A second paper accepted to AIED2013.
16th International Conference on Artificial Intelligence in Education
Memphis, TN, USA.
July 9-13, 2013
Abstract
While modeling dynamic systems in an efficient manner is an important skill to acquire for a scientist, it is a difficult skill to acquire. A simple step-based tutoring system, called AMT, was designed to help students learn how to construct models of dynamic systems using deep modeling practices. In order to increase the frequency of deep modeling and reduce the amount of guessing/gaming, a meta-tutor coaching students to follow a deep modeling strategy was added to the original modeling tool. This paper presents the results of two experiments investigating the effectiveness of the meta-tutor when compared to the original software. The results indicate that students who studied with the meta-tutor did indeed engage more in deep modeling practices.
Reference
Zhang, L., Burleson, W., Chavez-Echeagaray, M.E., Girard, S., Gonzalez-Sanchez, J., Hidalgo-Pontent, Y., and VanLehn, K. (2013). Evaluation of a Meta-Tutor for Construction Models of Dynamic Systems. Lecture Notes in Computer Science. Artificial Intelligence in Education. Proceedings of the 16th International Conference on Artificial Intelligence in Education (AIED). Memphis, TN, USA. July 2013. Springer-Verlag Berlin Heidelberg. Volume 7926 LNAI, pp 666-669. ISSN: 0302-9743. doi: 10.1007/978-3-642-39112-5_84.