Further Results from the Evaluation of an Intelligent Computer Tutor to Coach Self-Explanation
ITS '00 Proceedings of the 5th International Conference on Intelligent Tutoring Systems
Limitations of Student Control: Do Students Know When They Need Help?
ITS '00 Proceedings of the 5th International Conference on Intelligent Tutoring Systems
Evaluating the Effects of Open Student Models on Learning
AH '02 Proceedings of the Second International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Supporting Learning by Opening the Student Model
ITS '02 Proceedings of the 6th International Conference on Intelligent Tutoring Systems
Are self-assessments reliable indicators of topic knowledge?
Proceedings of the 73rd ASIS&T Annual Meeting on Navigating Streams in an Information Ecosystem - Volume 47
Students' understanding of their student model
AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
Fuzzy cognitive map based student progress indicators
ICWL'11 Proceedings of the 10th international conference on Advances in Web-Based Learning
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Student modeling approaches predominantly focus on modeling student knowledge. For effective learning, however, it is necessary to teach students how to learn, as well as to provide support for learning domain knowledge. Recently, a number of projects focused on students' learning strategies, and initiated work on modeling students' metacognitive skills, such as self-explanation and reflection. This paper focuses on self-assessment as an important metacognitive skill. We present results of an initial study carried out in the context of SQL-Tutor, a system that helps students to learn a database language. We found that not all students are good at evaluating their own knowledge, and that their knowledge level is an important factor. The study is an initial step towards incorporating the meta-level into the existing student model in SQL-Tutor.