Interacting with Inspectable Bayesian Student Models
International Journal of Artificial Intelligence in Education
Modeling students' metacognitive errors in two intelligent tutoring systems
UM'05 Proceedings of the 10th international conference on User Modeling
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
Can Help Seeking Be Tutored? Searching for the Secret Sauce of Metacognitive Tutoring
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
A New Paradigm for Intelligent Tutoring Systems: Example-Tracing Tutors
International Journal of Artificial Intelligence in Education
Improving students' meta-cognitive skills within intelligent educational systems: a review
FAC'11 Proceedings of the 6th international conference on Foundations of augmented cognition: directing the future of adaptive systems
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
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The Self-Assessment Tutor (SAT) is an add-on component to Cognitive Tutors that supports self-assessment in four steps: prediction, attempt, reflection, and projection. The SAT encourages students to self-assess their ability spontaneously while problem solving, and to use help resources accordingly. For that reason its episodes precede the students' work with the Cognitive Tutor, which itself remains unchanged. The SAT offers detailed feedback and help function to support the Self-Assessment process. A complementary instruction is given to students before working with the SAT. We hypothesize that working with the SAT will encourage students to self-assess on subsequent problems requiring similar skills, and thus will promote learning. A classroom evaluation of SAT is currently in progress.