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|Title:||A Data-driven Path Model of Student Attributes, Affect, and Engagement in a Computerbased Science Inquiry Microworld|
|Publisher:||International Society of the Learning Sciences (ISLS)|
|Citation:||Hershkovitz, A., Baker, R., Gobert, J., & Nakama, A. (2012). A Data-driven Path Model of Student Attributes, Affect, and Engagement in a Computerbased Science Inquiry Microworld. In van Aalst, J., Thompson, K., Jacobson, M. J., & Reimann, P. (Eds.), The Future of Learning: Proceedings of the 10th International Conference of the Learning Sciences (ICLS 2012) – Volume 1, Full Papers (pp. 167-174). Sydney, NSW, AUSTRALIA: International Society of the Learning Sciences.|
|Abstract:||Work in recent years has shown that a student's goals, attitudes, and beliefs towards learning impact their level of engagement during learning, and that engagement during learning plays a key role in learning outcomes. In this paper, we investigate the mechanisms through which a student's goals, attitudes, and beliefs impact the student's engaged and disengaged behaviors. In particular, we study whether affect is a mediating variable between learner attributes and engagement/disengagement during learning. To this end, we conduct exploratory path analysis on data from middle school learners who were conducting inquiry in science a microworld. We find weak but significant relationships between variables related to attitudes and beliefs and variables related to affective states and engagement. We present a path model that highlights boredom as an important mediator between a tendency towards avoiding novelty and off-task behavior during learning.|
|Appears in Collections:||ICLS 2012|
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