Game Analytics Evidence-Based Evaluation of a Learning Game for Intellectual Disabled Users.
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2019
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IEEE Access
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Abstract
Learning games are becoming popular among teachers as educational tools. However, despite
all the game development quality processes (e.g., beta testing), there is no total assurance about the game
design appropriateness to the students' cognitive skills until the games are used in the classroom. Furthermore,
games designed speci cally for Intellectual Disabled (ID) users are even harder to evaluate because of
the communication issues that this type of players have. ID users' feedback about their learning experience is
complex to obtain and not always fully reliable. To address this problem, we use an evidence-based approach
for evaluating the game design of Downtown, A Subway Adventure, a game created to improve independent
living in users with ID. In this paper we exemplify the whole process of applying Game Analytics techniques
to gather actual users' gameplay interaction data in real settings for evaluating the design. Following this
process, researchers were able to validate different game aspects (e.g., mechanics) and could also identify
game aws that may be dif cult to detect using formative evaluation or other observational-based methods.
Results showed that the proposed evidence-based approach using Game Analytics information is an effective
way to evaluate both the game design and the implementation, especially in situations where other types of
evaluations that require users' involvement are limited.
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Keywords
Evidence-based learning, Game analytics, Game design, Game evaluation, Intellectual disability, Learning games, Serious games