A Journey to Identify Users' Classification Strategies to Customize Game-Based and Gamified Learning Environments


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Game designers and researchers have sought to create gameful environments that consider user preferences to increase engagement and motivation. In this sense, it is essential to identify the most suitable game elements for users' profiles. Designers and researchers must choose strategies to classify users into predefined profiles and select the most appropriate game elements for each user. This activity may challenge designers, learning designers, and researchers since they must base their choice on personal aspects that require a deep understanding. Therefore, this article aims to assist game designers, learning designers, and researchers in selecting user classification strategies to customize and personalize game-based and gamified learning environments. By conducting systematic literature mapping, we consolidate the most common strategies and explore their applications in games and gamification. Our analysis, based on 25 publications, reveals that we can classify the strategies according to user interaction, user personality, learning style, and motivation for learning. Strategies based on user interactions emerge as the most popular, while questionnaires and log data systems are commonly used instruments for identifying user profiles. The findings of this SLM offer valuable knowledge for game designers and researchers to define the criteria that will be used to evaluate the effect of games and gamified environments in educational contexts.
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Key words
Games,Instruments,Task analysis,Systematics,Psychology,Taxonomy,User experience,Distal outcomes,game-based learning,game elements,games,gamification,learning performance,user classification,user type
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