Evaluation of a meta-tutor for constructing models of dynamic systems

Lishan Zhang, Winslow Burleson, Maria Elena Chavez-Echeagaray, Sylvie Girard, Javier Gonzalez-Sanchez, Yoalli Hidalgo-Pontet, Kurt VanLehn

Research output: Contribution to journalConference articlepeer-review


While modeling dynamic systems in an efficient manner is an im- portant 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 com- pared to the original software. The results indicate that students who studied with the meta-tutor did indeed engage more in deep modeling practices.

Original languageEnglish (US)
Pages (from-to)37-41
Number of pages5
JournalCEUR Workshop Proceedings
StatePublished - 2013
EventWorkshops at the 16th International Conference on Artificial Intelligence in Education, AIED 2013 - Memphis, United States
Duration: Jul 9 2013Jul 13 2013


  • Empirical evaluation
  • Intelligent tutoring systems
  • Meta-tutor

ASJC Scopus subject areas

  • General Computer Science


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