Gamification in e-learning: a MOodle implementation and its effect on student engagement and performance
Abstract
Purpose: This study aims to deploy game elements in an e-learning course on the Moodle platform. One of the greatest challenges of e-learning can be motivating and engaging students in learning. Gamification has been attracting increasing attention as a key underlying aspect of pedagogy that can be used to increase student engagement and motivation in learning. Design/methodology/approach: To investigate student satisfaction and engagement with an e-learning course, here an Information Literacy Skills course, the authors collected data from 104 undergraduate students enrolled on the course in Thailand. In addition, the authors used student interaction data obtained from Moodle to examine whether there were any differences in the frequency of online interaction with the course between the students who performed at an above-average level and those who were below average. Findings: The findings indicated that the students were highly satisfied with the gamification tools in Moodle and they were engaged in the gamified e-learning course. The authors found a significant difference in the frequency of online interaction with the course between the group who performed at an above-average level and the group who were below average. Practical implications: The findings have important implications for the development of gamification in e-learning. Originality/value: This paper fulfills an identified need to study how gamification idea can be implemented in e-learning.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Digital technologies have the capacity to impact psychological wellbeing in both positive and negative ways.
“Digital technologies have the capacity to impact psychological wellbeing in both positive and negative ways.”
From Technology evaluations are associated with psychological need satisfaction across different spheres of experience: an application of the METUX scales (2023) · cites this paper as Poondej and Lerdpornkulrat, 2019
Cites
Engaging Asian students through game mechanics: Findings from two experiment studies
Hew, K. F., Huang, B., Chu, K. W. S., & Chiu, D. K. W. (2016) · Computers & Education · doi:10.1016/j.compedu.2015.10.010 · Cited by 298 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Gamification in Education: Why, Where, When, and How?—A Systematic Review
Zeybek, N., & Saygı, E. (2024) · Games and Culture · doi:10.1177/15554120231158625 · Cited by 172 · see citing works
Burnell, R., Peters, D., Ryan, R. M., & Calvo, R. A. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1092288 · Cited by 33 · see citing works
- Authors
- Poondej, C., & Lerdpornkulrat, T.
- Affiliations
- Srinakharinwirot University (TH)
- Venue
- Interactive Technology and Smart Education
- Publisher
- Emerald
- Published
- 2019-09-19
- Volume
- 17
- Issue
- 1
- Pages
- 56-66
- ISSN
- 1741-5659 (ISSN-L)
- OpenAlex
- W2983150542
- Cited by
- 116
- References
- 1
- Citations by year
- 2026: 9 · 2025: 26 · 2024: 20 · 2023: 26 · 2022: 23 · 2021: 10 · 2020: 2
- FWCI
- 14.89
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Interactive Technology and Smart Education (publishedVersion)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Games and Gamification
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Physical Sciences › Computer Science › Information Systems › Educational Technology and E-Learning
- Keywords
- gamification, online learning, Moodle, student engagement, student motivation, student satisfaction, online interaction, information literacy skills, undergraduate students
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 ›
Are you an author, or do you see a problem with this page? Request a review