Titlebook: Artificial Intelligence in Education; 16th International C H. Chad Lane,Kalina Yacef,Philip Pavlik Conference proceedings 2013 Springer-Ver

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Exploring the Relationships between Design, Students’ Affective States, and Disengaged Behaviors wit past research. At the same time, we find that the affective state of engaged concentration is significantly associated with features associated with lower frequencies of disengaged behavior. This analysis suggests that simple re-designs of tutors along these lines may lead to both better affect and

Anticlimax

What Makes Learning Fun? Exploring the Influence of Choice and Difficulty on Mind Wandering and Engaparticipants also scored substantially higher on a subsequent knowledge test (.= 1.27). These results suggest that choice and text difficulty differentially impact mind wandering, engagement, and learning and provide important considerations for the design of ITSs and serious games with a reading co

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Class vs. Student in a Bayesian Network Student Modelhe result shows that modeling at coarser grain sizes can actually result in higher predictive accuracy, and data about classmates’ performance is results in a higher predictive accuracy on unseen test data.

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Comparing Student Models in Different Formalisms by Predicting Their Impact on Help Successsuccess rate of tutorial decisions. We test the method on data logged by Project LISTEN’s Reading Tutor, which chooses randomly which type of help to give on a word. We report the cross-validated accuracy of predictions based on four types of student models, and compare the resulting policies’ expec

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Defining the Behavior of an Affective Learning Companion in the Affective Meta-tutor Projectotivation while learning. Our project aims to investigate whether the use of affective interventions in a meta-cognitive tutor can help students achieve deeper modeling of dynamic systems by being persistent in their use of meta-cognitive strategies during and after tutoring. This article is an expe

Canary

Exploring the Relationships between Design, Students’ Affective States, and Disengaged Behaviors witoff-task. In particular the design features of a tutor have found to predict substantial amounts of variance in gaming and off-task behavior. However, it is not yet understood how this influence takes place. In this paper we investigate the relationship between a student’s affective state, their ten