Game-based learning has been in existence for decades, and the importance of games as an instructional teaching tool can no longer be overemphasized. Due to its benefits as a teaching and learning tool, mostly when compared to the traditional teaching style, game-based learning received considerable attention. Many training institutions have adopted this contemporary mode of learning. However, despite its success in the learning sector, there have been some looming critics in terms of its degree of intelligence. The ease of use, responsiveness, dynamicity, predictability, and information dissemination strategy to learners formed part of the main critics who pointed out its drawbacks. Various researchers provided findings regarding what constitutes intelligent game-based learning models suitable for learning and teaching purposes. This diverted the focus of attention to intelligent agents in pedagogical game development. Therefore, the introduction of intelligent agents in game-based learning models brought alongside another key concept called randomness. Randomness as a matter of uncertainty occurs when some actions occur haphazardly, and it plays a very vital role in game development. This research performed a survey of scholarly reviews on game-based learning and found that intelligence and randomness are the main hindrances behind the success of pedagogical games in the learning sector. Finally, this paper presents a framework for improving game-based learning models through rational intelligence and the application of balanced randomness for the benefit of learners, pedagogical game developers, trainers, and educational training institutes.

Author: Tefo Kgosietsile

Published in: International Conference for Internet Technology and Secured Transactions (ICITST-2022)

• Date of Conference: 6-8 December 2022
• DOI: 10.20533/ICITST.2022.0011
• ISBN: 978-1-913572-55-6
• Conference Location: Virtual (London, UK)