Daftar Isi:
  • The research entitled "A Conversational Analysis of Repair Uttered by Paul and Alex in In Treatment Season 1" aims to: (1) identify and describe the types of repair; (2) describe the positions of repair, and (3) analyze the patterns of repair completion. This research employed a descriptive qualitative method since the findings were presented in narrative or textual description. Data were collected from the TV series and the samples were taken from certain episodes using purposive sampling. The researcher used conversational analysis in pragmatics as the approach and theory of conversation repair to answer the research questions. The study examined the types and the positions of repair by using Schegloff's theory. Then, the patterns of repair completion were investigated by using Tang and Zhang's theory. The result of the research shows that there are 90 total data for repair utterances uttered by the participants in In Treatment Season 1. Each datum represent 3 kinds of repair characteristic. First is the types of repair, it is divided into four types: 48 data of self-initiated self-repair, 3 data of self-initiated otherrepair, 32 data of other-initiated self-repair, and 7 data of other-initiated otherrepair. Second is the positions of repair, they are 40 data of transition space repair, 39 data of second space repair, and 11 data of same turn repair. Third is the patterns applied to deliver repair completions. There are 31 data of elaboration, 12 data of specification, 9 data of abandonment and rewording, 8 data of reorganization and exemplification, 6 data of replacement, 4 data of modification and 3 data of restructuring. In brief, the dominant data that are found in the series are the conversation that has self-initiated self-repair, transition space repair and elaboration pattern. The result of this research is expected to enrich the knowledge about conversation analysis especially repair. The researcher also hopes to the other researchers who want to have similar topic should analyze the topic more specifically.