Abstract
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 language | English (US) |
|---|---|
| Title of host publication | CEUR Workshop Proceedings |
| Publisher | CEUR-WS |
| Pages | 37-41 |
| Number of pages | 5 |
| Volume | 1009 |
| State | Published - 2013 |
| Event | Workshops at the 16th International Conference on Artificial Intelligence in Education, AIED 2013 - Memphis, United States Duration: Jul 9 2013 → Jul 13 2013 |
Other
| Other | Workshops at the 16th International Conference on Artificial Intelligence in Education, AIED 2013 |
|---|---|
| Country/Territory | United States |
| City | Memphis |
| Period | 7/9/13 → 7/13/13 |
Keywords
- Empirical evaluation
- Intelligent tutoring systems
- Meta-tutor
ASJC Scopus subject areas
- General Computer Science