Table · dataset · 2026
<p dir="ltr"><b>Gamification and AI in Mobile Learning: Improving Chinese Cultural Understanding through Digital Applications</b></p>
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<p dir="ltr">The growing use of mobile learning (m-learning has opened new avenues for delivering effective cultural education.
Description
Previous literature mostly concentrated on language acquisition, but this work extends beyond language outcomes to cultural education. This research aims to determine the association of different m-learning features on Chinese cultural education.
It examines several m-learning features like interactive multimedia content (IMC), adaptive learning algorithms (ALA), gamification elements (GME), Virtual Reality & Augmented Reality (VR/AR), and social learning features (SLF) on m-learning in Chinese cultural education. A quantitative approach was adopted, and data were obtained via an online survey and offline questionnaires. A purposive sampling technique and stratified random sampling were used.
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The results indicate that each m-learning feature showed a positive association on cultural education. IMC showed the most significant association (β = 0.381, p < 0.001), followed by GME (β = 0.312, p < 0.001), and VR/AR (β = 0.289, p < 0.001), underscoring the significance of interactive, enjoyable, and immersive learning experiences. The results also revealed that SLF (β = 0.196; p < 0.001) and ALA (β = 0.157; p = 0.007) had significant positive association, which means that social interaction and personalized learning are responsible for mobile-assisted cultural education.
It also provides practical application for teachers, developers, and policymakers interested to make mobile-assisted cultural education effective, immersive, and learner-centered.</p>
Links
Where it is published
- DOI doi.org/10.6084/m9.figshare.33829642.v1 ↗
DOI / persistent id · from figshare com
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from figshare com
Topics
Provenance · 1 source records, 18 field assertions
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|---|---|---|---|
| figshare | oai:figshare.com:article/33829642 | 7 d ago | JSON v1 |
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