Game Mechanics and Artificial Intelligence Personalization: A Framework for Adaptive Learning Systems

Fawad Naseer; Muhammad Nasir Khan; Abdullah Addas; Qasim Awais; Nafees Ayub

doi:10.3390/educsci15030301

journal article Open Access Feb 27, 2025

Game Mechanics and Artificial Intelligence Personalization: A Framework for Adaptive Learning Systems

Fawad Naseer

Muhammad Nasir Khan

Abdullah Addas

Qasim Awais Nafees Ayub

Education Sciences Vol. 15 No. 3 pp. 301 · MDPI AG

View at Publisher Save 10.3390/educsci15030301

Abstract

The phenomenal growth of digital learning platforms has brought new learner engagement and retention challenges to higher education. This study proposes a framework that integrates game mechanics—leveling systems, badges, and timely feedback—with artificial intelligence (AI)-driven personalization to meet the challenges of enhanced adaptability, motivation, and learning outcomes in online environments. Key design elements were identified through literature reviews and consultations with instructional design experts, leading to the development an adaptive learning platform prototype. The prototype underwent an eight-week pilot study with 250 Prince Sattam Bin Abdulaziz University (PSAU) students randomly assigned to a control group (non-adaptive system) or an experimental group (adaptive system). Data sources included pre- and post-tests, platform engagement analytics, and learner perception surveys. The results showed that the adaptive group outperformed the control group in the post-test scores (M = 85.2, SD = 6.4 vs. M = 78.5, SD = 7.2) and motivation levels (M = 4.2, SD = 0.7 vs. M = 3.6, SD = 0.8). Additionally, 82% of the adaptive group achieved mastery-level performance compared to 64% in the control group. These findings demonstrate the potential of integrating game mechanics and AI-driven personalization to transform digital learning, offering a roadmap for scalable, data-driven adaptive platforms. Future research will address long-term retention and diverse subject applications.

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Citations

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References

Details

Published: Feb 27, 2025
Vol/Issue: 15(3)
Pages: 301
License: View

Authors

F

Fawad Naseer

Computer Science and Software Engineering Department, Beaconhouse International College, Faisalabad 38000, Pakistan

M

Muhammad Nasir Khan

Electrical Engineering Department, Government College University Lahore (GCUL), Lahore 54000, Pakistan

A

Abdullah Addas

Department of Civil Engineering, College of Engineering, Prince Sattam Bin Abdulaziz University, Alkharj 11492, Saudi Arabia; Landscape Architecture Department, Faculty of Architecture and Planning, King Abdulaziz University, P.O. Box 80210, Jeddah 21589, Saudi Arabia

Q

Qasim Awais

Department of Electronics and Computer Science, Fatima Jinnah Women University, Old Presidency, Rawalpindi 46000, Pakistan

N

Nafees Ayub

Computer Science Department, Government College University Faisalabad (GCUF), Faisalabad 38000, Pakistan

Funding

Prince Sattam bin Abdulaziz University Award: PSAU/2024/01/99520

Cite This Article

Fawad Naseer, Muhammad Nasir Khan, Abdullah Addas, et al. (2025). Game Mechanics and Artificial Intelligence Personalization: A Framework for Adaptive Learning Systems. Education Sciences, 15(3), 301. https://doi.org/10.3390/educsci15030301

Game Mechanics and Artificial Intelligence Personalization: A Framework for Adaptive Learning Systems

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