Content, Social, and Metacognitive Statements: An Empirical Study Comparing Human-Human and Human-Computer Tutorial Dialogue

Abstract. We present a study which compares human-human computermediated tutoring with two computer tutoring systems based on the same materials but differing in the type of feedback they provide. Our results show that there are significant differences in interaction style between human-human and human-computer tutoring, as well as between the two computer tutors, and that different dialogue characteristics predict learning gain in different conditions. We show that there are significant differences in the non-content statements that students make to human and computer tutors, but also to different types of computer tutors. These differences also affect which factors are correlated with learning gain and user satisfaction. We argue that ITS designers should pay particular attention to strategies for dealing with negative social and metacognitive statements, and also conduct further research on how interaction style affects human-computer tutoring.

• Type: Conference
• Year: 2010
• Where: ECTEL
• Authors: Myroslava Dzikovska, Natalie B. Steinhauser, Johanna D. Moore, Gwendolyn E. Campbell, Katherine M. Harrison, Leanne S. Taylor
• Keywords: ECTEL 2010, Human-computer Tutoring, Human-human Computermediated Tutoring, Machine Learning, Significant Differences