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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.

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.

No abstract