Genetic Programming Techniques for Enhancing Engagement in Educational Game Development

Authors

  • Maria Santos PhD Candidate, Faculty of Computer Science, University of Sa˜o Paulo, Brazil
  • Li Wei PhD Candidate, School of Educational Technology, Tsinghua University, China
  • Johan van Dijk PhD Candidate, Centre for Learning Sciences, University of Amsterdam, Netherlands

Keywords:

Genetic Programming, Educational Games, Learner Engagement, Adaptive Content

Abstract

Educational games offer powerful affordances for learning, yet designing engaging content remains complex. This study introduces a Genetic Programming (GP) framework to evolve game mechanics and content focused on learner engagement. Drawing on SelfDetermination Theory, the GP evolves game events to maximize engagement metrics. We validate across two school settings (N=150) and show a 22% increase in engagement time and 15% rise in intrinsic motivation. The evolved content also outperformed handcrafted versions in session length (p¡0.01), indicating GP’s potential for adaptive and personalized game design.

Published

2025-06-27

Issue

Vol. 1 No. 1 (2024)

Section

Articles

License

Copyright (c) 2025 Future - Educational Innovation and Soft Computing

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.