PI: Art Graesser
AutoTutor is a computer tutor that helps students learn by holding a conversation in natural language. AutoTutor tracks the cognition and emotions of the student and responds in a manner that adapts to the student. AutoTutor has been developed to help students learn about physics and computer literacy. Emotions are recognized by the dialogue patterns, facial expressions, and body posture of the student.
- Developing AutoTutor for Computer Literacy and Physics. Funding Agency: NSF. $1,274,075.
- Monitoring Emotions while Students Learn with AutoTutor. Funding Agency: NSF. $1,256,000.
- Simulating Tutors with Natural Dialog and Pedagogical Strategies. Funding Agency: NSF. $900,000.
- Why2000: A Tutor that Teaches Mental Models Using Natural Language Dialogs. Funding Agency: ONR. $1,258,875.
- D'Mello, S., Graesser, A. C., & King, B. (2010). Toward spoken human-computer tutorial dialogues. Human-Computer Interaction, 25(4), 289–323. doi:10.1080/07370024.2010.499850
- Graesser, A. C., Jeon, M., & Dufty, D. (2008). Agent technologies designed to facilitate interactive knowledge construction. Discourse Processes, 45, 298–322. doi: 10.1080/01638530802145395
- Graesser, A. C., Lu, S., Jackson, G. T., Mitchell, H., Ventura, M., Olney, A., & Louwerse, M. M. (2004). AutoTutor: A tutor with dialogue in natural language. Behavior Research Methods, Instruments, and Computers, 36(2), 180–193.
- VanLehn, K., Graesser, A. C., Jackson, G. T., Jordan, P., Olney, A., & Rose, C. P. (2007). When are tutorial dialogues more effective than reading? Cognitive Science, 31(1), 3–62.