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INVESTIGATING STUDENT SATISFACTION IN ONLINE LEARNING: THE ROLE OF STUDENT INTERACTION AND ENGAGEMENT IN DISTANCE LEARNING UNIVERSITY
Open accessAbstract
This study aimed to analyze student satisfaction and engagement effect in online learning which are influenced by student interaction. We use the concept of interaction which is divided into three types of interactions, namely student interactions with other students, student interactions with tutors/teachers, and student interactions with content. We conducted this research in an open and distance learning university in Indonesia. To answer the research goals, we applied a quantitative research approach utilizing structural equation modelling to verify our proposed hypotheses. To gain the data, we exploit an online survey through a questionnaire and the data were being collected randomly. The population of this study was all students in Faculty of Economics who registered in online learning at the first semester of 2018 that reach as many as 124,041 students. We attached the questionnaires in all online classes and 4,305 of them were completed and could be used for statistical analysis. We proposed four hypotheses and based on the result of structural modelling, we verified that all the hypotheses were supported. The statistical analysis has found that interaction among students, interaction between students and teacher, and interaction between students and content have positive impact on student engagement. The results also showed that student engagement has positive impact on student satisfaction. We discuss the practical implication and suggestion for future research in the results and discussion section.
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“In an online setting, student engagement is equally crucial to their success and performance [24].”
From Impact of online learning on student's performance and engagement: a systematic review (2024) · cites this paper as [24]
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Metadata
- Authors
- MUZAMMIL, M., SUTAWIJAYA, A., & HARSASI, M.
- Affiliations
- Indonesia Open University (ID)
- Venue
- Turkish Online Journal of Distance Education
- Published
- 2020-07-17
- Volume
- 21
- Issue
- Special Issue-IODL
- Pages
- 88-96
- ISSN
- 1302-6488 (ISSN-L)
- OpenAlex
- W3043515395
- Cited by
- 128
- References
- 18
- Citations by year
- 2026: 9 · 2025: 20 · 2024: 25 · 2023: 34 · 2022: 25 · 2021: 13 · 2020: 1
- FWCI
- 27.66
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Turkish Online Journal of Distance Education (publishedVersion)
- DergiPark (Istanbul University) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Social Sciences › Education › Online and Blended Learning
- Social Sciences › Education › Technology-Enhanced Education Studies
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Keywords
- student satisfaction, online learning, student engagement, student interaction, peer interaction, student-teacher interaction, learner-content interaction, distance education
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
