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An Assessment of Statistical Classification for Gamification and Socially Oriented Methodologies in Undergraduate Education

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Computer Supported Education (CSEDU 2021)

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Abstract

We present in this paper an analysis of the effect of gamification and social learning/teaching on the performance of students. We identify course variables that quantitatively explain the improvements reported when using these methodologies integrated in the course design, and apply techniques from the machine learning domain to conduct success/failure classification methods. We found that, generally, very good results are obtained when an ensemble approach is used, that is, when we blend the predictions made by different classifiers.

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Sousa-Vieira, M.E., López-Ardao, J.C., Fernández-Veiga, M. (2022). An Assessment of Statistical Classification for Gamification and Socially Oriented Methodologies in Undergraduate Education. In: Csapó, B., Uhomoibhi, J. (eds) Computer Supported Education. CSEDU 2021. Communications in Computer and Information Science, vol 1624. Springer, Cham. https://doi.org/10.1007/978-3-031-14756-2_19

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