Inclusive team participation is one of the most important factors that aids effective collaboration and pair programming. In this paper, we investigated the ability of linguistic features and a transformer-based language model to detect exclusive and inclusive language. The task of detecting exclusive language was approached as a text classification problem. We created a research community resource consisting of a dataset of 40,490 labeled utterances obtained from three programming assignments involving 34 students pair programming in a remote environment. This research involves the first successful automated detection of exclusive language during pair programming. Additionally, this is the first work to perform a computational linguistic analysis on the verbal interaction common in the context of inclusive and exclusive language during pair programming.