Abstract
As learning analytics is still an emerging discipline, there is a lack of a standardized method for its data collection and analysis, especially in educational games where players’ data can vary greatly. This paper presents an LA model for determining students’ motivation within a game-based learning environment by analyzing their in-game data. In the proposed model, three motivational factors are assessed: goal orientation, effort regulation, and self-efficacy. This paper also presents implementations of the game Fraction Hero developed using the RPG Maker MV engine as well as the Learning Analytics system and dashboard. In the experiment, thirty-one Grade 6 students from the University of the Philippines Integrated School were asked to answer a 10-item survey about their self-perceived motivation toward solving fraction problems, and afterwards play the game for data collection. Based on the results, it was revealed that the students’ in-game motivation was significantly higher than their self-perceived motivation.
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Flores, R.L., Silverio, R., Feria, R., Cariaga, A.A. (2019). Motivational Factors Through Learning Analytics in Digital Game-Based Learning. In: Tlili, A., Chang, M. (eds) Data Analytics Approaches in Educational Games and Gamification Systems. Smart Computing and Intelligence. Springer, Singapore. https://doi.org/10.1007/978-981-32-9335-9_11
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DOI: https://doi.org/10.1007/978-981-32-9335-9_11
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