Integrating Reinforcement AI into the Design of Educational Games

Abstract

The emergence of reinforcement-based AI for text generation (Chat-GPT) and image creation (Dall-E) has opened a wide range of possibilities for changing the game design and development process. While game development researchers have mostly focused on integrating these technologies to improve production workflow and demonstrate their use in the creation of content for entertainment purposes (intelligent NPCS), there is very little knowledge on how to integrate this technology into the design of educational games. In this paper, we present the results of integrating reinforcement AI (text and image generation) into educational gaming experiences by graduate students enrolled in a game-based learning course. The students were given a core set of requirements that enable the integration into their project with some flexibility on the desired educational outcome. The produced experiences were then evaluated by a small sample of experts (gaming and learning sciences) and their observations were compiled. Specifically, we describe the wide range of experiences developed by the students and the results of a qualitative study with a small group of experts that evaluated these experiences. Our results indicate that reinforcement AI-based integrations into educational game design and development helps enrich the user experience and has the potential to improve learning outcomes.