ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
International Journal of Human-Computer Studies
AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
Carelessness and goal orientation in a science microworld
AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
Contextual slip and prediction of student performance after use of an intelligent tutor
UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
Adapting to when students game an intelligent tutoring system
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
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We study the relationship between student carelessness and affect among high-school students using a Cognitive Tutor for Scatterplots, using a machine-learned detector of carelessness and field observations of student affect. In line with previous research, we say a student is careless when he/she makes a mistake performing a task that he/she already knows. This construct is also known as slipping. Somewhat non-intuitively, we find that students exhibiting high levels of engaged concentration slip frequently. These findings imply that a student who is engaged in a task may be overconfident, impulsive or hurried, leading to more careless errors. On the other hand, students who display confusion or boredom make fewer careless errors. Further analysis over time suggests that confused and bored students have lower learning overall. Therefore, these students' mistakes stem from a genuine lack of knowledge rather than carelessness. The use of two versions of the tutor in this study, with and without an Embodied Conversational Agent (ECA), shows no significant difference in terms of the relationship between carelessness and affect.