A Hybrid Methodology for Gamification Element Ranking Based on Big Five Traits Using Neutrosophic MCDM: Personalized Approach for Educational Games

In the domain of game design, comprehending players' personality traits is pivotal for crafting engaging and immersive gaming experiences. This paper presents a novel hybrid methodology for ranking gamification elements based on the Big Five Personality Traits, employing neutrosophic Multiple Criteria Decision Making (MCDM). The Big Five model encompassing openness, conscientiousness, extraversion, agreeableness, and neuroticism provides a comprehensive framework for analyzing personality variations. By exploring the interplay between these traits and gamification elements, designers can tailor gaming experiences to individual preferences, thereby enhancing player engagement. The methodology systematically ranks gamification elements according to users' scores on each personality trait, facilitating a personalized learning environment. Utilizing neutrosophic MCDM, which adeptly addresses decision-making under uncertainty and indeterminacy, this approach enables the optimization of game element selection. The time complexity of the proposed methodology ensures the methodology is scalable and efficient for large datasets, maintaining performance while delivering personalized experiences. This paper establishes a direct mapping between the Big Five traits and game elements, identifying the most suitable elements for each user. By incorporating neutrosophic decision-making, the proposed approach has the potential to transform educational gaming, resulting in a more effective and enjoyable player experience.