the aforementioned objective the Information System Success (ISS) and Technology Acceptance Model (TAM) were employed. A total number of 371 students responded to an online questionnaire. To test the hypothesized model and examine whether the data aligns with the research framework, Structural Equation Modeling (SEM) and confirmatory factor analysis (CFA) were performed. The Person correlation analysis revealed the strongest positive and significant correlation between the intention to use e-learning and user satisfaction, as well as between self-efficacy in e-learning and Internet habits, while moderate negative and significant correlations were found between computer anxiety and user satisfaction and technological complexity and user satisfaction. Further, the results of the study unveiled that internet habits and e-learning self-efficacy significantly predict students’ academic achievement. However, even though the study found that intention to use LMS, computer anxiety, technological complexity, subjective norms, and LMS user satisfaction are not significant predictors of students’ academic achievement, intention to use LMS, technological complexity, and subjective norms, were found to be significant predictors of students’ internet habits. Furthermore, intention to use LMS, computer anxiety, and technological complexity significantly predicted students’ self-efficacy of e-learning. Besides, bridging the gaps in the existing research, the study’s outcomes provide recommendations for educational policymakers, instructors, and students, on how to improve and enhance students’ learning outcomes in the technology-enhanced teaching and learning environment.

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Publication Details

Journal
SAGE Open
Published
2025-04-01
DOI
https://doi.org/10.1177/21582440251339286
Citations
3
Primary Topic
Technology Adoption and User Behaviour
Type
article
Field-Weighted Citation Impact
12.51
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article

Exploring the Factors Affecting Students’ Internet Habits, Self-Efficacy in E-Learning, and Academic Achievement: Structural Equation Modeling Approach

Senad Bećirović, Mersad Dervić, Boris Mattoš
3 citations
SAGE Open
Technology Adoption and User Behaviour
12.51
article

Exploring the Factors Affecting Students’ Internet Habits, Self-Efficacy in E-Learning, and Academic Achievement: Structural Equation Modeling Approach

Senad Bećirović, Mersad Dervić, Boris Mattoš
article en
3 citations

Abstract

This research seeks to investigate the variables that might affect university-level students’ internet habits, their e-learning self-efficacy and academic achievement in a technology-enhanced teaching and learning environment. To attain the aforementioned objective the Information System Success (ISS) and Technology Acceptance Model (TAM) were employed. A total number of 371 students responded to an online questionnaire. To test the hypothesized model and examine whether the data aligns with the research framework, Structural Equation Modeling (SEM) and confirmatory factor analysis (CFA) were performed. The Person correlation analysis revealed the strongest positive and significant correlation between the intention to use e-learning and user satisfaction, as well as between self-efficacy in e-learning and Internet habits, while moderate negative and significant correlations were found between computer anxiety and user satisfaction and technological complexity and user satisfaction. Further, the results of the study unveiled that internet habits and e-learning self-efficacy significantly predict students’ academic achievement. However, even though the study found that intention to use LMS, computer anxiety, technological complexity, subjective norms, and LMS user satisfaction are not significant predictors of students’ academic achievement, intention to use LMS, technological complexity, and subjective norms, were found to be significant predictors of students’ internet habits. Furthermore, intention to use LMS, computer anxiety, and technological complexity significantly predicted students’ self-efficacy of e-learning. Besides, bridging the gaps in the existing research, the study’s outcomes provide recommendations for educational policymakers, instructors, and students, on how to improve and enhance students’ learning outcomes in the technology-enhanced teaching and learning environment.

SAGE OpenVol. 15(2)
American University of the Middle East (KW), Kirchliche Pädagogische Hochschule Wien/Niederösterreich (AT), Bratislava University of Economics and Business (SK)
Openalex Percentile: Top 2%
Technology Adoption and User Behaviour
12.51
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