Abstract

Design elements of serious game recommender system is a web-based software to propose design elements of serious game to the system users. Design elements of serious game are components that required to design serious game such as features and game mechanics. The research about recommender system for design elements of serious game is a relatively new research in serious game domain because research about recommendation system mainly for game players not for game designers. Many things need to be considered by serious game developer to make a game which can help the players to learn something. The recommender system helped serious game developers to determine the design elements of the game from the learning content to make the game. The domain data are analyzed from the relationship of Bloom Digital Taxonomy with game genres and game mechanism. The system is developed using knowledge-based: case and constraint-based filtering. Case-based filtering is used to find similar serious game examples from the user input of learning goal, target rating, and target player. Constraint-based filtering is used to search recommendation from the knowledge base. To get recommendation from the recommender system, user need to input learning goal to the system, and the results are recommendation of serious game mechanics and features. The level of success of the recommendation system is measured by input some constraints into the system and match the constraints with the result of recommendation produced by the system. Furthermore, crosscheck of the system functionalities was done to evaluate the system. According to the evaluation result, design elements of serious game recommender system was able to provide game mechanics and game features as the base of serious game designing which suitable with the learning content. Another result of evaluation showed that the design of the recommender system could be developed to be a design elements of serious game recommender system to propose design elements of serious game that match with the learning contents.

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