Title

Predicting Student Carefulness within an Educational Game for Physics using Support Vector Machines

Document Type

Conference Proceeding

Publication Date

2017

Abstract

Student carefulness is defined as being attentive, mindful or focused on the task at hand. In this paper, we create a predictive model for student carefulness within an educational game called Physics Playground (PP). We used game logs and manually-labeled gameplay clips of 54 students from the Philippines to develop three support vector regression models that predict carefulness using: (1) predictors of the game developers, (2) predictors from social science research, and (3) the combination of these predictors. After preprocessing and feature selection, the support vector regression models were able to significantly predict student carefulness. This research’ empirical findings suggest that carefulness in Physics Playground can best be predicted by expanding the model of the game developers and including predictors that have been previously researched in the broader social science literature.

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