Game-based Learning Model through Intelligent Agents

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. Intelligent agent programs make decisions or perform operations based on information collected on a programmed schedule, user input, experiences, or their environment. Artificial Intelligence allows the application of intelligent assistance through intelligent agents and identifies their degree of intelligence which is the best way of improving game-based learning models. This research performed a survey of scholarly reviews on gamebased learning and found that educational game intelligence is the main hindrance behind the success of pedagogical games in the learning sector. Finally, this paper presents a framework for improving game-based learning models through intelligent agents, intelligent assistance, and rational intelligence for the benefit of learners, pedagogical game developers, trainers, and educational training institutes.