Enhancing language learning through adaptive gamification and a multi-agent approach with experience application programming interface and blockchain integration
This article proposes an adaptive gamified architecture model for next-generation language learning, driven by the synergistic integration of multi-agent systems, the Experience Application Programming Interface (xAPI), and blockchain technology. The proposed architecture employs intelligent multi-agent coordination to dynamically personalize learning content and e-assessment activities in real time, adapting continuously to individual learners’ behaviors and proficiency levels. To enhance engagement and retention, the system integrates card-based gamification mechanics, including interactive challenges and real-time reward mechanisms. The xAPI enables comprehensive learning analytics and interoperability across platforms, while blockchain technology ensures secure data storage and data integrity. A case study was conducted to evaluate the effectiveness of the proposed model. The results indicate that participants in the experimental group achieved significantly higher levels of language proficiency and motivation than those in the control group. These findings suggest that the integration of adaptive learning and gamification can effectively enhance language acquisition outcomes, contributing to the advancement of intelligent foreign language learning (FLL) systems.
Authors
- Yasmeen Alomair (ORCID: https://orcid.org/0000-0002-2153-9393)
- Salah Hammami (ORCID: https://orcid.org/0000-0002-1100-247X)
Institutions
- Jouf University (SA)
- King Saud University (SA)
Publication Details
- Journal
- PeerJ Computer Science
- Published
- 2026-02-23
- DOI
- https://doi.org/10.7717/peerj-cs.3508
- Primary Topic
- Educational Games and Gamification
- Type
- article
- Field-Weighted Citation Impact
- 0.00