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AutoTutor
is an intelligent tutoring system that helps students
learn by holding a conversation in natural language.
AutoTutor appears as an animated agent that acts
as a dialog partner with the learner. The animated agent
delivers AutoTutor's dialog moves with synthesized speech,
intonation, facial expressions, and gestures. Students
are encouraged to articulate lengthy answers that exhibit
deep reasoning, rather than to recite small bits of
shallow knowledge. It may take 50-100 turns between
the student and computer tutor for the collaboration
to converge on a good answer. For some topics,
there are graphical displays, animations, and interactive
simulation. One version of AutoTutor is sensitive
to learner emotions by tracking facial expressions,
speech parameters, body posture, and the dialogue history.
Over 15 experiments have been conducted
with AutoTutor to help students learn Newtonian physics,
computer literacy, and scientific reasoning. AutoTutor
improves learning by nearly one letter grade compared
with reading a textbook for an equivalent amount of
time. Funding for AutoTutor has come from National Science
Foundation, Institute of Education Sciences, and the
Department of Defense.
You can view our past and current National Science
Foundation Grant Proposals to gain a more comprehensive overview
of the Autoutor project:
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