Abstract
Team communication addresses a critical issue for software developments. Understanding human behavior and communication take an important role for cost optimized scheduling and adjustment of dysfunctional manner. But team phenomena are often not trivial to interpret. Empirical studies can disclose practical information. Many kinds of research with the focus on human factors justify findings solely through linear statistics. This leads to an estimation problem of formally interpreted effects, in particular for diagnosis models. In this paper, we investigate several team communication effects with data records from an empirical study with 34 academic software projects. In general, we want to increase the awareness for often insufficiently interpreted human factors. We apply conventional linear correlation statistics in comparison with the novel exploratory analysis MINE on three sample cases concerning team meetings and communication behavior. Both analyzing techniques approved to be capable in identifying the relevant team communication effects within the case studies, even though with different estimation of relevances. The study demonstrates how quickly e.g. group behavior and communication effects can be insufficiently interpreted with dangerous gaps for factor estimation in modeling approaches.
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Acknowledgment
This work was funded by the German Research Foundation (DFG) under grant number 263807701 (Project TeamFLOW, 2015–2017).
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Kortum, F., Klünder, J., Schneider, K. (2017). Don’t Underestimate the Human Factors! Exploring Team Communication Effects. In: Felderer, M., Méndez Fernández, D., Turhan, B., Kalinowski, M., Sarro, F., Winkler, D. (eds) Product-Focused Software Process Improvement. PROFES 2017. Lecture Notes in Computer Science(), vol 10611. Springer, Cham. https://doi.org/10.1007/978-3-319-69926-4_36
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DOI: https://doi.org/10.1007/978-3-319-69926-4_36
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