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It is often assumed that engaging in a one-on-one dialogue with a tutor is more effective than listening to a lecture or reading a text. Although earlier experiments have not always supported this hypothesis, this may be due in part to allowing the tutors to cover different content than the noninteractive instruction. In 7 experiments, we tested the(More)
The purpose of this study was to investigate students' patterns of interactions within a game-based intelligent tutoring system (ITS), and how those interactions varied as a function of individual differences. The analysis presented in this paper comprises a subset (n=40) of a larger study that included 124 high school students. Participants in the current(More)
AutoTutor is a learning environment with an animated agent that tutors students by holding a conversation in natural language. AutoTutor presents challenging questions and then engages in mixed initiative dialogue that guides the student in building an answer. AutoTutor uses latent semantic analysis (LSA) as a major component that statistically represents(More)