Abstract
In the present paper we present analysis of gaming actions with MathSpring, an established ITS for mathematics for high school students. Our findings indicate that both student and problem features were similarly predictive of gaming behaviors, as well as that gaming was associated with lower excitement and lower learning gains.
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Notes
- 1.
This analysis uses dependent samples, which impacts the validity of the p value. While p < .001 in our analysis, this is not our focus – we are interested in the model parameters, and these will still be valid under the conditions of the present analysis (e.g., A. Field, 8.3.2.1, Discovering Statistics).
References
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This research was supported by NSERC discovery grant #1507 and NSF grant #1324385.
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Peters, C., Arroyo, I., Burleson, W., Woolf, B., Muldner, K. (2018). Predictors and Outcomes of Gaming in an Intelligent Tutoring System. In: Nkambou, R., Azevedo, R., Vassileva, J. (eds) Intelligent Tutoring Systems. ITS 2018. Lecture Notes in Computer Science(), vol 10858. Springer, Cham. https://doi.org/10.1007/978-3-319-91464-0_41
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