Understanding Women's Remote Collaborative Programming Experiences: The Relationship between Dialogue Features and Reported Perceptions

In recent years, remote collaboration has become increasingly common both in the workplace and in the classroom. It is imperative that we understand and support remote collaborative problem solving, particularly understanding the experiences of people from historically marginalized groups whose intellectual contributions are essential for addressing the pressing needs society faces. This paper reports on a study in which 58 introductory computer science students constructed code remotely with a partner following either predefined structured roles (driver and navigator in pair programming) or without predefined structured roles. Between the structured-role and unstructured-role conditions, participants? normalized learning gain, Intrinsic Motivation Inventory scores, and system usability scores were not significantly different. However, regardless of the collaboration condition, women reported significantly higher levels of stress, lower levels of perceived competence, and less perceived choice compared to men. Because computer science is a context in which women have been historically marginalized, we next examined the relationship between student gender and collaborative dialogues by extracting lexical and sentiment features from the textual messages partners exchanged. Results reveal that dialogue features, such as number of utterances, utterance length, and partner sentiment, significantly correlated with women's reports of stress, perceived competence, or perceived choice. These findings provide insight on women's experiences in remote programming, suggest that dialogue features can predict their collaborative experiences, and hold implications for designing systems that help provide collaborative experiences in which everyone can thrive.