Automatic Game Experience Identification in Educational Games

Wilk Oliveira, Luiz Rodrigues, Armando Toda, Paula Palomino, Seiji Isotani

Resumo


One of the main challenges in the field of educational games is the automatic and implicit users' game experience identification. To face this challenge, we present an exploratory study by using a data-driven based approach for collecting and identifying this experience. We used two different data-mining techniques aiming to associate the user's data logs from an educational game with their game-like experience. Our main results indicate that it is possible to extract the automatic and implicit acquisition of the student's game experience in educational games and demonstrate how user's data logs drive their experiences. We also provided different associations between user data logs in educational games and the student's game experience.

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DOI: https://doi.org/10.5753/cbie.sbie.2019.952