Collaborative dialogue patterns in naturalistic one-to-one tutoring



Naturalistic one-to-one tutoring is more effective than traditional classroom teaching methods, but there have been few attempts to examine the features of normal tutoring that might explain its advantage. This project explored dialogue patterns in two samples of naturalistic tutoring with normal unskilled tutors (as opposed to expert tutors): graduate students tutoring undergraduates in research methods and high school students tutoring 7th graders in algebra. We analysed the extent to which those tutoring protocols manifested components that have been emphasized in contemporary pedagogical theories and intelligent tutoring systems: active student learning, sophisticated pedagogical strategies, specific examples and cases, collaborative problem solving and question answering, deep explanatory reasoning, convergance toward shared meanings, feedback, error diagnosis and remediation, and affect. The most prominent components consisted of collaborative problem solving, question answering, and explanation in the context of specific examples. We identify frequent dialogue patterns that characterize these collaborative processes.