Fine-Grained Analysis of Team Collaborative Dialogue
Perera, Ian, Johnson, Matthew, Wilber, Carson
–arXiv.org Artificial Intelligence
Poor the software development domain in which communication can lead to disastrous results even team members of different roles and levels of experience in situations where the individuals are competent coordinate efforts in a single chat channel in their own roles, while exemplary communication over days, weeks, or months. Unlike much can enable performance beyond the sum of prior work, the tasks under discussion are often individual capabilities. Automatic, fine-grained not explicitly defined and dynamically change in analysis of team dialogues could potentially identify response to new information and progress. Currently successes and failures in communication, while we do not have an endpoint to measure team identifying productive paradigms, roles, and areas performance in the data collected (and final results for improvement in collaboration. of software development tasks, especially in a research Currently, evaluation of team communication setting, are affected by many factors beyond during collaborative tasks often depends on human team dynamics), and so we focus on extracting metrics analysis, or if automated, does not typically have from human-designed patterns of positive and a means for explainable analysis of the underlying negative team dynamics. For example, repeated mechanisms of communication and collaboration requests for clarification may indicate that the listener that are tied to the task. Common methods is not sufficiently familiar with a concept to of productivity analysis or effort accounting suffer be able to provide assistance, or the speaker is not from focusing on quantitative metrics that may clearly describing relevant information.
arXiv.org Artificial Intelligence
Dec-9-2023
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