Teaching Tactics and Dialog in AutoTutor
12 (3): "Special Issue on Modelling Teaching "
The Tutoring Research Group at the University of Memphis has developed a computer
tutor (called AutoTutor) that simulates the discourse patterns and pedagogical strategies of a
typical human tutor. The dialog tactics were based on a previous project that dissected 100 hours
of naturalistic tutoring sessions. AutoTutor is currently targeted for college students in
introductory computer literacy courses, who learn the fundamentals of hardware, operating
systems, and the Internet. Instead of merely being an information delivery system, AutoTutor
serves as a discourse prosthesis (or collaborative scaffold) that assists the student in actively
constructing knowledge. A dialog manager coordinates the conversation that occurs between a
learner and a pedagogical agent, whereas lesson content and world knowledge are represented in
a curriculum script and latent semantic analysis. The agent is a talking head with discourse-
sensitive facial expressions and synthesized speech. Evaluations of AutoTutor have shown that
the tutoring system improves learning and memory of the lessons by .5 to .6 standard deviation
units. This article describes the components of AutoTutor and contrasts two versions that follow
somewhat different teaching tactics.