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- Behrooz Mostafavi, Tiffany Barnes
- EDM
- 2014

The interactions of concepts and problem-solving techniques needed to solve open-ended proof problems are varied, making it difficult to select problems that improve individual student performance. We have developed a system of data-driven ordered problem selection for Deep Thought, a logic proof tutor. The problem selection system presents problem sets of… (More)

- Behrooz Mostafavi, Michael Eagle, Tiffany Barnes
- LAK
- 2015

We have developed a novel data-driven mastery learning system to improve learning in complex procedural problem solving domains. This new system was integrated into an existing logic proof tool, and assigned as homework in a deductive logic course. Student performance and dropout were compared across three systems: The Deep Thought logic tutor, Deep Thought… (More)

- Behrooz Mostafavi, Zhongxiu Liu, Tiffany Barnes
- EDM
- 2015

Deep Thought is a logic tutor where students practice constructing deductive logic proofs. Within Deep Thought is a data-driven mastery learning system (DDML), which calculates student proficiency based on rule scores weighted by expert-decided weights in order to assign problem sets of appropriate difficulty. In this study, we designed and tested a… (More)

- I. WEI JIN, LORRIE LEHMANN, +6 authors Behrooz Mostafavi
- 2011

- Behrooz Mostafavi, Tiffany Barnes
- International Journal of Artificial Intelligence…
- 2016

Deductive logic is essential to a complete understanding of computer science concepts, and is thus fundamental to computer science education. Intelligent tutoring systems with individualized instruction have been shown to increase learning gains. We seek to improve the way deductive logic is taught in computer science by developing an intelligent,… (More)

- Behrooz Mostafavi, Tiffany Barnes
- LAK
- 2016

Data-driven methods have previously been used in intelligent tutoring systems to improve student learning outcomes and predict student learning methods. We have been incorporating data-driven methods for feedback and problem selection into Deep Thought, a logic tutor where students practice constructing deductive logic proofs. In this latest study we have… (More)

- Behrooz Mostafavi, Guojing Zhou, Collin Lynch, Min Chi, Tiffany Barnes
- AIED
- 2015

Research shows that expert-crafted worked examples can have a positive effect on student performance. To investigate the potential for data-driven worked examples to achieve similar results, we generated worked examples for the Deep Thought logic tutor, and conducted an experiment to assess their impact on performance. Students who received data-driven… (More)

- Christa Cody, Behrooz Mostafavi
- SIGCSE
- 2017

We have been incrementally adding data-driven methods into the Deep Thought logic tutor for the purpose of creating a fully data-driven intelligent tutoring system. Our previous research has shown that the addition of data-driven hints, worked examples, and problem assignment can improve student performance and retention in the tutor. In this study, we… (More)

- Zhongxiu Liu, Behrooz Mostafavi, Tiffany Barnes
- ITS
- 2016