Studies of one-on-one tutoring have found that expert tutoring is more effective than non-expert tutoring, but the reasons for its effectiveness are relatively unexplored. Since tutoring involves deep natural language interactions between tutor and student, we explore the differences between an expert and non-expert tutors through the analysis of individual dialogue moves, tutorial interaction patterns and multi-utterance turns. Our results are a first step showing what behaviors constitute expertise and provide a basis for modeling effective tutorial language in intelligent tutoring systems.