Skip to main content Skip to main navigation


Metacognitive practice makes perfect: Improving students’ self-assessment skills with an intelligent tutoring system.

I. Roll; V. Aleven; Bruce McLaren; K.R. Koedinger
In: G. Biswas; S. Bull; J. Kay; A. Mitrovic (Hrsg.). Proceedings of the 15th International Conference on Artificial Intelligence in Education - Lecture Notes in Computer Science. International Conference on Artificial Intelligence in Education (AIED), June 28 - July 1, Auckland, New Zealand, Pages 288-295, Vol. 6738, Springer, Berlin, 2012.


Helping students’ improve their metacognitive and self-regulation skills holds the potential to improve students’ ability to learn independently. Yet, to date, there are relatively few success stories of helping students enhance their metacognitive skills using interactive learning environments. In this paper we describe the Self-Assessment Tutor, an intelligent tutoring system for improving the accuracy of the judgments students make regarding their own knowledge. A classroom evaluation of the Self-Assessment Tutor with 84 students found that students improved their ability to identify their strengths while working with the Self-Assessment Tutor. In addition, students transferred the improved self-assessment skills to corresponding sections in the Geometry Cognitive Tutor. However, students often failed to identify their knowledge deficits a-priori and failed to update their assessments following unsuccessful solution attempts. This study contributes to theories of Self-Assessment and provides support for the viability of improving metacognitive skills using intelligent tutoring systems.